Recent advances in nanomaterial-enabled chemiresistive hydrogen sensors

Yao Yang Liu a, Zhong Li *ab, Yi Liang a, Tao Tang a, Jing Hao Zhuang a, Wen Ji Zhang a, Bao Yue Zhang c and Jian Zhen Ou *ac
aKey Laboratory of Advanced Technologies of Materials, Ministry of Education, School of Materials Science and Engineering, Southwest Jiaotong University, Chengdu 610031, China. E-mail: zhong.li@swjtu.edu.cn; jzou@swjtu.edu.cn
bJiangsu Key Laboratory of Advanced Structural Materials and Application Technology, Nanjing Institute of Technology, Nanjing 211167, China
cSchool of Engineering, RMIT University, Melbourne, Victoria 3000, Australia. E-mail: jianzhen.ou@rmit.edu.au

Received 14th October 2024 , Accepted 11th November 2024

First published on 21st November 2024


Abstract

With the growing adoption of hydrogen energy and the rapid advancement of Internet of Things (IoT) technologies, there is an increasing demand for high-performance hydrogen gas (H2) sensors. Among various sensor types, chemiresistive H2 sensors have emerged as particularly promising due to their excellent sensitivity, fast response times, cost-effectiveness, and portability. This review comprehensively examines the recent progress in chemiresistive H2 sensors, focusing on developments over the past five years in nanostructured materials such as metals, metal oxide semiconductors, and emerging alternatives. This review delves into the underlying sensing mechanisms, highlighting the enhancement strategies that have been employed to improve sensing performance. Finally, current challenges are identified, and future research directions are proposed to address the limitations of existing chemiresistive H2 sensor technologies. This work provides a critical synthesis of the most recent advancements, offering valuable insights into both current challenges and future directions. Its emphasis on innovative material designs and sensing strategies will significantly contribute to the ongoing development of next-generation H2 sensors, fostering safer and more efficient energy applications.


1. Introduction

With the rapid development of technology, the world is currently faced with a severe energy crisis resulting from excessive exploitation and utilization of non-renewable energy sources. Hydrogen gas (H2) has been generally regarded as a crucial component of the global energy system due to its abundance, efficiency, cleanliness and recyclability.1 In essence, hydrogen energy sources significantly contribute to the sustainable development of our world. However, H2 has a high burning velocity, a wide flammable range (4–75 vol%), a low ignition energy (0.017 mJ), and a high heat combustion (142 kJ g−1), which makes it extremely dangerous during production, transportation, storage, and utilization processes.2 In addition, its colorless, odorless, and tasteless properties pose challenges for human sensory detection.3 Therefore, the research and utilization of H2 sensors are indispensable for achieving real-time and comprehensive detection of H2.

In recent years, researchers have been dedicated to the development of H2 sensors with heightened sensitivity, expanded detection range, accelerated response time, improved stability, enhanced gas selectivity, and near-room-temperature operability to achieve timely, precise, and convenient H2 concentration detection. To date, the commercially available H2 sensors are mainly divided into eight categories based on their fundamental principles and detection methods, including work function, acoustic, optical, catalytic, thermal conductivity, mechanical, electrochemical and resistance types.2 Among these types, work function based H2 sensors are micromachinable, small in size, have low cost, and can be mass-produced; however, they are susceptible to drift and exhibit a hysteresis effect.4 Although acoustic sensors with high sensitivity can operate in the absence of oxygen (O2) from room temperature to 100 °C, it is challenging to operate at a higher temperature without interference from humidity and temperature.2,5 In terms of optical sensors, there is no source of ignition in explosive atmospheres and the utilization of optical fiber transmission makes them immune to electromagnetic interference, but the stringent requirements on the preparation process, complex structure, high cost, and challenging signal monitoring restrict their large-scale industrial application.6 Catalytic sensors are suitable for the detection of high concentrations of H2 (>4%) with exceptional stability and prolonged lifespan, but they do possess certain limitations including elevated operational temperatures, increased power consumption, limited capability to differentiate between other combustible gases, and a requirement for 5–10% O2.7 Furthermore, the thermal conductivity sensors have a higher detection limit and a poor selectivity for gases with high thermal conductivity.2 And the mechanical sensors also have disadvantages including slow response time, susceptibility to poisoning and hydrogen-induced aging effects.2 Compared with the above-mentioned H2 sensors, both electrochemical and chemiresistive H2 sensors are considered as state-of-the-art technologies for H2 sensing nowadays.8 Nevertheless, the electrochemical sensors are highly susceptible to ambient conditions (temperature, pressure, humidity and oxygen), difficult to integrate, and have rather complicated systems that require high fabrication costs.9 In contrast, chemiresistive H2 sensors, which operate by using sensitive materials to react with H2 and convert chemical reactions into electrical signals (resistance or conductance), have been considered particularly promising for development due to their high sensitivity, fast response, long lifetime, low cost, wide operating temperature range, simple production, and portable applications.8,10

There has also been a significant emphasis on chemiresistive H2 sensors in numerous studies due to the above-mentioned advantages. Generally, the performance of H2 sensors relies upon the reactions between H2 and sensing materials. Therefore, accurate processing of the dimensions and shapes of materials is essential for improving sensing performance. With the development of nanotechnology, numerous nanomaterials have been employed for H2 sensing due to their high surface area-to-volume ratio, abundant surface active sites, high carrier mobility, and interesting physical and chemical properties.11–15 On the one hand, palladium (Pd) can easily react with H2 inducing the formation of PdHx with a higher resistivity even at room temperature.16 Thus, Pd-based H2 sensors have been widely studied owing to their excellent sensing properties, especially their high selectivity and room temperature operation. However, the interference of O2 molecules in the ambient air significantly hinders the reaction between H2 and Pd resulting in degraded performance of the sensor in terms of sensitivity and response speed,17 while the sluggish diffusion of H atoms in Pd lattices also leads to severe hysteresis of the sensor.18 These challenges present obstacles to the advancement of high-performance H2 sensor technology. Therefore, researchers are currently focusing on enhancing the sensing characteristics of Pd-based H2 sensors by investigating various aspects such as Pd nanostructures, Pd-based bimetals, and Pd-based composites. On the other hand, metal oxide semiconductor (MOS)-based sensors, which rely on the modulation of electrical signals resulting from the interaction between H2 and chemisorbed oxygen on the surface of MOSs, have also been extensively employed for H2 sensing in diverse applications. Nevertheless, the adsorption and desorption of O2 of MOS-based sensors typically require elevated temperatures exceeding 200 °C,19 thereby restricting their commercial application due to the increased power consumption and reducing their selectivity owing to the high reactivity of other interfering gases induced by elevated temperatures. Consequently, to tackle these challenges, researchers have devised diverse effective approaches, encompassing the design of nanostructures, functionalization by noble metals, doping of elements, and constructing heterojunctions. Besides, emerging materials also demonstrate remarkable H2 sensing capabilities at room temperature, such as graphene, carbon nanotubes (CNTs), transition metal disulfides (TMDs), and MXenes. Thus, owing to technological advancements, the scope of research on hydrogen-sensitive materials is continuously broadening.

In this review, we classify chemiresistive H2 sensors into three categories from the perspective of sensitive materials: metal-based, MOS-based, and other materials (graphene, CNTs, TMDs, and MXenes). Firstly, we present a detailed introduction to the gas-sensing mechanisms employed by each type of chemiresistive H2 sensor. Subsequently, we provide a comprehensive overview of the latest research progress and development strategies for high-performance chemiresistive H2 sensors, focusing primarily on elucidating the physicochemical mechanisms that contribute to enhanced sensing performance through various improvement methods. We particularly emphasize the intricate relationship between sensing performance and factors such as structural characteristics, surface modifications, and chemical and electrical properties. Finally, we conclude the status of H2 sensor research, point out existing limitations, and provide prospects for future research directions.

2. Metal-based H2 sensors

Among various metals for H2 sensors, Pd has been known as the most appealing material due to its unique ability to reversibly and selectively form PdHx in the presence of H2 under ambient conditions at room temperature. Therefore, there have been developed numerous Pd-based H2 sensors, including Pd nanostructures, Pd-based bimetals and Pd-based composites. Additionally, except for Pd, Pt also exhibits a gas response to H2. O2 molecules in the surrounding air are readily dissociated and adsorbed onto the surface of Pt, leading to an increase in Pt resistance due to electron scattering on the adsorbed oxygen molecules. Subsequently, upon exposure to H2, the catalytic conversion of adsorbed oxygen into water occurs while H2 chemisorbs onto the surface of Pt forming Pt–H, resulting in a decrease in resistance unlike Pd.8,20 The response time of Pt towards H2 exposure was observed to be faster compared to that of Pd under the same operating conditions.20 However, a significant limitation of Pt-based sensors is that they exhibit identical resistance change for H2 concentrations exceeding 0.1% due to early saturation, which greatly limits their practical applications.20,21 Consequently, limited subsequent research has been conducted on pure Pt-based sensors. In this section, we provide a detailed discussion on sensing mechanisms and recent advancements related to Pd-based H2 sensors.

2.1. Sensing mechanisms for Pd-based H2 sensors

In general, the sensing mechanisms of Pd-based H2 sensors are attributed to the formation of PdHx. H2 molecules are easily adsorbed on the surface of Pd and dissociated into H atoms at room temperature (eqn (1) and (2)). Then, the H atoms spontaneously and selectively diffuse into the octahedral interstitial sites of the face-centered cubic (FCC) Pd lattice (Fig. 1a).22 In the Pd–H system, PdHx usually has two phases (α phase and β phase) due to the different H2 pressures.1 When exposed to an H2 pressure below 1%, Pd undergoes partial filling of its interstitial sites, leading to the formation of a solid-solution phase (α phase, eqn (3)).22 With the increase of H2 pressure (1% < [H2] < 2%), the interaction between dissolved H atoms in Pd metal becomes more pronounced, which induces the first transition in the PdHx matrix.23,24 Simultaneously, nucleation of the β phase occurs within the α phase and subsequently the α and β phases coexist until a complete phase transition from α to β ([H2] ≥ 2%, eqn (4)).24 Moreover, both α-PdHx and β-PdHx exhibit a higher resistivity compared to Pd, because the H atoms occupied in the interstitial sites act as scattering sites impeding the movement of free electrons.8 Generally, the increase in resistivity resulting from the formation of PdHx is considered the primary sensing mechanism for most of the Pd-based H2 sensors. However, the further formation of β phase induces significant volume expansions in the Pd lattice, which results in irreversible structural changes in Pd. Consequently, achieving linear detection of high concentrations of H2 ([H2] ≥ 2%) while maintaining excellent long-term stability poses a formidable challenge. Additionally, the presence of interfering gases, which is inevitable in practical applications, will influence the permeability of H2. The carbon monoxide (CO), nitrogen oxides, or hydrocarbon instead of H2 competitively absorb on the site of Pd and occupy the active sites, thereby reducing the H2 permeability into the Pd and further reducing the selectivity.25–27 Therefore, in practical applications, it is also necessary to consider how to eliminate the influence of interfering gases.
 
H2(gas) → H2(ads)(1)
 
H2(ads) → 2H(ads)(2)
 
Pd(s) + H(ads) → α-PdHx(s) ([H2] ≤ 1%)(3)
 
Pd(s) + H(ads) → β-PdHx(s) ([H2] ≥ 2%)(4)

image file: d4cc05430j-f1.tif
Fig. 1 (a) Schematic of hydrogen diffuse into the Pd lattice. (b) Schematic of chemisorption based on MOSs. (c) Schematic of physisorption.

2.2. Pd nanostructures

With the development of nanomaterials and nanotechnology, numerous Pd nanostructures, including Pd nanoparticles (NPs),28 Pd nanowires (NWs),29–31 Pd nanosheets,32 and Pd nano hollow shells,33 have been explored for H2 sensors. Pd nanostructures have significant advantages for H2 sensing applications due to their high surface area-to-volume ratio, electron transport ability, high porosity, and exposure of high-energy facets that are catalytically active.31

Among them, Pd NWs have been the most extensively studied. It was previously reported that precise control and design of the size of Pd NWs are critical for achieving highly efficient H2 sensing.34 However, conventional lithography techniques are incapable of fabricating Pd NWs with a diameter smaller than 10 nm and also entail relatively high costs. Solution-phase synthesis enables the production of Pd NWs exhibiting an exceptionally high aspect ratio and small diameter, but they are typically capped with surfactants or ligands that pose challenges in their removal and interfere with sensing applications.35 As a consequence, to address the aforementioned limitations, Kumar et al.31 showed a solution-phase synthesis of Pd NWs with an ultrathin diameter smaller than 5 nm and treated with an ultraviolet (UV-O) source to remove the ligands attached to their surface. Subsequently, a comparative analysis was conducted to evaluate the H2 sensing performance pre and post UV-O treatment, revealing that the sensor subjected to UV-O treatment exhibited enhanced sensitivity along with accelerated response and recovery speed. Additionally, the UV-O-treated sensor displayed response and recovery time of 3.4 and 11 s to 1% H2 with high selectivity to H2 in comparison with CO, CO2, and CH4. After being exposed to 100 ppm CO for 2 minutes, which was much higher than the allowable concentration in the ambient environment, the response to 100 ppm H2 only decreased by 10%. However, the author only mentioned short-term repeatability within 30 minutes, neglecting to investigate the long-term stability, which was one of the primary concerns in practical applications. In general, the high properties of the Pd NW-based sensor can be ascribed to its ligand-free surface and ultrathin diameter.

Interestingly, Jo et al.29 developed a phase-transition-inhibited Pd NW sensor with a linear response at 4% H2. The H2 sensing device, as illustrated in Fig. 2a, comprised a precisely aligned array of Pd NWs serving as the sensing material along with four electrodes. Since the bottom of Pd NWs was fixed to the substrate, compressive stress was generated near the substrate to partially inhibit volume expansion when H diffused into the interstitial sites of Pd. The inhibition of the PdHx phase transition in the high-stress region can be explained by the change of the free energy equation (Fig. 2b). According to ideal solid solution absorption effects, free energy was directly influenced by H2 pressure (PH2) and internal stress of the solid. The internal stress restricted the diffusion of atoms within the solid, leading to a change in chemical potential and an enhancement of α-phase PdHx stability. Consequently, when sufficiently high stress was generated in Pd NWs, diffusion of H atoms became challenging, thereby achieving an inhibitory effect on phase transition. Furthermore, it was determined that a critical stress of at least 0.25 GPa was required in PdHx to successfully inhibit the phase transition at 4% H2 (Fig. 2c) and it was presumed that regions with a high A>0.25[thin space (1/6-em)]GPa/Atotal, especially above 90%, are imperative for effectively inhibiting phase transition due to variations in stress induced by the size of the Pd NWs. As shown in Fig. 2d, the Pd NWs with width (wNW) greater than 160 nm and thickness (tNW) less than 15 nm were suitable for phase transition inhibition and fast response time. To verify the theoretical predictions experimentally, they compared the H2 response of Pd NWs with different widths and thicknesses. The Pd NWs with a width of 160 nm and a thickness exceeding 15 nm exhibited an abrupt increase in sensitivity at 1.5% of H2, indicating the initiation of β-phase transition and then showed identical gas responses from 2 to 4% of H2 because of the saturation of H content in the nanowire (Fig. 2e). Moreover, a similar phenomenon was also displayed in Pd NWs with a thickness of 10 nm and a width below 160 nm (Fig. 2f). Therefore, the Pd NWs with a width of 160 nm and a thickness of 10 nm exhibited linear response and repeatable performance to H2 concentrations from 0.1 to 4% (Fig. 2f and g).


image file: d4cc05430j-f2.tif
Fig. 2 (a) Schematic illustration of the Pd NW H2 sensor. (b) Schematic of the internal lattice structure of Pd NWs with two phases and the thermodynamic quantities related to H2 pressure and stress for the phase transition of PdHx from α to β. (c) Gibbs free energy of the PdHx phase transition varied with stress (σ) at four different concentrations of H2. (d) Curves of A>0.25[thin space (1/6-em)]GPa/Atotal and unit volume to surface concerning tNW or wNW. (e) Response–recovery curves of Pd NW sensors with different tNW and fixed wNW (160 nm) to different H2 concentrations ranging from 0.1 to 4%. (f) Response–recovery curves of Pd NW sensors with different wNW and fixed tNW (10 nm) to different H2 concentrations ranging from 0.1 to 4%. (g) Response–recovery curves of Pd NW sensors to various random H2 concentrations (wNW = 160 nm, tNW = 15 nm). Reproduced with permission from ref. 29. Copyright 2022 American Chemical Society. (h) Schematic representation of the Pd nanoelectromechanical H2 sensing device and its structural characteristics for rapid H2 detection. (i) Response/recovery time for Pd NW sensors of different H2 concentrations from 1–4%. (j) Chart of the six required performances in H2 detection compared the four different types of devices. Reproduced with permission from ref. 30. Copyright 2023 American Chemical Society.

It has already been above-mentioned that the phase transition is accompanied by an increase in resistance; however, as the H2 concentration further increases, it is difficult to distinguish the concentration of H2 due to the saturation of H2 resulting in the saturation of resistance. Therefore, it becomes challenging to achieve linear detection up to 10% H2. Meanwhile, the application of thermal energy to activate Pd has been recognized as an efficacious approach to accelerate the response rate without material engineering by improving the H2 adsorption efficiency and impeding the phase transition of PdHx.36 Accordingly, the following year, Jo et al.30 designed a coplanar Pt NW heater-integrated sensing architecture for optimal thermal activation of pure Pd NWs to achieve a subsecond (∼0.6 s) response time and a linear detection of up to 10% H2. The structure of the device can maximally expose the reaction sites of Pd NWs and form a uniform temperature in the sensing elements by constructing a conductive heat transfer design (Fig. 2h). Therefore, this sensor displayed a fast response time of 0.6 s in the concentration range of 1–4%, a wide detection range of 0.1–10% with 99.75% linearity and durable heating operation in a wide temperature range (−10 to 80 °C) with high repeatability (>104 cycles) and a long heating lifetime (>10 years) (Fig. 2i and j). It's worth noting that the influence of CO and high humidity can be ignored due to the high operating temperature, which lowered the adsorption of CO and condensation of water. However, the detection of high concentrations of H2 is always accompanied by a poor long-term stability, which was not investigated in this paper. On the whole, the synergistic effect of nanostructures and thermal activation can significantly enhance the H2 sensing characteristics.

2.3. Pd-based bimetals

To mitigate the irreversible damage caused by the α-β phase transition of PdHx in Pd-based H2 sensors, it is common practice to employ Pd-based bimetals as hydrogen-sensitive materials instead of pure Pd. This strategy has been shown to effectively mitigate phase changes by occupying Pd's interstitial sites with different metal atoms.29 Furthermore, the Pd-based bimetals have superior activity for surface reactions relative to pure Pd. Commonly, the metal elements used to form bimetals with Pd are Pt, Au, Ag, Sn and Ni.37–44

Owing to the same FCC structure and minimal lattice mismatch (0.77%),45 Pt is a promising candidate for the synthesis of Pd-based bimetals. One recent advance in Pd-based bimetals was the demonstration of a facile synthesis of ultra-small bimetallic nanoparticles (BM-NPs) of PdPt produced within porous ion-exchange polymers to create high-performance H2 sensors that enable wireless detection reported by Koo et al. (Fig. 3a).40 Herein, the porous ion-exchange polymer of imidazolium-functionalized triptycene polyether sulfone (ITPES) enabled homogeneous diffusion and immobilization of an ionic metal precursor of complementary charge into the polymer matrix, thus achieving precise regulation of the size (down to 1 nm) and composition of BM-NPs, which was critically important for sensing performance. Furthermore, upon exposure to H2, due to the synergistic effect of PdPt NPs, two reactions occurred: (1) the removal of surface-adsorbed oxygen resulted in a decrease in resistance, and (2) H2 adsorption led to an elevation in resistance (Fig. 3b). The two reactions occurred simultaneously, with the former dominating the resistance at high levels of [H2], while the latter prevailed at low levels of [H2]. Thus, the resistance of the ITPES-PdPt NPs sensors decreased when exposed to H2 concentrations above 100 ppm and then switched to an increase in resistance with H2 exposures below 16 ppm (Fig. 3d). Based on these results, the ITPES-PdPt NP-based sensor demonstrated remarkable stability and excellent H2 sensing properties with a response of 15.7% to 4% H2 and a low detection limit of 0.4 ppm (Fig. 3c–e). However, a linear gas response had not been achieved. Therefore, the reliability of the sensor necessitated further enhancement. In general, it is imperative to enhance the H2 sensing performance through the synthesis of small-sized (below a few nanometers) Pd-based bimetallic NPs exhibiting exceptional surface activity.


image file: d4cc05430j-f3.tif
Fig. 3 (a) Schematic illustration of the chemiresistive H2 sensing system with wireless detection. (b) Schematic illustration of the H2 sensing mechanisms of ITPES-PdPt NPs. (c) Response–recovery curves of ITPES-Pd NPs, ITPES-Pt NPs, ITPES-PdPt NPs, and PdPt films at room temperature to different H2 concentrations ranging from 1 to 4%. (d) Response–recovery curve of ITPES-PdPt NPs to 5 and 16 ppm and 0.05%, 0.01%, 0.25%, 1%, and 4% of H2 at room temperature. (e) Comparison of the detection limits of different Pd-based H2 sensors. Reproduced with permission from ref. 40. Copyright 2020 Elsevier. (f) Schematic illustration of the synthesis process for Pd–Sn alloy NTs. (g) Normalized response (S) versus H2 concentrations for Pd–Sn alloy NTs, Pd–Sn alloy NFs, Pd NFs, and Sn NFs at H2 concentrations of 0.5–200 ppm and (h) 5000–3000 ppm. Reproduced with permission from ref. 43. Copyright 2022 American Chemical Society.

In addition, various Pd-based bimetals can improve H2 sensing performances by constructing nanostructures with high specific surface area and multiple active sites. In this regard, Song et al.43 firstly fabricated hollow Pd–Sn alloy nanotubes (NTs) with a high surface area and ultrafine grain sizes by relying on particle migration and coalescence of neighboring particles. As shown in Fig. 3f, the SEM image revealed the shape of the Pd–Sn NTs in a hollow morphology having high porosity with superfine grain sizes. Besides, compared to Pd–Sn alloy nanofilms (NFs), Pd NFs and Sn NFs, the Pd–Sn NTs exhibited excellent sensitivity toward H2 (0.00005–3%) and a high response of 9.27% to a concentration of H2 (3%) at room temperature due to the highly porous structure with smaller nanograins offering more exposed active sites and higher gas accessibility (Fig. 3g and h). From the results, it is an efficient method to develop Pd-based bimetals with special nanostructures for the improvement of the H2 sensing performance.

However, the above-mentioned sensors exhibit long response/recovery times, which limits their application. Usually, appropriately increasing the operating temperature of the sensor will accelerate the diffusion of H2 resulting in a faster response/recovery speed. For instance, Liu et al.41 proposed a heating operation mode of the Pd/Ni-based H2 sensor integrating with a Pt heating wire. They found that the Pd/Ni film demonstrated a short response/recovery time of 7/6 s to 2% H2 at the optimal temperature of 75 °C. In addition, Deepti et al.37 reported that Pd–Au alloy exhibited a significantly reduced response/recovery time (7/50 s) to 2% H2 at 250 °C due to the ion irradiation, whereas the pristine sample displayed long response/recovery time (114/78 s). This improvement can be attributed to the ion-irradiation induced defects, which enhance the rate of H2 absorption. Nevertheless, the elevated operating temperature of 250 °C is accompanied by high power consumption, thereby impeding their commercial applications. Therefore, further investigation is imperative to facilitate the attainment of rapid response and recovery capabilities for this type of sensor while operating at near room temperature.

2.4. Pd-based composites

The combination of Pd with other materials induces synergistic effects, thus improving stability, enhancing sensitivity, and accelerating the response/recovery speed of the Pd-based sensors by using Pd-based composites. To date, many Pd-based composites have been developed, effectively addressing numerous challenges encountered in practical applications.46–51

For instance, Xing et al.50 developed an H2 sensor by using Pd NPs decorated on the carbon/nitrogen porous framework. It exhibited a wide concentration range of 200 ppm to 40% (S ≈ 73.8% and Tres ≈ 9 s) H2 sensing at room temperature, showing exceptional long-term stability with reliable H2 sensing maintained for up to 142 days. The exceptional performance can be attributed to the presence of Mott–Schottky heterojunctions between Pd NPs and N-doped carbon materials and the three-dimensional (3D) porous structures, which show excellent catalytic activity and provide abundant surface sites for gas diffusion and adsorption due to their large specific surface area. This result demonstrates the efficacy of incorporating other materials with Pd to enhance stability and reduce response/recovery time, thereby offering an efficient approach for improving Pd-based H2 sensors.

However, Pd-based H2 sensors are susceptible to poisoning and deactivation due to the adsorption of CO, nitrogen oxides, or hydrocarbons.27,52 Due to the relatively smaller size of H2 compared to other molecules, applying a polymer coating on H2 sensing materials can effectively act as a molecular sieve. However, this approach usually results in an extended response time and a compromised sensitivity of the sensor. Therefore, to overcome these issues, Xie et al.49 constructed a triple-layer Pd nanocluster film-metal organic framework (MOF)-polymer hybrid nanocomposite for H2 detection. Among them, the polymethyl methacrylate (PMMA) membrane acted as a molecular sieve, while the zeolitic imidazole framework-67 (ZIF-67) film served as an interfacial layer between the Pd NC film and the protective PMMA layer (Fig. 4a). To confirm that this structure had a good ability to resist CO poisoning without causing degradation of the sensor performance, they conducted an H2 sensing test in a CO background for various sensor types, including Pd, Pd/ZIF-67, PD/PMMA, and Pd/ZIF-67/PMMA. As shown in Fig. 4b and c, the presence of ZIF-67 film greatly enhanced the sensitivity of the sensor; however, upon exposure to CO, their performances were significantly diminished. However, even in the presence of CO, both Pd/PMMA and Pd/ZIF-67/PMMA exhibited consistent responses upon the introduction of the PMMA membrane (Fig. 4d and e). Hence, these results indicated that the obtained Pd/ZIF-67/PMMA hydride nanostructure effectively mitigated performance degradation associated with a single polymer coating and synergistically combined the satisfactory CO-poisoning resistance conferred by the PMMA membrane with improved sensing performance provided by the ZIF-67 film. In conclusion, Pd/ZIF-67/PMMA demonstrated optimal comprehensive performance owing to its unique nanocomposite structure.


image file: d4cc05430j-f4.tif
Fig. 4 (a) Schematic illustration of the fabricated Pd/ZIF-67/PMMA sensor. Response–recovery curves of (b) Pd, (c) Pd/ZIF-67, (d) Pd/PMMA, and (e) Pd/ZIF-67/PMMA to H2 with different concentrations along with 1% CO gas. Reproduced with permission from ref. 49. Copyright 2022 Wiley-VCH GmbH. (f) Structure diagram for Pd8SR16–SDBS–rGO used for H2 sensing. (g) Response–recovery curves for Pd8SR16–SDBS–rGO and PdNPs–SDBS–rGO sensors to 100 ppm H2 at room temperature. (h) Response–recovery curve of the Pd8SR16–SDBS–rGO sensor to different H2 concentrations ranging from 1 ppm to 2%. (i) 50-cycle response–recovery curve and response/recovery time for the Pd8SR16–SDBS–rGO sensor to 1000 ppm H2 at room temperature. (j) Selectivity of Pd8SR16–SDBS–rGO towards H2 in comparison with interfering gases including C3H8, CH4, H2S, Cl2, and SO2. Reproduced with permission from ref. 46. Copyright 2024 Wiley-VCH GmbH.

In addition to the formation of bimetals, Pd nanoclusters (NCs) also exhibit the ability to impede phase transitions through diverse H2 binding mechanisms.46,53 Moreover, metal NCs display atomic precision in composition, exceptional efficiency in metal utilization, and highly controllable geometries; thus, they emerge as promising candidates for sensing applications.54 However, attaining stable existence for pure metal nanoclusters has proven to be a formidable challenge due to their elevated surface energy and reactivity.55 Recently, a new advance of the Pd NC-based composites in H2 sensing was reported by Chen et al.46 They introduced thiolate-protected Pd nanoclusters (Pd8SR16), which unveiled the first-time application in H2 sensing, showing the significant potential for rapid detection. Amongst others, the synergistic interaction between metal and ligand of Pd8SR16 resulted in the formation of an intermediate palladium–hydrogen–sulfur (Pd–H–S) state during H2 adsorption. This state preserved the Pd–H binding while preventing excessive interaction, achieving a balance that reduced the activation energy required for H2 desorption and facilitating highly reversible and rapid response/recovery. Furthermore, the Pd8SR16 as H2 sensing sites were deposited on a sodium dodecylbenzene sulfonate/reduced graphene oxide (SDBS–rGO) carrier layer. The resulting Pd8SR16–SDBS–rGO sensor (Fig. 4f) effectively mitigated the restrictions associated with conventional Pd-based sensors across varying H2 concentrations, including durability degradation or failure arising from excessive Pd–H binding or phase transitions. As shown in Fig. 4g, compared to the PdNPs–SDBS–rGO sensor, the Pd8SR16–SDBS–rGO sensor exhibited consistent signal stability across 10 cycles at a low H2 concentration of 100 ppm, owing to the protection of thiolate. Additionally, the Pd8SR16–SDBS–rGO sensor displayed a wide detection range of H2 concentrations from 1 ppm to 2% (Fig. 4h) and showed a stable and prompt response (tres = 0.95 s) and recovery (trec = 6 s) at 1000 ppm H2 (Fig. 4i). The practical application of this sensor effectively mitigated the interference from other gases due to the superior selectivity (Fig. 4j). Therefore, this study demonstrated the practicality of using ligand-protected metal nanoclusters for gas sensing in the real-world. From this perspective, researchers can employ diverse materials in conjunction with Pd to fulfill the practical application demands of H2 sensing.

Currently, significant advancements have been achieved in the research on Pd-based H2 sensors. The suppression of the phase transition can be effectively achieved through the design of devices and construction of bimetals, while the selectivity of the sensor has been enhanced through the incorporation of polymer coatings. Table 1 summarizes the sensing performance of Pd-based sensors in recent years. These sensors all exhibit high H2 sensing performances, in terms of sensitivity, response/recovery speed, and detection limit. However, to mitigate the risk of H2 explosions, it is imperative to reduce the response/recovery time for concentrations exceeding 1% H2 to below 1 s. Therefore, further investigation is warranted to develop Pd-based H2 sensors with faster response/recovery speed.

Table 1 Summary of the sensing properties of Pd-based H2 sensors
Material Morphology Conc. (%) Tem. (°C) Res. (%) T res/Trec (s) MDL (ppm) Ref.
Conc.: gas concentration; Tem.: operating temperature of the sensor; Res.: response of the sensor and response is defined as (RgasRair)/Rair × 100%; Tres: response time of the sensor; Trec: recovery time of the sensor; MDL: minimum detection limit of the sensor; Ref.: reference; -: not reported; RT: room temperature (∼25 °C); MWCNT: multiwalled carbon nanotube.
Pd Hollow shells 1 RT 60 16/— 75 33
Pd Nanoparticles 1 RT 30.65 11.6/15.7 31
Pd Nanowires 1 RT 1.7 3.4/101 10 31
Pd Nanowires 4 RT 35.9 21/270 1000 29
Pd Nanosheets 1 RT 0.4 50/60 5 51
Pd Nanowires 1 RT 0.34 12/28 200 35
Pd–Sn Nanotubes 2 RT 4.8 20.2/17.9 1 43
PdPt Nanoparticles 1 RT 7.56 92/304 0.4 40
Pd/Ni Film 2 75 3.17 7/6 4000 41
Pd–Au Film 2 250 9.1 7/50 37
MWCNT@Pd Nanosheets 1 RT 3.6 74/25 5 51
Pd@rGO Nanowires 1 RT 2.06 52/45 20 35
Pd@rGO@ZIF-8 Nanowires 1 RT 2.17 5/31 20 35
Pd8SR16–SDBS–rGO Nanoclusters 0.1 RT 4 0.9/6 1 46
Pd–rGO Nanoparticles 2 RT 14.8 73/126 25 48


3. MOS-based H2 sensors

The MOS-based resistive gas sensors have attracted considerable attention owing to their remarkable stability, high sensitivity, rapid response/recovery time, low cost, and simple manufacturing process,10,56,57 rendering them a primary research focus for H2 sensors. However, the gas sensitivity of MOS-based sensors relies on the redox reaction with adsorbed oxygen, enabling electron exchange with a diverse range of gases and inherently limiting gas selectivity. Simultaneously, in order to ensure enough carriers entering the conduction band for active participation in the reaction, a substantial number of MOS-based gas sensors necessitate elevated operating temperatures exceeding 200 °C.10,19 The elevated operating temperature not only increases power consumption, impacts device integration, and compromises the gas selectivity of the sensor but also provides an additional ignition source, thereby posing safety hazards in proximity to combustible gases. Moreover, prolonged exposure to elevated temperatures can have a detrimental impact on the long-term stability of sensors by attenuating their sensitivity. Thus, in recent years, extensive research efforts have aimed at enhancing the gas selectivity and reducing the operational temperature of MOS-based H2 sensors. In this section, we elucidate the fundamental sensing mechanisms and present recent advancements in the development of MOS-based H2 sensors, focusing on MOS nanostructures, modification of noble metal NPs, doping of elements, and MOS-based composites.

3.1. Sensing mechanisms for MOS-based H2 sensors

In general, the mechanism of MOS-based H2 sensors is a change of electrical signals (current or resistance) caused by the interaction between H2 and chemisorbed oxygen on the surface of MOSs. The reception of H2 signals in the air background by MOSs primarily relies on two reactions that occur on the surface of MOSs: O2 adsorption leading to the formation of reactive oxygen species, and subsequent reaction between these reactive oxygen species and H2 (Fig. 1b). The O2 in the air readily absorbs onto the surface of the sensing materials, acting as an acceptor of electrons and dissociating on the surface of MOSs to capture electrons from the conduction band, resulting in the formation of species such as O2, O, and O2−. The adsorption reaction of oxygen is temperature-dependent (eqn (5)–(8)).58,59
 
O2(gas) → O2(ads)(5)
 
O2(ads) + e → O2(ads) (<100 °C)(6)
 
O2(ads) + e → 2O(ads) (100–300 °C)(7)
 
O(ads) + e → O2−(ads) (>300 °C)(8)

MOSs can be classified as either n-type or p-type, depending on whether the dominant carriers are electrons or holes. In the case of n-type MOSs, the adsorbed oxygen on the surface of the MOSs acts as a defect site and induces the Fermi level pinning effect. This effect leads to a reduction in electron density on the surface of MOSs, thereby forming an electron depletion layer (EDL) around the MOSs with a high potential barrier. The resistances of MOSs are significantly increased by the EDL, which arises from the reduction in net carrier density and the formation of potential barriers at the adsorption sites.8,11 When MOSs are exposed to H2, a reducing gas, H2, reacts with the adsorbed oxygen to generate water and release free electrons (eqn (9) and (10)).60 Consequently, the thickness of the EDL decreases, accompanying the decrease of the resistance of the MOS hydrogen gas sensors.61 Upon re-exposure to atmospheric conditions, chemisorbed oxygen is formed as O2 from the air gets adsorbed onto the surface of n-type MOSs again, increasing in resistance.

 
2H2(gas) + O2(ads) → 2H2O(gas) + e (<100 °C)(9)
 
H2(gas) + O(ads) → H2O(gas) + e (100–300 °C)(10)

On the other hand, p-type MOSs exhibit an opposite behavior to n-type MOSs. The combination of adsorbed oxygen and electrons will generate additional holes on the surface of the p-type MOSs, thereby forming a hole accumulation layer (HAL). However, the reaction of H2 with adsorbed oxygen effectively neutralizes these holes by releasing electrons, leading to a reduction in the thickness of the HAL and an increase in resistance. Subsequently, upon interaction between MOS-based sensors and H2 followed by re-exposure to air, atmospheric oxygen is reabsorbed to capture electrons from the conduction band, resulting in chemisorbed oxygen generation on the surface of the material and subsequent restoration of the surface space charge layer.11,62 Therefore, it is imperative for both n-type and p-type MOS-based materials to possess a large surface area and a high reactivity to analytes, thereby augmenting their sensing properties.63

3.2. MOS nanostructures

It is worth noting that MOS-based sensors rely on the gas–solid interfacial reaction between the target gas and the active sites on the surface of MOS, and thus the precise structural engineering of MOSs in terms of size and shape plays a crucial role in enhancing sensor properties. Consequently, many researchers have dedicated themselves to designing MOS-based nanostructures. At present, the common morphology design of MOS-based sensing materials includes nanoparticles,64 nanospheres,65 nanowires,66 nanorods,67 nanofilms,68 nanosheets,69 and nanoflowers.70

Among them, NPs and nanospheres exhibit high surface-to-volume ratios; however, their tendency to agglomerate can lead to a reduction in active sites. For instance, Zhu et al.65 studied the effects of three representative nanostructures on H2 sensing behaviors. As shown in Fig. 5a(i)–(iii), the three nanostructures namely solid spheres (0-SnO2), nanoneedle-assembled nano urchins (1-SnO2), and nanosheet-assembled nanoflowers (2-SnO2) were synthesized by a facile hydrothermal method. The three SnO2-based sensors were exposed to 400 ppm H2 at different operating temperatures from 200 to 500 °C in air, and the highest responses for 0-SnO2, 1-SnO2, and 2-SnO2 were estimated to be 12, 15, and 22 at the optimal operating temperature of 350 °C (Fig. 5b). Among them, the nanosheet-assembled nanoflowers displayed superior sensing performance owing to their abundant active absorption sites, whereas the solid spheres showed the lowest sensitivity due to their densely packed structures. Interestingly, it was observed that the three sensors demonstrated enhanced sensitivity under vacuum at the same conditions compared to the atmospheric environment (Fig. 5c). The first principles calculations revealed that the H2 molecule preferred to directly adsorb on the surface of SnO2 and transferred more electrons. According to the above results, it was revealed that a direct interaction between H2 and SnO2 took place in the absence of oxygen.


image file: d4cc05430j-f5.tif
Fig. 5 (a) SEM and TEM images of SnO2 samples: (i) and (iv) solid spheres, (ii) and (v) nanoneedle-assembled nano urchins, and (iii) and (vi) nanosheet-assembled nanoflowers. (b) Response of the three sensors exposed to 400 ppm H2 at different operating temperatures (from 200 to 500 °C) in air. (c) Response of the three sensors exposed to 400 ppm H2 at different operating temperatures (from 200 to 500 °C) in a vacuum. Reproduced with permission from ref. 65. Copyright 2018 Elsevier. (d) SEM and TEM images of aspect-ratio-controlled ZnO nanostructures: (i) and (ii) ZnO@350, (iii) ZnO@450, and (iv) ZnO@550. (e) Response of aspect-ratio-controlled ZnO nanostructures to 80 ppm H2 at different operating temperatures from 60 to 240 °C. (f) Response of aspect-ratio-controlled ZnO nanostructures to different H2 concentrations from 0.5 to 80 ppm at the optimal operating temperature of each sensor (ZnO@350 and ZnO@450: at 180 °C; ZnO@550: at 240 °C). Reproduced with permission from ref. 67. Copyright 2024 Elsevier. (g) (i) and (ii) SEM images of Sn3O4 nanosheets at different magnifications, (iii) TEM image of Sn3O4 nanosheets, (iv) HRTEM image of Sn3O4 nanosheets. (h) Room-temperature Sn Mössbauer spectroscopy. (i) Response–recovery curves of pristine and Sn2+-deficient Sn3O4 as well as commercial SnO2 towards 10 ppm H2. Reproduced with permission from ref. 69. Copyright 2024 Elsevier.

Additionally, one-dimensional (1D) nanostructures have garnered significant attention owing to their high surface-to-volume ratios and high porosity, including nanofibers, nanowires, and nanorods. Recently, Tran et al.67 demonstrated the role of aspect-ratio-controlled shape/size ZnO nanorods in H2 sensing. As depicted in Fig. 5d, the three different aspect-ratio-controlled ZnO nanorods were synthesized by the thermal decomposition method at various annealing temperatures (350, 450, and 550 °C), and the aspect ratio decreased with increasing temperature. The ZnO nanorods synthesized through thermal decomposition at 350 °C exhibited the highest aspect ratio (∼6.25) among all tested samples, which demonstrated superior H2 sensing capabilities with a response of approximately 483% to 80 ppm H2 at 180 °C (Fig. 5e and f). Hence, the enhanced H2 sensing response of the ZnO@350 sensor can primarily be attributed to its high aspect ratio morphology, which promoted the formation of oxygen vacancies and provided a greater number of active sites for gas adsorption.

Furthermore, Liu et al.69 developed ultra large Sn3O4 nanosheet hierarchies with (010)-facet exposure and surface Sn2+-deficiency via a facile hydrothermal method, which displayed excellent H2 sensing performance due to the thermodynamical stability in the SnO phase and the existence of oxygen vacancies. Fig. 5g revealed that the Sn3O4 nanosheets with ultra-large two-dimensional (2D) structures were hierarchically assembled into a flower-like morphology and reflected the crystal growth orientation. It was confirmed that the exposed surface can be indexed as the (010) facet because the two sets of lattice fringes with d-spacings of 0.37 nm and 0.34 nm can be correspondingly indexed to the (101) and (−102) planes of the monoclinic Sn3O4 (Fig. 5g(iv)). Furthermore, as shown in Fig. 5h, the atomic ratio of Sn2+/Sn4+ was approximately 41.7/58.3, demonstrating the deficiency of Sn2+ in Sn3O4, which can be attributed to etching of HCl. Finally, they compared the H2 sensing performance of the pristine and Sn2+-deficient Sn3O4 nanosheets as well as the commercial SnO2 nanopowders when exposed to 10 ppm H2. The results showed that the Sn2+-deficient Sn3O4 nanosheets consistently exhibited superior sensitivity and response/recovery speed compared to the other samples (Fig. 5i). Herein, the hierarchical structure of the Sn3O4 nanosheets facilitated rapid gas–solid interfacial contact reactions and fast release of target gases, while the Sn2+-deficient (010) surface of Sn3O4 nanosheets offered abundant active adsorption sites for H2 molecules. Therefore, the nanofilms or nanosheets have been used for H2 sensing due to their large lateral size with numerous active absorption sites.

However, the challenges of low sensitivity, poor selectivity, and high operating temperature persist in pure MOS nanostructure-based H2 sensors. Therefore, it is imperative to explore alternative approaches for enhancing sensor performance and minimizing energy consumption to align with the operational demands of the industry.

3.3. Modification of noble metal nanoparticles

The utilization of noble metal NPs (such as Pd,71 Pt,72 Au,73,74 and Ag75) for the functionalization of MOSs represents an efficacious approach to augment the response and selectivity of resistive H2 sensors based on MOSs. The modification of MOSs by noble metal NPs is predicated upon two fundamental mechanisms: chemical sensitization and electron sensitization, namely, the spillover effect and the Fermi-level control sensitization mechanism, respectively.76,77

Chemical sensitization is used to describe the process in which gas molecules are dissociated by metal NPs (e.g. Pd, Pt, and Au) and then spill over onto the surface of MOSs. Reducing the activation energy of the reaction effectively promotes the progress of the reaction without altering the intrinsic resistance of MOSs.78 In particular, sometimes H2 are dissociated into H+ and electrons in the presence of catalysts, which are then intercalated into MOSs. This so-called “spillover” effect is well reported in MoO3, WO3, and V2O5.79–82 Therefore, H2 reactions on the surface of MOSs are effectively promoted by metal NPs, thereby enhancing H2 sensing properties. On the other hand, electronic sensitization is generated through the electron interaction between metal NPs (e.g. Pd, Ag, and Cu) and the interface of MOSs. Upon exposure to air, the electronic sensitizers in the oxidized state act as strong acceptors of electrons that trap electrons from MOSs and generate a large amount of adsorbed oxygen on their surfaces, inducing a surface space charge layer which is strongly depletive of electrons in the MOSs near the interface.78,83 However, when exposed to H2, the electronic sensitizers are reduced back to their metallic states, causing relaxation of the space charge layer by giving electrons back to MOSs and resulting in a substantial resistance variation. The gas sensing performance of MOS-based sensors can be effectively enhanced by these two mechanisms involving metal NPs.

Among various noble metals, Pd and Pt are widely used as chemical sensitizers due to their excellent ability to induce the spillover effect of H2 molecules onto MOSs for H2 sensing. For instance, Cheng et al.84 demonstrated that Pt decoration can greatly improve the ZnO sensor performance both in dry and humid environments due to the spillover effect, and Amit et al.85 reported the significant contribution of Pd in augmenting the H2 sensing performance of V2O5 through the spillover effect. In addition, Pd can also be used as an electronic sensitizer for MOS-based resistive H2 gas sensors. In the presence of ambient air, oxygen adsorption on the surface of Pd leads to partial oxidation of metallic Pd into PdO. Consequently, the PdO as a potent electron acceptor induces an expanded surface space charge layer, resulting in electron depletion near the interface and giving rise to the formation of an electron depletion layer. In an H2 environment, PdO is reduced back to Pd, releasing electrons that subsequently react with H2 to form PdHx. The combination of PdO, Pd or PdHx with MOSs forms different heterojunctions that modulate electron transfer. For example, Meng et al.83 observed that Pd existed in the forms of PdO, Pd, and PdHx in different environments. Amongst others, PdO was a p-type semiconductor with a work function of 7.9 eV. Upon loading PdO onto the surface of n-type SnO2, an electron transfer occurred from SnO2 to PdO due to the lower work function of SnO2 (4.5 eV), resulting in the formation of a p–n heterojunction. Therefore, the working temperature decreased from 300 to 125 °C and the sensitivity remarkably upgraded after Pd loading in SnO2. Furthermore, in most cases, there is a strong correlation between chemical sensitization and electronic sensitization, which synergistically enhances the gas sensing performance of MOSs. For instance, Liu et al.86 fabricated a H2 sensor based on Pd/SnO2 and demonstrated the coexistence of both sensitization mechanisms in gas sensing reactions, which exhibited a pronounced dependence on the concentration of H2. When the H2 concentration was less than 1%, the electronic coupling effect at the PdHx and SnO2 interfaces became predominant (Fig. 6a). Upon a further increase in H2 concentration, the main mechanism was the redox reaction between H2 and Oα− on the surface of SnO2 (Fig. 6a). The loading of Pd effectively reduced the activation energy of the reaction, which significantly improved the sensor's kinetic performance. Furthermore, a significant decrease in its sensitivity to additional disruptive gases was observed, indicating an elevated degree of selectivity (Fig. 6b). Therefore, diverse MOSs, including SnO2,87 ZnO,84 In2O3,73 TiO2,72,88 WO3,89 and V2O5,85 functionalized by Pt, Pd, or Au, have been reported for selective H2 sensing layers so far.


image file: d4cc05430j-f6.tif
Fig. 6 (a) Schematic illustration of a model for the change in reception and transduction mechanisms for Pd/SnO2 films. (b) Selectivity of SnO2 and Pd/SnO2 to H2 in comparison with interfering gases including CH3OCH3, C2H5OH, C2H4 and CH4. Reproduced with permission from ref. 86. Copyright 2024 Elsevier. (c) Response–recovery curves of NOS-2, NCS-2 and NFS-3 to different H2 concentrations ranging from 100 to 1000 ppm at 50 °C. (d) Response–recovery curves for NOS-1, NOS-2, NOS-3 and NOS-4 of different H2 concentrations from 100 to 1000 ppm at 25 °C. (e) Response/recovery times for NOS-1, NOS-2, NOS-3 and NOS-4 to 1000 ppm H2 at 25 °C. Reproduced with permission from ref. 45. Copyright 2023 Elsevier. (f) The dynamic sensing responses of the pure ZnO, Pd@ZnO, PdPt@ZnO, and Pt@ZnO CSNP sensors of varied H2 concentration from 0.5 to 100 ppm at 350 °C. (g) Selectivity of pure ZnO, Pd@ZnO, Pt@ZnO, and PdPt@ZnO sensors to 100 ppm H2 at 350 °C in comparison with interfering gases including CH4, C2H5OH, CH3CHO, CH3COCH3, and CO. (h) A comparison with recently reported advanced sensors based on different types of single metal NP decorated MOSs in terms of H2 sensing performance. Reproduced with permission from ref. 90. Copyright 2022 Elsevier.

In particular, compared with widely used Pd NPs, bimetallic NPs demonstrate higher electro-catalytic characteristics due to their specific structure and the synergism of two components.91 At present, the commonly used bimetallic catalysts are PdPt,92 PdAu,93 PdAg,94 PtAu,95,96 PtAg,97 and AgAu97etc. For example, Meng et al.45 proposed that PdPt/SnO2 materials exhibited shape-dependent H2 sensing performances due to the different morphologies of the PdPt sensitizer, such as nano-octahedrons, nanocubes and nanoflowers. Amongst others, the nano-octahedron modified SnO2 (NOS) exhibited ultrahigh response (22821) and superfast response/recovery time (1/8 s) towards 1000 ppm H2 at 25 °C, which was superior to the MOS-based H2 sensing materials reported so far in terms of working temperature, response speed and response value (Fig. 6c–e). Kumar et al.94 demonstrated that the sensor with a 1[thin space (1/6-em)]:[thin space (1/6-em)]1 Ag[thin space (1/6-em)]:[thin space (1/6-em)]Pd/ZnO has shown a high response of 51.36 towards 100 ppm of H2 at an operating temperature of 275 °C. Consequently, the bimetallic NPs can efficiently increase the response value and decrease the operating temperature.

However, the decorated metal NPs on the surface of MOSs tend to undergo facile aggregation and delamination from the MOS-based materials.98 In particular, the surfaces of metal NPs can be easily poisoned by many chemicals that contain sulfur (H2S, SO2, and thiols) or phosphorus.99 Therefore, the metal@oxide core–shell nanostructures can overcome the above-mentioned drawbacks. In this context, core–shell sensing materials can offer a substantial increase in surface area, structural stability, enhanced activities, and synergistic properties.100 For instance, Nguyen et al.90 reported that PdPt@ZnO core–shell nanoparticles (CSNPs) exhibited impressive H2 sensing performances. The results showed that the PdPt@ZnO sensor displayed a high response of 48 with respect to Pd@ZnO (22), Pt@ZnO (14), and free ZnO (9), along with fast response and recovery times (0.7 and 3 min) to 100 ppm H2 at 350 °C. Here, the various core–shell sensors all exhibited a higher response towards each of the tested target gases (especially towards H2) compared to that of the pure ZnO (Fig. 6f and g). Further, the superiority of the PdPt@ZnO CSNPs over other previously reported devices for H2 detection was indicated in Fig. 6h. The observed enhancements can be ascribed to several factors: (1) the exceptional catalytic activity of the alloyed PdPt core, (2) the abundant presence of oxygen vacancies and chemisorbed oxygen in the ZnO shell, (3) the facile two-way transfer of electrons between the core and shell, and (4) the substantial surface area and porosity exhibited by CSNPs. From this perspective, diverse core–shell nanostructures based on MOSs have been reported as highly sensitive and selective H2 sensing layers.90,101,102

3.4. Doping of elements

Many investigations have indicated that doping of elements can significantly influence the morphology, crystal structure, adsorption capacity, and electrical properties of materials, thus serving as a prevalent strategy to enhance the gas-sensing performance of MOSs. In particular, when elements enter the lattice of MOS as accepter or donor impurities, they induce a shift in the Fermi level and consequently change the band structure.103 For n-type semiconductors, the Fermi level shifts up after the introduction of the donor impurity (providing electrons), because the donor impurity can introduce a set of fully occupied energy levels in the forbidden band near the conduction band, known as the donor level. Electrons at this level can readily transition to the conduction band, facilitating electrical conductivity. For p-type semiconductors, upon introducing an acceptor impurity (providing holes), there is a downward movement of the Fermi level. This is because the acceptor impurity introduces a set of completely unoccupied energy levels within the forbidden band close to the valence band, referred to as the acceptor level. Electrons in the valence band can easily transition to this level, leaving behind holes that contribute to conductivity in the valence band. So far, numerous MOSs doped by various elements have been developed, including SnO2, Fe2O3, CuO, ZnO, and TiO.104–109

For example, Li et al.105 employed the electrospinning and calcination technique to incorporate La3+ ions into SnO2 nanofibers at varying atomic molar ratio (AMR) concerning Sn. They found that the introduction of La changes the grain size of SnO2. The average grain sizes of SnO2 nanofibers and La-doped SnO2 nanofibers (Fig. 7a) were calculated to be 11.9 nm (AMR 0), 11.5 nm (AMR 0.5%), 11.4 nm (AMR 1%) and 11.7 nm (AMR 3%), respectively. And all the La-doped SnO2 showed higher sensitivity than pristine SnO2 due to the polaron effect induced by La, which can provide fast dissociative adsorption of H2 on the surface (Fig. 7b). Among them, the sensor with 1% AMR exhibited the best H2 sensing performance (Fig. 7b and c). In addition, Hsiao et al.108 developed five different doping concentrations ranging from 0 to 4% W to the ZnO structure to find an appropriate doping concentration in H2 sensing. As shown in Fig. 7d, the grain structure was uniformly deposited on the surface (Fig. 7d(vi)), and with an increase in the doping concentration of W, the grain size of W-doped ZnO decreased correspondingly (Fig. 7d(i)–(v)) due to the smaller ionic radius of W (0.064 nm) compared to that of Zn (0.074 nm). Furthermore, the performance test results showed that the optimal doping concentration of W was 3% and the optimal working temperature was 150 °C (Fig. 7e). As depicted in Fig. 7f, the 3% W doped ZnO exhibited a high response of 67% for 100 ppm concentration of H2 at 150 °C. Herein, W served as a catalyst for enhancing the adsorption of oxygen species on the surface of ZnO.


image file: d4cc05430j-f7.tif
Fig. 7 (a) SEM images of the SnO2 nanofibers with La doping concentrations at (i) 0%, (ii) 0.5%, (iii) 1%, and (iv) 3%. (b) Response of SnO2 and La-doped SnO2 nanofibers to 100 ppm H2 at different operating temperatures. (c) Response of SnO2 and 1% La-doped SnO2 to different H2 concentrations from 5 to 35[thin space (1/6-em)]000 ppm. Reproduced with permission from ref. 105. Copyright 2019 Elsevier. (d) SEM images of ZnO with W doping concentrations at (i) 0%, (ii) 1%, (iii) 2%, (iv) 3%, and (v) 4%. (vi) Cross-sectional image of W(4%)/ZnO. (e) Response of W(3%)/ZnO to H2 from 20 to 100 ppm at different temperatures. (f) Response–recovery curve of W(3%)/ZnO to different H2 concentrations ranging from 20 to 100 ppm at 150 °C. Reproduced with permission from ref. 108. Copyright 2023 Elsevier. (g) SEM and TEM images of α-Fe2O3 and Mn/α-Fe2O3-5. (i) SEM image of α-Fe2O3, (ii) TEM image of α-Fe2O3, (iii) SEM image of Mn/α-Fe2O3-5, (iv) TEM image of Mn/α-Fe2O3-5. (h) Schematic diagram of the core/shell conductive structure of α-Fe2O3 and Mn doping of α-Fe2O3 in the air and Mn doping of α-Fe2O3 in different H2 concentrations. (i) Response of α-Fe2O3, Mn/α-Fe2O3-20, Mn/α-Fe2O3-10, Mn/α-Fe2O3-5, and Mn/α-Fe2O3-2 to 200 ppm H2 with different temperatures. Reproduced with permission from ref. 106. Copyright 2022 Elsevier.

In addition to affecting the morphology of materials, doped elements can also reduce the charge carrier concentration and affect the thickness of the material space charge layer by causing hole electron recombination in MOSs, thus improving the sensor sensitivity.110 For instance, Ai et al.106 reported that Mn-doped α-Fe2O3 synthesized by the hydrothermal method in H2 sensing. Herein, the morphology of α-Fe2O3 changed from rod to polyhedron by introducing Mn, as depicted in Fig. 7g. Furthermore, it was observed that the substitution of high-priced Fe ions with low-priced Mn ions led to the formation of a relatively high concentration of surface oxygen vacancy defects on the Mn/α-Fe2O3-x nanoparticles. Consequently, compared to α-Fe2O3, Mn/α-Fe2O3-x exhibited an increased adsorption capacity for oxygen ions (Fig. 7h). Upon exposure to H2 gas, the trapped electrons were released into Mn/α-Fe2O3-x through the reaction between H2 molecules and absorbed oxygen ions, resulting in a reduction in the thickness of the hole accumulation layer (Fig. 7h). Therefore, this change in carrier concentration caused by gas reactions resulted in a more significant alteration in sensor resistance and consequently enhanced gas response (Fig. 7i). Consequently, doping of elements can significantly improve the performance of MOS-based H2 sensors in various aspects.

3.5. MOS-based composites

The incorporation of MOSs with other materials can improve the H2 sensing properties due to their synergistic effect. The introduction of other materials into MOSs can lead to the formation of heterojunctions, which updates the charge distribution within the material and establishes a barrier at the material interface. This results in carrier depletion in one material and carrier accumulation in another, thereby significantly altering the total number of charge carriers present and enhancing both the sensitivity and selectivity of the sensor.11,111,112

Notably, the electronic properties of heterojunctions rely fundamentally on band alignment/bending and the accompanying charge transfer/separation. For semiconductor–semiconductor heterojunctions, three distinct types of band alignments exist, namely straddling (type I), staggered (type II), and broken gap (type III).113 Regarding the type I band alignment, the conduction band minimum (CBM) and valence band maximum (VBM) of both semiconductor materials are straddled, making the two band edges of one material completely fall into another.113 This results in the spontaneous transfer of electrons and holes from the large-bandgap material to the small-bandgap material, which improves the migration efficiency of charge carriers without providing additional energy, thereby further enhancing the H2 sensing performance (Fig. 8a). In the case of type II band alignment, there is a staggered arrangement of band edges between the two materials, resulting in only the CBM of one material falling within the bandgap of the other material.113 Unlike type I band alignment, this alignment allows for effective spatial separation of holes and electrons as they are transferred to different materials, which significantly increases the concentration of charge carriers, thereby improving the sensitivity of H2 sensors. The type III band alignment is characterized by a complete breaking of the band edges between the two materials, with the CBM of one material positioned lower than the VBM of the other material, indicating a partial overlap between their respective bands (Fig. 8c).113 However, heterostructures with type III band characteristics are relatively rare due to the unique nature of band structures and there is no migration of electrons and holes between the two materials. Consequently, there are few research studies on hydrogen sensors based on type III heterojunctions.


image file: d4cc05430j-f8.tif
Fig. 8 Schematic of three types of heterojunctions. (a) Type of straddling. (b) Type of staggered. (c) Type of broken gap.

To date, extensive reports have been published on the utilization of MOSs for forming heterojunctions to enhance the performance of H2 sensors, including SnO2/Sb2O3,114 SnO2/WO3,115 SnO2/ZnO,116 In2O3/ZnO,117 and In2O3/SnO2.118 For example, Wang et al.117 investigated the effect of In2O3 modified by ZnO with different weight percentages on H2 sensing performance. As depicted in Fig. 9a, the ZnO synthesized by calcination of precursor ZIF-8 with a regular dodecahedral structure and the In2O3 exhibited two different crystal phases, namely cubic phase c-In2O3 (Inc) and hexagonal h-In2O3 (Inh). The H2 sensing performance test results demonstrated that the ZnO (5%)-Inc/Inh-based sensor exhibited the highest sensitivity at 450 °C when ZnO constituted 5 wt% of In2O3 (Fig. 9b). Herein, the n-type In2O3 and n-type ZnO formed a type II heterojunction, as shown in 7c. When exposed to H2, the adsorbed oxygen on the surface of ZnO (5%)-Inc/Inh reacted with H2, resulting in the release of electrons that effectively reduced the potential barrier and significantly enhanced the conductivity of the sensitive layer. Furthermore, the performance advantages of ZnO-Inc/Inh were investigated using density functional theory. The response of the composite system consisting of c-In2O3 and h-In2O3 to H2 was theoretically more pronounced compared to that of the single crystalline phase In2O3. In addition, the incorporation of ZnO results in more pronounced charge transfer, variations in band gap, and alterations in the density of states in the composite, thereby indicating the presence of enhanced H2 sensing performance.


image file: d4cc05430j-f9.tif
Fig. 9 (a) SEM images of (i) ZnO and (ii) Inc/Inh; HRTEM images of (iii) Inc/Inh and (iv) ZnO-Inc/Inh. (b) Response of Inc/Inh-based sensors to 2000 ppm H2 at different operating temperatures ranging from 100 to 500 °C. (c) Sensing mechanism of the heterojunction between In2O3 and ZnO. Reproduced with permission from ref. 117. Copyright 2024 Elsevier. (d) (i) SEM image of 10 wt% MXene–SnO2, (ii) HRTEM image of SnO2, and (iii) and (iv) HRTEM image of 10 wt% MXene–SnO2. (e) Response of SnO2-based sensors to 600 ppm H2 at different operating temperatures ranging from 200 to 500 °C. (f) Schematic diagram of the heterojunction between MXene and SnO2. Reproduced with permission from ref. 119. Copyright 2024 Elsevier. (g) SEM images of t-ZnO@ZIF-8 at different reaction times of 4, 8, 20, and 60 h. (h) Selectivity of the t-ZnO@ZIF-8 (4 h)-based sensor to 100 ppm of different gases at different operating temperatures on log10 scales. (i) Response–recovery curve of t-ZnO@ZIF-8 (4 h) to 100 ppm H2 in CH4 at 100 °C. Reproduced with permission from ref. 120. Copyright 2023 American Chemical Society.

In addition to MOS/MOS-based composites, the integration of MOSs with other materials can also give rise to heterojunctions, such as graphene,121 MoS2,122 WS2,123 and MXene.119 Recently, Chen et al.119 compared the H2 sensing performance of single SnO2 and a MXene–SnO2 composite. As illustrated in Fig. 9d, the connection between the hexagonal SnO2 nanosheets and the MXene layered nanomaterial was well-established. Compared to the single SnO2-based sensor, all the MXene–SnO2-based sensors exhibited a significantly enhanced response to H2. Notably, among them, the 10 wt% MXene–SnO2-based sensor demonstrated the highest sensitivity at an optimal temperature of 400 °C (Fig. 9e). Herein, the p-type MXene and the n-type SnO2 participated in the formation of p–n heterostructures in the composite (Fig. 9f), which enhanced the H2 sensing properties due to the strong interaction formed by the surface adsorption of the H2 molecular heterojunction interface.

Moreover, the incorporation of MOFs with MOSs is commonly employed to enhance selectivity owing to their tunable pore sizes, which enables them to function as molecular sieves.120,124,125 For instance, Poschmann et al.120 reported a ZIF-8 functionalized single-crystalline tetrapodal ZnO gas sensor, which can detect H2 in CH4. Amongst others, the formation of ZIF-8 was achieved through the reaction between ZnO tetrapods (t-ZnO) and evaporating 2-methylimidazole (HMeIM), followed by gas-phase crystallization to obtain t-ZnO@ZIF-8. As shown in Fig. 9g, the amount of ZIF-8 formed and the thickness of the ZIF-8 coating were significantly influenced by the reaction time, with a higher conversion of t-ZnO into ZIF-8 for observed longer reaction times. Among them, the t-ZnO@ZIF-8 (4 h) sample was selected for gas sensing behavior study due to the decrease in surface area of tetrapod arm ends with increased reaction time, making electrical contact more challenging; additionally, thin MOF coatings can result in faster response/recovery speed. As depicted in Fig. 9h, the t-ZnO@ZIF-8 (4 h)-based sensor had no response for all tested gases at room temperature; however, with the operating temperature increasing, it exhibited extremely high response to H2 with a high selectivity. The exceptional sensing performance can be summarized as follows: (1) ZIF-8 acted as a molecular sieve, enhancing the selectivity and sensitivity of t-ZnO to H2; (2) the formation of ZIF-8 introduced defects at the interface with t-ZnO, enabling modulation of the resistance of single crystalline ZnO by H2 in the absence of atmospheric O2. Furthermore, they tested the response of a t-ZnO@ZIF-8 (4 h)-based sensor to 100 ppm H2 in CH4. However, the presence of CH4 did not affect the fast response to H2 of the sensor. Therefore, it should also be feasible to quantify the concentration ratio of an H2/CH4 mixture, rendering it a promising sensor for H2 detection in natural gas pipelines. From this perspective, the introduction of selective sieving layers on MOSs is one of the most promising strategies to attain enhanced selectivity towards H2.

To date, the performance of MOS-based H2 sensors has been significantly enhanced through various improvement methods. Table 2 summarizes the sensing characteristics of recently reported MOS-based H2 sensors. The response values, response/recovery times, selectivity, long-term stability, and detection limits of a few sensors have been demonstrated to be exceptional at room temperature. However, the practical applications of the majority of sensors are still hindered by their requirement for operation at high temperatures. At elevated operating temperatures, other gas molecules are also able to react with MOSs, leading to resistance changes and consequently compromising the selectivity of MOS-based sensors. Additionally, prolonged exposure to high temperatures can adversely impact the long-term stability of sensors by diminishing their sensitivity and shortening their lifespan. Furthermore, MOS-based sensors are also prone to the influence of H2O molecules in the surrounding environment. Hence, operating at near room temperature and exhibiting excellent humidity resistance in practical applications are essential for MOS-based H2 sensors.

Table 2 Summary of sensing properties of MOS-based H2 sensors
Material Morphology Conc. (ppm) Tem. (°C) Res. T res/Trec (s) MDL (ppm) Ref.
Conc.: gas concentration; Tem.: operating temperature of the sensor; RT: room temperature (∼25 °C); Res.: response of the sensor.a Response is defined as Rgas/Rair.b Response is defined as (RgasRair)/Rair × 100%.c Response is defined as (IgasIair)/Iair × 100%.d response is defined as Igas/Iair; Tres: response time of the sensor; Trec: recovery time of the sensor; MDL: minimum detection limit of the sensor; Ref.: reference; —: not reported; 3D: three-dimensional.
SnO2 Nanowires 150 250 54a 19/45 0.5 66
ZnO Nanorods 80 180 483%b 15.1/100.1 0.5 67
Sn3O4 Nanosheets 10 150 2.2a 9.4/24 0.05 69
ZnO Hollow hexahedron 300 250 101%b 611/1137 5 75
Pd/SnO2 Nanowires 40 150 8.5a 6/3 66
Pd/CeO2 Hollow strings 10[thin space (1/6-em)]000 RT 2.68%b 10/— 100 71
Pd/SnO2 Nanoparticles 500 125 254a 1/22 10 83
Ag/ZnO Hollow hexahedron 300 250 479%b 175/655 5 75
Pt/TiO2 Nanorods 1 RT 1.21a 42/30 1 88
Pd/WO3 Nanoflowers 500 150 8658.98a 1/3 20 89
Pd–Au/In2O3 Nanocubes 500 250 55a 5/3 0.3 73
PdPt@In2O3 Spheres 100 RT 29.8a 58/200 5 102
Ag–Pd/ZnO Nanorods 100 275 51.36a 94
PdPt@ZnO Nanoparticles 100 350 48a 0.7/180 0.5 90
Pd–Au@SnO2 Nanorods 100 175 46.4a 19/302 25 93
Au@Pd/SnO2 Nanospheres 100 100 16.75a 1/5 10 91
PdPt/SnO2 Nano-octahedrons 1000 RT 22821a 1/8 100 45
Mn/α-Fe2O3 Polyhedrons 200 300 63.5a 10/24 10 106
Cu/TiO2 Films 1000 200 2284%c 128/129 109
W/ZnO Films 100 150 67%b 20 108
Cu/SnO2 Multilayer 3D 100 180 45%b 18/84 20 110
In2O3/SnO2 Nanofibers 50 350 3.5a 1.1/1.9 50 118
SnO2/WO3 Spheres/plates 500 150 91%b 35/269 10 115
In2O3/ZnO Nanoparticles/dodecahedrons 5000 450 79.91a 1/6 0.053 117
SnO2/ZnO Films 30 200 93a 50/29 0.25 116
Pd–WO3/WS2 Nanoflowers 1000 125 4227.35a 1/25 20 123
SnO2/MXene Nanosheets 500 400 76%b 13/15 10 119
ZnO@ZIF-8 Tetrapods 100 100 546d 2/2 5 120


4. Others

4.1. Graphene

Graphene has gathered significant interest as a sensing material owing to its large specific surface area, high carrier mobility, high conductivity, and excellent physical and chemical properties.126 It has been demonstrated that the gas sensing mechanism based on graphene heavily relies on physisorption.127 Physisorption refers to the absorption of gas molecules onto the surface of sensing materials through intermolecular forces (van der Waals force) without forming chemical bonds, and the corresponding charge transfer mechanism does not rely on the breakdown of the absorbed gas. Gas molecules absorb on the surface of graphene and act as electron donors or acceptors.127 Herein, H2 molecules serve as electron donors (Fig. 1c). It is worth noting that this absorption process can occur at low temperatures and in the absence of oxygen. However, it always requires the sensing material with a favorable surface adsorption energy value for the target gas molecules and optimal electronic band structure facilitating the charge transfer.128 Additionally, physisorption exhibits some problems including poor reversibility and weak response magnitude. Based on these results, bare graphene is not great for H2 sensing, so the introduction of catalysts to enhance the H2 adsorption was crucially important.

So far, many H2 sensors based on catalyst-functionalized graphene have been reported.129–132 For instance, Zhu et al.129 designed a flexible H2 sensing film based on Pd nanoclusters/reduced graphene oxide (rGO) via one-step vacuum filtration. Amongst others, the rGO/Pd film sensor demonstrated superior response, rapid response/recovery kinetics, and exceptional stability in comparison to the bare rGO film due to the pronounced catalytic effect of ultrasmall (3.3 nm) Pd nanoclusters. Besides, the rGO/Pd-based flexible film sensor achieved a stable response to 2% H2 after different bending states and still maintained excellent sensing performance after suffering from repeated bending/recovery deformations (Fig. 10a–c).


image file: d4cc05430j-f10.tif
Fig. 10 (a) Photos of the rGO/Pd film at different bending degrees. (b) Response value and response time of the rGO/Pd-based sensor to 2% H2 under different bending degrees at room temperature. (c) Response value and response time of the rGO/Pd-based sensor to 2% H2 at room temperature after different bending cycles (one cycle: from 0° to 180° and back to 0°). Reproduced with permission from ref. 129. Copyright 2022 Elsevier. (d) Response–recovery curves of PdNPs (3 nm, the thickness of Pd layer)/2D graphene and (e) PdNPs (3 nm)/3D graphene to 3% H2 at 30 °C. Reproduced with permission from ref. 131. Copyright 2024 Elsevier. (f) Response of G, Sb, and Sb/G-based sensors to different H2 concentrations ranging from 0.05–5 ppm at room temperature. Reproduced with permission from ref. 133. Copyright 2024 Elsevier. (g) The response–recovery curve of the PMMA-Pd-SWNT sensor to different H2 concentrations ranging from 0.002–2% at room temperature. (h) Response/recovery time of the PMMA-Pd-SWNT sensor to 1% H2 at room temperature. (i) Response–recovery curves of the PMMA-Pd-SWNT sensor for different humidity to 0.1% H2 at room temperature. Reproduced with permission from ref. 134. Copyright 2023 Wiley-VCH GmbH.

However, limited research has been conducted on enhancing the sensing performance through structural modifications of graphene. According to some reports, graphene obtained through exfoliation and chemical vapor deposition (CVD) exhibits chemical inertness due to the absence of dangling bonds,135 while the nanocomposites based on 2D graphene tend to aggregate owing to π–π stacking and van der Waals forces acting between the layers of graphene.131,136,137 These will all lead to the degradation of the H2 sensing properties. Thus, to take full advantage of graphene, it is important to modify the intrinsic 2D structure of graphene. Recently, Lee et al.131 developed an H2 sensor based on Pd-decorated 3D graphene, which was fabricated by introducing Cu vapor as the remote catalyst in a metal–organic CVD system to directly grow 3D graphene on 300 nm SiO2/Si substrates and decorating with thermally evaporated Pd NPs. As shown in Fig. 10d and e, when the same thickness of Pd NPs were deposited on 2D and 3D graphene, the 3D graphene demonstrated a higher response of 41.9% towards 3% H2 at 30 °C because of the larger surface area and dense distribution of Pd NPs on 3D graphene than those of 2D graphene. Therefore, this study provides a new idea for the improvement of the H2 sensing properties.

On the other hand, the heterostructures of graphene-based composites also display interesting H2 sensing characteristics. In the heterostructures, graphene serves as a versatile platform, which not only possesses a huge specific surface area but also provides a highly conductive path for charge transport upon gas adsorption and desorption. For example, Kumar et al.133 fabricated a class of heterostructures based on 2D Pnictogens and graphene by photolithography and pattern transfer methods for H2 detection at room temperature. Amongst the Pnictogen class, antimonene/graphene (Sb/G) showed excellent H2 sensing properties. As depicted in Fig. 10f, the Sb/G heterostructure displayed a superior response of 54.5 towards 5 ppm H2 as compared to individual Sb (15.3) and G (12.1). Besides, it also showed short response/recovery time (12/34 s), low detection limit (50 ppb), high selectivity, and long-term stability. In a nutshell, the extraordinary H2 sensing behavior can be ascribed to the heterostructure and electronic states, which provided a large density of active pathways, a high surface-to-volume ratio, and a tunable Schottky barrier. Thus, it provides the possibility to expand a novel family of Pnictogen-graphene sensors.

4.2. CNTs

CNTs have been investigated for real-time detection of gases at room temperature due to their high-quality crystal lattices, tunable electrical properties, and chemical sensitivity.138,139 However, similar to graphene, the bare CNTs have no appreciable interaction with H2, thus necessitating the exploration of suitable H2 sensitive materials for CNTs functionalization.140 To date, Pd is the most commonly employed catalyst for H2 sensing due to its superior selectivity in absorbing H2, while conducting polymers are commonly used as molecular sieves.134,141–144 Moreover, there are also reports available based on Pt/CNTs.145,146 Typically, CNTs are employed to enhance the conductivity of the composites, thereby improving the efficiency of electron transport and aggregation. Additionally, they act as supporting frameworks for increasing the surface-to-volume ratio, providing more active sites and consequently enhancing the absorption of H2.147

Recently, Du et al.141 constructed nanoarchitectures of Pd and poly-3, 4-ethylenedioxythiophene (PEDOT) coatings on multi-walled CNTs, which achieved dual H2 and NH3 detection. Herein, the multi-walled CNTs were used for both improving the surface ratio and assisting electron transfer. Notably, the PEDOT@CNTs exhibited negligible sensitivity to H2, indicating that the presence of PEDOT wrapping on the CNTs did not directly influence H2 sensing. Instead, the H2 sensing capability of Pd&PEDOT@CNTs was primarily governed by the Pd NPs. Furthermore, it was also observed that the size distribution of the Pd NP coating on the CNTs also affected the H2 sensing characteristics. In another case, Girma et al.134 successfully fabricated reproducible and highly sensitive semiconducting single-walled carbon nanotube (SWNT) sensors by coating PMMA and decorating Pd. The uniform-density and monolayer SWNT films were synthesized using chemical immobilization through the click reaction between azide-functionalized polymer-wrapped SWNTs and immobilized alkyne polymer on a substrate before decorating with Pd nanoparticles (0.5–3.0 nm). As illustrated in Fig. 10g and h, the PMMA-Pd-SWNT sensor demonstrated a wide detection range of H2 concentrations (0.002–2%) and a high response up to 285 at 1% H2 with the response/recovery time of 10/3 s at room temperature. Amongst others, Pd efficiently reduced the activation energy of the surface reactions and enhanced the adsorption of H2 and desorption of H2O molecules, while the PMMA layer greatly optimized the film morphology and reduced the apparent activation energy, contributing to a high response and a fast response/recovery speed. Furthermore, the introduction of the PMMA layer effectively prevented H2O molecules from diffusing and allowed H2 permeation, which guaranteed stable operation at high humidity of the PMMA-Pd-SWNT sensor (Fig. 10i).

In addition to catalyst type and size distribution, the band gap of CNTs also exerts an influence on H2 sensing performance. The difference in the band gap of CNTs will restrict the transition of electrons from the valence to the conduction band, resulting in an unequal number of holes in the valence band. For example, Zhang et al.144 explored the effect of the diameters of SWNTs on H2 detection. The results demonstrated that the response of the sensor with 0.7–1.2 nm SWNTs to 1 ppm H2 was approximately 6 times compared to that of the one with 1.2–1.6 nm. That was because the wider band gap of 0.7–1.2 nm p-type SWNTs resulted in fewer holes in the valence band and easier depletion of holes by electrons from the dissociation of H2. Therefore, researchers can optimize the performance of CNT-based H2 sensors from multiple perspectives, including type of catalysts, size distribution of catalysts, and band gap of CNTs.

4.3. TMDs

Recently, 2D TMDs have demonstrated great potential for gas detection at room temperature due to their high surface-to-volume ratio, high carrier mobility, and tunable electrical and chemical properties.148,149 To date, numerous studies have demonstrated the physisorption of H2 on the surface of TMDs at room temperature.128,150,151 However, TMDs always display relatively lower adsorption energy compared to other gases (such as NO2, NO, CO, NH3, CH4, CO2),128,151 which is not conducive to developing highly sensitive and selective H2 sensors based on pure TMDs. Therefore, extensive investigations have been conducted to address this issue by researchers. So far, many literatures have suggested that it is efficient to improve the TMD-based H2 sensing properties by combining catalysts with TMDs.152–154

For instance, Jiaswal et al.153 reported a highly sensitive and selective H2 sensor based on Pd NP-functionalized MoS2 thin films. They prepared Pd/MoS2 thin films via a single-step DC magnetron sputtering technique. As illustrated in Fig. 11a–c, compared to the pristine MoS2 sensor, the Pd/MoS2 sensor exhibited significantly enhanced H2 sensing characteristics, including a high response of 33.7%, fast response/recovery time of 16/38 s to 500 ppm H2 at room temperature, low detection limit of 1 ppm, and high H2 selectivity against NH3, NO2, H2S, and ethanol. Therefore, the introduction of Pd NPs improved the sensing performance of MoS2 owing to the catalytic activity of Pd and the creation of the Schottky barrier at the junction between Pd NPs and the MoS2 semiconductor.


image file: d4cc05430j-f11.tif
Fig. 11 (a) Response–recovery curve of Pd/MoS2 to different H2 concentrations ranging from 10–500 ppm at room temperature; the inset shows a response–recovery curve of Pd/MoS2 to 500 ppm H2 at room temperature. (b) Response/recovery times of Pd/MoS2 and MoS2 to 500 ppm H2 at room temperature. (c) Selectivity of Pd/MoS2 to 500 ppm H2 in comparison with interfering gases including NH3, NO2, H2S, and ethanol at room temperature. Reproduced with permission from ref. 153. Copyright 2020 Elsevier. (d) The response–recovery curve of Pt@MoS2 to different H2 concentrations ranging from 0.5–50 ppm. (e) Repeatability of Pt@MoS2 to 50 ppm H2 at room temperature. (f) Selectivity of Pt@MoS2 to 50 ppm H2 in comparison with interfering gases including NO2, NH3, H2S, SO2, and CO2 at room temperature. Reproduced with permission from ref. 154. Copyright 2023 American Chemical Society. (g) Structure diagram of Pt = Pd/Ti3C2Tx. (h) Response/recovery times of Ti3C2Tx-based sensors to 200 ppm H2 at room temperature; Pt–Pd represents an alloy of Pt and Pd. (i) Response–recovery curves of Ti3C2Tx-based sensors to 1 ppm and 20[thin space (1/6-em)]000 ppm H2. Reproduced with permission from ref. 155. Copyright 2023 Elsevier. (j) Response–recovery curves of PdCu and PdCu/Ti3C2Tx to different H2 concentrations ranging from 0.5–4% at 25 °C. (k) Response–recovery curve of PdCu/Ti3C2Tx nanocomposites to different H2 concentrations ranging from 0.1–40% at 25 °C. Reproduced with permission from ref. 156. Copyright 2024 Elsevier.

In addition to incorporating Pd NPs, Pt NPs were also integrated into 2D TMDs for the advancement of H2 sensors. Wadhwa et al.154 developed vertically aligned large-area MoS2 flakes with enhanced H2 sensing characteristics modified by Pt NPs. The presence of Pt NPs offered a surface reaction between H atoms and MoS2 and supported the diffusion of H atoms into MoS2. As depicted in Fig. 11d, the Pt@MoS2-based sensor showed a high response of 23.2% to 50 ppm H2 and an ultra-low detection limit of 0.5 ppm at room temperature, whereas the pristine MoS2 only had a response of 9%. Besides, it displayed excellent repeatability and high selectivity (Fig. 11e and f). Therefore, it is imperative to modify TMDs with sensitizers, to develop TMD-based H2 sensors with high sensing properties.

4.4. MXenes

MXenes represent a class of ternary, layered, machinable transition metal carbide, nitride and carbon nitride two-dimensional materials, and their chemical formula is Mn+1AXn, where n = 1, 2, or 3, “M” is an early transition metal, “A” is a group of A (mostly groups 13 and 14), and “X” is the C element or N element.157 In particular, MXenes exhibit a narrow band gap, a large specific surface area, an abundance of surface functional groups, and a high electron transfer rate,157 rendering them highly suitable for applications in the field of H2 detection. Herein, the sensing mechanisms for MXenes are similar to the above-mentioned MOS-based H2 sensors.

Charan et al.158 synthesized Ti3C2 nanosheets by selective etching of the Al layer from a prefabricated MAX phase (Ti3AlC2) percusor using hydrofluoric (HF) acid, which demonstrated a response of 1.24 with a response/recovery time of 32/125 s to 3000 ppm H2 at room temperature. However, the pure MXene-based H2 sensors usually present certain challenges including long response time, poor repeatability, and baseline drift.119,158 Therefore, researchers have tried to employ metal NPs for the functionalization of MXenes or combine MXenes with other materials to augment their H2 sensing properties.155,156,159,160 For instance, Wang et al.155 prepared spatially separated Pt and Pd modified Ti3C2Tx (Pt = Pd/Ti3C2Tx, Fig. 10g) by a hydrothermal chemical reduction, which displayed excellent sensing performance at room temperature. A comparison of H2 sensing performance between four different Ti3C2Tx-based sensors modified by Pt, Pd, Pt–Pd alloy, and Pt = Pd respectively was shown in Fig. 11h and i. All of them exhibited high responses to different H2 concentrations at room temperature, whereas the pure Ti3C2Tx-based sensor almost had no response to H2. Among them, the Pt = Pd/Ti3C2Tx-based sensor demonstrated the best sensing performance including the highest response value (24.6%) and the shortest response/recovery time (6/8 s) to 200 ppm H2. Besides, it also exhibited an ultra-low limit of detection of 1 ppm (Fig. 11i), good repeatability, long-term stability, and high selectivity. Herein, Pt can enhance the dispersion of the Pt = Pd owing to the strong metal–support interaction (SMSI) effect and Pd had high adsorption and dissociation activity for H2, so compared to monometallic-modified Ti3C2Tx the Pt = Pd/Ti3C2Tx showed superior H2 sensing performances. Additionally, the higher H2 sensing capabilities of Pt = Pd/Ti3C2Tx than Pt–Pd/Ti3C2Tx can be ascribed to the alloy formation of Pt–Pd weakening the electron transfer.

In addition, Qiu et al.156 reported a 3D PdCu-modified Ti3C2Tx nanocomposite prepared by a self-sacrificing template method. As depicted in Fig. 11j, compared to PdCu NPs, the PdCu/Ti3C2Tx nanocomposites showed superior H2 sensing behavior. Notably, the PdCu/Ti3C2Tx nanocomposites exhibited consistent and stable response and recovery behaviors when exposed to a wide range of H2 concentrations from 0.1 to 40% (Fig. 11k). Herein, the synergistic interaction and the heterostructure between PdCu NPs and Ti3C2Tx resulted in the outstanding sensing performance of the PdCu/Ti3C2Tx nanocomposites. Based on these findings, the utilization of metal NPs for the functionalization of MXenes and their integration with other materials have demonstrated remarkable efficacy in enhancing their hydrogen sensing capabilities.

So far, emerging materials, including graphene, CNTs, TMDs, and MXens, have exhibited some advancements in the realm of H2 sensing. Table 3 summarizes the sensing performance of these materials in recent years. The sensing performance of these materials is highly efficient at room temperature; however, certain challenges persist. Graphene and CNTs exhibit low selectivity towards polar molecules and poor reproducibility. TMD-based H2 sensors demonstrate prolonged response/recovery times, susceptibility to oxygen interference in ambient air, and high reactivity towards polar gases. Additionally, MXenes display inadequate sensing performance for low concentrations of H2.

Table 3 Summary of the sensing properties of other H2 sensors
Material Conc. Tem. (°C) Res. T res/Trec (s) MDL (ppm) Ref.
Conc.: gas concentration; Tem.: operating temperature of the sensor; RT: room temperature (∼25 °C); Res.: response of the sensor.a Response is defined as Rair/Rgas.b Response is defined as (RgasRair)/Rair × 100%.c Response is defined as Rgas/Rair; Tres: response time of the sensor; Trec: recovery time of the sensor; MDL: minimum detection limit of the sensor; Ref.: reference; —: not reported; HKUST-1: MOF copper(II) benzene-1,3,5-tricarboxylate.
rGO/Pd 2% RT 2.28a 18/— 2500 129
Pd-GO 35 ppm 100 2.1%b 18/20 130
Sb/G 5 ppm RT 54.5a 12/34 0.05 133
PMMA-Pd-SWNT 1% RT 285c 10/3 20 134
Pd/HKUST-1/SWNT 1 ppm RT 6.09c —/1 1 144
Pt/MoS2 1% RT 8.7%b 8.1/16 500 152
Pd/MoS2 500 ppm RT 33.7%b 16/38 10 153
Pt/MoS2 50 ppm RT 23.2%b 33/121 0.5 154
Ti3C2 3000 ppm RT 1.24a 32/125 500 158
PdCu/Ti3C2Tx 2% RT 20%b 4/35 1000 156
Pt = Pd/Ti3C2Tx 200 ppm RT 24.6%b 6/8 1 155


5. Conclusion and outlook

With the widespread application of hydrogen energy sources in various fields, there is a growing demand for high-performance chemiresistive H2 sensors. In this review, we present a comprehensive overview of the recent advancements in chemiresistive H2 sensors and provide a summary of the strategies employed for enhancing performance. For Pd-based sensors, the suppression of the phase transition and improvement in selectivity can be achieved through various approaches, encompassing nanostructure construction, device optimization, bimetallic formation, and integration with other materials. In the case of MOS-based sensors, enhancement of performance and reduction in operating temperature are attained via nanostructure design, surface modification, doping, and heterostructure construction. Regarding materials like graphene, CNTs, TMDs, and MXenes that are not inherently sensitive to H2 themselves; their H2 sensing primarily relies on the incorporation of Pd. In conclusion, we primarily discuss their enhancement mechanisms based on some representative research achievements in recent years.

Table 4 summarizes the advantages and disadvantages of each material. Despite significant advancements in the research of resistive H2 sensors, there still exist certain challenges that necessitate further enhancements:

Table 4 Summary of the advantages and disadvantages of each kind of material for chemiresistive H2 sensors
Material Advantages Disadvantages
Pd-based High selectivity Poor long-term stability to high concentrations of H2
Operating at room temperature Long response/recovery time
High cost
MOS-based High sensitivity High operating temperature
Low detection limit Poor selectivity
Rapid response/recovery time Susceptible to humidity
Graphene Operating at room temperature Poor selectivity
Large specific surface area Long response/recovery time
High carrier mobility Low sensitivity
CNTs Operating at room temperature Poor reproducibility
High conductivity Low selectivity
High surface-to-volume ratio
TMDs Operating at room temperature Poor selectivity
Tunable band gap Long response/recovery time
MXene Operating at room temperature Poor sensitivity to low concentrations of H2
Large specific surface area Susceptible to humidity and oxygen


(1) Accurate measurement in different environments: the response signals of most sensors can be influenced by temperature and humidity, thereby constraining the reliability of practical applications for H2 sensors. Furthermore, it is imperative to mitigate the influence of interfering gases in practical applications to achieve precise detection of the target gas. Hence, it is necessary to avoid cross-response and prevent false alarms.

(2) Achieving room temperature detection: most MOS-based H2 sensors still operate at elevated temperatures, which not only improves their power consumption but also shortens their lifespan. Therefore, achieving room temperature operation is of great significance in reducing costs and improving safety in practical applications.

(3) Improving long-term stability: the poor long-term stability remains a significant challenge for most sensors in practical applications, particularly for Pd-based sensors, where achieving linear detection of high concentration H2 while maintaining exceptional long-term stability proves to be arduous.

(4) Exploring novel materials: currently, the development based on Pd and MOS has gradually reached a state of maturity. Hence, it holds immense significance to explore novel materials capable of attaining heightened sensitivity, rapid response, superior selectivity, excellent humidity resistance, and operation at room temperature.

(5) Integration and miniaturization: with the advancement of the Internet of Things, the application scenarios for hydrogen gas sensors are progressively expanding. The integration of multiple functionalities into a compact sensor facilitates meeting diverse requirements across various scenarios.

Author contributions

Yao Yang Liu: writing original draft, collecting references. Zhong Li: writing review & editing, supervision, funding acquisition. Yi Liang: writing review & editing. Tao Tang: writing review & editing. Jing Hao Zhuang: collecting references. Wen Ji Zhang: collecting references. Bao Yue Zhang: writing review & editing. Jian Zhen Ou: writing review & editing, project administration, supervision.

Data availability

No primary research results, software or code and no new date were generated or analyzed as part of this review.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (52172155), the Sichuan Science and Technology Program (2024ZYD0010), the Opening Project of Jiangsu Key Laboratory of Advanced Structural Materials and Application Technology (ASMA202201), and the Fundamental Research Funds for the Central Universities (2682024ZTPY053). We would like to acknowledge Analytical and Testing Centre of Southwest Jiaotong University for field emission transmission microscope JEM-2100F.

References

  1. H. S. Lee, J. Kim, H. Moon and W. Lee, Adv. Mater., 2021, 33, 2005929 CrossRef CAS PubMed.
  2. T. Hübert, L. Boon-Brett, G. Black and U. Banach, Sens. Actuators, B, 2011, 157, 329–352 CrossRef.
  3. B. Jang, W. Kim, M.-J. Song and W. Lee, Sens. Actuators, B, 2017, 240, 186–192 CrossRef CAS.
  4. T. Sahoo and P. Kale, Adv. Mater. Interfaces, 2021, 8, 2100649 CrossRef CAS.
  5. X. Wang, L. Du, L. Cheng, S. Zhai, C. Zhang, W. Wang, Y. Liang, D. Yang, Q. Chen and G. Lei, Sens. Actuators, B, 2022, 351, 130952 CrossRef CAS.
  6. Y. Liu and Y. Li, Sens. Actuators, B, 2016, 227, 178–184 CrossRef CAS.
  7. S. Kim, Y. Song, H.-R. Lim, Y.-T. Kwon, T.-Y. Hwang, E. Song, S. Lee, Y.-I. Lee, H.-B. Cho and Y.-H. Choa, Int. J. Hydrogen Energy, 2017, 42, 749–756 CrossRef CAS.
  8. W.-T. Koo, H.-J. Cho, D.-H. Kim, Y. H. Kim, H. Shin, R. M. Penner and I.-D. Kim, ACS Nano, 2020, 14, 14284–14322 CrossRef CAS PubMed.
  9. Z. Zhi, W. Gao, J. Yang, C. Geng, B. Yang, C. Tian, S. Fan, H. Li, J. Li and Z. Hua, Sens. Actuators, B, 2022, 367, 132137 CrossRef CAS.
  10. A. Dey, J. Mater. Sci. Eng. B, 2018, 229, 206–217 CrossRef CAS.
  11. B. Wang, L. Sun, M. Schneider-Ramelow, K.-D. Lang and H.-D. Ngo, Micromachines, 2021, 12, 1429 CrossRef PubMed.
  12. K. Hu, F. Wang, Z. Shen, Y. Yan and H. Liu, Int. J. Hydrogen Energy, 2021, 46, 20119–20138 CrossRef CAS.
  13. Y. Chen, Z. Li, T. Tang, Y. Cheng, L. Cheng, X. Wang, A. A. Haidry, A. Jannat and J. Z. Ou, ACS Appl. Nano Mater., 2024, 7, 3229–3238 CrossRef CAS.
  14. T. Tang, Z. Li, Y. F. Cheng, H. G. Xie, X. X. Wang, Y. L. Chen, L. Cheng, Y. Liang, X. Y. Hu, C. M. Hung, N. D. Hoa, H. Yu, B. Y. Zhang, K. Xu and J. Z. Ou, J. Hazard. Mater., 2023, 451, 131184 CrossRef CAS PubMed.
  15. T. Tang, Z. Li, Y. F. Cheng, K. Xu, H. G. Xie, X. X. Wang, X. Y. Hu, H. Yu, B. Y. Zhang, X. W. Tao, C. M. Hung, N. D. Hoa, G. Y. Chen, Y. X. Li and J. Z. Ou, J. Mater. Chem. A, 2023, 11, 6361–6374 RSC.
  16. F. Favier, E. C. Walter, M. P. Zach, T. Benter and R. M. J. S. Penner, Science, 2001, 293, 2227–2231 CrossRef CAS PubMed.
  17. F. Yang, S.-C. Kung, M. Cheng, J. C. Hemminger and R. M. Penner, ACS Nano, 2010, 4, 5233–5244 CrossRef CAS PubMed.
  18. V. Kafil, B. Sreenan, M. Hadj-Nacer, Y. Wang, J. Yoon, M. Greiner, P. Chu, X. Wang, M. S. Fadali and X. Zhu, Sens. Actuators, A, 2024, 373, 115440 CrossRef CAS.
  19. I.-D. Kim, A. Rothschild and H. L. J. A. M. Tuller, Acta Mater., 2013, 61, 974–1000 CrossRef CAS.
  20. F. Yang, K. C. Donavan, S.-C. Kung and R. M. Penner, Nano Lett., 2012, 12, 2924–2930 CrossRef CAS PubMed.
  21. R. M. Penner, Acc. Chem. Res., 2017, 50, 1902–1910 CrossRef CAS PubMed.
  22. G. Li, H. Kobayashi, S. Dekura, R. Ikeda, Y. Kubota, K. Kato, M. Takata, T. Yamamoto, S. Matsumura and H. Kitagawa, J. Am. Chem. Soc., 2014, 136, 10222–10225 CrossRef CAS PubMed.
  23. S. K. Konda and A. Chen, Mater. Today, 2016, 19, 100–108 CrossRef CAS.
  24. R. Bardhan, A. M. Ruminski, A. Brand and J. J. Urban, Energy Environ. Sci., 2011, 4, 4882 RSC.
  25. S. H. Jung, K. Kusakabe, S. Morooka and S.-D. J. Kim, J. Membr. Sci., 2000, 170, 53–60 CrossRef CAS.
  26. J. Catalano, M. Giacinti Baschetti and G. C. Sarti, J. Membr. Sci., 2010, 362, 221–233 CrossRef CAS.
  27. C. P. O’Brien and I. C. Lee, J. Phys. Chem. C, 2017, 121, 16864–16871 CrossRef.
  28. D. Gupta, D. Dutta, M. Kumar, P. B. Barman, C. K. Sarkar, S. Basu and S. K. Hazra, Sens. Actuators, B, 2014, 196, 215–222 CrossRef CAS.
  29. M.-S. Jo, K.-H. Kim, K.-W. Choi, J.-S. Lee, J.-Y. Yoo, S.-H. Kim, H. Jin, M.-H. Seo and J.-B. Yoon, ACS Nano, 2022, 16, 11957–11967 CrossRef CAS PubMed.
  30. M.-S. Jo, K.-H. Kim, J.-S. Lee, S.-H. Kim, J.-Y. Yoo, K.-W. Choi, B.-J. Kim, D.-S. Kwon, I. Yoo, J.-S. Yang, M.-K. Chung, S.-Y. Park, M.-H. Seo and J.-B. Yoon, ACS Nano, 2023, 17, 23649–23658 CrossRef CAS PubMed.
  31. A. Kumar, T. Thundat and M. T. Swihart, ACS Appl. Nano Mater., 2022, 5, 5895–5905 CrossRef CAS.
  32. L. Du and D. Yang, Appl. Surf. Sci., 2023, 607, 154992 CrossRef CAS.
  33. X. Li, T. Cao, X. Zhang, Y. Sang, L. Yang, T. Wang, Y. Li, L. Zhang, L. Guo and Y. Fu, Sens. Actuators, B, 2019, 295, 101–109 CrossRef CAS.
  34. S.-Y. Cho, H. Ahn, K. Park, J. Choi, H. Kang and H.-T. Jung, ACS Sens., 2018, 3, 1876–1883 CrossRef CAS PubMed.
  35. A. Kumar, M. M. Mohammadi, Y. Zhao, Y. Liu, J. Liu, T. Thundat and M. T. Swihart, ACS Appl. Nano Mater., 2021, 4, 8081–8093 CrossRef CAS.
  36. J. Yun, J.-H. Ahn, D.-I. Moon, Y.-K. Choi and I. Park, ACS Appl. Mater. Interfaces, 2019, 11, 42349–42357 CrossRef CAS PubMed.
  37. Deepti, H. Kumar, A. Tripathi, A. B. Dey, M. Gupta, R. Krishna and D. K. Avasthi, Sens. Actuators, B, 2019, 301, 127006 CrossRef CAS.
  38. L. Du, D. Feng, X. Xing, C. Wang, G. S. Armatas and D. Yang, Chem. Eng. J., 2020, 400, 125864 CrossRef CAS.
  39. W. B. Jung, S. Y. Cho, B. L. Suh, H. W. Yoo, H. J. Jeon, J. Kim and H. T. Jung, Adv. Mater., 2018, 31, 1805343 CrossRef PubMed.
  40. W.-T. Koo, Y. Kim, S. Kim, B. L. Suh, S. Savagatrup, J. Kim, S.-J. Lee, T. M. Swager and I.-D. Kim, Chem, 2020, 6, 2746–2758 CAS.
  41. Q. Liu, J. Yao, Y. Wang, Y. Sun and G. Ding, Sens. Actuators, B, 2019, 290, 544–550 CrossRef CAS.
  42. T. A. Peters, P. A. Carvalho, M. Stange and R. Bredesen, Int. J. Hydrogen Energy, 2020, 45, 7488–7496 CrossRef CAS.
  43. L. Song, J. Ahn, D.-H. Kim, H. Shin and I.-D. Kim, ACS Appl. Mater. Interfaces, 2022, 14, 28378–28388 CrossRef CAS PubMed.
  44. K. Yu, X. Tian, X. Wang, F. Yang, T. Qi and J. Zuo, Sens. Actuators, B, 2019, 299, 126989 CrossRef CAS.
  45. X. Meng, M. Bi and W. Gao, Sens. Actuators, B, 2023, 390, 133976 CrossRef CAS.
  46. Z. Chen, P. Yuan, C. Chen, X. Wang, J. Wang, J. Jia, B. Davaasuren, Z. Lai, N. M. Khashab, K. W. Huang, O. M. Bakr, J. Yin and K. N. Salama, Adv. Mater., 2024, 2404291 CrossRef PubMed.
  47. H. D. Mai, S. Jeong, T. K. Nguyen, J.-S. Youn, S. Ahn, C.-M. Park and K.-J. Jeon, ACS Appl. Mater. Interfaces, 2021, 13, 14644–14652 CrossRef CAS PubMed.
  48. M. M. Mohammadi, A. Kumar, J. Liu, Y. Liu, T. Thundat and M. T. Swihart, ACS Sens., 2020, 5, 2344–2350 CrossRef CAS PubMed.
  49. B. Xie, B. Ding, P. Mao, Y. Wang, Y. Liu, M. Chen, C. Zhou, H. M. Wen, S. Xia, M. Han, R. E. Palmer, G. Wang and J. Hu, Small, 2022, 18, 2200634 CrossRef CAS PubMed.
  50. X. Xing, Z. Li, X. Chen, L. Du, Y. Tian, D. Feng, C. Wang, G. Liu and D. Yang, ACS Appl. Mater. Interfaces, 2022, 14, 17911–17919 CrossRef CAS PubMed.
  51. A. Kumar, Y. Zhao, M. M. Mohammadi, J. Liu, T. Thundat and M. T. Swihart, ACS Sens., 2022, 7, 225–234 CrossRef CAS PubMed.
  52. J. Hong, S. Lee, J. Seo, S. Pyo, J. Kim and T. Lee, ACS Appl. Mater. Interfaces, 2015, 7, 3554–3561 CrossRef CAS PubMed.
  53. M. J. López, M. Blanco-Rey, J. I. Juaristi, M. Alducin and J. A. Alonso, J. Phys. Chem. C, 2017, 121, 20756–20762 CrossRef.
  54. I. Chakraborty and T. Pradeep, Chem. Rev., 2017, 117, 8208–8271 CrossRef CAS PubMed.
  55. L. Geng, Q. Liu, J. Zhao, H. Ye, H. Sun, X. Zhang, P. Zhang, T. Yang, Y. Su, H. Li, D. Zhu, J. Yao, J. Chen, P. Jia, J. Yan, L. Zhang, Y. Tang and J. Huang, Mater. Today Nano, 2022, 18, 100189 CrossRef CAS.
  56. D. R. Miller, S. A. Akbar and P. A. Morris, Sens. Actuators, B, 2014, 204, 250–272 CrossRef CAS.
  57. Y. Song, F. Chen, Y. Zhang, S. Zhang, F. Liu, P. Sun, X. Yan and G. Lu, Sens. Actuators, B, 2019, 287, 191–198 CrossRef CAS.
  58. T. P. Mokoena, H. C. Swart and D. E. Motaung, J. Alloys Compd., 2019, 805, 267–294 CrossRef CAS.
  59. S. U. Mutkule, S. T. Navale, V. V. Jadhav, S. B. Ambade, M. Naushad, A. D. Sagar, V. B. Patil, F. J. Stadler and R. S. Mane, J. Alloys Compd., 2017, 695, 2008–2015 CrossRef CAS.
  60. Z. Li, S. Yan, Z. Wu, H. Li, J. Wang, W. Shen, Z. Wang and Y. Fu, Int. J. Hydrogen Energy, 2018, 43, 22746–22755 CrossRef CAS.
  61. H.-J. Kim and J.-H. Lee, Sens. Actuators, B, 2014, 192, 607–627 CrossRef CAS.
  62. N. Barsan, C. Simion, T. Heine, S. Pokhrel and U. Weimar, J. Electroceram., 2010, 25, 11–19 CrossRef CAS.
  63. Y. Shen, W. Wang, A. Fan, D. Wei, W. Liu, C. Han, Y. Shen, D. Meng and X. San, Int. J. Hydrogen Energy, 2015, 40, 15773–15779 CrossRef CAS.
  64. K. Inyawilert, A. Wisitsoraat, A. Tuantranont, S. Phanichphant and C. Liewhiran, Sens. Actuators, B, 2017, 240, 1141–1152 CrossRef CAS.
  65. L. Zhu, W. Zeng and Y. Li, Mater. Res. Bull., 2019, 109, 108–116 CrossRef CAS.
  66. S. Lu, Y. Zhang, J. Liu, H.-Y. Li, Z. Hu, X. Luo, N. Gao, B. Zhang, J. Jiang, A. Zhong, J. Luo and H. Liu, Sens. Actuators, B, 2021, 345, 130334 CrossRef CAS.
  67. T. T. Tran, V. Bhatt, M.-J. Choi, H. T. Nguyen, A. Sharma, M. Kumar and J.-H. Yun, Int. J. Hydrogen Energy, 2024, 84, 768–779 CrossRef CAS.
  68. I. H. Kadhim, H. A. Hassan and Q. N. Abdullah, Nano-Micro Lett., 2015, 8, 20–28 CrossRef PubMed.
  69. Y. Liu, S. Chen, B. Xiao, J. Chu, H. Wang, Y. Chen, T. Yao, A. Yang, X. Han, M. Rong and X. Wang, Sens. Actuators, B, 2024, 401, 135025 CrossRef CAS.
  70. Y. Zhang, W. Zeng and Y. Li, Mater. Res. Bull., 2018, 107, 139–146 CrossRef CAS.
  71. Y. Tian, X. Xing, Z. Li, X. Lang, X. Chen, X. Zhao and D. Yang, Sens. Actuators, B, 2023, 388, 133852 CrossRef CAS.
  72. X. Zhou, T. Tao, Y. Bao, X. Xia, K. Homewood, Z. Wang, M. Lourenço, Z. Huang, G. Shao and Y. Gao, ACS Appl. Mater. Interfaces, 2021, 13, 25472–25482 CrossRef CAS PubMed.
  73. X. Zhao, L. Du, X. Xing, Z. Li, Y. Tian, X. Chen, X. Lang, H. Liu and D. Yang, Small, 2024, 20, 2311840 CrossRef CAS PubMed.
  74. M. Kamal Hossain and Q. Ahmed Drmosh, Chem. Rec., 2022, 22, e20020090 Search PubMed.
  75. S. Agarwal, S. Kumar, H. Agrawal, M. G. Moinuddin, M. Kumar, S. K. Sharma and K. Awasthi, Sens. Actuators, B, 2021, 346, 130510 CrossRef CAS.
  76. A. Mirzaei, H. R. Yousefi, F. Falsafi, M. Bonyani, J.-H. Lee, J.-H. Kim, H. W. Kim and S. S. Kim, Int. J. Hydrogen Energy, 2019, 44, 20552–20571 CrossRef CAS.
  77. D. Degler, U. Weimar and N. Barsan, ACS Sens., 2019, 4, 2228–2249 CrossRef CAS PubMed.
  78. N. Yamazoe, G. Sakai and K. Shimanoe, Catal. Surv. Asia, 2003, 7, 63–75 CrossRef CAS.
  79. J. Z. Ou, J. L. Campbell, D. Yao, W. Wlodarski and K. Kalantar-zadeh, J. Phys. Chem. C, 2011, 115, 10757–10763 CrossRef CAS.
  80. J. Z. Ou, M. H. Yaacob, M. Breedon, H. D. Zheng, J. L. Campbell, K. Latham, J. D. Plessis, W. Wlodarski and K. Kalantar-zadeh, Phys. Chem. Chem. Phys., 2011, 13, 7330–7339 RSC.
  81. C. Seo, H. Cheong and S.-H. Lee, Sol. Energy Mater. Sol. Cells, 2008, 92, 190–193 CrossRef CAS.
  82. S. K. Deb, Sol. Energy Mater. Sol. Cells, 2008, 92, 245–258 CrossRef CAS.
  83. X. Meng, M. Bi, Q. Xiao and W. Gao, Int. J. Hydrogen Energy, 2022, 47, 3157–3169 CrossRef CAS.
  84. I. K. Cheng, C.-Y. Lin and F.-M. Pan, Appl. Surf. Sci., 2021, 541, 148551 CrossRef CAS.
  85. A. Sanger, A. Kumar, A. Kumar, J. Jaiswal and R. Chandra, Sens. Actuators, B, 2016, 236, 16–26 CrossRef CAS.
  86. Y. Liu, Y. Lei, X. Mao, H. Qian, H.-M. Wen, S. Xia, Y. Xiang, Q. Chen, B. Xie and J. Hu, Int. J. Hydrogen Energy, 2024, 62, 783–793 CrossRef CAS.
  87. V. T. Duoc, H. Nguyen, T. M. Ngoc, C. T. Xuan, C. M. Hung, N. V. Duy and N. D. Hoa, Int. J. Hydrogen Energy, 2024, 61, 774–782 CrossRef CAS.
  88. Z. Sun, L. Huang, Y. Zhang, X. Wu, M. Zhang, J. Liang, Y. Bao, X. Xia, H. Gu, K. Homewood, M. Lourenco and Y. Gao, Sens. Actuators, B, 2024, 398, 134675 CrossRef CAS.
  89. X. Wang, X. Meng and W. Gao, Sens. Actuators, B, 2023, 387, 133790 CrossRef CAS.
  90. T. T. D. Nguyen, D. V. Dao, N. Thi Thu Ha, T. Van Tran, D.-S. Kim, J.-W. Yoon, N. N. Ha, I.-H. Lee and Y.-T. Yu, Sens. Actuators, B, 2022, 354, 131083 CrossRef CAS.
  91. X. Meng, M. Bi, Q. Xiao and W. Gao, Sens. Actuators, B, 2022, 366, 131971 CrossRef CAS.
  92. X. Meng, M. Bi and W. Gao, Sens. Actuators, B, 2022, 370, 132406 CrossRef CAS.
  93. G. Pandey, S. D. Lawaniya, S. Kumar, P. K. Dwivedi and K. Awasthi, J. Mater. Chem. A, 2023, 11, 26687–26697 RSC.
  94. S. Kumar, S. D. Lawaniya, S. R. Nelamarri, M. Kumar, P. K. Dwivedi, Y.-T. Yu, Y. K. Mishra and K. Awasthi, Sens. Actuators, B, 2023, 394, 134394 CrossRef CAS.
  95. F. Fan, J. Zhang, J. Li, N. Zhang, R. Hong, X. Deng, P. Tang and D. Li, Sens. Actuators, B, 2017, 241, 895–903 CrossRef CAS.
  96. H. Zhao, J. Li, X. She, Y. Chen, M. Wang, Y. Wang, A. Du, C. Tang, C. Zou and Y. Zhou, ACS Sens., 2024, 9, 2183–2193 CrossRef CAS PubMed.
  97. A. Vahl, O. Lupan, D. Santos-Carballal, V. Postica, S. Hansen, H. Cavers, N. Wolff, M.-I. Terasa, M. Hoppe, A. Cadi-Essadek, T. Dankwort, L. Kienle, N. H. de Leeuw, R. Adelung and F. Faupel, J. Mater. Chem. A, 2020, 8, 16246–16264 RSC.
  98. Y.-T. Yu and P. Dutta, Sens. Actuators, B, 2011, 157, 444–449 CrossRef CAS.
  99. P. Rai, R. Khan, S. Raj, S. M. Majhi, K.-K. Park, Y.-T. Yu, I.-H. Lee and P. K. Sekhar, Nanoscale, 2014, 6, 581–588 RSC.
  100. D. Van Dao, T. T. D. Nguyen, T. D. Le, S.-H. Kim, J.-K. Yang, I.-H. Lee and Y.-T. Yu, J. Mater. Chem. A, 2020, 8, 7687–7694 RSC.
  101. H.-J. Le, D. Van Dao and Y.-T. Yu, J. Mater. Chem. A, 2020, 8, 12968–12974 RSC.
  102. J. Li, Z. Yuan, Z. Mu, Z. Yang and F. Meng, Sens. Actuators, B, 2024, 405, 135404 CrossRef CAS.
  103. H. Chen, Y. Zhao, L. Shi, G.-D. Li, L. Sun and X. Zou, ACS Appl. Mater. Interfaces, 2018, 10, 29795–29804 CrossRef CAS PubMed.
  104. A. I. Khudiar and A. M. Oufi, Sens. Actuators, B, 2021, 340, 129633 CrossRef CAS.
  105. Z. Li, Q. Yang, Y. Wu, Y. He, J. Chen and J. Wang, Int. J. Hydrogen Energy, 2019, 44, 8659–8668 CrossRef CAS.
  106. T. Ai, J. Li, S. Nie, Y. Yin, J. Lu, S. Bao and L. Yan, Int. J. Hydrogen Energy, 2022, 47, 20561–20571 CrossRef CAS.
  107. M. E. Güldüren, D. Iskenderoğlu, H. Güney, E. Gür, M. Acar and S. Morkoç Karadeniz, Int. J. Hydrogen Energy, 2023, 48, 828–839 CrossRef.
  108. Y.-J. Hsiao, Y. Nagarjuna, G.-Y. Huang and M. Lin, J. Alloys Compd., 2023, 960 Search PubMed.
  109. B. Ceviz Şakar, Int. J. Hydrogen Energy, 2024, 50, 1197–1208 CrossRef.
  110. S. Kim, G. Singh, M. Oh and K. Lee, ACS Sens., 2021, 6, 4145–4155 CrossRef CAS PubMed.
  111. C. Yu, J. Liu, H. Zhao, M. Wang, J. Li, X. She, Y. Chen, Y. Wang, B. Liu, C. Zou, Y. He and Y. Zhou, IEEE Trans. Instrum. Meas., 2024, 73, 1–8 Search PubMed.
  112. M. Sun, K. Ding, Y. Lu, X. She, Y. Chen, M. Wang, C. Zou, X. Liu and Y. Zhou, Microchem. J., 2024, 207 Search PubMed.
  113. Z. Li, Z. Yao, A. A. Haidry, Y. Luan, Y. Chen, B. Y. Zhang, K. Xu, R. Deng, N. Duc Hoa, J. Zhou and J. Z. Ou, Nano Today, 2021, 40, 101287 CrossRef CAS.
  114. H. Bai, H. Guo, J. Wang, Y. Dong, B. Liu, F. Guo, D. Chen, R. Zhang and Y. Zheng, Sens. Actuators, B, 2021, 331, 129441 CrossRef CAS.
  115. V. Ambardekar, T. Bhowmick and P. P. Bandyopadhyay, Int. J. Hydrogen Energy, 2022, 47, 15120–15131 CrossRef CAS.
  116. X.-Y. Zhang, Q. Ren, C. Wang, L. Zhu, W.-J. Ding, Y.-Q. Cao, W.-M. Li, D. Wu and A.-D. Li, Appl. Surf. Sci., 2023, 639, 157973 CrossRef CAS.
  117. Z. Wang, D. Zhang, M. Tang, Y. Chen, Y. Sun, Q. Chen, J. Bian and X. Shao, Sens. Actuators, B, 2024, 420, 136422 CrossRef CAS.
  118. Q. Xing, X. Chen, Y. Cai and M. Zhang, Sens. Actuators, B, 2024, 419, 136407 CrossRef CAS.
  119. Q. Chen, Y. Zhang, M. Tang, Z. Wang and D. Zhang, Sens. Actuators, B, 2024, 405, 135229 CrossRef CAS.
  120. M. P. M. Poschmann, L. Siebert, C. Lupan, O. Lupan, F. Schütt, R. Adelung and N. Stock, ACS Appl. Mater. Interfaces, 2023, 15, 38674–38681 CrossRef CAS PubMed.
  121. G. Li, Y. Shen, S. Zhao, A. Li, T. Zhao, C. Tang, C. Yan, S. Gao, Z. Yuan and F. Meng, Sens. Actuators, B, 2023, 396, 134560 CrossRef CAS.
  122. S. Yang, Z. Chen, Z. Wang, G. Lei, J. Xiong, H. Xu and H. Gu, Sens. Actuators, B, 2022, 367, 132026 CrossRef CAS.
  123. X. Wang, X. Meng, Y. Zhu and W. Gao, Sens. Actuators, B, 2024, 401, 134991 CrossRef CAS.
  124. P. Ji, X. Hu, R. Tian, H. Zheng, J. Sun, W. Zhang and J. Peng, J. Mater. Chem. C, 2020, 8, 2927–2936 RSC.
  125. M. Guo, N. Luo, Y. Bai, Z. Xue, Q. Hu and J. Xu, Sens. Actuators, B, 2024, 398, 134151 CrossRef CAS.
  126. A. K. Geim and K. S. J. N. m Novoselov, Nat. Mater., 2007, 6, 183–191 CrossRef CAS PubMed.
  127. F. Schedin, A. K. Geim, S. V. Morozov, E. W. Hill, P. Blake, M. I. Katsnelson and K. S. Novoselov, Nat. Mater., 2007, 6, 652–655 CrossRef CAS PubMed.
  128. J. Z. Ou, W. Ge, B. Carey, T. Daeneke, A. Rotbart, W. Shan, Y. Wang, Z. Fu, A. F. Chrimes and W. Wlodarski, ACS Nano, 2015, 9, 10313–10323 CrossRef CAS PubMed.
  129. Z. Zhu, X. Ma, C. Liu, S. Liang, S. Xu, L. Wang and J. Xu, Ceram. Int., 2023, 49, 12840–12845 CrossRef CAS.
  130. M. Mehta, Deepti, A. K. Sinha, S. Wadhwa, A. Kumar and D. K. Avasthi, Int. J. Hydrogen Energy, 2023, 48, 33372–33381 CrossRef CAS.
  131. B. Lee, S. Cho, B. J. Jeong, S. H. Lee, D. Kim, S. H. Kim, J.-H. Park, H. K. Yu and J.-Y. Choi, Sens. Actuators, B, 2024, 401, 134913 CrossRef CAS.
  132. X. Lu, X. Song, C. Gu, H. Ren, Y. Sun and J. Huang, J. Phys. Chem. Solids, 2018, 116, 324–330 CrossRef CAS.
  133. N. Kumar, J. Jasani, Y. Sonvane, J. G. Korvink, A. Sharma and B. Sharma, Sens. Actuators, B, 2024, 399, 134807 CrossRef CAS.
  134. H. G. Girma, K. H. Park, D. Ji, Y. Kim, H. M. Lee, S. Jeon, S. H. Jung, J. Y. Kim, Y. Y. Noh and B. Lim, Adv. Funct. Mater., 2023, 33, 2213381 CrossRef CAS.
  135. S. Basu and P. Bhattacharyya, Sens. Actuators, B, 2012, 173, 1–21 CrossRef CAS.
  136. F.-L. Meng, Z. Guo and X.-J. Huang, TrAC, Trends Anal. Chem., 2015, 68, 37–47 CrossRef CAS.
  137. Y. Xia, R. Li, R. Chen, J. Wang and L. Xiang, Sensors, 2018, 18, 1456 CrossRef PubMed.
  138. E. Llobet, Sens. Actuators, B, 2013, 179, 32–45 CrossRef CAS.
  139. V. Schroeder, S. Savagatrup, M. He, S. Lin and T. M. Swager, Chem. Rev., 2018, 119, 599–663 CrossRef PubMed.
  140. D. R. Kauffman and A. Star, Angew. Chem., Int. Ed., 2008, 47, 6550–6570 CrossRef CAS PubMed.
  141. L. Du, X. Xing, D. Feng, C. Wang, Z. Li, Y. Tian and D. Yang, Sens. Actuators, B, 2023, 375, 132873 CrossRef CAS.
  142. A. Gamboa and E. C. Fernandes, Sens. Actuators, A, 2024, 366, 115013 CrossRef CAS.
  143. F. Liu, M. Xiao, Y. Ning, S. Zhou, J. He, Y. Lin and Z. Zhang, Sci. China Inform. Sci., 2022, 65, 162404 CrossRef.
  144. Z. Zhang, Y. Yang, S. Zhu, Y. liu, Y. Shi, J. Song, G. Ren, S. Deng, X. Tian and Z. Zheng, Int. J. Hydrogen Energy, 2024, 50, 870–877 CrossRef CAS.
  145. D. Jung, M. Han and G. S. Lee, ACS Appl. Mater. Interfaces, 2015, 7, 3050–3057 CrossRef CAS PubMed.
  146. B. Liu, M. Alamri, M. Walsh, J. L. Doolin, C. L. Berrie and J. Z. Wu, ACS Appl. Mater. Interfaces, 2020, 12, 53115–53124 CrossRef CAS PubMed.
  147. Y. Yan, G. Yang, J.-L. Xu, M. Zhang, C.-C. Kuo and S.-D. Wang, Sci. Technol. Adv. Mater., 2021, 21, 768–786 CrossRef PubMed.
  148. Y. Da, J. Liu, L. Zhou, X. Zhu, X. Chen and L. Fu, Adv. Mater., 2018, 31, 1802793 CrossRef PubMed.
  149. C. Anichini, W. Czepa, D. Pakulski, A. Aliprandi, A. Ciesielski and P. Samorì, Chem. Soc. Rev., 2018, 47, 4860–4908 RSC.
  150. T. Minezaki, P. Krüger, F. E. Annanouch, J. Casanova-Cháfer, A. Alagh, I. J. Villar-Garcia, V. Pérez-Dieste, E. Llobet and C. Bittencourt, Sensors, 2023, 23, 4623 CrossRef CAS PubMed.
  151. Q. Yue, Z. Shao, S. Chang and J. Li, Nanoscale Res. Lett., 2013, 8, 1–7 CrossRef PubMed.
  152. C. H. Park, W.-T. Koo, Y. J. Lee, Y. H. Kim, J. Lee, J.-S. Jang, H. Yun, I.-D. Kim and B. J. Kim, ACS Nano, 2020, 14, 9652–9661 CrossRef CAS PubMed.
  153. J. Jaiswal, P. Tiwari, P. Singh and R. Chandra, Sens. Actuators, B, 2020, 325, 128800 CrossRef CAS.
  154. R. Wadhwa, A. Kumar, R. Sarkar, P. P. Mohanty, D. Kumar, S. Deswal, P. Kumar, R. Ahuja, S. Chakraborty, M. Kumar and M. Kumar, ACS Appl. Nano Mater., 2023, 6, 2527–2537 CrossRef CAS.
  155. L. Wang, Z. Xiao, X. Yao, X. Yu, S.-T. Tu and S. Chen, Int. J. Hydrogen Energy, 2023, 48, 30205–30217 CrossRef CAS.
  156. C. Qiu, H. Zhang, Q. Li, Y. Song, F. An, H. Wang, S. Wang, L. Zhu, C. Lv and D. Zhang, Sens. Actuators, B, 2024, 417, 136215 CrossRef CAS.
  157. M. Naguib, O. Mashtalir, J. Carle, V. Presser, J. Lu, L. Hultman, Y. Gogotsi and M. W. Barsoum, ACS Nano, 2012, 6, 1322–1331 CrossRef CAS PubMed.
  158. S. Charan, N. Sharma, K. Arjun, S. Mathur, A. K. Vishwkarma and S. Shrivastava, Int. J. Hydrogen Energy, 2023, 48, 38118–38124 CrossRef CAS.
  159. M. S. Nam, J.-Y. Kim, A. Mirzaei, H. W. Kim and S. S. Kim, Sens. Actuators, B, 2024, 404, 135189 CrossRef CAS.
  160. Z. Zhu, C. Liu, F. Jiang, J. Liu, X. Ma, P. Liu, J. Xu, L. Wang and R. Huang, J. Hazard. Mater., 2020, 399, 123054 CrossRef CAS PubMed.

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