DOI:
10.1039/D5TA02070K
(Paper)
J. Mater. Chem. A, 2025,
13, 26255-26267
Thermally induced cyclic resistance transition of a transparent and flame-retardant layered oxidized MXene composite nanocoating for remote-sync fire monitoring†
Received
13th March 2025
, Accepted 12th May 2025
First published on 20th May 2025
Abstract
Fire safety of flammable materials in buildings and wooden houses is a critical global challenge since they are easily ignited and facilitate rapid fire spread in several seconds, thus escalating into serious fire disasters. Therefore, there is an urgent need to develop efficient strategies and solutions to tackle fire hazards before fire becomes uncontrollable. Herein, we report a transparent and flame-retardant layered oxidized MXene (OM) and aramid nanofiber (ANF) composite nanocoating to construct a smart fire-warning device (FWD) for remote-sync fire prevention in buildings. Novel lamellar OM was precisely synthesized to fabricate a hybrid OM/ANFs/BA (OMAB) nanocoating. This nanocoating not only endows the flammable polymer foam and wooden materials with outstanding flame retardancy (e.g. UL94-V0 and LOI of 34.6% for the coated woods), but also provides a sensitive and cyclic fire warning response in 1.5 s for >60 cycles. The formation of a compact layered C/N/B doped titanium oxide network and its heat-induced resistance transition under flame are demonstrated. Consequently, the FWD system built via integrating the OMAB coating with wireless transmission hardware and homemade visualization software provides a real-time and remote-sync fire monitoring response, which is promising to mitigate or even prevent critical fire disasters in buildings or wooden houses.
Introduction
Fire is a critical energy source for human civilization, but uncontrolled fires cause significant risks to both the environment and human safety.1–3 Fires are characterized by their sudden onset, extensive destruction, and inherent unpredictability, making them a major threat to human life and property. Notable incidents include the 2017 Grenfell Tower fire in London, which tragically claimed 71 lives, and other significant fire disasters, such as the Notre Dame fire in Paris in 2019 and the forest fires in California and South Australia between 2020 and 2021.4–6 These fire events not only caused severe damage to cultural landmarks but also had a profoundly negative impact on the ecological environment. Therefore, there is a critical need to monitor early fire risks or inhibit the serious fire hazard of flammable materials before fires become uncontrollable.
As urbanization accelerates, the construction of high-rise buildings has become increasingly prevalent. These structures often employ thermal insulation materials like polyurethane and polystyrene foams for their exterior walls, and use wooden materials as decoration.7,8 In the event of a fire, the complex structure of these buildings and the rapid spread of flames pose considerable challenges to fire control and suppression, which underscores the urgent need for the development of effective flame retardants and early warning systems.9,10 Current fire safety strategies primarily rely on the use of flame-retardant materials and fire warning systems to slow fire progression and provide critical time for evacuation and firefighting efforts. Fire warning systems are designed to detect fires at an early stage, issuing timely alerts to minimize damage and prevent further outbreaks. However, commonly used fire detectors, such as infrared, gas and smoke detectors, have certain limitations: delayed flame detection (often exceeding 100 s),11 limited resolution and spatial coverage, no fire warning signal prior to combustion and a lack of fire-resistant functionality. Furthermore, these conventional systems are often unsuitable for outdoor environments due to poor weather resistance. Moreover, traditional fire sensors typically rely on warning lighting for detection, which can be impractical in various real-world situations.12 These limitations highlight the need for advanced, intelligent fire-warning materials and systems that can transmit fire information remotely and in real time, with the added benefit of visual monitoring through user-friendly interfaces.
In recent years, various novel fire-warning materials and sensors have been designed with different functions and signal modes, which are briefly described as follows: temperature-induced resistance transition,13–18 thermoelectric response,19–21 shape change,22,23 and color change.24,25 For example, Mai and co-workers fabricated a flame-retardant silicone resin/graphene oxide (GO) composite nanocoating,13 and once encountering a flame, the GO/silicone coating can form a compact reduced GO/nano-silica layer to restrict the flame spread and also provide a sensitive fire waring signal within 3 s due to heat-induced reduction behavior of the GO network. Wang et al.,24 drawing inspiration from the plant chlorophyll metabolism, synthesized a precursor molecular sensor (PMS) that can undergo a chemical structural transformation to form phthalocyanine (Pcs) and exhibit a color change signal at temperatures around 180 °C, providing a real-time monitoring strategy for early fire warning detection in precombustion. Although the above researches have made some progress in the field of fire warning systems, there are some limitations, especially the opacity of systems and the adequacy of signal alertness. Zeng et al.19 developed a cotton fabric (denoted as MXene/CCS@CF) with thermoelectric fire-warning performance. When being burned, it generated a voltage that can reach the set threshold in about 3.8 s to trigger the fire alarm. Despite its good efficacy in fire safety, the inherent black property of the nano-fillers narrows its potential decoration applicability. Thus, the design and development of transparent, flame-retardant coatings with wireless signal transmission would greatly enhance the reliability and effectiveness of fire warning, compensating for the deficiencies of conventional fire detection methods and thus improving overall fire safety. Additionally, the remote transition of the fire-warning signal through short-distance wireless communication (Bluetooth) was developed,26 while real-time synchronization between fire scenes and stations remains a critical challenge due to the inevitable delay in obtaining timely warning signals.
Herein, we report an unprecedented transparent and flame-retardant composite nanocoating based on a 2D oxidized MXene (OM) and 1D aramid nanofiber (ANF) network modified with boric acid (BA) to construct a smart fire-warning device (FWD) via simply connecting the nanocoating with the as-developed signal transmission hardware and visualization software. Translucent OM sheets are synthesized by the tunable oxidation of MXene sheets and are then applied as a transparent composite nanocoating on wooden materials or polymer foams for improving their flame-retardancy. Especially, when exposed to a flame, the hybrid OM/ANFs/BA composite nanocoating generates a rapid early warning signal (in 1.5 s), which is transmitted via a wireless transmitter to a visualization interface. Such flame-retardant nanocoating combined with an intelligent FWD system can monitor critical fire risks in the exterior walls of high-rise buildings and thus significantly improve fire safety by providing a remote-sync warning response for timely firefighting, evacuation and rescue operations.
Results and discussion
Design concept of a transparent nanocoating and fire-warning device (FWD)
To construct a reliable fire-warning device (FWD), we developed and fabricated a transparent composite nanocoating comprising a lamellar OM/ANFs/BA (OMAB) interconnected network (Fig. 1a), which can form a compact and robust layer to delay the fire spread of the flammable materials. Specifically, the as-synthesized translucent lamellar OM20 demonstrates a substantial enhancement in early fire-warning performance relative to the black MXene sheets. The BA molecule was employed and worked as a flame-retardant, and hydroxyl groups of its structure would form strong interfacial interactions with ANFs and OM sheets. During the flame attacking process, the transparent OMAB composite nanocoating effectively improves the flame resistance of the combustible wooden materials and polymer foams to delay their fire spread. Meanwhile, the formation of a compact C/N/B-doped TiO2 network can produce a sensitive fire-warning response within 1.5 s. As a result, these hybrid OMAB composite nanocoatings not only endow the flammable substrates with good transparency, mechanical flexibility, and excellent flame retardancy, but also provide sensitive early fire-warning capacity, showing promise for monitoring the critical fire risk in buildings or wooden houses, such as external walls, roofs and internal partitions.
 |
| Fig. 1 Design concept of the layered oxidized MXene nanocoating for remote-sync fire monitoring. (a) Schematic of the transparent OM/ANFs/BA (OMAB) layered network as an efficient flame-retardant composite nanocoating on flammable substrates for constructing the fire-warning device system in the exterior-wall of buildings. (b) Schematic of the rapid and sensitive fire warning mechanism based on heat-induced electrical resistance transition of the OMAB composites. (c) As-developed signal transmission hardware and visualization software connected with the OMAB nanocoating for (d) remote-sync and real-time monitoring at early spreading stages of fires. | |
When exposed to flame, the OMAB composite nanocoating rapidly transitions from an insulating state to a conductive state, generating a sensitive signal that triggers a rapid fire-warning signal in several seconds via heat-induced resistance transition (Fig. 1b). This response is reversible since the electrical resistance values of the nanocoating show good cyclic change between the insulating and conductive states once the flame is removed/exposed. Additionally, the OMAB nanocomposite coatings also present good transparency, robust flame resistance and excellent weather durability. Consequently, the FWD system that integrates the OMAB nanocoating and the as-developed signal transmission hardware and visualization software (Fig. 1c) can transmit the real-time warning signal remotely, allowing timely monitoring of critical fire risks at the fire scene and thus providing a remote-sync signal to the fire station or building occupants. Such FWD systems can be installed throughout a building, enabling comprehensive fire monitoring and supporting prompt evacuation and firefighting actions, particularly in diverse fire scenarios such as the incipient and spreading stages of fires. They enable the adoption of rational and efficacious intervention strategies to mitigate fire hazards or facilitate timely evacuation and notification of the fire department (Fig. 1d). Clearly, the FWD system based on the OMAB coating can offer reliable warning detection and timely alerts for fire risk, thereby showing promise to mitigate or even prevent critical fire disasters.
Tunable oxidization of MXene to lamellar OM sheets
To overcome the black nature of traditional GO and MXene-based coatings, the lamellar OM material was synthesized through the facile and precise oxidation of MXene. Typically, hydrogen peroxide (H2O2) was introduced into the MXene solution (Fig. 2a), which can oxidize the MXene sheets effectively at room temperature, thus gradually producing color transitions from black to a transparent state (Fig. 2b and c) with extending the oxidation time (Fig. S1†). The MXene sheets were initially wrinkled in structure (Fig. 2d),27 and after 20 min of oxidation with H2O2 (Fig. 2e), a lamellar TiOx with some holes on the backbone was obtained.28 Terminating the reaction yields a structure that is more conducive to building an early warning network. Notably, further oxidation can cause the holes to enlarge (Fig. S2†) and the lamellar structure was destroyed after 60 min, finally forming the TiO2 nanoparticles (20–50 nm in diameter, Fig. 2f). Fig. 2g presents the HRTEM images of OM20 sheets; the images indicate that a layered structure is formed under controlled oxidation. The above controllable oxidation of MXene sheets also aligns with the observed resistance changes shown in Fig. S3† since the oxidation would degrade their electrical conductivity greatly.29
 |
| Fig. 2 Synthesis, structure and chemical analysis of layered OM sheets. (a and c) Digital photos of MXenes and OM dispersions; the color of the MXene solution transformed from black to light yellow after oxidation. (b) Schematic of the preparation process of OM sheets. (d and f) SEM images of MXenes and OM sheets. (e and g) TEM images of MXenes and OM sheets. (h) HRTEM images of OM sheets. (i) XRD patterns of MXene and OM sheets with different oxidation times. (j) Raman spectra and (k) Ti 2p XPS spectra of MXenes and OM sheets, indicating an insufficient oxidation degree. | |
To further confirm the chemical structure, Fourier-transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), Raman spectroscopy and X-ray photoelectron spectroscopy (XPS) were conducted. Typically, FTIR results, in the range of 408–443 cm−1, reveal a Ti–O–Ti bond (Fig. S4a†),30 indicating Ti atom oxidation and the formation of TiO2. XRD analysis in Fig. 2i showed that TiO2 appeared after 20 min of oxidation and increased sharply after 120 min, further indicating the gradual oxidation process. Raman spectra (Fig. 2j) exhibit characteristic TiO2 peaks, including rutile (Eg at 417 cm−1 and A1g at 620 cm−1) and anatase phases (Eg at 161 cm−1), with shifts due to oxygen vacancies (OVs).31 This causes Ti atoms near the vacancies to shift outward, locally shortening the Ti–O bond, leading to a blue-shifted and broadened anatase Eg signal,32 further indicating incomplete oxidation of MXene. In the high-resolution Ti 2p XPS spectrum (Fig. 2k), the peaks at 459.4 and 465.3 eV (Ti–O bonds) and signals for Ti–C, Ti–F, and Ti–OH bonds at 455.6 and 461.6 eV suggest the surface group transformations.33 With the prolonged oxidation, Ti–O bonds increase, confirming TiO2 formation on the flake surface while retaining some original structure (Ti–C, Ti–F, and Ti–OH), which is well supported by the SEM images in Fig. S2† and the FTIR spectra results in Fig. S4b.† And the lamellar structure has been largely destroyed in OM120, with a significant amount of titanium dioxide (TiO2) appearing. TEM analyses further support these above findings, confirming the single-layer of MXene with an ultrathin structure, clean surface (Fig. S5a†) and retention of the hexagonal symmetry and crystallinity of the parent Ti2AlC phase.34,35
High-Resolution TEM (HRTEM) images of OM20 sheets shown in Fig. 2g reveal sheets with characteristic holes and lattice fringes, indicating anatase phases with interlayer spacings of 0.241 nm and 0.343 nm (Fig. 2h). In contrast, TEM images of OM120 display particle aggregates lacking complete nanosheets (Fig. S5c†), with fringes corresponding to various anatase and rutile phases of TiO2. Both OM20 sheets and OM120 samples show a loss of the hexagonal symmetry seen in the original MXene (Fig. S5†). XRD analysis (Fig. 2i) further supports this, showing peaks specific to anatase and rutile TiO2 phases, which align with TEM observations and indicate partial oxidation of titanium layers. In the oxidation process of MXene with H2O2, as shown in Fig. 2b, the addition of H2O2 to MXene (Ti3C2Tx) initiates the oxidation of titanium (Ti) and carbon (C) within the structure. Some Ti atoms oxidize into TiO2, remaining attached to the layers, while others detach to form free TiO2 particles. This detachment exposes underlying carbon layers, which then oxidize, resulting in hole formation. Unreacted Ti and C atoms maintain the original sheet-like structure, thus preserving the general morphology. Clearly, the above controllable oxidation process yields a yellow, transparent laminar structure (TiOx) with TiO2 deposition on the surface, while some original MXene structure is retained. This oxidation reaction can be represented as follows:36
| aTi3C2Tx + H2O2 → bTiOx + cCO + dCO2 + TiO2 | (1) |
Design, preparation, and structural characterization of the OMAB network
As illustrated in Fig. 3a and b, the OMAB network was prepared by low-temperature induced evaporation,37 and it exhibits better transparency in comparison to the MAB paper (Fig. S6e†). Moreover, the mechanical flexibility (Fig. S6g†) enables it to be folded into a box-like shape (Fig. 3c), and no crack or structural damage formation is observed for OMAB paper during the 100 fold test under a polarization microscope (Fig. 3d). Moreover, the SEM cross-section image (Fig. 3e) reveals that the OMAB network maintains its structural integrity even after being compressed, highlighting its good mechanical flexibility, which may be due to the nacre-like aligned structure (Fig. 3f). In comparison with the cross-section of ANFs (Fig. S7a†), the OMAB structure clearly shows the entanglement of ANFs and encapsulation of OM20 within it (Fig. 3g). This is due to the formation of strong interfacial interactions among numerous functional groups such as the amide groups of ANFs, hydroxyl groups of BA molecules and the O–H or F group/element on the Ti–OH of OM20 sheets,38 which is evidenced by the good distribution of B, N, Ti, and C elements shown in Fig. 3h and the following FTIR analysis.
 |
| Fig. 3 Structural characterization and analysis of OMAB samples. Digital photos of (a) OMAB solution and (b) OMAB paper (10 × 10 cm), and (c) excellent mechanical flexibility of the OMAB paper. (d) Optical images and (e) cross-sectional SEM images of the OMAB paper after different folding times, demonstrating the formation of a well-interconnected network. (f–g) Cross-sectional SEM images of the OMAB paper, and (h) the corresponding EDS mapping images of B, N, Ti and C elements. (i) FTIR curves of ANFs, OMA and OMAB. (j) C 1s XPS results of ANFs and OMAB. (k) Schematic of interfacial interactions in the interconnected OMAB network. | |
FTIR and XPS results confirm the formation of strong interfacial interactions in the final OMAB composites. Fig. 3i shows the typical absorption bands of ANFs, and the –NH and C
O peaks can be seen in the FTIR spectrum,39 which would produce a good hydrogel bonding in the ANF film.40 This is well supported by the good structure integrity of the ANF film in water for 90 days, shown in Fig. S8a,† and the compact structure observed in Fig. S7a.† More importantly, Fig. S8b and c† also indicate that the OMAB film has superior stability in DMSO/KOH solution compared to OMA and pure ANF films; this may be due to the multiple hydrogen bonding interactions between OM sheets and ANFs as well as BA.41–44 The shifts in the FTIR spectrum and the changes in XPS results confirm this hypothesis. Compared with the pure OM sheets (Fig. S4a†) and ANFs, the OMAB composites show a broadened FTIR peak corresponding to the –OH group at 3590–3340 cm−1, with a shift in the –NH peak from 3320 to 3340 cm−1, in the C
O peak from 1650 to 1660 cm−1 and in the Ti–O peak from 895 to 892 cm−1. These results confirm the formation of strong hydrogel bonding interactions among the –OH, –NH, Ti–O and C
O groups,45 and this is also supported by the compact structure observed in Fig. S7c.† Additionally, the presence of BA molecules could generate intermolecular hydrogen bonds in the ANFs/OM interconnected network,46 further facilitating their strong interfacial interactions. The XPS results (Fig. S9a† and 3j) further support this. Compared with ANFs, the peak of the O
C–NH group shifts to a lower binding energy from 286.8 to 286.4 eV, and the C
O peak also shifts to a lower binding energy from 288.8 to 288.4 eV. In the N 1s spectra (Fig. S9b†), the –NH peak of OMAB paper shifts from 401.8 to 401.5 eV. Compared with OM20 and BA47 (Fig. S9c and d†), the Ti–O1/2 peak of OMAB paper also presents a clear shift from 464.5 to 460.4, and the peak of B–OH shifts from 191.6 to 191.9 eV. All of the above results suggest the formation of multiple hydrogen bonds in the final OMAB composites (Fig. 3k),48 thus endowing the OMAB composite films with exceptional structural stability and outstanding resistance to acid/alkaline solutions, saline solution and water (Fig. S8d†). Clearly, the formation of a well interconnected network and strong interfacial interactions in the final OMAB nanocoating together with their intrinsic performance can produce transparent and mechanically flexible composite nanocoatings, thereby facilitating both excellent flame retardancy and electron transport during flame exposure, which will be discussed in the following section.
Flame-retardant performances and mechanism analysis
The fireproof performance of the OMAB nanocoating on flammable substrates including polymer foam and wooden materials widely used in buildings was evaluated. As illustrated in Fig. 4a, the OMAB-coated substrate demonstrates transparency, allowing the pattern “HZNU” beneath to remain clearly visible, whereas the MAB coating appears opaque and black. To assess the flame resistance of the OMAB coated polyurethane (OMAB@PU) composite, the sample was ignited using a butane flame (∼1200 °C). As shown in Fig. S10,† a digital camera and an infrared thermal imager were used for monitoring flame spread and thermal insulation effects during the fire testing. As expected, untreated PU was ignited immediately and burned intensely upon exposure to the butane flame (Fig. 4b), becoming fully consumed within 138 s and thus forming a carbonized residue (Fig. S11a†). In contrast, the OMAB@PU showed rapid self-extinguishment within 40 s after a 10 s flame attack (Fig. 4c), greatly reducing the fire spread rate and preventing further combustion of PU (Fig. S11b†). Following the application of the OMAB coating onto the wooden substrate, we further proceeded to evaluate the flame retardancy of the coated wood with the coating thickness of 30–50 μm (Fig. S12†). UL-94 vertical combustion test of the OMAB@W shows rapid self-extinguishing behavior within only 7 s, superior to the complete combustion of pure wood and the slow self-extinguishing of the OM/ANFs coating (Fig. S13 and S14a†), demonstrating the flame-retardant V-0 degree (Table S1†).49 The Limiting Oxygen Index (LOI) test also confirmed the improved flame resistance. For example, the LOI value was enhanced from 20.2% for pure wood to 34.8% for the OMAB@W (Fig. S14b†), which is also evidenced by the flame self-extinguishing of the OMAB nanocoating at the oxygen concentration of 30% when compared with the continuous combustion behaviors of the pure wood and the binary ANFs/OM coating (Fig. S15†). The above findings suggested that the interconnected OM/ANFs/BA network effectively improves the flame retardancy of both wood and foam substrates, indicating the potential of flame-retardant composite coatings for the flammable materials widely used in buildings and wooden houses.
 |
| Fig. 4 Flame-retardant performance and mechanism analysis. (a) Photographs of PU foams coated with OMAB (top) and MAB (bottom), showing different transparent features. Digital images of the burning behaviors of (b) pure PU and (c) OMAB-coated PU foam under flame for 10 s, along with their side temperature variation with time recorded by an IR camera. (d) Surface SEM images of OMAB at different burning times, (e) and corresponding EDS mapping images for Ti, C, N, O and B elements. (f) HRTEM images of OMAB after being burned, indicating the formation of a C/N/B-doped TiO2 network. (g) OMAB shows the crystal morphology during the combustion process. (h) C 1s XPS spectra and (i) TG-IR results of OMAB after/during the burning test. (j) Proposed flame-retardant mechanism and structural feature of OMAB after flame exposure. | |
To disclose the flame-retardant mechanisms of the OMAB coatings, the coated samples were subjected to controlled burning using an alcohol lamp for different durations, and the post-combustion microstructure and morphology of both OMAB and TiO2 network were also examined. Compared with the TiO2 coating after burning that retained independent spherical particles with an unchanged size (Fig. S16†), the OMAB formed a compact interconnected network of irregular nanoparticles after 30 s of burning and continued burning induced elliptical TiO2 particles to grow from tens to hundreds of nanometers, transforming into a fish-scale-like compact structure (Fig. 4d). This structure transformation would be resulted from the formation of C/N/B doped in rutile TiO2 during combustion,15 and with the extension of combustion time, the amount of TiO2 increased in the crystal form of rutile, and all changed into rutile after 60 s (Fig. S17†). The C, N and B elements that are well distributed in the burned TiO2 network (Fig. 4e and S18†) indicated the formation of C/N/B doping after 120 s of burning. TEM images of the OMAB also demonstrated the presence of a rutile phase (101 and 110) with slight lattice spacing reductions in Fig. 4f. The special network structure generated by the combustion of the OMAB network can be plausibly explained as follows: during the combustion process, the C, N, and B elements facilitate the transformation of TiO2, leading to the formation of a robust and continuous network (as shown in Fig. 4g). This hypothesis is also supported by the observed continuous, cell-like internal porous structure that becomes more evident as the burning time increases, as presented in Fig. S19.†
The thermal decomposition of ANFs, OMA and OMAB samples, which were analyzed by TGA, can provide more evidence. As shown in Fig. S20,† all samples showed an initial mass loss below 100 °C and a slight decrease at 200–400 °C corresponding to water evaporation and degradation of oxygen-containing groups.50 Notably, after the addition of OM20 and BA, the OMAB displayed higher thermal stability and weight residue, indicating that the formation of char in OMAB has been improved. Post-combustion XPS spectra of the burned OMAB samples for the C 1s (Fig. 4h) and B 1s (Fig. S21†) demonstrated the disappearance of C–O and C
O peaks during the pyrolysis, and new peaks for C
N (288.6 eV) and B–O–C (190.6 eV) were observed. TG-IR results (Fig. 4i) of the OMAB further confirm the release of NH3, H2O, and CO/CO2 at 400–600 °C, promoting carbonization under BA.51 Concurrently, the gas compounds can react with OM sheets in the presence of BA, thus accelerating the doping process for TiOx sheets to generate a dense and porous C/N/B-doped TiO2 structure (Fig. 4j). The formation of the robust and compact hierarchical porous structure can work as a physical barrier to effectively isolate oxygen and heat, thus improving the flame retardancy of the flammable polymer foam and wooden materials.
Fire warning behaviors and mechanism analysis of the OMAB network
The transparent and flame-retardant OMAB composite nanocoating can provide rapid and sensitive fire warning response once encountering flame, making it promising as a decorative coating for reducing critical fire risks. As shown in Fig. 5a, the OMAB network maintains electrical insulation under room temperature, while upon flame, the OMAB nanocoating triggers the warning lamp within only 4 s (triggering the lamp requires the resistance to change by five orders of magnitude, below 1000 Ω). When the flame is removed, the warning lamp turns off (Fig. S22a†). Furthermore, the OMAB also shows cyclic fire-warning capabilities. In contrast, the MAB coating has high electrical conductivity and the warning light remains unchanged, which cannot release the rapid fire-warning signal (Fig. S22b†), rendering it unsuitable as a fire-warning sensor. The OMAB functions as an insulator but rapidly transfers to a conductive state when exposed to flame,52 which enables reliable and rapid fire-warning capability. Real-time monitoring of the resistance change with a multimeter demonstrated this. As shown in Fig. 5b, during a fire event, the internal temperature rise in the OMAB network decreases resistance, thus activating the warning light. The OMAB sample's resistance quickly drops below the resistance threshold (the sensor's response and recovery time are defined as the interval required for the resistance to change by two orders of magnitude), thus yielding a flame attack response time of only 1.5 s (Fig. 5c), which outperforms the long response time of >100 s of conventional smoke detectors.11 Notably, the OMAB returns to its insulating state within 1 s when removing the flame, displaying a stable cyclic warning feature. Further, compared with the MAB coating, the OMAB coating can produce much better sensitivity and stability in the resistance change upon exposure to or removal of the flame (Fig. 5d). Additionally, the OMAB coated sample also demonstrated reversible behavior under flame cycles of 10, 30 and 60 s (Fig. 5e) and reliable cyclic fire warning behavior after long-term outdoor storage (66 fire-warning cycles for one month, Fig. 5f), indicating reliable fire warning performance.
 |
| Fig. 5 Fire-warning performance. (a) Photographs of the flame detection process of the OMAB sample, and (b) its thermographic images and electrical resistance transition behaviors under flame. (c) Typical resistance–time curve of the OMAB sample, and (d) comparison of resistance response curves of OMAB and MAB samples upon flame attack, demonstrating an ultrafast fire detection response of ∼1.5 s and resistance change of five orders of magnitude of the layered OM network. (e) Cyclic resistance–time curves at different flame attacking times and (f) cyclic fire detection process for 66 cycles (a flame attacking time of 60 s for each cycle), indicating reliable fire warning performance. (g) Resistance transition mechanism and energy band variation analysis of the layered OMAB network upon flame exposure. (h) Comparison of the fire-warning response time of the as-prepared OMAB sample and similar fire-warning material systems reported previously. | |
Fig. 5g illustrates the resistance transition mechanism and energy band variation analysis of the layered OMAB network upon flame exposure. The cyclic early-fire warning response of the OMAB nanocoating is attributed to the heat-induced resistance transition mechanism of the doped TiO2 network. Typically, the TiO2 network produces heat-excited electrons and holes due to an oxygen vacancy-dependent band structure with a 3.2 eV energy gap,53 allowing electron excitation from the valence to conduction bands.54 This shift reduces the resistance, triggering conductivity change. Notably, the C/N/B-doped TiO2 structure in the OMAB may further reduce the effective band gap energy.55 The bandgap energy of E1 represents the energy required for OMAB to transition from an insulating state to a conductive state. Doping with C/N//B can increase the carrier concentration, making the material more conductive. Macroscopically, it reduces the energy required for the transition of TiO2 from an insulating state to a conductive state, which may be lower than the energy (E2) required for the transition of the pure OM20 sheet. As a result, the OMAB nanocoating can provide a sensitive fire-warning response and stable cyclic signal, shown in Fig. 5a–d. Further, we summarize the alarm response time and the responsive temperature of various fire-warning materials (Fig. 5h);13,56–63 the response time of our OMAB nanocoating (red star) has the shortest alarm performance compared to other samples. Furthermore, the OMAB nanocoating features a short warning time, transparent feature and reusable fire-warning performance (Table S2†), underscoring its promising applications as a fire-safety decorative material.
Early fire warning application of the OMAB coating in the FWD system
The transparent OMAB nanocoating not only endows the flammable substrates with good passive flame retardancy to delay the rapid flame spread, but also provides a sensitive and stable cyclic fire-warning response for fire prevention. These features make the OMAB nanocoating promising for effectively monitoring critical fire risks in the exterior-wall of buildings. In most building fires, the flame was usually ignited by a cigarette or glow wire and rapidly spread in several minutes, inducing serious fire hazards. Thus, timely obtaining the fire warning signal of the fire risk is critically needed for extinguishing fires manually and fighting fires rapidly or offering the timely signal for timely evacuation in the initial combustion process. Based on the as-prepared OMAB nanocoating, an advanced fire-warning device (FWD) system was constructed via directly connecting the signal transmission hardware and visualization software. This system integrates seamlessly into high-rise structures, enabling continuous tracking of fire hazard signals, including the real-time progression and spread of fire incidents.64–66 As depicted in Fig. 6a, the FWD system employs a resistance-based detection mechanism to monitor the resistance of the OMAB nanocoating. Specifically, the OMAB is physically connected to the Resistance Acquisition Chip to acquire the real-time resistance. The data can be sent to the 4G/5G network by the Microprocessor Control Unit. Furthermore, a link is generated to enter the web to get fire information from a dynamic visual interface by any device with internet access. Fig. 6b depicts the high-rise building model utilized for subsequent simulated combustion experiments, as well as the interface for computer and mobile device login access. When the resistance of the OMAB sensor drops below a set threshold, signaling a fire, the FWD lights (the layout of the lights is based on the positions of OMAB in the building model) on the interface shift from green to red for an immediate visual alert. This color-coded layout not only confirms the presence of fire risk, but also indicates its spread direction and progression (Fig. 6c).
 |
| Fig. 6 Remote-sync fire monitoring application in the exterior-wall of a building. (a) Schematic of the FWD system connected with (b) signal detection-transmission hardware and (c) visualization software (real-time display on a website). (d) Remote-sync monitoring illustration for a high-rise building fire, including four positions: position 1—the local fire accident scene of a building, position 2—the monitoring room near the building fire (∼150 m), (e) position 3—the fire station (2–3 km away), and position 4—a homeowner located 850 km away. (f) Photographs of a fire ignition and spread process in the exterior-wall of a high-rise building, and the corresponding infrared thermal images at position 1. (g) Real-time fire monitoring screenshot on the phone/computer interface at position 3 or position 4, demonstrating remote-sync fire prevention. | |
Finally, to illustrate the practical implementation of our FWD system, we coated wood blocks with the OMAB nanocoating and embedded them within a PU foam wall (Fig. S23a†). In accordance with the previously reported specific fire behavior,67–70 the positions of the OMAB sensors were designed to have a diverse height distribution within the exterior wall during the building model phase (Fig. S23b†). And each of the wood blocks was connected with the wireless transmission devices to construct the FWD system for effectively monitoring the whole building (Fig. S23c†), corresponding to the same image shown in the visualization software (Fig. 6c). Based on the as-developed hardware and software, the multi-location real-time monitoring capabilities of the FWD system can be obtained, as illustrated in Fig. 6d. Typically, four positions were designed for real-time monitoring of the high-rise building fire, including position 1—the local fire accident scene of a building, position 2—the monitoring room of the building (∼150 m away from position 1), position 3—the fire station 2–3 km away from the building, and position 4—a homeowner located 850 km away.
Notably, the FWD system based on the OMAB coated samples can provide a real-time fire warning response for monitoring the fire risk. When a fire originates at position 1 (as demonstrated in Video S1†), alerts are instantly sent to the monitoring room (150 m away) (Fig. 6e(i) and S24a†), the fire station (2–3 km away) (Fig. 6g) and the homeowner (850 km away) (Fig. 6e(ii) and S24b†), demonstrating the outstanding remote-sync fire monitoring capacity. For example, the model is ignited from the ignition point, and the color of the FWD lamps changed with the spread of the flame (Fig. 6f and g). At the time of 16
:
18
:
35, when the flame spread from the ground floor to the second floor, the first alarm light was activated. At 16
:
18
:
40, as the flame continued to rise, three alarm lights sequentially transitioned from green to red. At 16
:
18
:
44, the flame spread horizontally, and the red alarm lights on both sides were activated in real time. Subsequently, as the fire spread across the entire wall, nearly all the alarm lights turned red, effectively visualizing fire spread. Experiments have proven (Fig. S24a and b†) that the aforementioned data can be viewed in real-time on the web page within a range of 0–850 km without any signal delay. This achieves synchronized communication among all relevant parties. The OMAB-based FWD system offers sufficient time of only several seconds for the building guard to manually extinguish the small fire risk or launch the fire warning signal for timely evacuation of people who live in the high-rise level of the building. More importantly, the fire station at position 3 can also obtain the real-time remote-sync fire alarm signal to timely assess the building fire and make a reasonable and rapid fire-fighting strategy, and this will greatly mitigate or even prevent critical fire disasters. Additionally, the FWD system's remote, multi-location monitoring allows efficient dissemination of fire data, supporting timely decision-making across homeowners. Clearly, these above features collectively underscore the OMAB-based FWD system's potential for integration into practical fire safety applications, representing a significant advance in fire safety and prevention in buildings and houses.
Conclusion
In summary, we reported a transparent hybrid composite nanocoating based on a novel layered oxidized MXene and thus constructed a remote-sync fire-warning device for real-time monitoring of the fire risks in buildings. The lamellar OM sheets were synthesized by using a controllable oxidation of MXene at room temperature and a transparent OM/ANFs/BA interconnected network was thus constructed to improve the flame resistance of the flammable polymer foam and wooden materials, for example, a flame extinguishing phenomenon in 10 s and an improved LOI value from 20.2% for pure wood to 34.6% for the coated wood. Further, the hybrid nanocoating also provided a rapid and sensitive cyclic fire warning response in 1.5 s for >60 cycles. The structural observation disclosed that the inclusion of ANFs significantly accelerated the transformation of OM sheets to form a compact and continuous C/N/B-doped TiO2 layer during pyrolysis. Meanwhile, upon flame exposure, the dense titanium oxide mesh underwent electron excitation, leading to a notable transition in resistance from an insulating to a conductive state, resulting in ultra-fast fire-warning response and recovery times (<1.5 s). Integration of this nanocoating with the as-developed hardware and software enabled real-time transmission of fire signals over a long distance of 850 km, achieving remote-sync fire warning and monitoring between the local fire scene and fire station, which is promising to mitigate or even prevent critical fire disasters. Clearly, the OMAB nanocoating and the FWD system as-developed are anticipated to play an increasingly critical role in fire prevention in buildings and wooden houses.
Data availability
The data supporting this article have been included as part of the ESI.†
Author contributions
Ye-Jun Wang, Bi-Fan Guo and Ling-Yu Lv performed the experiments, analyzed the data, and wrote the manuscript, and they contributed equally to this work. Pei-Yuan Lv and Yang Li helped in the experiment for the construction of the visual system. Pei-Yuan Lv assisted with the experiments and collated the data. Guo-Dong Zhang, Jie-Feng Gao, Pingan Song and Kun Cao revised the content of the article and provided useful suggestions. Cheng-Fei Cao performed supervision, review, and editing. Long-Cheng Tang formulated the project and designed the concept and performed supervision, review, and editing. All the authors discussed the results and commented on the manuscript.
Conflicts of interest
The authors declare no conflict of interest.
Acknowledgements
This work was financially supported by the Natural Science Foundation of China (52373033), the Key R&D Program Project of Zhejiang Province (2024C01194, 2025C01159) and the Science and Technology Key Project of Zhejiang Province (LZ22E030002).
References
- M. P. North, S. L. Stephens, B. M. Collins, J. K. Agee, G. Aplet, J. F. Franklin and P. Z. Fulé, Science, 2015, 349, 1280–1281 CrossRef CAS PubMed.
- D. M. J. S. Bowman and J. J. Sharples, Science, 2023, 381, 616–619 CrossRef CAS PubMed.
- I. R. Van Der Velde, G. R. Van Der Werf, S. Houweling, J. D. Maasakkers, T. Borsdorff, J. Landgraf, P. Tol, T. A. Van Kempen, R. Van Hees, R. Hoogeveen, J. P. Veefkind and I. Aben, Nature, 2021, 597, 366–369 CrossRef CAS PubMed.
- A. A. Stec, K. Dickens, J. L. J. Barnes and C. Bedford, Chemosphere, 2019, 226, 576–586 CrossRef CAS PubMed.
- A. Vallée, E. Sorbets, H. Lelong, J. Langrand and J. Blacher, Environ. Pollut., 2021, 269, 116140 CrossRef PubMed.
- J. Pickrell, Science, 2019, 366, 1427–1428 CrossRef CAS PubMed.
- Z. Ma, J. Zhang, C. Maluk, Y. Yu, S. M. Seraji, B. Yu, H. Wang and P. Song, Matter, 2022, 5, 911–932 CrossRef CAS.
- M. Zhu, Z. Ma, L. Liu, J. Zhang, S. Huo and P. Song, J. Mater. Sci. Technol., 2022, 112, 315–328 CrossRef CAS.
- E. Guillaume, V. Dréan, B. Girardin, F. Benameur, M. Koohkan and T. Fateh, Fire Mater., 2020, 44, 35–57 CrossRef CAS.
- D. Xu, C. Gao, Y. Liu, C. Ge, Y. Wei, Z. Peng, K. Liu, Y. Hong, W. Xu and J. Fang, Device, 2024, 2, 100366 CrossRef.
- J. Milke and R. Zevotek, Fire Technol., 2016, 52, 1235–1253 CrossRef.
- L.-Y. Lv, C.-F. Cao, Y.-X. Qu, G.-D. Zhang, L. Zhao, K. Cao, P. Song and L.-C. Tang, Mater. Sci. Eng., R, 2022, 150, 100690 CrossRef.
- Q. Wu, L.-X. Gong, Y. Li, C.-F. Cao, L.-C. Tang, L. Wu, L. Zhao, G.-D. Zhang, S.-N. Li, J. Gao, Y. Li and Y.-W. Mai, ACS Nano, 2018, 12, 416–424 CrossRef CAS PubMed.
- L. Cao, Q. Liu, J. Ren, W. Chen, Y. Pei, D. L. Kaplan and S. Ling, Adv. Mater., 2021, 33, 2102500 CrossRef CAS PubMed.
- M. Mao, K.-X. Yu, C.-F. Cao, L.-X. Gong, G.-D. Zhang, L. Zhao, P. Song, J.-F. Gao and L.-C. Tang, Chem. Eng. J., 2022, 427, 131615 CrossRef CAS.
- F.-F. Chen, Y.-J. Zhu, F. Chen, L.-Y. Dong, R.-L. Yang and Z.-C. Xiong, ACS Nano, 2018, 12, 3159–3171 CAS.
- Q. Liu, X. Li, H. Zhang, J. Ren, S. Yang, L. Cao, J. Liang and S. Ling, Nano Energy, 2022, 101, 107630 CrossRef CAS.
- W. Liu, X. Wang, Y. Song, R. Cao, L. Wang, Z. Yan and G. Shan, Nano Energy, 2020, 73, 104843 CrossRef CAS.
- B. Wang, X. Lai, H. Li, C. Jiang, J. Gao and X. Zeng, ACS Appl. Mater. Interfaces, 2021, 13, 23020–23029 CrossRef CAS PubMed.
- X. Wu, N. Gao, X. Zheng, X. Tao, Y. He, Z. Liu and Y. Wang, ACS Appl. Mater. Interfaces, 2020, 12, 27691–27699 CrossRef CAS PubMed.
- H. Xie, X. Lai, H. Li, J. Gao and X. Zeng, J. Colloid Interface Sci., 2021, 602, 756–766 CrossRef CAS PubMed.
- J. Jia, N. Gao, R. Li, S. Liao, S. Lyu and Y. Wang, Chem. Eng. J., 2022, 431, 133285 CrossRef CAS.
- X. Zhao, L.-M. Peng, Y. Chen, X.-J. Zha, W.-D. Li, L. Bai, K. Ke, R.-Y. Bao, M.-B. Yang and W. Yang, Mater. Horiz., 2021, 8, 1230–1241 RSC.
- T. Fu, X. Zhao, L. Chen, W. Wu, Q. Zhao, X. Wang, D. Guo and Y. Wang, Adv. Funct. Mater., 2019, 29, 1806586 CrossRef.
- Y. Xu, L. Huang, J. Long, R. Zhang, Z. Zhong, L. Yang, L. Liu and Y. Huang, Compos. Sci. Technol., 2022, 217, 109083 CrossRef CAS.
- G. Li, Y. Hu, J. Chen, L. Liang, Z. Liu, J. Fu, C. Du and G. Chen, Adv. Funct. Mater., 2023, 33, 2303861 CrossRef CAS.
- A. VahidMohammadi, J. Rosen and Y. Gogotsi, Science, 2021, 372, eabf1581 CrossRef CAS PubMed.
- S. Li, W. Gu, Y. Sun, D. Zou and W. Jing, Ceram. Int., 2021, 47, 29930–29940 CrossRef CAS.
- B. Guo, Y. Wang, C. Cao, Z. Qu, J. Song, S. Li, J. Gao, P. Song, G. Zhang, Y. Shi and L. Tang, Adv. Sci., 2024, 11, 2309392 CrossRef CAS PubMed.
- J. B. Lee, G. H. Choi and P. J. Yoo, J. Alloys Compd., 2021, 887, 161304 CrossRef CAS.
- R. B. Rakhi, B. Ahmed, M. N. Hedhili, D. H. Anjum and H. N. Alshareef, Chem. Mater., 2015, 27, 5314–5323 CrossRef CAS.
- J. C. Parker and R. W. Siegel, J. Mater. Res., 1990, 5, 1246–1252 CrossRef CAS.
- J. Pang, R. G. Mendes, A. Bachmatiuk, L. Zhao, H. Q. Ta, T. Gemming, H. Liu, Z. Liu and M. H. Rummeli, Chem. Soc. Rev., 2019, 48, 72–133 RSC.
- 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.
- M. Naguib, M. Kurtoglu, V. Presser, J. Lu, J. Niu, M. Heon, L. Hultman, Y. Gogotsi and M. W. Barsoum, Adv. Mater., 2011, 23, 4248–4253 CrossRef CAS PubMed.
- C. E. Ren, M. Zhao, T. Makaryan, J. Halim, M. Boota, S. Kota, B. Anasori, M. W. Barsoum and Y. Gogotsi, ChemElectroChem, 2016, 3, 689–693 CrossRef CAS.
- Z.-H. Zhang, J.-W. Zhang, C.-F. Cao, K.-Y. Guo, L. Zhao, G.-D. Zhang, J.-F. Gao and L.-C. Tang, Chem. Eng. J., 2020, 386, 123894 CrossRef CAS.
- Z.-R. Yu, S.-N. Li, J. Zang, M. Zhang, L.-X. Gong, P. Song, L. Zhao, G.-D. Zhang and L.-C. Tang, Composites, Part B, 2019, 177, 107347 CrossRef CAS.
- J. Huang, Z. Lu, J. Li, D. Ning, Z. Jin, Q. Ma, L. Hua, E. Song and M. Zhang, Carbohydr. Polym., 2021, 255, 117330 CrossRef CAS PubMed.
- B. Wang, Z. Mao, D. Li, K. Zhang, C. Zhou, M. Ren and T. Li, Comput. Mater. Sci., 2020, 185, 109957 CrossRef.
- F. Liu, P. Ye, Q. Cheng, D. Zhang, Y. Nie, X. Shen, M. Zhu, H. Xu and S. Li, Inorg. Chem., 2024, 63, 14630–14640 CrossRef CAS PubMed.
- Y.-C. Wang, M.-H. Chen, Z.-W. Fan, Y. Wang, C.-X. Huang, H.-F. Wang, J.-P. Lang and Z. Niu, Chem. Commun., 2024, 60, 10692–10695 RSC.
- X. Wang, S. Liao, H. Huang, Q. Wang, Y. Shi, P. Zhu, Y. Hu, R. Sun and Y. Wan, Small Methods, 2023, 7, 2201694 CrossRef CAS PubMed.
- D. Manna, R. Lo, J. Vacek, V. M. Miriyala, P. Bouř, T. Wu, Z. Osifová, D. Nachtigallová, M. Dračinský and P. Hobza, Angew. Chem., Int. Ed., 2024, 63, e202403218 CrossRef CAS PubMed.
- Y. Cheng, Y. Xie, H. Cao, L. Li, Z. Liu, S. Yan, Y. Ma, W. Liu, Y. Yue, J. Wang, Y. Gao and L. Li, Chem. Eng. J., 2023, 453, 139823 CrossRef CAS.
- A. Roy, A. Choudhury and C. N. R. Rao, J. Mol. Struct., 2002, 613, 61–66 CrossRef CAS.
- Q. Li, S. Zheng, Z. Liu, W. Li, X. Wang, Q. Cao and F. Yan, Adv. Mater., 2024, 2413901 CrossRef CAS PubMed.
- H. He, Y. Qin, J. Liu, Y. Wang, J. Wang, Y. Zhao, Z. Zhu, Q. Jiang, Y. Wan, X. Qu and Z. Yu, Chem. Eng. J., 2023, 460, 141661 CrossRef CAS.
- S. T. Lazar, T. J. Kolibaba and J. C. Grunlan, Nat. Rev. Mater., 2020, 5, 259–275 CrossRef CAS.
- Z. Yu, Y. Wan, Y. Qin, Q. jiang, J.-P. Guan, X.-W. Cheng, X. Wang, S. Ouyang, X. Qu, Z. Zhu, J. Wang and H. He, Chem. Eng.
J., 2023, 477, 147187 CrossRef CAS.
- Z. Y. Chen, Y. Y. Wu, S. C. Liu, Y. Li, Z. Q. Guan, C. F. Cao, G. D. Zhang, B. Tuten, J. F. Gao, Y. Q. Shi, P. Song and L. C. Tang, Adv. Funct. Mater., 2025, 35, 2413362 CrossRef CAS.
- S. Chertopalov and V. N. Mochalin, ACS Nano, 2018, 12, 6109–6116 CrossRef CAS PubMed.
- Y. Yang, L. Yin, Y. Gong, P. Niu, J. Wang, L. Gu, X. Chen, G. Liu, L. Wang and H. Cheng, Adv. Mater., 2018, 30, 1704479 CrossRef PubMed.
- C. Negi, P. Kandwal, J. Rawat, M. Sharma, H. Sharma, G. Dalapati and C. Dwivedi, Appl. Surf. Sci., 2021, 554, 149553 CrossRef CAS.
- T. Boningari, S. N. R. Inturi, M. Suidan and P. G. Smirniotis, Chem. Eng. J., 2018, 350, 324–334 CrossRef CAS.
- L. Chen, H.-B. Zhao, Y.-P. Ni, T. Fu, W.-S. Wu, X.-L. Wang and Y.-Z. Wang, J. Mater. Chem. A, 2019, 7, 17037–17045 RSC.
- H. Chen, J. Zhou, S. Liu, S. Wang and X. Gong, Composites, Part A, 2022, 158, 106994 CrossRef.
- W. Chen, P. Liu, Y. Liu, Q. Wang and W. Duan, Chem. Eng. J., 2018, 353, 115–125 CrossRef CAS.
- T. Fu, X. Zhao, L. Chen, W. Wu, Q. Zhao, X. Wang, D. Guo and Y. Wang, Adv. Funct. Mater., 2019, 29, 1806586 CrossRef.
- X. Li, J. S. Del Río Saez, X. Ao, A. Yusuf and D.-Y. Wang, Chem. Eng. J., 2022, 431, 134108 CrossRef CAS.
- H. He, J. Liu, Y. Wang, Y. Zhao, Y. Qin, Z. Zhu, Z. Yu and J. Wang, ACS Nano, 2022, 16, 2953–2967 CrossRef CAS PubMed.
- Z.-R. Yu, M. Mao, S.-N. Li, Q.-Q. Xia, C.-F. Cao, L. Zhao, G.-D. Zhang, Z.-J. Zheng, J.-F. Gao and L.-C. Tang, Chem. Eng. J., 2021, 405, 126620 CrossRef CAS.
- W. Wei, Y. Yi, J. Song, X. Chen, J. Li and J. Li, ACS Appl. Mater. Interfaces, 2022, 14, 13790–13800 CrossRef CAS PubMed.
- S. Qiu, R. Allan, R. Nilavalan, J. Ivey, S. Butterfield and M. Li, SN Appl. Sci., 2021, 3, 379 CrossRef.
- C. F. Cao, G. T. Zhu, B. Yu, W. Y. Hu, L. Xue, B. F. Guo, W. Cai, S. Huo, W. Wang, P. Song, L. C. Tang and H. Wang, Nano Today, 2025, 62, 102719 CrossRef CAS.
- D. Bhattacharyya, T. Kim and S. Pal, Sensors, 2010, 10, 10506–10523 CrossRef PubMed.
- F. Bode, A. Simion, I. Anghel, M. Sandu and D. Banyai, Fire, 2023, 6, 451 CrossRef.
- N. Weerakkody, N. White and K. Moinuddin, Fire Mater., 2024, 48, 668–681 CrossRef CAS.
- E. Guillaume, V. Dréan, B. Girardin, F. Benameur, M. Koohkan and T. Fateh, Fire Mater., 2020, 44, 35–57 CrossRef CAS.
- S. Yuan, K. Xiang, F. Yan, Q. Liu, X. Sun, Y. Li and P. Du, Buildings, 2022, 12, 575 CrossRef.
|
This journal is © The Royal Society of Chemistry 2025 |
Click here to see how this site uses Cookies. View our privacy policy here.