Recent progress of 3D-printed polymeric gel sensors for flexible electronics

Abstract

Solvent-impregnated polymeric gels, distinguished by their remarkable property tunability and excellent mechanical compatibility with biological tissues, emerge as highly promising candidates for flexible sensing materials and devices. These gel sensors are capable of transducing diverse health-related stimuli into detectable signals, thereby facilitating point-of-care diagnostics and advanced cyborg feedback systems. The reliable construction of materials or devices for gel sensors necessitates the development and application of suitable manufacturing techniques. Additive three-dimensional (3D) printing has substantial potential in this context, offering advantages such as high production efficiency and precision. This review provides a comprehensive examination of the materials and applications of 3D-printed gel sensors. The classification and physical properties of polymeric gels are first introduced as a foundation. We then focus on direct ink writing and digital light processing, with a comparative analysis of their key characteristics. Additionally, the diverse application scenarios of gel-based sensors are summarized, highlighting their versatility. Finally, the limitations of current research are critically analyzed, and potential future directions are outlined, providing a strategic framework for advancing this rapidly evolving field.

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Wider impact

Recent advancements in soft, flexible materials have opened exciting possibilities for next-generation wearable technology and health monitoring systems. This review explores the potential of gel-based materials, which are soft, adaptable, and compatible with human tissues, making them ideal for developing flexible sensors. These sensors can detect important health signals, such as movement, pressure, and temperature, and could revolutionize fields like personalized healthcare and robotics. A key focus of this review is the use of 3D printing to precisely shape and customize these materials, enabling faster, more efficient manufacturing. Beyond healthcare, these innovations could lead to smarter wearables, improved human–machine interfaces, and even advanced environmental sensors. By examining both current advancements and future directions, this review contributes to the ongoing development of materials that could transform how we interact with technology in daily life.

1. Introduction

In recent years, solvent-impregnated polymeric gels have emerged as highly versatile materials, with significant advancements in multiple applications such as flexible sensors,^1–3 bio-implantable electrodes,^4–6 skin protection,^7,8 drug delivery,⁹ and object recognition.¹⁰ Their exceptional physical and chemical properties, combined with their tunable mechanical characteristics resembling soft biological tissues, make these gels ideal for the development of next-generation flexible electronics.¹¹ Unlike conventional rigid semiconductors and brittle circuit boards, flexible electronics can effectively resolve the mechanical mismatch at the biotic–abiotic interface,¹² enabling their immense potential in continuous health monitoring,^13–15 interventional therapies,¹⁶ biomimetic materials,¹⁷ and bioengineering.^18–22 Semisolid polymeric gels can serve as a viable material candidate for providing mechanical support or acting as key sensing elements in flexible electronics. Current research has successfully demonstrated various types of flexible polymeric gel sensors capable of transmitting environmental signals,^23,24 monitoring human motion,^25–27 and detecting vital signs,^28–30 paving the way for broader applications.

Among the various fabrication techniques for polymeric gel films in sensors, 3D printing has garnered remarkable attention. As an advanced additive manufacturing technology, 3D printing enables the construction of intricate structures through a layer-by-layer deposition under the precise control of programmed procedures. This technique has been widely adopted across diverse fields, such as microelectronics,^31–33 construction,^34–38 and aerospace.^39,40 Compared to conventional approaches like photolithography,^41,42 transfer printing,^43–46 and stencil-based blade coating,^47–49 3D printing offers distinct advantages of reduced production costs, enhanced material versatility, environmental sustainability, high precision, and improved efficiency. Furthermore, its capability to create intricate 3D microstructures is particularly advantageous for fabricating gel sensors with complex architectures that enhance sensitivity. By tailoring the composition of precursor solutions, 3D printing can achieve resolutions ranging from the micron to millimeter scale,^33,50–53 facilitating the fabrication of sensors that conform to irregular surfaces and enabling customizable device designs for practical applications. Two popular 3D printing approaches for gel sensor fabrication are extrusion-based direct ink writing (DIW) and light-based digital light processing (DLP). These approaches support the development of sophisticated gel structures tailored for diverse sensors (Fig. 1).

Fig. 1 Schematic overview of the approaches and applications for 3D-printed gel sensors.

The conceptual foundation of hydrogels was first established in the late 19th century to describe inorganic salt-containing colloidal systems. A transformative breakthrough occurred in 1960, when Wichterle et al. developed biocompatible hydrogels, subsequently pioneering their application in contact lens fabrication – a milestone that laid the material foundation for flexible electronics.⁵⁴ Seminal advances in tough gels (Suo et al., 2012)⁵⁵ and ionic skins (Suo et al., 2014)⁵⁶ subsequently enabled the design of stimuli-responsive sensing systems. The evolution of 3D-printed polymeric gel sensors traces its origins to three key developments: (1) bioprinting of cell-laden hydrogels (Boland et al., 2003),^57,58 (2) 3D microvascular network fabrication (Lewis et al., 2011),²⁰ and (3) hydrogel-based actuators and robotics (Zhao et al., 2017).⁵⁹ These innovations, combined with shape-morphing 3D gel architectures (Lewis et al., 2016)⁶⁰ and multi-material additive manufacturing techniques, established the infrastructure for scalable production. Current research (2020-present) builds upon these foundations through integrated multifunctional sensor system applications.

Despite the burgeoning research interest, only a limited number of reviews are dedicated to the advancements in the field of 3D-printed flexible gel sensors.^61–64 Some review articles predominantly focus on a single material type, thereby overlooking the far-reaching implications and technological nuances of 3D printing technologies in the development of flexible gel sensors.^65–67 Others are narrowly centered around the progress of a particular sensor type, failing to provide a holistic view.^61,68–70 Notably, 3D-printed polymeric gels have not been thoroughly examined and summarized in terms of their fabrication processes, forming techniques, and the full spectrum of sensor applications. Here, this review aims to present a comprehensive and in-depth overview of the recent progress in 3D printed gel sensors. The context is systematically organized into three main sections. Firstly, an intuitive classification of polymeric gels is established based on the chemical composition of solvent systems, and a detailed analysis of their mechanical properties is conducted in relation to different cross-linked networks. Next, 3D printing techniques of DIP and DIW are illustrated, and a diverse range of applications from 3D printed sensors are highlighted. Finally, we present a forward-looking perspective on the future of 3D-printed gel sensors, covering key areas such as material selection strategies, innovative forming techniques, advanced sensor design concepts, and potential application scenarios.

2. Classification of polymeric gels for sensing applications

From a chemical composition perspective, a polymeric gel is a composite material consisting of a cross-linked polymer framework, with its interstitial spaces filled by solvents. To impart specific functions to gels, various substances are incorporated to enhance their physical, chemical, and biological properties. The vast diversity of gel materials and their complex compositions make establishing a clear and consistent classification challenging. A more practical approach involves categorizing gels based on the type of filling solvents or the nature of their polymer cross-linking networks.

2.1. Classification of gels based on solvent types

The gels can be classified into organogels, organohydrogels, and hydrogels based on the chemical nature of the solvent (Fig. 2(a)).

Fig. 2 Classification of polymeric gels based on solvent types. (a) Schematic illustration of the different solvents and properties of organogels, organohydrogels, and hydrogels. (b) Demonstration of an organogel.⁷¹ Copyright© (2021) Advanced Material. (c) Demonstration of an organohydrogel.⁷² Copyright© (2022) Chemical Engineering Journal. (d) Demonstration of a hydrogel.⁷⁴ Copyright© (2024) Nature.

Organogels utilize organic liquids as the filling solvents, exhibiting multifunctional properties such as inherent hydrophobicity, anti-freezing capability, and low swelling. Wu et al. reported the polymerization of a fluorinated ionic liquid within another fluorinated ionic liquid, resulting in a conductive organogel that was stretchable, 3D printable, and self-healing underwater.⁷¹ The organogel was composed of two ionic liquids (ILs) sharing the same hydrophobic anion, bis(trifluoromethanesulfonyl) imide (TFSI). The organogel's resistance to interference from water molecules was attributed to the weak hydrogen bonding capabilities of the C–F bond. Notably, when two pieces of gel were joined, they demonstrated strong anti-swelling and self-healing properties, even after soaking in water for 3 hours (Fig. 2(b)).

Organohydrogels employ aqueous blends of water-miscible solvents as the filling liquids, imparting adjustable softness and enhanced temperature tolerance. Sun et al. reported the synthesis of an organohydrogel by using a binary solvent system of dimethyl sulfoxide (DMSO) and water in a polymer framework of polyvinyl alcohol–lignin nanoparticles (PVA–LNs).⁷² DMSO formed extensive hydrogen bonds with water molecules, effectively preventing the formation of ice crystals and reducing water evaporation. The gel preserved its soft, stretchable, and bendable characteristics for 7 days. These properties make water-containing organohydrogels a reliable option for the production of environmentally stable flexible gels (Fig. 2(c)). Similarly, polyol compounds exhibit analogous properties. Zhao et al. developed an organohydrogel using an ethylene glycol (EG) and H₂O binary solvent system, where the polymer network was based on acrylated β-cyclodextrin (β-CD) and formed through precise host–guest self-assembly to create a polymerizable rotaxane hydrogel (PR-Gel).⁷³

Hydrogels, with water serving as the solvent, are inherently hydrophilic. Typical monomers include: acrylic acid (AAc), N-isopropylacrylamide (NIPAM), and acrylamide (AAm). Strong hydrogen bonds within the polymer networks can promote high water inclusion and enhance mechanical properties, while soluble ions or incorporated conductive nanomaterials and polymers contribute to ionic and electrical conductivities. Moreover, they can exhibit excellent biocompatibility, and can also degrade gradually within the human body. These properties are essential for the development of biocompatible flexible sensors. Zang et al. reported an injectable, degradable, and wireless microstructural hydrogel composed of PVA/chitosan (CS) for ultrasound monitoring of intracranial signals.⁷⁴ The hydrogel sensor was capable of independently detecting intracranial pressure, temperature, pH, and flow rate, with a detection depth of up to 10 cm. It simulated the in vivo environment in phosphate-buffered saline (PBS) solution at 37 °C and degraded almost completely within 4 months (Fig. 2(d)).

2.2. Classification of gels based on gel networks

The process by which a solution transforms into a gel is known as gelation. A gel is a semi-solid material composed of multiple components and a high proportion of liquid. Although a gel is predominantly liquid by weight, the 3D cross-linked network within the liquid allows it to exhibit solid-like behavior. The crosslinking imparts strength to the gel, and enhances its adhesive properties, allowing for a broad spectrum of characteristics.

A polymeric gel can consist of either a physically or a chemically cross-linked network. A physically cross-linked network is formed through ionic or intermolecular interactions, such as dipole–dipole interactions, dipole–induced interactions, hydrogen bonding, and hydrophobic forces (Fig. 3(a)). These physical crosslinks are often reversible, making gels particularly attractive for applications like drug delivery⁷⁵ and reversible reactions.^76,77 Furthermore, physically cross-linked gels do not need additional crosslinking agents, thereby reducing the risk of introducing toxic substances and aligning with eco-friendly standards. Methods such as freeze–thaw cycles and Coulomb force interactions are commonly implemented to produce physically cross-linked network gels, with successful applications in systems like PVA,^78,79 Fe³⁺/P(AAm-co-AAc),⁸⁰ CaCO₃/PAA/alginate,⁸¹ and supramolecular polyelectrolyte.^71,82,83 In contrast, a chemically cross-linked network is formed through stable covalent bonds between polymer chains (Fig. 3(b)). Chemically cross-linked networks are irreversible, more stable, and offer superior mechanical properties compared to their physically cross-linked counterparts, making them ideal for applications that demand greater durability, such as PVA/Borax⁸⁴ and PAAm.^56,85

Fig. 3 Schematic illustrations and examples of gel network types. (a) Physically cross-linked networks. PVA.⁷⁹ Copyright © (2023) Advanced Material. (b) Chemically cross-linked networks. PAAm.⁸⁵ Copyright© (2023) Advanced Material. (c) Double cross-linked networks. H₃PO₄/PVA/CS/GA.³⁰ Copyright© (2024) ACS Applied Materials & Interfaces. (d) Semi-interpenetrating networks or semi-IPN. PBZ/PVA-co-PE.⁹³ Copyright© (2024) Chemistry-A European Journal. (e) Interpenetrating networks or IPN. PVA/PAAm.⁹⁷ Copyright© (2023) Journal of Energy Storage. Alginate/PAAm.⁵⁵ Copyright© (2012) Nature. PVA/PAAm.⁹⁶ Copyright© (2024) ACS Applied Materials & Interfaces.

A polymeric gel can feature a double cross-linked network. This network is composed of one or more polymers that form composite materials via multiple types of crosslinks. This can entail a combination of physical and chemical crosslinking, two different types of chemical bonds, or distinct physical interactions (Fig. 3(c)). Examples include maleiated sodium hyaluronate (MHA)/thiolated sodium hyaluronate (SHHA),⁸⁶ κ-carrageenan/PAAm,⁸⁷ H₃PO₄/PVA/CS/glutaraldehyde,³⁰ Fe³⁺/MBAA/P(AAm-co-AAc),⁸⁸ agar/PAAm,⁸⁹ PVA/SiO₂/PAAm,⁹⁰ and PAA/zwitterion.⁹¹ Additionally, gel monomers bearing multiple functional groups are often used to fabricate gels with densely cross-linked networks, tuning the gel mechanical properties.^26,86,92

A polymeric gel can be equipped with a semi-interpenetrating polymer network (semi-IPN),⁹³ which consists of one or more cross-linked networks interwoven with linear polymer chains forming a three-dimensional structure (Fig. 3(d)). The hallmark of semi-IPN is the presence of at least one linear polymer chain, which interacts with the network through physical interactions rather than covalent bonds. Despite being non-covalent and linear, the polymers in semi-IPNs remain entangled within the cross-linked network. This strategy is often used to improve the mechanical properties and structural stability of gels, as demonstrated in systems of Ag/PAAm/alginate¹³ and polybenzoxazine/poly(vinyl alcohol-co-ethylene) (PBZ/PVA-co-PE).⁹³

A polymeric gel can have an interpenetrating polymer network (IPN), which consists of two or more independent cross-linked networks that do not form covalent bonds between each other (Fig. 3(e)). These networks are spatially interlocked, meaning they cannot be separated without breaking chemical bonds. To form an IPN, at least one polymer must be synthesized or cross-linked in the presence of another polymer, as simply mixing two already cross-linked networks will not result in an IPN. The multiple interlocking networks within the IPN allow for the design of gels with exceptional mechanical strength. Typically, the primary network is highly rigid and serves as a sacrificial component, while the secondary network provides flexibility, enabling greater deformation. Numerous IPN gels have been prepared, such as PAMPS/PAAm,⁹⁴ PAMPS/PAA,⁹⁵ PVA/PAAm,^96,97 and alginate/PAAm.⁵⁵ These IPNs exhibit outstanding sensing performance and mechanical properties, offering a robust material foundation for advanced sensor applications. The innovative structure significantly enhances traditional gels in terms of stretching, compression, and torsion, making them ideal for next-generation materials in sensor technology.

3. Key properties of gels for sensing applications

As a key component in flexible sensors, polymeric gels can exhibit favorable mechanical, rheological, electrical, optical, and bioactive characteristics. The functionalized polymeric networks together with the impregnated solvent in a gel, collectively play a crucial role in enhancing or tuning various properties, such as electrical or ionic conductivity, adhesion, biocompatibility, Young's modulus, stretchability, toughness, and strength,^98,99 which are essential for sensing applications.

3.1. Electrical properties

To meet a growing demand for high integration, simplicity, and portability in flexible electronics, electrical-signals based sensors are typically a preferred choice due to their versatility and ease of integration. External stimuli, such as physical, biochemical, and biological signals, can be transduced into capacitive and conductive signals from polymeric gels for sensing applications.

As a common design approach for flexible sensors, conductive hydrogels are used as resistive sensors, where the sensor's resistance exhibits a linear or nonlinear relationship with the signal. And polymeric gels can serve as dielectrics in parallel-plate-type capacitors, whose capacitance can be dictated by the change of area or thickness of the gel dielectric under external stimuli.^98,99 Free-moving ions can be present in the incorporated gel liquid, therefore forming electric double layers (EDLs) at the electrolyte-electrode interfaces.¹⁰⁰ These EDLs can impart large capacitances on the order of several μF cm⁻² in the kHz frequency range, and are exploited for sensitively measuring small pressures or strains.^101–103

Polymeric gels are also capable of functioning as a conductor. Depending on the nature of their charge carriers, they can be categorized into electrically conductive gels and ionic conductive gels. In electrically conductive gels, the charge carriers are electrons. Conductive fillers such as carbon nanotubes (CNTs),¹⁰⁴ graphene,¹⁰⁵ metal nanowires¹⁰⁶ and metal nanoparticles,¹⁰⁷ are commonly incorporated to boost gel conductivity. The abundance of fillers creates reliable conductive pathways within gels, thereby establishing their conductivities (Fig. 4(a)). The electrical conductivity of such gels can span a range of 10⁻³ to 5 × 10⁴ S cm⁻¹.^13,108–115 Another approach to preparing electrically conductive gels involves the introduction of conductive polymer monomers such as 3,4-ethylenedioxythiophene (EDOT), aniline, and pyrrole into the gel precursor solution. Through post-treatment, conductive polymer networks are formed, endowing the gel with conductive functionality. Alternatively, conductive polymers can be directly added into the gel, and are then thoroughly dispersed to create conductive pathways (Fig. 4(b)). Gels containing these conductive polymers can exhibit conductivities ranging from 0.1 to 40 S cm⁻¹.^116–122

Fig. 4 Schematic diagram of approaches for fabricating conductive gels. (a) Electrically conductive gels using conductive nanofillers. (b) Electrically conductive gels using conductive polymers. (c) Ionically conductive gels using free conductive ions. (d) Ionically conductive gels using cationic or anionic polymers.

Ionic conductive gels rely on free-moving ions in the gel liquid to carry the current. These gels are usually homogeneous composite materials, characterized by uniform and stable physicochemical properties. The addition of free ions or ionic polymers, such as Na⁺, Ca²⁺, K⁺ Cl⁻, NO₃⁻, SO₄²⁻, and poly(2-acrylamido-2methylpro-panesulfonic acid) (PAMPS) leads to the formation of conductive pathways as the free ions move within the gel (Fig. 4(c) and (d)). The ionic conductivity of these gels is typically a range from 10⁻⁶ to 10 S cm⁻¹, and is dependent on directional transportation of ions.^71,123–130

3.2. Mechanical properties

The mechanical properties of polymeric gels are crucial physical characteristics that determine their applicability across different fields. However, in the application scenarios of gel sensors, the devices must withstand repeated deformation to meet testing requirements. Therefore, a well-designed gel cross-linked network is essential to ensure excellent tensile and compressive recovery, along with minimal hysteresis.

IPN gels have been designed and proven to be an effective approach for improving mechanical properties. For example, Fu et al. developed a 3D printable network structure by enhancing IPN hydrogels with microgels, achieving remarkable mechanical toughness and high detection sensitivity in strain sensors (GF = 0.253) and pressure sensors (0.925 kPa⁻¹).⁹⁵ First, the PAMPS microgels were soaked in an AAc solution to form a shear-thinning ink. Followed by 3D printing and UV curing, the precursors underwent crosslinking to form an interpenetrating network structure, resulting in mechanically enhanced IPN gels (Fig. 5(a)). The mechanical properties of these IPN gels were dependent on the concentrations of PAMPS microgels and AAc. As the proportion of PAMPS microgels increased, there was a substantial improvement in the fracture strength, Young's modulus, and toughness of hydrogels. Specifically, with 5 wt% PAMPS microgels and 30 wt% AAc, the hydrogel achieved a tensile strength of 1.61 MPa, toughness of 5.08 MJ m⁻³, and a Young's modulus of 155 kPa (Fig. 5(b) and (c)). In tests of cyclic loading–unloading, the hydrogel exhibited minimal hysteresis during an 85% compression cycle, with negligible energy dissipation (Fig. 5(d)). The observed reduction in hysteresis is likely attributed to the deformation of the microgels, highlighting the gel's long-term stability during prolonged deformation and underscoring its promising potential as an advanced sensor material.

Fig. 5 Mechanical properties of gels for sensing applications. (a) DIW-printed IPN gels using inks composed of PAMPS microgels soaked with AAc, followed by UV light post-printing curing. (b) Tensile stress–strain curves of tough gels with varying microgel concentrations. (c) Young's modulus and toughness of gels with 30 wt% AAc and varying microgel concentrations. (d) Cyclic compressive loading–unloading curves of gels.⁹⁵ Copyright© (2023) Materials Horizons. (e) Schematic illustration of the chemical composition of a nanocomposite gel. (f) Tensile stress–strain curve of a nanocomposite gel. (g) Stretchability of nanocomposite gels under different tensile strains. (h) Compressive stress–strain curves of nanocomposite gels at the strain of 10%, 20%, 30%, 40% and 50%, respectively.¹³¹ Copyright© (2024) Chemical Engineering Journal. (i) The peptide cross-linker exhibited an α-helical structure in DESs. (j) Cyclic loading–unloading stress–strain curves at a maximum strain of 100%, 300%, and 500%. (k) Resilience of the gel. (l) Stress–strain curves of gel during 5 testing cycles.¹³² Copyright© (2022) Nature Communications.

Powder fillers not only enhance the rheological properties of precursor solutions but also act as effective mechanical reinforcements. With surface-functionalized groups, powder fillers facilitate strong intermolecular interactions with both solvent and polymer networks, leading to exceptional mechanical properties in hydrogels. For example, Liu et al. utilized cellulose nanocrystals (CNCs) to modulate polyaniline (PANI) for the preparation of composite inks, which were subsequently processed into wearable strain sensors via DIW 3D-printing technology.¹³¹ Initially, a cross-linked network of the composite material gel was formed by creating microcrystals through repeated freeze–thaw cycles of a PVA solution. CNCs served as an effective dispersant for polymer chains and stabilizer by electrostatic interactions. The functional groups of CNCs formed relatively weak, non-covalent interactions (electrostatic and hydrogen bonding) with PANI and PVA chains, forming a reversible cross-linked network in the gel. This network enabled mechanical reconstruction after disruption by external forces (Fig. 5(e)). The DIW-printed composite gel exhibited impressive mechanical properties, withstanding tensile strains up to 550% and a maximum tensile stress of 0.85 MPa (Fig. 5(f) and (g)), while showing minimal hysteresis during compression (Fig. 5(h)). The GF of the assembled strain sensor reached 20.5, likely due to the formation of the reversible non-covalent cross-linked network between the CNCs and the polymers, as well as the deformation of the porous structure within the composite gel.

Another effective approach involves optimizing the combination of gel solvents to promote intermolecular interactions with polymer chains, thereby further modifying mechanical properties. Zhang et al. developed peptide-enhanced eutectic gels by integrating α-helical structures into deep eutectic solvents (DESs), yielding a material with remarkable mechanical and functional performances. The gel exhibited exceptional versatility, operating across a temperature range from −20 °C to 80 °C, while maintaining stable and consistent electrical signals, even after undergoing 10 000 deformations over a duration of 30 hours.¹³² The peptide crosslinking agent, dissolved within the DESs matrix, facilitated the formation of α-helical structures stabilized by intramolecular hydrogen bonds between carbonyl and amino groups within the helix. Under the application of external forces, these hydrogen bonds were disrupted, enabling efficient dissipation of mechanical energy, thereby preserving the structural integrity of the gel (Fig. 5(i)). The peptide-enhanced eutectogels exhibited a combination of elasticity and stretchability, rendering them highly suitable for strain sensor applications. At a maximum strain of 100%, the gel had minimal energy loss, with only 2.25% of energy dissipated during the first deformation cycle, which further decreased to 1.34% in the second cycle and dropped to 0.88% by the fifth cycle. Comparable trends were observed at higher maximum strains of 300% and 500% (Fig. 5(j) and (k)). At a maximum strain of 500%, the gel showed a notable tensile recovery, regaining 78% of its original shape in the first cycle and 88% in the subsequent four cycles. At lower strains of 100% and 300%, the gel showed highly consistent tensile recovery over five cycles, closely approximating the mechanical behavior of biological tissues and natural rubber. The gel maintained excellent recovery properties during continuous compression cycles (Fig. 5(l)).

3.3. Interfacial adhesion

Interfacial adhesion is a critical property in wearable technologies, particularly in real-time applications, specifically: (1) the gel sensor adheres firmly to the surface, maintaining its secure attachment during testing while accurately detecting changes in deformation or pressure. (2) When the gel is combined with other materials to form a sensor, stable bonding at the interface preserves the structural integrity of the sensor. Interfacial adhesion involves various interactions, including dipole–dipole,^133,134 ion-dipole,^71,135 electrostatic forces,^136,137 cation–π interactions,^136,138 van der Waals forces,¹³⁹ and hydrogen bonding.^128,140 These intermolecular interactions occur between the gel and the material surface, providing effective dissipation mechanisms at the adhesive interface that help resist separation under external forces. Although flexible sensors can be assembled using appropriate adhesives,^141–143 developing stable and robust interfaces during the fabrication process remains a key focus of current scientific research.

In the composition of gel sensors, polymer molecular chains containing various functional groups, such as those found in dopamine derivatives,^144–146 tannic acid (TA),¹⁴⁷ and silk fibroin (SF),^148,149 interact with other materials and enable strong interfacial adhesion. SF, known for its functional groups capable of engaging in multiple interactions, has been widely utilized in biomedical applications, with its inherent adhesive properties being particularly evident when incorporated into hydrogels. Wang et al. demonstrated that incorporating SF into the gels of P(AAc-co-AAm)/PEGDA enhances their mechanical properties, tunable adhesive characteristics, and moisture retention. By adjusting SF content and 3D-printed microstructures on the surface, they achieved outstanding bonding performance, making the gel ideal for wearable strain sensors.¹⁴⁹ The adhesive properties on a glass substrate were measured by a 180° peeling test (Fig. 6(a)), showing 30–110 N m⁻¹. A 500 g weight was able to be attached to the hydrogel without falling, demonstrating sufficient interfacial strength to resist detachment under gravitational force (Fig. 6(b)). In addition, compared to the planar gel, the gel with a microstructured surface formed by DLP exhibited stronger bonding strength, due in part to the smaller angle between the interface and stretching direction (Fig. 6(c)).

Fig. 6 Interfacial properties of gels for sensing applications. (a) Schematic diagram of a 180° peeling test. (b) Strong adhesion between the hydrogel and a 500 g weight. (c) Adhesion forces of samples with oblique triangle prisms with different direction.¹⁴⁹ Copyright© (2024) Advanced Functional Materials. (d) Schematic illustration of another 180° peeling test. (e) Snapshots of the peeling test process. (f) The curves to investigate the interfacial toughness.¹⁵⁰ Copyright© (2021) International Journal of Smart and Nano Materials. (g) Schematic illustration of the 90° peeling test on various hydrogel–elastomer hybrids. (h) Photos of the hydrogel–elastomer interface during the peeling test, and a thin residual layer of hydrogel on the elastomer substrates. (i) Measured peeling forces per width of the hydrogel sheets for various hydrogel–elastomer hybrids.¹⁵¹ Copyright© (2016) Nature Communications.

Robust gel–elastomer interfaces are of great significance. This is because elastomers are commonly utilized in sensing devices, where they serve as encapsulation materials or substrates. Ge et al. reported the formation of a hybrid material by curing an elastomer of benzyl acrylate (BA) and poly(ethylene glycol) diacrylate (PEGDA) with UV light, followed by the subsequent curing a hydrogel layer of AAm and PEGDA on its surface, resulting in a robust interfacial bond.¹⁵⁰ The hydrogel and elastomer layers were attached to a stiff backing layer during the 180° peeling test in Fig. 6(d) and (e). It was observed that cohesive failure occurred within the hydrogel at the interface, leaving residual hydrogel on the elastomer surface. The interfacial toughness was measured to be 150 N m⁻¹ (Fig. 6(f)), enabling a robust strain sensor fabricated by DLP with a GF of 1.6. The high interfacial toughness was due to unreacted monomers or crosslinkers penetrating the elastomer–hydrogel interface and forming covalent bonds between the hydrogel and elastomer. To further enhance the interfacial adhesion between hydrogels and elastomers, Zhao et al. reported a simple and versatile method to achieve robust interfacial toughness exceeding 1500 N m⁻¹.¹⁵¹ In this approach, the elastomer surface was soaked in a benzophenone solution, followed by curing the hydrogel monomer on the elastomer surface. A standard 90° peeling test with stiff backing layers attached on the elastomer and hydrogel was employed to measure their interfacial adhesion strength (Fig. 6(g)). During the peeling test, it was found that cohesive failure occurred near the interface in the tough hydrogel, leaving a residual hydrogel layer on the elastomer (Fig. 6(h)). When the benzophenone concentration reached 10 wt%, the adhesion strength between the hydrogel and elastomer reached 1600 N m⁻¹. Moreover, the hydrogel maintained consistent bonding strength with various elastomers, highlighting the versatility of fabricating hydrogel–elastomer hybrid materials (Fig. 6(i)).

4. 3D-printing technology for the fabrication of gel sensors

Polymeric gels can be 3D printed through extrusion-based or light-based techniques, represented by DIW or DLP respectively. And a comparative summary of the two 3D printing techniques is provided below in Table 1. DIW utilizes a print head to extrude precursor ink in a predefined pattern, which is subsequently transformed into a gel via appropriate post-processes. While maintaining minimal ink consumption and multi-material compatibility, DIW imposes stricter requirements on ink rheological properties, coupled with its characteristic use of complex processes.^51,152 DLP leverages light projection to polymerize photosensitive monomers within a solvent, rapidly constructing 3D gel structures in a layer-by-layer manner. And this technology is particularly suitable for assembling complex components, enabling broader precision adjustment through mask pattern modification.^153,154 However, it typically requires sophisticated and costly equipment, with most current applications focusing on homogeneous precursor solutions.^155,156 Both DIW and DLP have been extensively employed in the fabrication of polymeric gels for sensing applications. Meanwhile, we systematically summarize the precursors, sensing performance, and several representative research achievements of 3D-printed sensors, as detailed in Tables 2 and 3.

Table 1 Mechanisms and characteristics of 3D printing methods

Printing methods	Illustration	Mechanisms	Pros	Cons
DLP		Photocuring in precursor solution	Complex component fabrication	Capital-intensive instrumentation
			Adjustable resolution	Monophasic composition
DIW		Precursor ink extrusion	Material compatibility	Complex process
			Minimal ink	Rigorous ink rheology

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Table 2 Comparison of the performance of gel sensors fabricated by DIW

Printed materials	Resolution (μm)	Mechanical properties		Application & sensitivity		Ref.
		E/σt/σc	Maximum strain
Notes: peptide cross-linkers (PCs), n-octadecyl acrylate (C18), tyramine-modified poly(vinyl alcohol) (PVA-Ph), 3-thiopheneboronic acid (TBA), poly(3,4-ethylenedioxythiophene):poly(4-styrene sulfonate) (PEDOT:PSS), potato anthocyanins (PSPA), glyceride monooleate (GMO), polyurethane (PU), transition metal carbides (MXenes), 3-dimethyl (methacryloyloxyethyl) ammonium propane sulfonate (DMAPS), 1-ethyl-3-methylimidazolium ethyl sulfate ([EMIM]ES), methyl chloride quaternized N,N-dimethylamino ethylacrylate (DMAEA-Q), relative humidity (RH), Young's modulus (E), tensile strength (σt), compressive strength (σc), not reported (NR).
PAMPS microgels, AAc	1000	155 kPa (E)	Tensile 1000%	Strain	GF = 0.253 (resistive)	a^95
		1.61 MPa (σt)	Compressive 85%	Pressure	0.925 kPa^−1 (resistive)
PVA, CNCs, glycerol, phytic acid, aniline	200	0.8 MPa (σt)	Tensile 550%	Strain	GF = 20.7 (resistive)	b^131
PCs, AAm, DESs	100	>1.0 MPa (σt)	Tensile 1800%	Strain	GF = 3.17 (resistive)	c^132
		4.5 MPa (σc)	Compressive 90%
C18 micelles, DMA, NaCl	410	23 kPa (σc)	Compressive 55%	Pressure	0.45 kPa^−1 (capacitive)	d^158
				Temperature	−6.25% °C^−1 (capacitive)
NIPAM, nanoclays, SCFs, PEGDA	<200	0.43 MPa (E)	Tensile 670%	Strain	GF = 7.0 (resistive)	e^160
				Temperature	−4% °C^−1 (resistive)
Carbomer, microgels, PVA, ceramic microplatelets, Fe^3+	600	6.9 MPa (σt)	Tensile 347.3%	Strain	GF = 2.5 (resistive)	f^161
EDOT, PVA-Ph, PSS, TBA	∼100	0.7 MPa (σt)	Tensile 580%	Pressure	2 kPa^−1 (capacitive)	g^159
					0.67 kPa^−1 (resistive)
				Temperature	−2.1% °C^−1 (resistive)
PEDOT:PSS, PVA	500	NR	Tensile 300%	Strain	GF = 4.07 (resistive)	h^174
PEDOT:PSS, HPU	200	58 kPa (σt)	Tensile 35%	Chemistry (pH)	0.55 pH^−1 (resistive)	i^180
Agar, sunflower oil, PSPA, GMO, beeswax	2000	NR	NR	Chemistry (amine)	−0.0404 μM^−1 (color)	j^181
Alginate, methylcellulose, sensor nanoparticles, living cells	1000	NR	NR	Chemistry (O2)	4.3/% (color)	k^182
CS, PVA, rGO	400	NR	Tensile >400%	Temperature	−1.1205% °C^−1 (resistive)	l^175
PU, PVA, MXene	1000	2.28 MPa (σt)	Tensile 400%	Strain	GF = 5.7 (resistive)	m^179
				Temperature	−5.27% °C^−1 (resistive)
Silver paste	1000	7.79 MPa (σt)	Tensile 107.21%	Temperature	−9.810 °C^−1 (resistive)	n^184
PAA, DMAPS, [EMIM]ES	260	2 MPa (E)	Tensile > 10 000%	Strain	GF = 1 (capacitive)	o^83
				Pressure	0.03 kPa^−1 (capacitive)
				Temperature	0.9 °C^−1 (resistive)
				RH	0.75 mV/% (voltage)
PAA, DMAEA-Q	260	∼1 MPa (E)	Tensile > 10 000%	Strain	GF = 1 (capacitive)	p^169
				Pressure	0.02 kPa^−1 (capacitive)
				RH	1 mV/% (voltage)
AAm, carbomer, CaCl2	50–510	0.82 MPa (σt)	Tensile 1100%	Strain	GF = 1.8 (resistive)	q^51
				Temperature	−0.82% °C^−1 (resistive)

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Table 3 Comparison of the performance of gel sensors fabricated by DLP

Printed materials	Resolution (μm)	Mechanical properties		Application & sensitivity		Ref.
		E/σt/σc	Strain
Notes: hexadecyl trimethyl ammonium bromide (CTAB), lauryl methacrylate (LMA), glycerol (Gly), 2-hydroxy ethyl acrylate (HEA).
AAm, AAc, PEGDA, Sudan I, glycerol, SF	150	45 kPa (E)	Tensile 1100%	Strain	GF = 1.29 (resistive)	a^149
AAm, BA, LiCl, PEGDA	NR	1.6 MPa (σt)	Tensile 900%	Strain	GF = 1.6 (resistive)	b^150
WPUA, NaCl, AAm, AAc	300	22.9 MPa (σt)	Tensile 583%	Strain	GF = 1.02 (resistive)	c^155
				Pressure	0.103 kPa^−1 (resistive)
AAc, Zr^4+	100	1.35 MPa (σt)	Tensile 855%	Pressure	2.8 kPa^−1 (capacitive)	d^164
			Compressive 60%
AAm, CTAB, AAc, NaCl, HEC, Gly, LMA, PEGDA	100	150 kPa (E)	Tensile 500%	Strain	GF = 5.84 (resistive)	e^166
			Compressive 90%	Pressure	1.13 kPa^−1 (resistive)
					4.0 kPa^−1 (capacitive)
AAm, PEDOT:PSS, HEA, ZnS phosphor	∼70	18.2 kPa (E)	Tensile 430%	Strain	GF = 2 (resistive)	f^170
					GF = 0.7 (capacitive)
				Pressure	0.102 kPa^−1 (capacitive)
AAc, PEGDA, nanoclay, DESs	50	6.2 MPa (E)	Tensile 292%	Pressure	0.08 kPa^−1 (resistive)	g^171
					9.15 kPa^−1 (capacitive)
PVA, MXene, AAm, AAc, DESs	500	0.2 MPa (σt)	Tensile 2770%	Strain	GF = 4.12 (resistive)	h^176
AAm, PEGDA, MgCl2	140	0.9 MPa (σt)	Tensile 650%	Strain	GF = 0.92 (capacitive)	i^172
				Pressure	0.84 kPa^−1 (capacitive)
PEE, DE, KCl	NR	100–480 kPa (σt)	Tensile 100–225%	Tensile	GF = 0.51 (capacitive)	j^156
				Shear	GF = 0.75 (capacitive)
				Pressure	3.41 kPa^−1 (capacitive)
				Twist	0.62% deg^−1 (capacitive)
AAm, carbomer, CaCl2	50–510	0.82 MPa (σt)	Tensile 1100%	Pressure	1.821 kPa^−1 (capacitive)	k^51
BA, PEGMA, PEGDA, ILs	5	63 kPa (E)	Tensile > 1500%	Pressure	15.1 kPa^−1 (capacitive)	l^173

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4.1. Direct ink writing for gel sensors

DIW is a cost-effective fabrication technique that uses compact equipment to extrude precursor ink into continuous filaments, enabling precise control over their deposition and layered assembly onto a substrate. To maintain consistent extrusion and structural integrity, it is essential to optimize the rheological properties of the ink. Key factors include high viscosity, shear-thinning behavior, appropriate yield stress, and pronounced thixotropy, which collectively enhance printability and ensure broad compatibility across diverse applications.¹⁵⁷ The properties and performance of representative 3D printed gel sensors via DIW are summarized in Table 2.

Inks with shear-thinning or thixotropic properties are ideal for DIW, covering a viscosity range of 10⁻¹ to 10⁴ Pa s.⁵¹ At high shear rates, the viscosity of the ink decreases, allowing it to pass through the nozzle. However, once the ink exits the nozzle, the shear rate approaches zero, and the viscosity changes by 2 to 3 orders of magnitude during this transition (Fig. 7(a)). A sufficient storage modulus is necessary for ensuring the printed object to maintain its shape after extrusion. By applying a force greater than the yield stress, the ink can be extruded from the nozzle, but once the printing is completed, the pressure drops below the yield stress, allowing the ink to retain the printed shape.

Fig. 7 Gels printed by DIW. (a) Stress/viscosity–shear rates curve of the hydrogel. (b) Schematic illustration of the grid microstructure by 3D printing. (c). Schematic illustration of an ionic skin.¹⁵⁸ Copyright© (2017) Materials Horizons. (d) Viscosity–shear rates curve of various XLS contents. (e) Schematic printing of monomers, XLS, SCFs, and PEGDA in hydrogels. The inset shows the printing path and strain sensor.¹⁶⁰ Copyright© (2023) Chemical Engineering Journal. (f) Schematic showing the fabrication of hydrogel electronics via DIW printing.¹¹² Copyright© (2022) Nature Electronics. (g) The viscosity–shear rate of different ceramic content inks. (h) 3D printing of a composite gel. (i) Glycerol–water displaces the solvent, and Fe³⁺ contributes to the conductivity of gels.¹⁶¹ Copyright© (2024) Nature Communications.

The DIW technique requires minimal ink, making it ideal for the customized fabrication of gel-based devices. The gel inks are extruded from the nozzle by air pressure or screw driving, and form a close contact with the substrate, which facilitates their combination with other materials to create functional sensing devices (Fig. 7(b)).¹⁵⁸ For instance, by sandwiching a polyethylene dielectric layer between two grid-structured conductive hydrogel membranes, a skin-like capacitive sensor was constructed (Fig. 7(c)).

Mechanically weak inks may result in structural collapse after printing, or the ink spread after printing may degrade the printing resolution. To address these challenges, post-processing steps, such as photonic or thermal curing, can be applied immediately after extrusion.¹⁵⁹ Additionally, incorporating additives, such as nanoclays or nanofibers, into the ink formulation can enhance its storage moduli, improving structural stability and print fidelity (Fig. 7(d) and (g)). Fu et al. introduced a strategy for fabricating anisotropic gels via 3D-printing of composites comprising NIPAM and short carbon fibers (SCFs).¹⁶⁰ During the ink extrusion process, SCFs were effectively aligned within the composite gel, yielding an anisotropic structure that enhanced the sensitivity of wearable sensors. The incorporation of nanoclays was crucial for regulating the thixotropic behavior of the DIW ink, and the viscosity profiles at varying nanoclay concentrations and shear rates demonstrated the superior printability of the composite gel (Fig. 7(d)). As shown, the extrusion process oriented the SCFs through the print nozzle, aligning in the direction of extrusion, and following UV curing, the gel solidified into an anisotropic structure (Fig. 7(e)). The addition of suitable solid fillers not only improves the rheological properties but also substantially enhances the mechanical performance of the gel. Zhai et al. proposed a hierarchical strategy for fabricating ceramic-reinforced PVA hydrogels, utilizing DIW printing to align ceramic flakes.¹⁶¹ In the composite ink, the ceramic flakes, combined with Carbomer microgels, formed a rigid gel structure with viscoelastic properties ideal for DIW printing. As the ceramic content increased, the material's viscosity, storage modulus, and yield stress increased (Fig. 7(g)). The pretreated conductive ceramic flakes were mixed with a PVA solution containing a small amount of Carbomer colloids as a rheology modifier to produce a 3D-printable ink (Fig. 7(h)). Additionally, by replacing the matrix of the highly crystalline PVA organic hydrogel with a glycerol–water solution and introducing Fe³⁺ to impart conductivity, the resulting ink exhibited enhanced printability and functionality (Fig. 7(i)).

To create complex 3D geometries, inks can be printed by DIW within a supporting matrix. Zhou et al. developed a method for printing electronically conducting hydrogels embedded with Ag flakes, enabling the formation of complex 3D structures while preserving high conductivity along the printed pathways.¹¹² The supporting matrix, consisting of a hydrogel microsphere suspension, facilitated the precise deposition of the Ag flake composite ink. As the nozzle traversed the matrix, a continuous 3D conductive path was formed, with the ink establishing a percolation network within the interstitial spaces of the hydrogel particles. This approach ensured both structural stability and high electrical conductivity (Fig. 7(f)).

4.2. Digital light processing for gel sensors

Gel inks for DLP typically consist of photocurable monomers dissolved in appropriate solvents, covering a viscosity range of 10⁻³–10⁻² Pa s.⁵¹ Upon UV exposure, these monomers undergo polymerization, forming a cross-linked network that transitions the gel from a liquid to a solid state. By carefully selecting precursor materials, the mechanical properties of gels can be tailored, achieving an optimal Young's modulus, high stretchability, enhanced toughness, and superior strength. DLP utilizes a digital light projector for exposure, enabling planar printing with several distinct advantages, including printing speeds ranging from 25 to 1000 mm min⁻¹, resolution as fine as 1 μm, and high throughput.¹⁶² The core components of a DLP system include the digital micromirror device (DMD) and a movable platform, which work in tandem to enable the precise, scalable fabrication of complex, multi-layered, and arrayed structures. This advanced capability establishes a strong foundation for the industrialization of 3D-printing technologies.¹⁶³ A summary of the performance of representative 3D gel sensors via DLP is provided in Table 3.

DLP printing encompasses two primary methodologies: layer-by-layer printing and continuous liquid interface printing (CLIP). Each of these offers distinct mechanisms for fabricating complex 3D structures. In the layer-by-layer method, the print stage moves incrementally along the z-axis to pattern a 2D layer. During each iteration, unpolymerized precursors are introduced into the build areas. This process is iteratively repeated until the object is fully formed. By modulating the light intensity and spatial distribution, it allows for the fabrication of uniform and high-fidelity objects. CLIP represents the most advanced formation of DLP printing technology. It utilizes an oxygen-permeable, optically transparent window to create a unique “dead zone”, where oxygen inhibits resin polymerization at the window's surface. This method enables continuous printing by allowing resin to flow back into the build areas as the stage moves upward after each layer is completed. The printing model is first sliced into a series of 2D grayscale bitmaps with varying layer thicknesses using computer aided design (CAD) software. These bitmap patterns are then projected onto the window via a UV light engine at the required intensity, selectively curing the liquid resin above the “dead zone.” As the print stage moves upward, high-precision 3D structures are gradually formed.⁵³

Leveraging the unique capabilities of DLP technology, various materials and delicate structures can be integrated during the printing process to fabricate hybrid sensitive sensor devices, which often exhibit superior functional and mechanical properties compared to single-material devices. Huang et al. reported a method for fabricating hybrid gel sensors using DLP printing, where waterborne polyurethane acrylate (WPUA) was utilized to encapsulate the gel sensor, ensuring its stability during operation.¹⁵⁵ Post-treatment with FeCl₃ enhanced the printed hydrogel's mechanical properties, endowing it with a tensile strength of 22.9 MPa and an elasticity of up to 583%. The multi-material DLP printing process involved firstly WPUA (blue) as the top encapsulation layer, and then a hydrogel layer (orange) with the desired pattern and structure, and finally WPUA again as the bottom encapsulation layer (Fig. 8(a)). The WPUA shared similar elasticity to the hydrogel, with a maximum elongation at break of 580%. Conductive hydrogels, when integrated with microstructures, significantly enhance sensor sensitivity. A pressure sensor along with micron-sized pyramids demonstrated microstructural changes upon pressure application (Fig. 8(b)). To demonstrate the capacitive performance of the pressure sensors, a comparison of sensitivity between flat non-structured sensors and micro-structured sensors revealed a 34-fold increase in sensitivity for the latter ones (Fig. 8(c)).

Fig. 8 Gels printed by DLP. (a) Schematic illustration of the dual-material printing process via DLP printing. (b) Schematic diagram of a pressure sensor with pyramid-shaped microstructures. (c) Comparison of sensitivity–pressure curves between flat sensors and microstructured sensors.¹⁵⁵ Copyright© (2021) ACS Applied Materials & Interfaces. (d) Schematic for DLP-based 3D printing of tough supramolecular hydrogels by in situ formation of carboxyl–Zr⁴⁺ coordination complexes. (e) Photos of printed hydrogel architectures of hollow-pyramid and solid-pyramid. (f) Real-time variations of the pressure sensor performance, dropping water from different height.¹⁶⁴ Copyright© (2022) Advanced Materials. (g) 3D-printed hydrogel dielectric layer and capacitive pressure sensor. The inset is a design of surface structure for the hydrogel dielectric layer.¹⁶⁶ Copyright© (2023) Additive Manufacturing. (h) DLP-based 3D printing of various sensors for multi-mode sensing using DE and PEE precursor with robust interfaces.¹⁵⁶ Copyright© (2023) Nature Communications.

High compressive Young's modulus of 3D-printing microstructured gel pressure sensors limits their ability to effectively distinguish small pressure values, and printing hollow microstructures enhances sensitivity to lower pressures. Wu et al. reported a tough hydrogel system using DLP printing, which enables the creation of intricate 3D architectures with adjustable mechanical properties.¹⁶⁴ The precursor solution, containing concentrated AAc and Zr⁴⁺, formed a tough gel upon rapid curing under digital light, with in situ carboxyl–Zr⁴⁺ coordination complexes providing strong physical crosslinks for the polyacrylic acid (PAA) chains (Fig. 8(d)). A microstructured hydrogel layer, featuring hollow pyramid-like bulges, was fabricated using DLP printing technology. Compared to solid pyramids, the hollow pyramids exhibited superior compressibility (Fig. 8(e)), and the hydrogel layer was assembled into a pressure sensor with high sensitivity. The testing process is shown in the inset, involving a water droplet (∼50 mg) dropped from heights of 5, 10, and 15 cm, highlighting the sensor's excellent performance in detecting low pressures (Fig. 8(f)).

To achieve higher sensitivity while maintaining a broader linear range, PDMS dielectric layers with a gradient micro-dome architecture have been applied in capacitive sensors.¹⁶⁵ This concept is applied to hydrogels, with DLP printing technology to fabricate hydrogels with gradient surface microstructures, offering a reliable method for developing highly sensitive capacitive sensors. Liu et al. reported the preparation of UV-curable hydrogels based upon polymer micelles,¹⁶⁶ showing that DLP technology could precisely print protruding structures on the hydrogel surface, with a total of 121 protrusions. A capacitive sensor was fabricated by integrating two flat electrodes with the irregularly surfaced hydrogel (Fig. 8(g)).

The integration of conductive and dielectric materials, which are often physically and chemically distinct, typically requires manual assembly, leading to weak interfaces that can result in signal drift and component degradation. DLP technology facilitates the assembly of multiple materials, creating robust interfaces for stable and durable sensors. A multi-mode sensor with such a stable interface was achieved using DLP to combine two precursor solutions.¹⁵⁶ By alternating between these precursor solutions and controlling platform movement, various materials were assembled to create the sensor. Furthermore, sensors mimicking the sensory functions of human skin were designed and printed to detect a range of modalities, including tension, compression, shear, torsion, and their combinations (Fig. 8(h)).

5. Application

Polymeric gel-based flexible electronic devices are instrumental in advancing human–machine interaction, enabling point-of-care diagnostics, and enhancing cyborg feedback. Their exceptional mechanical and electrical properties make polymeric gels highly suitable for the development of customizable electronic devices. Conductive gel-based flexible electronics, known for their excellent biocompatibility and responsiveness to external stimuli, have already been successfully integrated into implantable devices,¹⁶⁷ significantly contributing to the progress of bioelectronics.¹⁶⁸ Notably, 3D-printed gel devices present even greater potential by further enhancing overall device performance and expanding functional capabilities. This section provides an overview of 3D-printed gels in flexible electronics, highlighting their applications in pressure sensors, stretchable strain sensors, chemical sensors, temperature sensors, multifunctional sensors and integrated sensor systems.

5.1. Pressure sensor

Pressure sensors respond to external forces through changes in capacitance or resistance signals. Gel-based capacitive pressure sensors commonly employ a gel featuring microstructured surfaces as the dielectric layer, complemented by an electrode layer of planar configuration, achieving a sensitivity range of 0.1 to 16 kPa⁻¹ in Tables 2 and 3.^{52,83,156,158,159,164,166,169–173} The gel layers can be printed by DIW or DLP. The gel-based resistive sensors usually use conductive gels with customized microstructures, demonstrating a sensitivity range of 0.1 to 1.2 kPa⁻¹ in Tables 2 and 3.^{95,155,166,171} Beyond advantages in assembly processes, 3D-printed gel sensors demonstrate superior microstructural programmability for diverse pressure-testing scenarios, achieving 2-fold to 170-fold enhancement in pressure sensitivity compared to conventional architectures through precision-controlled fabrication (Table 4).

Table 4 Performance comparison between 3D printed and non-3D printed gel sensors

Technology	Microstructure	Mechanism	Application & sensitivity		Ref.
3D printed	Pyramid	Capacitive	Pressure	0.103 kPa^−1 (0–1.25 kPa)	a^155
				0.008 kPa^−1 (1.25–10 kPa)
Non-3D printed	Flat			0.055 kPa^−1 (0–0.2 kPa)
				0.003 kPa^−1 (0.2–10 kPa)
3D printed	Hollow pyramid	Capacitive	Pressure	2.6 kPa^−1	b^164
	Solid pyramid			0.5 kPa^−1
Non-3D printed	Flat			0.1 kPa^−1
3D printed	Vertex	Resistive	Pressure	1.13 kPa^−1	c^166
Non-3D printed	Bulk			0.11 kPa^−1
3D printed	Microstructure	Capacitive	Pressure	3.41 kPa^−1	d^156
Non-3D printed	Flat			0.02 kPa^−1
3D printed	Trigonal beam	Capacitive	Pressure	0.102 kPa^−1 (0–3 kPa)	e^170
				0.039 kPa^−1 (3–10 kPa)
Non-3D printed	Flat			0.02 kPa^−1 (0–4 kPa)
				0.004 kPa^−1 (4–10 kPa)
3D printed	Cylinder	Capacitive	Pressure	2 kPa^−1	f^159
	Cylinder	Resistive		0.67 kPa^−1
Non-3D printed	Flat	Capacitive		0.023 kPa^−1
3D printed	Octahedron	Resistive	Pressure	0.08 kPa^−1	g^171
	Gyroid			0.04 kPa^−1
Non-3D printed	Bulk			0.01 kPa^−1

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To enhance the sensitivity of pressure sensors, DIW or DLP-based 3D printing can easily incorporate microstructures in the active layer. For example, Qu et al. developed a capacitive pressure sensor by utilizing DLP to alternate the deposition of two photocurable precursors, creating functionalized precision mixed structures, for gel electrodes.¹⁷⁰ The top electrode consisting of PAAm/PEDOT:PSS hydrogel featured a trigonal beam-shaped structure, which produced a great change in capacitance under applied pressure. The bottom electrode comprising the same hydrogel was a flat thin layer. A DLP-printed poly(2-hydroxyethyl acrylate) (PHEA) layer served as the dielectric layer (Fig. 9(a)). The microstructure created an increased gap between the top electrode and the dielectric layer, providing greater deformation space and a larger output capacitance. The trigonal beam-shaped structure exhibited a significantly greater change in pressure-sensing capacitance compared to the unstructured thin film (Fig. 9(b)). The microstructural pressure sensor showed a sensitivity of 0.102 kPa⁻¹ in the 0–3 kPa range and 0.039 kPa⁻¹ in the 3–10 kPa range. At maximum pressures of 0.5, 1, and 3 kPa, the relative capacitances recorded were 58.24, 65.58, and 72.93 pF, respectively (Fig. 9(c)). Additionally, the sensor showed fast response and recovery times of approximately 200 ms, demonstrating its suitability for pressure monitoring applications (Fig. 9(d)). Yu et al. reported a photochemistry-assisted DIW printing strategy that utilized carefully engineered photosensitive inks to construct tough hydrogels within ∼30 seconds.¹⁵⁹ A 3D array of tough conductive hydrogels (TCHs), consisting of 7 × 7 conical units inspired by the structure of sea cucumbers, was printed and assembled into a flexible capacitive sensor capable of responding to external pressure (Fig. 9(e)). The 3D-printed TCH capacitive sensor demonstrated higher sensitivity to external forces compared to both 3D-printed resistive and planar capacitive sensors (Fig. 9(e) and (f)), achieving a sensitivity of 330 N⁻¹ for the capacitive sensor versus 110 N⁻¹ for the resistive sensor. It was highlighted that the conical TCH with the shortest height had superior compressive strain sensitivity compared to other 3D-printed shapes, such as cylindrical, truncated, and taller conical samples (Fig. 9(g)). Under an external force of 0.5 N, the conical TCHs produced greater strain, leading to a more significant change in resistance sensitivity (Fig. 9(g) and (h)). These results indicated that 3D-printing technology has significant potential for applications in high-performance flexible sensors and electronics.

Fig. 9 3D printed pressure sensors. (a) Schematic diagram of a microstructured capacitance sensor. (b) Capacitance response of the two structured sensors under various pressures. (c) Stable performance of the sensor under different cyclic pressures. (d) Loading and unloading time of the sensor under pressure (2 kPa).¹⁷⁰ Copyright© (2021) ACS Applied Materials & Interfaces. (e) 3D capacitor, flat capacitor and 3D resistor. (f) The sensitivity of flat, 3D capacitors, and 3D resistor with growing forces. (g) Resistance response of TCHs under growing strains with different geometry shapes. Scale bar: 1 cm. (h) Finite element simulation of force distribution and strains for the corresponding TCHs in (g).¹⁵⁹ Copyright© (2021) Nature Communications. (i) Optical images of the printed SCIE-based building blocks (cubic, octahedral, and gyroid lattice). (j) Schematic illustration of the printed SCIE-based gyroid lattice for the fabrication of a piezoresistive sensor (up) and the printed gap-based tactile sensor consisting of two printed SCIE-based microcircuits and air gap (down). (k) Piezoresistive performance of sensors as a function of pressures. (l) Capacitance performance of printed SCIE-based tactile sensors with growing gap thicknesses as the function of pressures.¹⁷¹ Copyright© (2022) Advanced Materials.

Other than solid microstructures, lattice designs offer significant advantages for developing sensitive pressure sensors. Wang et al. reported high-performance pressure sensors using a fast photocurable solid-state conductive ionoelastomer (SCIE) via DLP printing.¹⁷¹ Gyroid-based piezoresistive sensors and gap-based capacitive sensors (Fig. 9(j)), developed using SCIE, achieved sensitivities 3.7 and 44 times higher than their bulk counterparts, respectively. The gyroid and octahedral lattices provided superior energy dissipation compared to cubic lattices and the gyroid lattice had a more uniform stress distribution than the octahedral lattice, effectively preventing stress concentration (Fig. 9(i)). In addition to excellent compressive elasticity, the gyroid lattice also displayed strong fatigue resistance, validated through multiple compression-release experiments. Under increased external pressure from 0 to 100 kPa, sensors with gyroid and octahedral lattices achieved resistance changes of approximately 90.9% and 68.7%, that is, 2.7 and 2.0 times greater than those on cubic lattices (Fig. 9(k)). This highlighted the critical role of lattice structures in enhancing sensing performance. The integration of two SCIE-based printed microcircuits and an adjustable air gap resulted in a highly sensitive tactile sensor, in which the gap-based design improved sensitivity and reduced response time by enabling greater structural deformation (Fig. 9(l)). At pressures below 1 kPa, the gap-based tactile sensor reached a sensitivity of up to 9.15 kPa⁻¹, which is 44 times higher than that of non-gap sensor (0.21 kPa⁻¹). Compared to traditional hydrogel/elastomer-based tactile sensors, the gap-based tactile sensor exhibited significantly higher sensitivity and a lower pressure detection limit.

In the design of highly sensitive capacitive pressure sensors, utilizing 3D printing technology to fabricate surface-microstructured dielectric materials also represents a highly promising strategy. Ge et al. developed a novel method for fabricating surface-microstructured organogels using DLP technology.¹⁷³ The printing ink was formulated with BA, poly(ethylene glycol) methyl ether methacrylate (PEGMA), 1-ethyl-3-methylimidazolium dicyanamide ([EMIM][DCA]), and PEGDA. Utilizing 3D printing, they successfully created microstructures with gradient heights, where the gel layer was sandwiched between top and bottom metal-based electrodes, forming a capacitive sensor with a sandwich-like structure for pressure detection. Due to the tailored microstructures of the organogel, the sensor exhibited a remarkable pressure sensing response, demonstrating a sensitivity of 15.1 kPa⁻¹ within the 0 to 12 kPa range. Furthermore, the sensor proved effective in monitoring human physiological activities such as deep breathing and swallowing.

5.2. Strain sensor

A strain sensor measures the deformation of a material when it is subjected to external forces. Strain sensors based on 3D printed gels offer advantages, such as high stretchability, biocompatibility, and self-healing capabilities, high resolution and precision, and rapid and scalable fabrication, making them suitable for wearable health monitoring and soft robotics. Similar to gel-based pressure sensors, resistive and capacitive electrical signals are used to monitor the dimensional changes in strain sensors. Strain sensors respond to deformation through changes in capacitance or resistance signals. Gel-based capacitive strain sensors typically utilize a flexible substrate as the dielectric layer and conductive gel as the electrode layer, with a GF ranging from 0.51 to 1 in Tables 2 and 3. Moreover, the electrode layers fabricated through 3D printing technology possess intricate microstructures.^{83,156,169,170,172} Gel-based resistive sensors are commonly composed of conductive gels with fine structures produced by 3D printing, and they exhibit a GF range that spans from 1.0 to 21, as shown in Tables 2 and 3.^{52,95,131,132,149,150,155,160,161,166,170,174–176}

Resistive strain sensors are operated by altering their resistance in response to external stimuli that modify the conductive pathways within the material. Electrically or ionically conductive gels can function as active layers in strain sensors.¹⁷⁷ Gu et al. reported a highly stretchable strain sensor based on DIW-printed electrically conductive polymer hydrogels.¹⁷⁴ The DIW inks contained PVA and PEDOT nanofibers, and could be printed with a resolution of 500 μm. Subsequent freeze–thaw cycling after printing enabled a unique microphase-separated conductive polymer hydrogel network. The sensor demonstrated object recognition when integrated into a soft gripper, showcasing its great potential in motion detection and intelligent recognition in soft robotics (Fig. 10(a)). The introduction of PVA significantly improved the hydrogel's stretchability compared to pure PEDOT hydrogel, which exhibited brittleness and a maximum strain deformation of 40%.¹⁷⁸ Excitingly, the PEDOT hydrogel exhibited a resistance response with less than 1.5% hysteresis during loading-unloading cycles within a stretch deformation range of up to 300%. The GF of the strain sensor was calculated to be 4.07, along with a good linear correlation (R² = 0.98) between resistance change and strain, further confirming its capability for precise detection scenarios (Fig. 10(b)). The sensor also exhibited good stability without noticeable performance degradation when subjected to strain levels ranging from 60% to 300% (Fig. 10(c)). At a maximum strain of 100%, uniaxial tensile testing over 2000 loading–unloading cycles highlighted minimal decline in sensing performance or increase in hysteresis, underscoring its durability and robustness. Other than conductive polymers, conductive nanomaterials, such as transition metal carbides (MXenes), have also been added to enhance the electrical conductivity of 3D printed gels for strain sensors.^176,179 Guan et al. reported DLP-printed PVA/MXene/DESs (PMD) hydrogels with mechanical properties (2770% strain), high conductivity (1.21 S m⁻¹), mechanical stability (over 2000 cycles of stretching), and electrical responsiveness (a response time of 160 ms) for strain sensors.¹⁷⁶ The strain sensors are produced through DLP technology, utilizing inks composed of PVA, DESs, AAc, AAm, and MXene (Fig. 10(d)). The bidirectional strain sensor, consisting of two perpendicularly arranged unidirectional sensors with three terminals, simultaneously measured resistance changes in the X and Y directions (Fig. 10(e) and (f)). Finite element analysis further validated the strain transmission mechanism with a strain distribution transition from blue to red, indicating an increasing of strain that primarily concentrated in the Y sensor during Y-axis stretching, aligning well with experimental results (Fig. 10(f) and (g)). As a result, the 3D-printed bidirectional strain sensor enabled effective and precise detection for both magnitude and direction of strain based on the signal strength.

Fig. 10 3D printed strain sensors. (a) Schematic illustration of a flexible manipulator integrated with a PEDOT:PSS–PVA hydrogel strain sensor. (b) Loading and unloading resistance responses of the PEDOT:PSS–PVA hydrogel strain sensor with 0–300% strain. (c) Resistance response of the strain sensor under a series of step-up strains of 60% to a maximum of 300% and next a series of step-down strains to the initial state.¹⁷⁴ Copyright© (2022) Advanced Materials. (d) The process of 3D printing the strain sensor of a PMD hydrogel. (e) The stretching process of a bidirectional sensor in the Y direction. (f) Resistance response of a bidirectional sensor in the orthogonal direction. (g) Finite element analysis results of flexible bidirectional sensors.¹⁷⁶ Copyright© (2023) Advanced Materials Technologies. (h) Schematic illustrations of a capacitance sensor. (i) Linear relationship of capacitance response against strain ranging from 0 to 100%. (j) Cycling stability at a strain of 25% within 2000 cycles.¹⁷² Copyright© (2019) Materials Horizons.

Capacitive strain sensors detect strain-induced variation in capacitance. In such sensors, 3D-printed gels can serve as electrodes or dielectrics in a parallel-plate capacitor configuration, enabling enhanced flexibility and customizability. Hydrogels, due to their low elastic modulus, excellent flexibility, satisfactory printing resolution, good conductivity, and minimal resistance change under severe deformation, are ideal materials for such applications. Wang et al. reported a facile approach for the fabrication of elastic, ionically conductive hydrogels with microstructures using a commercial DLP printer.¹⁷² The DLP inks contained AAc, NVP, carboxymethyl cellulose (CMC) and ZnCl₂. The stretchable sensor adopted a sandwich structure akin to a parallel plate capacitor, with VHB 4905 tape serving as both the dielectric layer and adhesive for bonding hydrogel electrodes. Additional VHB tape layers were applied to the top and bottom of the device to isolate the sensor and prevent hydrogel evaporation (Fig. 10(h)). When stretched horizontally, the thickness of the dielectric layer decreased while the contact area between the electrode and the dielectric increased, leading to enhanced capacitance. The strain sensor was measured by monitoring changes in the capacitance during uniaxial stretching, demonstrating excellent linearity across a strain range from 0% to 100% (Fig. 10(i)). In 10-cycle stretch-and-release testing, it demonstrated consistent behavior without significant hysteresis at strains up to 50%, while after 1000 cycles of 25% strain, the detected signal drift was less than 5% (Fig. 10(l)), underscoring the sensor's high stability and suitability for long-term applications. Ge et al. reported a method for fabricating capacitive sensors using DLP by alternately printing polyelectrolyte elastomer (PEE) and dielectric elastomer (DE) in an integrated manner.¹⁵⁶ This approach utilized a one-step printing process to construct a sandwich-structured parallel-plate capacitor, which was employed for tensile testing. Experimental results demonstrated that the sensor achieved a gauge factor (GF) of 0.51 within the 0–50% tensile range, showcasing excellent tensile sensing performance.

5.3. Chemical sensor

3D-printed gel sensors exhibit significantly larger specific surface areas than conventional structures, enabling effective monitoring of biological activities via transduction of chemical concentration changes into electrical or optical signals. In living systems, cells continuously exchange materials and energy with their surroundings, leading to dynamic environmental changes. Chemical signal sensors play a crucial role in investigating these processes, making them valuable tools in biomedicine, healthcare, and related fields.

Among chemical sensors, pH sensors find extensive applications, as pH is a fundamental environmental indicator and a critical factor that significantly influences biological activities. Additionally, the correlation between CO₂ production during respiration and pH makes pH monitoring a key parameter for assessing biological processes. At the molecular levels, pH reflects the proton concentration in a solution, which can influence the conductivity of materials, such as PEDOT:PSS. The pH sensitivity of PEDOT:PSS stems from the ionic interactions between PEDOT and PSS polymer chains. Dehghani et al. reported the development of a highly sensitive pH sensor fabricated using DIW printing. The inks of the active layer incorporated hydrophilic polyurethane (HPU) and PEDOT:PSS.¹⁸⁰ A PEDOT/HPU hydrogel, containing 1.25 wt% PEDOT in the solid component, was printed as a 220 μm-thick sensor layer. In aqueous environments, negatively charged PSS polymer chains acted as counterions to balance the positively charged PEDOT segments (Fig. 11(a)). Under mildly acidic conditions, the PEDOT chains were uniformly distributed along the PSS polymer chains, ensuring continuous electrical connectivity. However, as pH shifted from acidic to basic, negatively charged hydroxyl ions disrupted the optimal distribution within the system. The neutralization of shorter PEDOT chains by OH⁻ ions led to the formation of a hydrophobic phase that was encapsulated by longer PSS chains. Upon exposure to a solution at pH 3, the conductive hydrogel's resistivity exhibited a sharp decrease and stabilized within several minutes (Fig. 11(b)). Meanwhile, it exhibited a clear linear relationship with pH across the range from 3 to 13 (Fig. 11(c)). Resistance changes were nearly linear during both pH increases and decreases, although a slight hysteresis was observed due to ion interactions in the solution (Fig. 11(d)).

Fig. 11 3D printed chemical sensors. (a) Schematic diagram depicting the impact of solution properties on PEDOT:PSS chain conformation. (b) Resistance response of PEDOT:PSS/HPU hydrogels to the pH change. (c) Resistance response as the function of pH for PEDOT:PSS/HPU hydrogels. (d) Resistance response of pH sensors.¹⁸⁰ Copyright© (2018) Advanced Materials Technologies. (e) Schematic of the PVDF-bigel film fabrication process. (f) Photos of PVDF-bigel films exposed to TMA with concentrations of 0–240 μM. (g) Calibration curve between the a* values of the PVDF-bigel film and TMA concentrations. The a* values of PVDF-bigel film when exposed to TMA. (h) Changes of TVBN and TVC values of beef, and the a* value of bigel film with time.¹⁸¹ Copyright© (2022) Food Hydrocolloids. (i) Approach for 3D printing with bioink functionalized with sensor nanoparticles. (j) Time course of O₂ concentrations after a light–dark shift in different regions of interest as shown in the photo. (k) Changes in oxygen concentration over several hours at different locations of the 3D printed structure.¹⁸² Copyright© (2018) Advanced Functional Materials.

Protein-rich foods are highly susceptible to spoilage when stored improperly, posing significant risks to food safety and human health. The spoilage process generates volatile amines, and monitoring the levels of total volatile basic nitrogen (TVBN) and trimethylamine (TMA) provides an effective way to assess food freshness. Anthocyanins, plant pigments known for their color-changing properties, undergo noticeable color changes upon exposure to volatile amines, making them useful for detecting spoilage. Povey et al. reported the fabrication of gel sensors using a hydrogel-in-oleogel bigel containing anthocyanins, which were printed onto a porous PVDF film using DIW technology,¹⁸¹ allowing for the detection of organic amines corresponding to their color changes (Fig. 11(e)). As TMA concentration increased, the color of the bigel film underwent distinct changes that could be evaluated and quantified by a* value (Fig. 11(f)). This value decreased with increasing TMA concentration and reached a maximum of 240 μM, and a linear relationship between the a* value and TMA concentration was observed in the range of 20–160 μM (Fig. 11(g)). When the film was separated from TMA and exposed to air to investigate its recovery behavior, the anthocyanins degraded, indicating a limited recovery potential. To assess food freshness, the TVBN and total viable count (TVC) values were used to evaluate beef (Fig. 11(h)), with the shelf life of beef stored at 4 °C determined to be 5 days.

Cellular activities are closely related to the oxygen levels in the surrounding environment, making the development of culture units via DIW-3D printing and monitoring cellular dynamics within these structures a crucial approach. Kühl et al. reported a method to create inks by incorporating optical sensing nanoparticles and dyes with biological cells,¹⁸² enabling the printing of microstructures for real-time imaging of oxygen dynamics during cellular respiration and photosynthesis, as well as providing insights into the metabolic activities of various cell types within 3D architectures. For the preparation of oxygen sensors, biological cells were combined with functionalized nanoparticles and dispersed in a mixture of alginate and methylcellulose to form a printable ink (Fig. 11(i)). Upon blue light excitation, the nanoparticles emitted red light from an O₂-sensitive luminescent indicator, while the fluorescent dyes emitted green light, facilitating the visualization of oxygen distribution with a standard digital SLR camera system. By varying the hydrogel compositions, the combination of functionalized inks and luminescent imaging revealed heterogeneous material distribution within 3D-printed architectures. Horizontal lines contained both cells and nanosensors, while vertical lines consisted exclusively of nanosensors. Under high photon irradiation (400–700 nm) with saturated photosynthesis without organic carbon sources, O₂ levels within 3D-printed architectures initially exhibited supersaturation, followed by a gradual depletion during the dark incubation period (Fig. 11(j)). After 30 minutes of light illumination and 2 hours of dark incubation, O₂ distribution reached a steady state, indicating its lowest concentration in the hydrogel chains containing respiring microalgae. During light-to-dark transition experiments, the hydrogel scaffolds coated with both microalgae and nanoparticles displayed the strongest dynamic change in O₂ concentration, while those with only sensing nanoparticles showed less fluctuations. This discrepancy was primarily attributed to slower diffusion and exchange processes between the scaffold, the embedded components, and the surrounding medium (Fig. 11(k)).

5.4. Temperature sensor

Wearable sensors have made significant advancements in healthcare and artificial intelligence, enabling continuous monitoring of various signals of physiological states and environmental factors. To evaluate the thermal signal response of temperature sensors, the temperature coefficient of resistance (TCR) is defined as TCR = (ΔR/R₀)/ΔT.

Temperature sensing can be based on the electrical resistance change of gels in response to external temperature variations. Conductive nanofillers are often incorporated into the gel inks to enhance the electrical conductivity of gels. For example, Maimaitiyiming et al. reported a printable gel based on PVA and CS, incorporating reduced graphene oxide (rGO) to enhance its temperature sensitivity. This modification endowed the ink with temperature-sensitive properties, making it suitable for the fabrication of temperature sensors using DIW printing.¹⁷⁵ The composite hydrogel ink was applied in a layer-by-layer fashion, allowing the creation of structures in various shapes and configurations (Fig. 12(a)). The sensor design featured two copper strips acting as electrodes on a PVA film, with a single-layer square region measuring 15 mm × 15 mm of single-layer hydrogel connecting the copper strips. When employed for temperature detection, it exhibited a TCR of −1.1205% °C⁻¹ and indicated high sensitivity (Fig. 12(b)). The sensor exhibited excellent linearity within the 10 to 70 °C range, and it maintained good stability in 10 heating–cooling cycles (18 °C and 59 °C), underscoring its potential for use in practical temperature sensing applications (Fig. 12(c)). Other than reduced graphene oxide (rGO), MXenes, known for their excellent conductivity and high specific surface area, have become widely utilized in such applications. Huang et al. reported an integration of MXene into PU/PVA gels, forming a robust hydrogen-bond network that imparted excellent stretchability and a high sensitivity of GF = 5.7 over a strain range of 0–191%. They further developed a gel-based temperature sensor using DIW, incorporating glycerol in the gel to achieve a temperature sensitivity of −5.27% °C⁻¹ within a wide working range of 0–80 °C.¹⁷⁹ Copper electrodes were affixed to the hydrogel to ensure efficient charge transfer during temperature fluctuations (Fig. 12(d)). The sensor's conductivity was analyzed across various temperatures. The R/R₀ response over the 0 to 80 °C range showed that the printed hydrogel exhibited stable temperature sensing, with a TCR of −5.27% °C⁻¹ in the 0–30 °C range and −1.11% °C⁻¹ in the 30–80 °C range, outperforming most of the polymer composite-based temperature sensors (Fig. 12(e)). The normalized resistance change rate (R/R₀) as a function of temperature, starting at 24 °C (Fig. 11(f)), exhibited a sharp increase during rapid cooling from 24 °C to the target temperatures (0, 3, 10, and 15 °C) and stabilized within 90 seconds (Fig. 11(f)), while it showed an opposite trend if the target temperature exceeded 24 °C (Fig. 12(g)).

Fig. 12 3D printed temperature sensors. (a) Schematic illustration of a flexible temperature sensor. (b) Resistance response as the function of temperatures. (c) Relationship between the rate of change of resistance at different temperatures.¹⁷⁵ Copyright© (2018) ChemistrySelect. (d) Schematic illustration of a temperature sensor. (e) Resultant TCR for the sensor. (f) and (g) Resistance variation under different temperature (starting temperature: 24 °C).¹⁷⁹ Copyright© (2022) Nature Communications. (h) Schematic diagram of the ionogel-based temperature sensor. (i) TCR for the temperature sensor (H₃S₂-40 organogel). (j) and (k) Resistive performance variation at different temperatures (starting temperature: 40 °C and 25 °C).¹⁸⁴ Copyright© (2024) Chemical Engineering Journal.

Ionic resistance can also be exploited for measuring temperature. In ionic sensors, elevated temperatures enhance ion mobility, facilitate ion dissociation, and increase the number of free ions, thereby amplifying the gel's ionic conductivity.¹⁸³ Gui et al. proposed a method for synthesizing P(HFA-co-SBMA)/[LI-BMIM] ionic gels by integrating complex ionic liquid mixtures and employing molecular structure design principles.¹⁸⁴ Through meticulous optimization of the gel composition, the ionic gel exhibited remarkable performance, including a tensile strength of 7.79 MPa, a fracture elongation of 107.21%, and a TCR of −9.810 °C⁻¹ in the 0–20 °C range. Temperature sensor fabrication via DIW printing to pattern silver paste through a stainless-steel nozzle, formed silver electrodes on a 25-μm polyimide (PI) film. After introducing the ionic gel precursor solution and completing the curing process, a layer of adhesive PI tape was applied over the ionic gel layer to complete the sensor assembly (Fig. 12(h)). The ionic gel included polymer monomers, namely [2-(methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl)ammonium hydroxide (SBMA) and 2,2,3,4,4,4-hexafluorobutyl acrylate (HFA), while the filling liquid was a hybrid ionic liquid ([LI-BMIM]) formed by combining lithium salt (LI[TFSI]) with the ionic liquid [BMIM][TFSI] in a 1 : 4 mass ratio. The optimized formulation, H₃S₂-40, comprised a 3 : 2 molar ratio of HFA to SBMA and a 40% mass fraction of [LI-BMIM]. The resulting ionic gel exhibited excellent temperature sensitivity across the range of 0–80 °C, with TCR values of −9.810 °C⁻¹, −4.154 °C⁻¹, and −0.859 °C⁻¹ for the ranges of 0–20 °C, 20–40 °C, and 40–80 °C, respectively, all showing excellent linearity (Fig. 12(i)). Above 40 °C, the resistance changes remained consistent and stable during 10 heating–cooling cycles at 60, 70, and 80 °C (Fig. 12(j)), while the sensitivity remained stable and reliable when the temperature decreased from 25 °C to 15, 10, and 7 °C (Fig. 12(k)).

5.5. Multifunctional sensor

While flexible sensors with single functions have been extensively studied and have seen substantial advancements, their practical applications are often constrained by inherent limitations. To overcome these challenges, the development of flexible multifunctional or multimodal sensors, which are capable of simultaneously detecting multiple signals, has become increasingly important. 3D-printed gel-based multimodal sensors offer unique advantages, including seamless integration of diverse sensing elements, enhanced sensitivity, and adaptability to complex environments. By leveraging the versatility of 3D printing, these sensors can be tailored to detect multiple stimuli, thereby significantly expand capabilities and applications of sensor technology across various fields.

Wu et al. reported a gel ink composed of ionic liquid, polyzwitterion, and PAA with a conductivity of 1 × 10⁻² S m⁻¹. The ink was DIW-printed onto VHB tape to form a sandwich-structured multifunctional sensor (Fig. 13(a)), which can simultaneously detect strain, humidity, and temperature changes.⁸³ After drying, four metal electrodes were connected to the sensor, enabling it to exhibit reversible voltage changes between electrodes 1 and 3 in response to humidity variations via self-powered voltage. Due to the hydrophilic nature of polyzwitterion, humidity-induced changes in ionic concentration gradients generated a voltage difference between the electrodes, yielding output voltages that correlated with varying humidity levels. The data showed good linearity with a sensitivity up to 0.72, making it suitable for measuring a wide range of humidity levels (Fig. 13(b)). The capacitance between electrodes 1 and 2 was measured to detect mechanical movement, stretching, and compression, demonstrating a reversible, linear relationship during stretching and recovery with consistent sensitivity across the 0–100% strain range. The sensor also maintained stable capacitive sensing performance following compression (Fig. 13(c)). Additionally, a stretchable resistive sensor formed between electrodes 2 and 4 monitored the relationship between temperature and resistance. The sensor's performance was shown to be unaffected by temperature changes during tensile deformation from the “capacitance/strain/temperature” space, while strain values derived from capacitance changes and temperature variations were further determined through the “resistance/strain/temperature” relationship (Fig. 13(d)).

Fig. 13 3D printed multifunctional sensors. (a) Illustration of a 3D-printed structure and the circuit for multifunctional sensors. (b) Voltage changes as a function of environmental RH changes. (c) Demonstration of strain and pressure sensing. (d) Capacitive/resistive response of the 3D printed sensor to different temperatures and strains.⁸³ Copyright© (2019) Nature Communications. (e) Schematic diagram of a controller system containing five ionotronic sensors for a drone. (f) ΔC/C₀ varies with testing cycles. The red dashed line indicates the threshold, above which the corresponding sensor is switched on. (g) Schematics of the operation modes of the shear and pressure sensors. (h) Operating mechanism of the shear sensor.¹⁵⁶ Copyright© (2023) Nature Communications.

The development of multifunctional sensors often encounters signal interference due to the integration of different sensor types. The inherent properties of the materials used can make it difficult to balance mechanical and electrical performance, preventing the sensors from achieving optimal functionality. Ge et al. addressed this challenge by designing a multimodal sensor capable of integrating stretching, compression, shear, and twisting through DLP technology.¹⁵⁶ Using a preset printing program, they constructed the sensors from photopolymerizable precursors of polyelectrolyte elastomer (PEE) and dielectric elastomer (DE), which were printed via DLP printing. The capacitive sensor consisted of a layer of DE sandwiched between two layers of PEE, forming a covalently cross-linked interface that enhanced the sensor's stretchability. By combining one compression sensor with four shear sensors, they developed a wearable control device (Fig. 13(e)). During loading–unloading cycles, the device showed a capacitance change factor of 10⁵ for the shear sensors (C₁, C₂, C₃, and C₄), while the pressure sensor exhibited a change factor of 1.2, and it could effectively function as a switch, by establishing appropriate thresholds (Fig. 13(f)). In the remote control unit, the shear sensor initially exhibited low capacitance due to air capacitance; however, upon shearing, the PEE layers made contact, eliminating the air capacitor and resulting in a dramatic change in capacitance by several orders of magnitude (Fig. 13(g) and (h)).

5.6. Integrated sensor system

A single-type sensor is often insufficient to meet the diverse data requirements for accurate diagnosis in wearable point-of-care devices. Therefore, integrating multiple sensors onto a single soft polymer substrate is essential to create a capable and fully functional system. 3D-printed gels, with intrinsic softness and flexibility, can serve as active layers in various sensors to detect stimuli such as strain, pressure, temperature, humidity, and environmental gases. This integration not only enhances the versatility of wearable devices but also broadens their scope, enabling real-time monitoring of a wide range of physiological and environmental parameters.

Wu et al. reported the development of an integrated sensor system using 3D printable ionic polymer gels, which exhibited high transparency (∼90%), exceptional stretchability (>10 000% strain), and a Young's modulus compatible with biological tissues (∼1 MPa).¹⁶⁹ The sensor system could respond to strain, pressure, touch, humidity and temperature, integrating multiple sensors onto a flexible substrate through DIW printing (Fig. 14(a)). The sensor system possessed high transparency, flexibility, and adhesiveness, allowing it to be easily attached to a prosthetic hand model for various sensor-related tests (Fig. 14(b)). Mechanical sensors detected capacitance changes due to mechanical deformation, with capacitance increasing as the plastic prosthetic hand bent, while different capacitance reductions were observed when bare fingers contacted the tactile sensors compared to gloved fingers. The humidity sensor was operated by leveraging the ionic gel's interaction with moisture, which induced ionization and created a concentration gradient, resulting in ion movement and a generated potential difference. Additionally, temperature was detected through a change in resistance, as the sensor monitored a decrease in resistance in response to an increase in temperature, exploiting the relationship between temperature and ionic conductivity (Fig. 14(c)).

Fig. 14 Integrated sensor system using 3D printed gel sensors. (a) Schematic diagram of the sensor system combining different bionic receptors. (b) Photograph of the sensor system attached on a plastic hand (scale bar: 1 cm). (c) Diverse applications of sensor systems.¹⁶⁹ Copyright© (2019) Materials Horizons. (d) Photo of the flexible integrated sensor system fabricated by DLP and DIW 3D printing. (e) Demonstration of the bendable sensor system. (f) Sensing performance of pressure, strain, and temperature. (g) Schematic diagram of the integrated sensor array via DLP-3D printing. (h) Photos of different objects placed on the sensor array and the corresponding pressure mapping images. Scale: 2 cm.⁵¹ Copyright© (2024) ACS Nano.

Creating integrated flexible systems with integrated functions requires the use of multiple printing techniques to combine diverse functionalities. Guan et al. reported a method for synthesizing hydrogels with tunable viscosity that could be adjusted by altering the pH, allowing the gel to transition smoothly between liquid and solid states across a broad viscosity range.⁵¹ The feature endowed the hydrogel with excellent 3D-printing capabilities, making it compatible with both DLP and DIW techniques, thus facilitating the creation of integrated sensor systems and sensor arrays. Additionally, the hydrogel exhibited outstanding mechanical properties, including high stretchability (>1100%) and tensile strength (0.82 MPa). PEDOT:PSS ink was printed using DIW to form electrode patterns, while the hydrogel precursor was printed with DLP to form the active layer with microstructures. Through straightforward assembly, pressure, strain, and temperature sensors were integrated into a unified sensor system (Fig. 14(d)). The system, with multiple sensors embedded onto a PET film, exhibited excellent flexibility when bent (Fig. 14(e)). During practical testing, the integrated sensor system detected light touch, wrist bending, and temperature variations by monitoring changes in capacitance and resistance (Fig. 14(f)). The pressure sensor fabricated via DLP exhibited a sensitivity of 1.821 kPa⁻¹ and provided reliable signal responses within the 2.5–40 kPa range. Taking advantage of the hydrogel's superior printability, a sensor array was assembled to create an electronic skin based on pressure sensors (Fig. 14(g)), which could detect capacitance changes induced by pressure from objects of various shapes. The shape of these objects was clearly identifiable through statistical capacitance signal mapping, as represented in the cloud images (Fig. 14(h)).

6. Conclusion and outlook

In this review, we present a comprehensive overview of the research progress in the fabrication of gel-based sensors using 3D-printing technologies. Gel materials offer a range of advantages, including excellent adhesion, compatibility with the mechanical properties of biological tissues, ease of molding, low toxicity, and biodegradability. When combined with 3D printing, these gels enable the precise customization of microstructures, facilitate rapid and scalable fabrication, and allow for integration of multi-functional materials. The synergy between gel materials and 3D printing not only makes possible the optimization of individual sensing devices, but also enables the fabrication of multimodal sensors and integration of multiple sensors into a unified system. As a result, 3D-printed gel sensors are emerging as a crucial component in the development of next-generation sensing technologies.

Despite significant advancements in the research of 3D-printed gel sensors, several aspects still fall short of expectations. These challenges are discussed in the following aspects:

(1) Environmental instability. Gels, especially hydrogels, inherently contain large amounts of solvent, and exposure to the environment during use can lead to solvent evaporation, which even with encapsulation strategies, cannot be entirely prevented. In applications that involve stretching and compression, prolonged use can also result in the depletion of free ions, which progressively degrades the overall performance of the sensor, potentially leading to failure. Additionally, in real-world scenarios, variations in environmental temperature, as well as sudden impacts or large deformations, can cause the gel sensors to malfunction, further complicating their use in practical applications. Although high boiling point solvents, such as ILs or DES can potentially address this issue, their biocompatibility is still a concern.

(2) Comfort and wearability. The comfort of gel sensors, particularly when used for monitoring physiological signals during human movement, remains an area in need of improvement. These sensors often suffer from poor breathability due to direct contact with skin, and the presence of sweat during physical activity can cause the sensors to shift or even detach, significantly impacting the stability of the signal. Furthermore, the need for an external power source or connection to a detection device for signal transmission and conversion into electrical signals adds bulk to the system, limiting its comfort and portability. These limitations highlight the need for further advancements in the sensor's design to enhance both usability and wearability.

(3) Printing precision. In the 3D printing process, the extrusion and expansion properties of the gel ink limit the precision of structures fabricated using the DIW method, leading to a relatively low level of accuracy. Despite improvements in DLP technology, such as the introduction of grayscale printing, the achievable precision remains around 50 μm,¹⁷¹ and the printing accuracy can reach 5 μm for specially designed gel precursors.¹⁷³ However, as a general-purpose manufacturing technique, the resolution of most sensors fabricated using DLP typically ranges from tens to hundreds of micrometers, which still falls short of the higher precision achievable with 3D printing of other materials.

(4) Biocompatibility and mechanical mismatch. During the UV curing process used to form gels, residual monomers, which may be biologically toxic, can remain trapped within the gel matrix, preventing the direct use of gels in implantable sensor applications. Additionally, while multiple cross-linked networks are often introduced to enhance the gel's deformation recovery and mechanical properties, this increases the mismatch between the gel's modulus and that of biological tissues. This mismatch can compromise the stability and reliability of the sensor signals in practical biomedical applications, posing a significant challenge for the development of biocompatible and implantable sensors.

Author contributions

Lei Cui: conceptualization, investigation, writing – original draft, Yuxuan Lin: investigation, visualization, Chenning Li: investigation, visualization, Zhenhua Yang: investigation, visualization, Chao-Peng Wang: investigation, visualization, Jun Yin: writing – review & editing Jian Zhu: writing – review & editing.

Conflicts of interest

There are no conflicts to declare.

Data availability

The data used to support the findings of this study are included within the article.

Acknowledgements

This work was supported by NSFC (52273076 and 12004195), 111 Project (B18030), and the Natural Science Foundation of Tianjin (23JCQNJC00350).

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