Introduction

Flexible pressure sensors serve as fundamental components for external force monitoring and signal transduction, playing a pivotal role in applications ranging from healthcare monitoring and electronic skin to intelligent robotics and wearable electronics1,2,3,4,5,6,7. Based on their working mechanisms, flexible pressure sensors can be categorized into four types: piezoresistive8, capacitive9, piezoelectric10, and triboelectric11. Among these, piezoresistive pressure sensors have garnered significant attention due to their facile fabrication, structural simplicity, high flexibility, and efficient signal acquisition12,13. However, the practical deployment of these sensors remains constrained by a critical tradeoff between sensitivity and detection range, which is an inherent limitation that has long challenged sensor design and optimization. High sensitivity is typically achieved by enhancing material flexibility and surface response, but this often comes at the cost of a limited detection range. For instance, piezoresistive sensors based on leather composites decorated with silver nanowires achieve a high sensitivity of 0.13 kPa−1 but operate within a narrow detection window of 17.5 kPa14. Similarly, wearable sensors utilizing polyimide nanofiber/MXene composite aerogels achieve 0.14 kPa−1 sensitivity, yet their working pressure range remains confined to 85.21 kPa13. Additionally, MGF pressure sensors show a sensitivity of 0.233 kPa−1, but their detection range is limited to 120 kPa15. Conversely, expanding the detection range typically demands an increase in material modulus, which inevitably compromises sensitivity. For example, piezoresistive sensors based on SEBS/TPU/CB/CNF nanocomposites extend the detection range to over 200 kPa, but their sensitivity drops to 0.0316 kPa−1 16. Similarly, a flexible sensor with high resistance to interference based on an AgNWs@TiO2 core-shell structure achieves an impressive detection range of 1500 kPa, yet its sensitivity is as low as 0.0012 kPa−1 17. Thus, achieving a dynamic balance between sensitivity and detection range, and designing a sensor structure that combines both high sensitivity and a wide detection range, remains a pressing technical bottleneck. This challenge is particularly pronounced in aerospace applications, where astronauts must cope with extreme temperature fluctuations caused by alternating stellar radiation and deep space cold, creating harsh “fire and ice” conditions. As a result, pressure sensors for aerospace applications must not only combine high sensitivity and a wide detection range but also maintain exceptional mechanical and electrical stability across extreme temperatures to ensure reliable operation in complex mission scenarios. Flexible pressure sensors have made notable progress in extreme environments in recent years, such as MWCNTs/GP/TPU composite materials achieving a 2 MPa pressure detection range within a temperature range of 25 to 70 °C18, and pressure sensors based on flexible, porous phenyl siloxane/functionalized carbon nanotube (PS/FCNT) films showing good durability at high temperatures (200 °C)19, and sensors based on modified silicone rubber/functionalized carbon nanotubes (MSR/FCNT) maintaining excellent durability at low temperatures (−80 °C) and withstanding 200 °C high temperatures20. However, due to the complexity of testing in extreme environments, current understanding of sensors’ mechanical and sensing performance under such conditions remains at the level of theoretical potential rather than validated application. Therefore, developing a flexible sensing material that can operate stably under extreme conditions while simultaneously achieving high sensitivity and a wide detection range has become an urgent need in aerospace applications.

Currently, piezoresistive pressure sensors are predominantly realized through conductive polymer composites, wherein external pressure induces the reconfiguration of conductive networks, leading to variations in electrical resistance. These sensors are typically composed of a flexible polymer matrix embedded with conductive fillers, with their performance finely tuned through meticulous structural engineering and sophisticated fabrication techniques13. Aerogels, renowned for their exceptional porosity, ultralow density, and electrical properties, have recently garnered significant interest in the field of flexible sensing21,22,23,24. Their unique three-dimensional network architecture enables dynamic optimization of functional properties by regulating pore size, compositional elements, and mechanical characteristics25,26,27,28. However, conventional crystalline ceramic aerogels exhibit inherent brittleness due to the absence of dislocation slip and grain boundary softening mechanisms. Although amorphous ceramics achieve a certain degree of toughness via plastic deformation induced by shear bands, their susceptibility to crystallization at elevated temperatures severely limits long-term material stability29. In contrast, nanofiber aerogels, constructed from one-dimensional fibrous networks, form highly flexible porous skeletons through a combination of physical entanglement and chemical bonding, endowing them with exceptional mechanical resilience and broad functional adaptability30,31,32,33. Among these, polyimide nanofiber (PINF) aerogels stand out as an ideal substrate for next-generation flexible electronics, owing to their extraordinary thermal stability, chemical inertness, cost-effectiveness, and superior processability13,34. Their excellent thermal endurance, coupled with high strength and ultralight properties, renders them particularly suited for aerospace applications, where they must withstand extreme fluctuations between intense thermal radiation and deep-space cryogenic conditions, positioning them as a promising solution for advanced flexible sensing in harsh operational environments.

At present, nature offers abundant biomimetic insights for optimizing the structures of flexible sensors35,36,37,38,39. For example, inspired by human fingerprints, researchers have confined 3D-stacked MXenes within fingerprint channel structures, enabling sensors to exhibit finer spatial deformation40. Drawing inspiration from gecko skin, its hemispherical arrays and porous structure ensure high sensitivity at low pressures41. Additionally, inspired by the robust and interconnected honeycomb structures found in nature, sensors effectively conduct stress to enhance mechanical performance42. Notably, gradient structures in nature offer unique advantages in stress distribution and functional regulation. For example, the gradual fiber distribution in bamboo, transitioning from the flexible pith at the core to the hard outer layer, not only provides excellent bending resistance but also retains flexibility43. The multi-layered gradient porous structure of pomelo peel exhibits exceptional energy absorption when subjected to impact, protecting the internal pulp from damage44. These structures achieve a synergistic optimization of strength and flexibility through spatial variations in density, pore size, and material stiffness. Inspired by these designs, constructing a dual-gradient structure that transitions from high to low density and from small to large pore size provides a promising approach to resolving the tradeoff between sensitivity and detection range. Previous studies have shown that graphene pressure sensors with a gradient structure exhibit exceptional reliability and rapid response times across a pressure range of 0.1–50 kPa45. Additionally, pressure sensors based on gradient and stretchable rGO/PUF composite aerogels demonstrate an ultra-wide response range of 1 Pa–12.6 MPa and excellent fatigue resistance46. Wearable piezoresistive pressure sensors made from multi-layer gradient conductive poly(ε-caprolactone) nanofiber membranes exhibit a sensitivity of 33.955 kPa−1 within a pressure range of 0–80 kPa47. Gradient structures effectively control the saturation behavior of resistance changes, enhancing the difference between initial and saturated resistances, thus achieving high sensitivity and a wide pressure detection range. However, the coupling relationship between the mechanisms of gradient structures and their performance has yet to be systematically and deeply explored, remaining a critical issue that requires further investigation.

In this work, inspired by the multi-gradient structures found in nature, we propose a bottom-up self-assembly strategy. By employing a multi-step synergistic approach that incorporates electrospinning, layer-by-layer freezing, and thermal imidization, we successfully fabricated a polyimide nanofiber/carbon nanotube (PINF@CNTs) dual-gradient aerogel with a dynamic stiffness transition from flexible to rigid states. This design overcomes the traditional tradeoff between sensitivity and detection range in sensors, effectively addresses the technological bottleneck in extreme environment adaptability, and realizes multi-functionality by integrating heat insulation and health detection. Using finite element analysis, we systematically explore the coupling relationship between the deformation mechanisms of the gradient structure and material properties, providing a theoretical foundation for the design and optimization of gradient structures. Experimental results show that the dual-gradient aerogel not only exhibits an ultralow density (0.023 g cm−3) and excellent thermal insulation performance (28 mW m−1 K−1), but also demonstrates notable compressibility and fatigue resistance. Furthermore, an exceptional balance between sensitivity and detection range is achieved, with a sensitivity of 156 MPa−1 and an expanded detection range of 223 kPa. Benefiting from the excellent thermal stability of the polyimide matrix, the PINF@CNTs dual-gradient aerogel retains notable mechanical and electrical properties across an extreme temperature range from −196 °C to 533.30 °C. This integrated material, which combines lightweight, extreme temperature resistance, and multi-functionality, shows immense potential for applications in harsh environments such as aerospace, providing a design approach and technical foundation for the development of high-performance flexible pressure sensors.

Results and discussion

Design, preparation and application

In nature, numerous gradient structures exist, which have played a critical role in the process of natural selection48,49,50. A prime example of such a design is found in the equine hoof, which serves as a model of gradient optimization51,52. The outer layer of the equine hoof is characterized by small pores and high density, rendering it hard and compact to provide robust structural support. In contrast, the inner layer features larger pores and lower density, endowing it with enhanced flexibility that effectively absorbs impact and offers superior cushioning (Fig. 1a). This gradient structure not only achieves an optimal balance between rigidity and flexibility but also efficiently dissipates external forces, preventing excessive strain on the hoof while enhancing stability and comfort during locomotion. Inspired by the equine hoof gradient architecture, this study introduces a bottom-up self-assembly strategy combined with layer-by-layer freezing techniques, successfully fabricating a nanofiber aerogel with a dual-gradient structure. The resulting aerogel exhibits a gradual decrease in density from the bottom to the top, accompanied by an increase in pore size, allowing for a dynamic transition between flexibility and rigidity. This precisely engineered gradient structure provides an innovative solution to the tradeoff between a wide operational range and high sensitivity, addressing a long-standing challenge in conventional pressure sensors.

Fig. 1: Biomimetic design and applications of the dual-gradient nanofiber aerogel.
Fig. 1: Biomimetic design and applications of the dual-gradient nanofiber aerogel.
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a Equine hoof and its gradient structure. Photographs of equine hoof were captured by the author. b Schematic diagram of the preparation process of the PINF@CNTs dual-gradient aerogel. Different colors are used to denote distinct layers within the gradient structure. Micrograph is representative of 3 independent samples. c Applications of the aerogel in spacesuits for health monitoring and thermal insulation under extreme conditions. The left plot shows the sensor’s piezoresistive response under extreme cold, indicating minimal impact on performance. The inset displays a photo of the sensor under cold conditions. The right plot demonstrates the sensor’s thermal insulation properties under extreme heat. Source data are provided as a Source Data file.

The synthesis pathway of the dual-gradient nanofiber aerogel is illustrated in Fig. 1b and Fig. S1 (Supplementary Information). Its core principle lies in the multi-step synergistic regulation of both density and pore size gradients, achieved through electrospinning, layer-by-layer freezing, and thermal imidization. First, highly uniform polyamic acid (PAA) nanofiber membranes were fabricated via electrospinning (Supplementary Fig. S2a). The fibers exhibited excellent diameter uniformity, with an average diameter of 156.1 nm, and no noticeable bead formation (Supplementary Fig. S3). These fibers were then dispersed in deionized water, where strong shear forces generated by high-speed homogenization ensured thorough dispersion, yielding stable nanofiber suspensions with controlled concentrations of 20 mg/cm3, 18 mg/cm3, 16 mg/cm3, 14 mg/cm3, and 12 mg/cm3. Subsequently, triamine-terminated polyamic acid (PAA-TEA, Supplementary Fig. S2b) and carbon nanotube (CNT) precursor solutions (8 mg/mL, Supplementary Fig. S2c) were introduced. PAA-TEA, synthesized through the polycondensation of pyromellitic dianhydride (PMDA) and 4,4′-oxydianiline (ODA), served as a binder to rein- force the fiber network’s structural stability and mechanical strength53. Compared to aerogels without PAA-TEA, those incorporating PAA-TEA exhibited significantly enhanced structural integrity (Supplementary Fig. S4, Supplementary Video 1).

The implementation of the gradient structure is achieved through a multi-step directional freezing process. Initially, a nanofiber suspension with a concentration of 20 mg/cm3 is uniformly injected into a custom mold and subjected to directional freezing with liquid nitrogen, resulting in the frozen block of the first gradient unit. To facilitate directional freezing, the mold sidewalls are made of acrylic, which has low thermal conductivity, whereas the bottom plate is copper, which exhibits excellent thermal conductivity, so that the cold airflow passes through the fibers from bottom to top. Subsequently, by gradually reducing the concentration of the dispersive liquid, a gradient in the polyamic acid content is formed in the vertical direction. After freeze-drying to remove the ice crystals, a density gradient is established along the vertical axis. As the distance from the cooling source increases, the freezing temperature of each layer decreases progressively, leading to larger ice crystals in each successive layer. As a result, after the ice crystals are removed, a pore size gradient is formed along the vertical direction. Unlike traditional gradient structures, where interface issues often weaken the interlayer bonding, compromising the overall stability and mechanical properties of the gradient structure, this approach avoids such problems. The temperature gradient and crystallization behavior during freezing often lead to weak transition interfaces between layers, causing interlayer separation or discontinuity. In this work, to ensure robust interfacial bonding between gradient units, the next-stage dispersion is rapidly injected when the upper-stage unit is on the verge of solidification during the pre-freezing process. This causes slight melting of the upper-stage unit’s surface, allowing homogeneous mixing with the lower-stage unit, resulting in tight interlayer bonding in the as-obtained gradient frozen blocks. To verify the gradient structure and interfacial properties of aerogels, we characterized them using transmission electron microscopy/energy-dispersive X-ray spectroscopy (TEM/EDS). As shown in Fig. S5 (Supplementary Information), the density disparity across the interface is pronounced, with the deeper lower region exhibiting a high-density domain and the shallower upper region constituting a low-density domain. The EDS further corroborates the gradient architecture through the spatial distribution of C, N, and O elements. Furthermore, we performed scanning electron microscopy (SEM) characterization on the axial cross-section of the gradient aerogels. As shown in Fig. S6 (Supplementary Information), the interlayer interface (denoted by the orange dashed frame) displays distinct gradient structures on either side, with high-magnification SEM imaging (right panel) revealing a tight combination at the interface. Furthermore, mercury intrusion porosimetry was used to obtain the overall pore size distribution of the gradient aerogel, as shown in Fig. S7a (Supplementary Information), indicating that the gradient aerogel has a distribution from small to large pores. To further characterize the pore size distribution of each layer of the aerogel, we performed automated statistical analysis and manual marking on SEM images using ImageJ software. As shown in Fig. S7b−f (Supplementary Information), the first layer aerogel (with a concentration of 20 mg/cm3) exhibits the smallest average pore size of 17.81 μm, while the fifth layer aerogel has the largest average pore size of 61.60 μm. This is because the first layer aerogel has the highest suspension concentration, the shortest distance from the cold source, the lowest freezing temperature, and the smallest formed ice crystals, resulting in the smallest pore size after ice crystal removal. This further confirms the successful construction of the gradient structure. The frozen block is then transferred to a freeze dryer for vacuum drying and thermal imidization. During the freeze-drying process, the directionally grown ice crystals evaporate, leaving behind a three-dimensional, directionally aligned pore structure. The subsequent thermal imidization process removes the imidazole and carboxyl groups from the polyamic acid (PAA) molecular chains, cyclizing them to form polyimide (PI), which exhibits superior mechanical and thermal insulation properties.

The porous structure of this dual-gradient aerogel arises from the precise control of the ice-templating method. Through the ordered alignment of ice crystals and the complete removal of ice crystals during the freeze-drying process, the material achieves an ultralow density (0.023 g cm−3, Supplementary Fig. S8). Its remarkable lightness allows it to effortlessly rest on the surface of a flower stamen without any bending or deformation (Supplementary Fig. S9). Furthermore, the aerogel exhibits exceptional shape adaptability, meeting the requirements of various application scenarios (Supplementary Fig. S10). With its ultralightweight, highly flexible properties, and the excellent performance brought about by the dual-gradient structure, the PINF@CNTs dual-gradient aerogel holds great potential for applications in the pressure sensing field. Its excellent stability across a wide temperature range makes it particularly suitable for extreme environments, such as those encountered in aerospace. When integrated into spacesuits, this aerogel is expected to facilitate real-time monitoring of astronaut motion signals and physiological parameters, while simultaneously providing thermal insulation and cold protection through the thermal stability of the polyimide matrix (Fig. 1c). Compared to traditional polymer-based pressure sensors, this aerogel has the potential to demonstrate higher reliability and adaptability under extreme conditions, offering a technological solution for health monitoring and personnel protection in challenging environments.

Characterizations and deformation mechanism

Benefiting from the reduction in the concentration of the dispersive liquid and the cooling source temperature at each layer, a biomimetic dual-gradient nanofiber aerogel, resembling the gradient structure of an equine hoof, was achieved. The multi-layered microstructure of the dual-gradient aerogel is shown in Fig. 2a. As observed in the SEM images, the first gradient unit (with a concentration of 20 mg/cm3) exhibits the densest fiber network and the smallest pore size, while the fifth gradient unit (with a concentration of 12 mg/cm3) shows the loosest fiber structure and the largest pore size. Through the dual control of the dispersive liquid concentration and freezing temperature, a gradient transition from small pores at high density to large pores at low density was realized, successfully mimicking the dual-gradient features found in the natural structure of the equine hoof.

Fig. 2: Compression deformation mechanisms and morphological structure characterizations of the dual-gradient nanofiber aerogel.
Fig. 2: Compression deformation mechanisms and morphological structure characterizations of the dual-gradient nanofiber aerogel.
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a Scanning electron microscope (SEM) images of the gradient units of the PINF@CNTs dual-gradient aerogel. Micrographs are representative of 3 independent samples. Finite element models and deformation mechanisms of (b) the dual-gradient aerogel and (c) the non-gradient aerogel. d FT-IR spectra of PINF@CNTs aerogel, PAANF@CNTs aerogel, PI nanofiber membrane, and PAA nanofiber membrane. TG and DTG curves of (e) PINF@CNTs aerogel and (f) pure PINF aerogel. Source data are provided as a Source Data file.

To systematically investigate the coupling relationship between the deformation mechanisms of the gradient structure and the material properties, we conducted finite element simulations under quasi-static compression, constructing 3D models of dual-gradient and non-gradient nanofiber aerogels. As shown in Fig. 2c, the non-gradient aerogel exhibits homogeneous deformation under applied stress, attributed to its uniform structure that yields consistent stiffness throughout the material (Supplementary Fig. S11a). As a result, sensors based on non-gradient aerogels face an inherent tradeoff: increasing the detection range necessarily compromises sensitivity, whereas enhancing sensitivity inherently reduces the detection range. However, the dual-gradient aerogel exhibits a progressive, layer-by-layer deformation mode due to its gradient architecture (Supplementary Fig. S11b). As shown in Fig. 2b, upon the application of external stress, the low-modulus layers with larger pore sizes and lower densities deform first, while the other gradient units remain stable with no noticeable deformation. This is because the low-density layers possess lower stiffness, causing them to deform before the other layers under external force. As the loading progresses, the deformation from these low-modulus layers gradually propagates to the high-modulus layers, which have smaller pores and higher densities. This layer-by-layer deformation mechanism, which enables a dynamic transition from flexibility to rigidity, is expected to address the challenge of reconciling high sensitivity with a wide operational range in sensors.

To confirm the successful polymerization of PAA into PI, Fourier-transform infrared spectroscopy (FT-IR) was employed to characterize the chemical structures of PAA nanofiber membranes, PI nanofiber membranes, PAANF@CNTs aerogels, and PINF@CNTs aerogels, as shown in Fig. 2d. The three peaks observed at 1716, 1656, and 1542 cm−1 in the PAA nanofiber membrane and PAANF@CNTs aerogel correspond to the stretching vibrations of C = O in the COOH group, C = O in the CONH group (amide I), and C-N in the C-NH group (amide II), respectively. For the PI nanofiber membrane and PINF@CNTs aerogel, two new peaks appear at 1776 and 1718 cm−1 due to the asymmetric and symmetric stretching vibrations of C = O in the imide band. Additionally, two new peaks at 1371 and 721 cm−1 correspond to the C-N stretching and C = O bending modes of the imide group13,54. These newly observed peaks clearly indicate that PAA has successfully polymerized into PI. Moreover, thermal gravimetric analysis (TGA) was employed to evaluate the thermal stability of PINF@CNTs aerogels and pure PINF aerogels in an air atmosphere. As depicted in Fig. 2e, f, the onset decomposition temperature (Tonset) and maximum decomposition rate temperature (Tmax) of the PINF@CNTs aerogel were determined to be 533.30 °C and 602.27 °C, respectively, both lower than those of the pure PINF aerogel (Tonset = 547.42 °C, Tmax = 627.81 °C). The decrease in thermal stability is primarily attributed to the excellent thermal conductivity of CNTs, which induce the decomposition of PI at a lower temperature13. Nonetheless, owing to the excellent thermal stability of the polyimide matrix, the PINF@CNTs aerogel still exhibits significant potential for operation over a wider temperature range compared to other conventional polymer-based pressure sensors, which will be explored further in subsequent studies.

Mechanical properties

When designing aerogels with desired functionalities, an important performance criterion is their mechanical properties, specifically their ability to deform excellently while preventing structural failure caused by environmental factors such as mechanical stress, thermal gradients, and capillary forces. Figure 3 comprehensively illustrates the mechanical characteristics of the dual-gradient nanofiber aerogels and highlights the potential advantages of gradient design in achieving high sensitivity and a wide operational range in pressure sensors. The dual-gradient nanofiber aerogels exhibit remarkable flexibility and recoverability, attributed to the flexibility of the nanofibers and the effective entanglement and sliding within the fiber network. Furthermore, the interlayer structures provide ample compression space, allowing the aerogel to quickly return to its original shape after undergoing significant compression, demonstrating excellent resistance to deformation (Fig. 3a and Supplementary Video 2). More importantly, the graded structure of the gradient aerogels provides unique hierarchical response characteristics in their mechanical behavior. As shown in Fig. 3b and Fig. S12 (Supplementary Information), when the gradient aerogel is subjected to external pressure, the low-modulus fifth gradient unit deforms significantly first. As strain increases, the deformation gradually propagates to higher-modulus fourth and third gradient units, until the highest-modulus first gradient unit carries the remaining compressive stress. Through this stepwise deformation process, the gradient aerogel exhibits significant strain transfer and graded load-bearing capability, enabling the pressure sensor to maintain high sensitivity over a wide operating range. In contrast, the non-gradient aerogel, lacking layered control, exhibits uniform deformation during compression, making it difficult to effectively distribute stress and prone to localized failure. Comparing the experimental results with the finite element simulation outcomes, we observe a high consistency in the deformation modes between the experiments and the simulations.

Fig. 3: Mechanical properties of the dual-gradient nanofiber aerogel.
Fig. 3: Mechanical properties of the dual-gradient nanofiber aerogel.
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a Compression recovery photographs of the dual-gradient aerogel. All the panels have the same magnification as the provided scale image. b Deformation modes of the dual-gradient aerogel and the non-gradient aerogel. Dashed lines indicate interlayer localized deformation. All the panels have the same magnification as the provided scale image. c Stress-strain curves and (d) energy absorption curves of the dual-gradient and non-gradient aerogels. e A comparative bar chart of stress and compressive modulus for the dual-gradient and non-gradient aerogels at 80% strain. Values in e represent the mean ± s.d. (n = 3 independent samples). f Four stress-strain curves of the dual-gradient aerogel under 20%, 40%, 60%, and 80% strain conditions. g Maximum stress variation and plastic deformation of the dual-gradient aerogel after 1000 cycles of loading at 50% strain. h Comparative radar chart of energy absorption (EA), specific energy absorption (SEA), modulus, load, and stress for the dual-gradient and non-gradient aerogels at 80% strain. Compressive images of PINF@CNTs dual-gradient aerogel treated at (i) room temperature, (j) extreme cold, (k) extreme heat. Source data are provided as a Source Data file.

The gradient design not only imparts the aerogel with a layer-by-layer deformation capability but also optimizes its dynamic response characteristics in terms of compressive modulus. Experiments show that, during the initial compression phase, the modulus of the gradient aerogel is lower than that of the non-gradient aerogel, reflecting its soft properties. This softness enhances the sensitivity of the pressure sensor and allows for flexible contact with the human body, significantly improving wearability. As compression deformation increases, the modulus of the gradient aerogel increases significantly, demonstrating its dynamic transition from flexibility to rigidity (Fig. 3c). This transition is crucial for expanding the operational range of the pressure sensor, while also achieving higher energy absorption through stepwise load-bearing (Fig. 3d and Supplementary Fig. S13), thereby providing effective protection.

Figure 3e presents the compression stress and modulus data of the gradient aerogel under 80% strain. Compared to the non-gradient aerogel, the gradient aerogel shows a significant increase in stress and modulus under high-strain conditions. This indicates that the gradient design effectively enhances the aerogel’s load-bearing capacity under extreme strain conditions. The stress-strain curves (Fig. 3f) further validate this result, demonstrating that even at 80% strain, the gradient aerogel still exhibits high recoverability. In contrast to the stress-strain curves at 20%, 40%, and 60% strain, the stress of the aerogel sharply increases under 80% strain, reflecting the supporting role of the high-modulus gradient units at the extreme deformation stage. This nonlinear response is crucial for achieving a wide dynamic range and high sensitivity in pressure sensors. Fatigue tests (Fig. 3g and Supplementary Fig. S14) show that after 1000 cycles of loading at 50% strain, the gradient aerogel retains a maximum stress of 9.36 kPa, with only 15.3% plastic deformation, demonstrating its super-elasticity and exceptional fatigue resistance, which are key attributes for durable aerogel-based pressure sensors. Figure 3h provides a comparative radar chart of the mechanical properties of the gradient and non-gradient aerogels at 80% strain. It is evident from the figure that the gradient aerogel outperforms the non-gradient aerogel in terms of maximum load, maximum stress, compressive modulus, energy absorption (EA), and specific energy absorption (SEA). Additionally, we investigated the mechanical property differences of the gradient aerogels in horizontal and vertical directions, as well as the effects of carbon nanotube content and thickness on the mechanical properties of the composite aerogels. The details are presented in Figs. S15−S17 (Supplementary Information). Furthermore, benefiting from the thermal stability of the polyimide matrix, the PINF@CNTs dual-gradient aerogel exhibits excellent mechanical stability under extreme conditions (Fig. 3i–k), which will be further investigated in the following sections.

Sensing properties

The pressure sensor based on the PINF@CNTs dual-gradient aerogel demonstrates impressive sensing performance. Its unique gradient structure and high flexibility provide robust support for the sensor’s high sensitivity and broad dynamic response range. The structural schematic and physical images of the pressure sensor are shown in Figs. S18, S19 (Supplementary Information). Due to the incorporation of CNTs, the dual-gradient aerogel exhibits excellent conductivity (Fig. 4a)55. To visually validate its sensing performance, the pressure sensor was integrated into a series circuit with a light-emitting diode (LED) (Supplementary Fig. S20). As the aerogel is compressed, the LED changes from dim to bright, and upon recovery, the LED dims again (Supplementary Fig. S21 and Supplementary Video 3). This phenomenon arises from the increased contact between the CNTs in the conductive network after compression, significantly reducing the aerogel’s resistance (Supplementary Fig. S22)46. Compared to the non-gradient aerogel pressure sensor, the gradient aerogel significantly enhances both the detection limit and sensitivity. As shown in Fig. 4b, c the detection limit of the gradient aerogel pressure sensor is 223 kPa, while the non-gradient aerogel only reaches 107 kPa. This performance improvement is attributed to the gradual increase in modulus of the dual-gradient aerogel under compressive deformation, enabling a dynamic transition from flexibility to rigidity.

Fig. 4: Sensing performance of the dual-gradient nanofiber aerogel.
Fig. 4: Sensing performance of the dual-gradient nanofiber aerogel.
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a The hierarchical PINF@CNTs network forms an in-plane electrical conduction system. The variation in relative resistance with pressure for the pressure sensors based on (b) dual-gradient aerogels and (c) non-gradient aerogels. d The electrical resistance response of the pressure sensor based on dual-gradient aerogels to different compression strains from 2% to 80%. e Compression-unloading durability test of the pressure sensor based on dual-gradient aerogels under 50% strain and 1000 cycles. f Response of the pressure sensor based on dual-gradient aerogels to the pulse at the wrist, and monitoring of human motion by detecting plantar pressure, such as standing, walking, and running. Source data are provided as a Source Data file.

Sensitivity is another crucial parameter for pressure sensors, and for all these pressure sensors, the sensitivity decreases with increasing pressure. The pressure sensor based on the dual-gradient sensor demonstrates higher sensitivity within a pressure range of 223 kPa (0–3.2 kPa: 156 MPa−1, 3.2–13.4 kPa: 14 MPa−1, 13.4–38.3 kPa: 2 MPa−1, 38.3–223 kPa: 0.002 MPa−1). In contrast, the pressure sensor based on the non-gradient sensor exhibits lower sensitivity within a pressure range of 107 kPa (0–20.4 kPa: 34 MPa−1, 20.4–31.7 kPa: 11 MPa−1, 31.7–107 kPa: 0.034 MPa−1). The dual-gradient aerogel pressure sensor demonstrates highly stable changes in relative resistance under a range of external loads from 0.6 to 223 kPa, indicating its ultra-wide response range for pressure sensing under practical conditions (Fig. 4d). To further evaluate the durability and stability of the pressure sensor based on the dual-gradient aerogel, it was subjected to 1000 cycles of compression-unloading at 50% strain. After 1000 compression-unloading cycles, the resistance of the gradient aerogel-based pressure sensor remained virtually unchanged, demonstrating excellent durability and stability. Additionally, the sensor exhibits excellent bending and torsional properties, as shown in Fig. S23 (Supplementary Information). When the sensor is bent or twisted, enhanced contact between carbon nanotubes induces resistance changes, and the sensor maintains a stable resistive response during mechanical deformation. This further demonstrates that the sensor can effectively respond to force sensing under various mechanical deformations.

To validate the vast potential of the dual-gradient aerogel in pressure sensor applications with a wide operating range, we assembled it into a resistive pressure sensor and adhered it with regular tape to various parts of the human body to detect a range of human motion and physiological signals. As shown in Fig. 4f, by placing the gradient aerogel-based pressure sensor on the wrist, we effectively recorded periodic pulses in real-time. The pulse signal was strong and distinct, with a calculated frequency of 70 beats per minute, providing solid evidence that the sensor can effectively detect low-frequency, small-amplitude vibration signals. Additionally, placing the sensor on the sole allowed for real-time monitoring of dynamic changes in the plantar pressure during human movement, including different states such as standing, walking, and running. This experimental result demonstrates that the dual-gradient aerogel-based sensor can not only detect low-frequency signals but also precisely respond to changes under higher pressure, highlighting its broad adaptability across varying loads. Further experiments verified the sensor’s excellent performance in capturing motion signals, accurately monitoring subtle movements such as finger flexion, wrist activity, and finger touch (Supplementary Fig. S24). Compared with other existing piezoresistive sensors, the sensor based on dual-gradient aerogel has achieved an excellent balance in terms of the scalability of the working range and sensitivity (Supplementary Fig. S25). This series of experimental results fully demonstrates the immense potential of dual-gradient aerogels in sensor applications and provides an innovative solution for developing high-performance, wide-range, high-sensitivity pressure sensors with broad practical application prospects.

Thermal insulation properties

The extreme complexity of the space environment presents significant challenges for astronauts, who must contend with the vast temperature differences caused by the alternating stellar heat radiation and deep space extreme cold, resulting in harsh “fire and ice” conditions. This poses a severe challenge to sensor performance. Exceptional thermal insulation is a critical feature of flexible wearable devices, as it not only effectively prevents extreme temperatures from harming the human body but also ensures the stable operation of sensors in both cold and hot environments. Due to the high porosity (98.41%) of the dual-gradient aerogels, our sensors maintain a lightweight structure while offering excellent thermal insulation performance. Figure 5a illustrates the complex thermal conduction mechanisms of dual-gradient nanofiber aerogels, with their effective thermal conductivity (λeff) theoretically determined by solid conduction (λs), gas conduction (λg), thermal convection (λc), and thermal radiation (λr)56,57, The pore size of the aerogel (61.60 μm for the fifth gradient unit) is far smaller than the onset scale for natural thermal convection (1 mm), making the contribution of λc negligible. Additionally, the enhanced solid-gas interface reflectivity significantly reduces the contribution of thermal radiation (λr), while the low solid volume fraction (0.023 g cm−3) substantially suppresses solid conduction (λs). Furthermore, the aerogel’s high porosity and smaller pore size further disrupt the thermal conduction path, limiting the long-range thermal transport of air molecules, thereby effectively reducing gas conduction (λg)58.

Fig. 5: Thermal insulation performance of the dual-gradient nanofiber aerogel.
Fig. 5: Thermal insulation performance of the dual-gradient nanofiber aerogel.
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a Schematic diagram of the heat transfer mechanism of the dual-gradient aerogel. Temperature-time curves of the top and bottom surfaces of (b) the dual-gradient aerogel and (c) the non-gradient aerogel. d Thermal conductivity of different materials as a function of volume density. e Temperature-time curves of the dual-gradient aerogel and cold plate upon injection of liquid nitrogen. f Thermal infrared image of the dual-gradient aerogel under a simulated light source. Compression recovery images of the dual-gradient aerogel (g) on a 200 °C hot plate and (h) in −196 °C liquid nitrogen. i Surface temperature of the aerogel (15.0 mm thick) placed on the palm. j Change in surface temperature of the aerogel and palm over time. Source data are provided as a Source Data file.

To evaluate the thermal insulation performance of the dual-gradient aerogel, samples of ~15.0 mm in thickness (Supplementary Fig. S26) were placed on a 200 °C heating plate (Supplementary Fig. S27), and the temperature distribution was recorded using an infrared camera (Supplementary Fig. S28). As shown in Fig. S29 (Supplementary Information), after 300 sec, the surface temperature of the dual-gradient aerogel was only 43.6 °C, significantly lower than the 56.8 °C observed for the surface of the non-gradient aerogel. Additionally, the temperature difference between the top and bottom surfaces of the dual-gradient aerogel reached 152.3 °C (Fig. 5b), which was notably superior to the 139.7 °C observed for the non-gradient aerogel (Fig. 5c). The excellent thermal insulation performance of the dual-gradient aerogel can be attributed to its biomimetic gradient structure, which effectively reduces heat conduction and thermal radiation effects by layer-by-layer regulation of pore size and density. Compared to other insulation materials29,58,59, the prepared PINF@CNTs dual-gradient aerogel demonstrates favorable performance in both lightweight and low thermal conductivity (Fig. 5d). The combination of extreme temperature tolerance and thermal insulation properties exhibited by the resulting dual-gradient nanofiber aerogel offers a potential material system capable of maintaining body temperature under extreme conditions. As a proof of concept, the gradient aerogel, with a surface diameter and thickness both of 15.0 mm, was placed on a cooling stage, with temperature-sensitive probes and a data acquisition system connected to both the stage surface and the aerogel surface to record temperatures (Supplementary Fig. S30). As shown in Fig. 5e, due to the presence of liquid nitrogen, the cooling stage temperature dropped to −29.5 °C, while the top surface temperature of the gradient aerogel reached a minimum of 11 °C. As the liquid nitrogen evaporated, the aerogel stabilized at ~18.7 °C. Furthermore, the photothermal performance of CNTs can serve as a heat source for wearers in cold winter, providing the appropriate temperature for normal physiological activities. Under a solar simulation light source for 30 min, the gradient aerogel’s temperature reached ~67.6 °C (Fig. 5f and Supplementary Fig. S31). Additionally, the material exhibited excellent resilience and mechanical stability under both thermal and liquid nitrogen low temperature conditions (Fig. 5g, h and Supplementary Videos 4,5). Unlike traditional materials, which often face the risk of high-temperature decomposition or low-temperature brittleness under extreme conditions, significantly affecting their resilience, this material, with its wide temperature range adaptability, can maintain exceptional mechanical properties across large temperature fluctuations. As a result, it holds great potential for protecting sensor stability in aerospace applications while effectively shielding astronauts from the impacts of extreme temperature conditions. To further assess the thermal insulation performance of the prepared PINF@CNTs dual-gradient aerogel in real-world environments, an application demonstration was conducted by monitoring the surface temperature change of a palm covered with a small piece of PINF@CNTs aerogel (thickness: 15.0 mm). Throughout the test, the top surface temperature remained at ~26.2 °C, despite the palm temperature being much higher (≈35.3 °C) (Fig. 5i, j). The PINF@CNTs dual-gradient aerogel demonstrates excellent thermal insulation performance and extreme temperature tolerance over a wide temperature range, ensuring the stable performance of aerogel-based pressure sensors and presenting potential application value for personal thermal protection in various fields.

To evaluate the material stability under extreme environments, we tested the mechanical and sensing properties of the aerogels under extreme cryogenic and high-temperature conditions. As shown in Fig. S32 (Supplementary Information), the aerogels exhibited notable mechanical stability: at room temperature, the maximum stress at 50% strain decreased from 17.0 kPa to 14.3 kPa (15.9% reduction) after 100 cycles; under extreme cold, it dropped from 17.8 kPa to 14.7 kPa (17.4% reduction); and in extreme heat, it decreased from 17.5 kPa to 14.7 kPa (16.0% reduction). The aerogels exhibited no obvious structural damage and maintained excellent mechanical elasticity throughout all cycles, even under extreme environments, further validating their potential for pressure sensing in harsh conditions. As shown in Fig. S33 (Supplementary Information), the sensor exhibited a consistent relative resistance change of 0.43 at 50% strain across room temperature, extreme cold, and extreme heat conditions, with a distinct and stable piezoresistive response in all environments. This consistency confirms its superior reliability and environmental adaptability. Additionally, to validate the effect of environmental pH on the sensor’s sensing performance, we immersed the sensor in deionized water (pH = 7.18), HCl solution (pH = 0.69), and NaOH solution (pH = 12.92), followed by sensing tests. As shown in Fig. S34 (Supplementary Information), the sensor maintained consistent piezoresistive responses after acidic and alkaline treatments, highlighting its robust adaptability in different pH environments. Moreover, owing to the inherent hydrophobicity of polyimide (PI) (Supplementary Fig. S35), the sensor effectively resists degradation from exposure to human sweat during practical use. This significantly enhances its durability and long-term operational stability. Such robust resistance to environmental challenges is particularly crucial for applications in flexible and wearable electronics, where prolonged functionality and stability under complex service conditions are essential.

This study successfully designs and develops a dual-gradient nanofiber aerogel based on biomimetic design principles, addressing the long-standing core challenges between sensitivity and detection range, as well as the performance stability requirements under extreme environmental conditions in the field of flexible pressure sensors. Inspired by multi-gradient structures in nature, we propose a bottom-up self-assembly strategy, utilizing electrospinning, layer-by-layer freezing, and thermal imidization through a multi-step synergistic approach to construct polyimide nanofiber/carbon nanotube (PINF@CNTs) dual-gradient aerogels, with dynamic transitions from high-density small pores to low-density large pores. This dual-gradient aerogel combines the exceptional thermal stability of polyimide with the high conductivity of carbon nanotubes, exhibiting an ultra-low density (0.023 g/cm3), excellent thermal insulation properties (28 mW m−1 K−1), impressive mechanical stability (retaining a maximum stress of 9.36 kPa after over 1000 cycles of compression at 50% strain), high sensitivity (156 MPa−1), and a wide detection range (223 kPa). This combination has not been observed in traditional aerogels. Further- more, this aerogel retains excellent mechanical and sensing properties across the extreme temperature range of −196 °C to 533.30 °C, outperforming most conventional flexible pressure sensors. The multi-functionality and environmental adaptability of this material make the dual-gradient aerogel an ideal candidate for addressing challenges in demanding fields such as aerospace, particularly for multi-task applications in extreme environments like “ice and fire” conditions, including precise pressure sensing, health monitoring, and thermal insulation protection.

Methods

Materials

Pyromellitic dianhydride (PMDA) and triethylamine (TEA) were commercially purchased from Sinopharm Chemical Reagent Co., Ltd. Multi-walled carbon nanotubes (CNTs), 4,4’-oxidianiline (ODA) and N,N-dimethylacetamide (DMAc) were supplied by Aladdin Chemical Reagent Co., Ltd. All chemicals were used as received without further purification. Deionized water was used in all experiments.

Preparation of polyamide acid (PAA)-TEA

PAA was synthesized via polycondensation of ODA and PMDA. Typically, 2.2 g of ODA was dissolved in 25.0 g of DMAc. Subsequently, 2.0 g of PMDA was added to the solution, followed by vigorous stirring until completely dissolved. Afterward, 1.511 mL of TEA was introduced into the mixture, and the solution was stirred overnight to produce a PAA-TEA solution. Finally, the PAA-TEA was vacuum-dried in a freeze dryer, yielding PAA-TEA powder.

Preparation of PAA nanofibers

PAA nanofibers were fabricated using the electrospinning technique. Specifically, 2.15 g of ODA was dissolved in 27.5 mL of DMAc under vigorous stirring at 0°C until fully dissolved. Subsequently, 2.35 g of PMDA was added in portions, followed by a 5-h reaction under vigorous stirring in an ice bath. The resulting solution, with a concentration of 15%, was prepared as the spinning solution for the subsequent electrospinning process. Electrospinning was performed at an applied voltage of 10.1 kV with a feeding rate of 0.3 mL h−1 and a working distance of 15 cm between the syringe needle and the aluminum collector.

Preparation of a CNT precursor solution

0.4 g of CNT powder was added to 50 mL of deionized water and processed using a cell homogenizer for 20 min to obtain a CNT precursor solution with a concentration of 8 mg/mL.

Preparation of PINF@CNTs dual-gradient aerogel

A certain amount of PAA nanofiber membranes was cut into small pieces and dispersed in deionized water. The mixture was processed using a homogenizer at a speed of 14,000 rpm to obtain a PAA nanofiber suspension. Subsequently, 0.3 g of PAA-TEA and 0.15 g of TEA were dissolved in deionized water to prepare a crosslinking (PAA-TEA) solution. The PAA-TEA solution, PAA nanofiber suspension, and CNT precursor solution were then mixed and stirred until homogeneous. Five PAA nanofiber suspensions with different concentrations (20 mg/cm3, 18 mg/cm3, 16 mg/cm3, 14 mg/cm3, and 12 mg/cm3) were prepared following the same method. The dual-gradient nanofiber aerogels were prepared by a layer-by-layer freezing method using liquid nitrogen as the cold source and a copper block as the substrate. First, the 20 mg/cm3 PAA nanofiber suspension was transferred into a directional freezing apparatus to form the frozen block for the first gradient layer. To ensure no distinct interface between gradient layers, the 18 mg/cm3 suspension was quickly added when the upper surface of the first gradient layer was almost fully solidified, allowing for the integration of dispersions at the interface. Similarly, 16 mg/cm3, 14 mg/cm3, and 12 mg/cm3 PAA nanofiber suspensions were sequentially added using the same method to form additional gradient layers. The prepared frozen block was then transferred to a freeze-dryer and vacuum-dried for 48 h. Finally, the material was placed in a muffle furnace, and the temperature was raised at a rate of 3 °C/min under air conditions. Thermal imidization was carried out at gradient temperatures of 100 °C, 200 °C, and 300 °C for a total duration of 1 h to obtain the dual-gradient PINF@CNTs aerogel. The preparation of the non-gradient nanofiber aerogel followed the same procedure, except the suspension concentration was fixed at 16 mg/cm3. All the sensors we used in the testing process were cylindrical, with a bottom diameter and thickness of 18 ± 2 mm (unless otherwise specified).

Characterization

The microstructure of the obtained nanofiber aerogels was characterized using scanning electron microscopy (FLEX 1000). The chemical structure of the aerogels was characterized using Fourier transform infrared (FT-IR) spectroscopy (S1600416). The water contact angle of the materials was measured with optical contact angle meter & interface tensiometer (SL200KS). Mechanical properties of the materials were assessed using a CTM 2050 microcomputer controlled electronic universal material testing machine. The TG curves of the materials were obtained in the atmosphere of air using thermal gravimetric analyzer (STA8000). The thermal insulation performance of the aerogels was evaluated using an infrared thermography camera (Fotric 226 s#L28). Realtime surface temperature measurements of the materials were recorded with a thermocouple (JK500C-8). The sensing performance of the aerogels was measured using a 2450 SourceMeter. The thermal conductivity of aerogel was measured using the TPS3500 thermal constant analyzer from Hot Disk, Sweden, at an ambient temperature of 19.7 °C. ImageJ software was utilized for automatic statistical analysis and manual marking on SEM images to determine the pore size of the aerogel.

Pressure sensing tests

The pressure sensor was placed between the upper and lower compression plates of the universal testing machine, with its copper electrodes connected to the SourceMeter. To ensure the comparability of experiments, the fifth gradient unit (with a concentration of 12 mg/cm3), corresponding to the low-modulus layer, was used as the compression surface in each test. At the same time, to eliminate any errors caused by thickness variation, the thickness of each sample in the comparative experiments was ensured to be consistent before testing. Additionally, the dual-gradient aerogel-based flexible pressure sensor was attached to different parts of a volunteer’s body to monitor human motion and physiological signals. All participants involved in this study were healthy adults (one female and one male, both aged 26) with independent action abilities. All participants provided informed consent prior to the experiments. During these tests, the low-modulus layer was positioned on the side in contact with the body. Compared to the high-modulus layer, the low-modulus layer exhibited greater sensitivity to low pressures, allowing it to effectively detect subtle pressures generated by physiological signals and body movements. Furthermore, the softer nature of the low-modulus layer improved wearer comfort when in direct contact with the body. Meanwhile, the high-modulus outer layer, characterized by superior mechanical strength, served as a protective barrier for the aerogel-based sensor, shielding it from potential damage caused by external forces.

Ethics

The experiment was approved by the Science and Technology Ethics Committee of Donghua University (SRSY202510240089). Each participant gave informed written consent.