Accurate in situ contact temperature measurement in rocket motor exhaust plumes relies on tungsten-rhenium (W-Re) thermocouples, yet their stability is limited by oxidation-induced interfacial degradation. Here, we report an oxidation-resistant W-Re thermocouple enabled by a WSi2 interfacial transition layer and a ZrO2-Al2O3-SiO2 (ZAS) ceramic barrier coating. The resulting thermocouple achieves continuous lifetimes of 67.4, 24.1, and 6.3 min at 20 0 0, 230 0, and 270 0 K, representing similar to 25.9-, similar to 24.1-, and similar to 31.5-fold increases over an uncoated thermocouple, respectively. Across 273-2700 K, it delivers an accuracy of 1.49 %, repeatability of 1.05 %, and consistency of 0.51 %, indicating robust thermoelectric stability. In a supersonic flame test mimicking an engine exhaust plume with an average temperature of 2292.9 K, the W-Re thermocouple with WSi2/ZAS multilayer barriers operates stably for 30.5 min, confirming durability under extreme oxidizing combustion. Mechanistic studies attribute the enhanced oxidation resistance to the synergistic protection of the transition layer and composite coating. This work establishes a design strategy for stabilizing W-Re thermocouples in ultrahigh-temperature oxidative environments, enabling reliable temperature diagnostics in rocket exhaust plumes. (c) 2026 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.

Lunar dust often poses a critical challenge to the durability and safety of spacecraft with its strong adhesion, severe abrasiveness, and high electrostatic charge. The passive preventive strategy of enhancing super-hydrophobic surfaces provides a promising avenue for suppressing dust adhesion. Here, we introduce a graphene (Gr)-enabled surface modification strategy that integrates aluminum-based microstructures with a grapheneperfluorosilane (Gr-PFS) hybrid coating. Gr plays a key role in this process. It weakens the interfacial van der Waals (vdW) force (5.66 nN) through the layered sp2 carbon framework. The ultralow vdW force between layers gives it significant interlayer slip properties, facilitating droplet movement and dust removal. Its thermal and radiation resistance also enhance environmental stability. Compared with uncoated aluminum, the modified surface achieved an ultralow sliding angle (SA) of 0.5 degrees, a high contact angle (CA) of 153.61 degrees, ultralow roughness (0.78 nm), and dust repellency improved by 97.30%. Equally important, the Gr-PFS coating maintains its performance under extreme environments, including proton irradiation, ultraviolet irradiation, and extreme temperatures. This work highlights Gr's unique role in engineering ultralow-adhesion interfaces, offering a robust and efficient dust prevention solution for future spacecraft and lunar exploration equipment.

Flexible strain sensors require a wide strain range and high sensitivity for applications from human joint monitoring to robotic motion detection. Conventional wired systems limit motion, especially in underwater and wearable scenarios. Here, we present an ion-electron synergy-enhanced flexible highly sensitive wireless sensing system (IESS) with wide strain range, in which ionic and electronic conduction synergistically amplify strain-induced resistance changes. By combining multi-walled carbon nanotubes (MWCNTs), ionic liquid, and a gold layer, a three-dimensional porous conductive network forms. Applied strain induces microcracks that interrupt electron pathways while reconfiguring ionic transport channels, enabling high sensitivity over a wide strain range (gauge factor, GF = 1.985 × 104, 100%). The system integrates sensing, power, and wireless communication in a compact platform for multimodal applications. With machine learning, it achieves 93.3% accuracy in phonation recognition and distinguishes diving, ascending, and forward swimming of bionic shark robots, as well as monitors buoy strain underwater. These results demonstrate the advantage of ion-electron synergy in enhancing sensing performance and highlight the system's versatility for bioinspired robotics and wearable health monitoring.

Flexible pressure sensors that mimic human skin are attractive for electronic skin, soft robotics, and healthcare, but it remains difficult to combine ultrahigh sensitivity, wide range, and long-term stability in one device. Here, we present an ultra-sensitive iontronic pressure sensor (USIPS) based on a fingerprint-inspired spiral interpolating electrode, a laser-processed spacer, and a thermoplastic polyurethane (TPU)/graphene/multi-walled carbon nanotube (MWCNT)/ionic-liquid composite layer microstructured into cylindrical protrusions by femtosecond-laser engraving. This architecture amplifies contact mechanics and electric-double-layer modulation, delivering ultrahigh sensitivities of ∼1.92 × 105 kPa-1 (0-110 kPa), ∼6.58 × 104 kPa-1 (110-300 kPa), and ∼1.91 × 104 kPa-1 (300-900 kPa), together with a wide detection range (from ∼577 Pa to 900 kPa), fast response (∼20 ms), and excellent stability under prolonged high-pressure loading. Coupled with a tailored signal-processing and machine-learning pipeline, the USIPS enables quantitative hardness/softness perception and accurate discrimination of representative materials, while also supporting pulse monitoring, robotic grasping, and plantar gait analysis. These results demonstrate a unified iontronic-AI platform for wide-range, high-fidelity tactile sensing and intelligent perception.

ABSTRACT Poly (vinylidene fluoride) (PVDF) and its copolymers have become pivotal materials for piezoelectric tactile sensing in wearable electronics, human–machine interfaces, and electronic skin. This review presents a structured overview linking material fundamentals, device engineering, and data‐driven intelligence. First, we outline PVDF fundamentals, including development history, polymorphism, electroactive properties, and operating principles of PVDF‐based piezoelectric tactile sensors. Second, we review material‐level optimization strategies, covering phase‐engineering routes (mechanical stretching, electrical poling, thermal annealing) and composite, copolymer, interfacial, and core–shell designs, and relate them to β‐phase formation, polarization, dielectric response, and figures of merit (d 33 , g 33 , dielectric loss). Third, we compare device‐level microstructured sensing layers, electrodes, substrates, and multilayer or array architectures in terms of sensitivity–linearity trade‐offs, response dynamics, and directional recognition capability. We then highlight the emerging role of machine learning in phase prediction, process optimization, tactile‐signal classification, and multimodal fusion for robust perception. Finally, we survey representative applications in health monitoring, wearable human–machine interaction, and electronic skin, and summarize key outlooks on scalable fabrication, standardized evaluation, sustainability, neuromorphic tactile computing, and AI‐assisted system design, outlining opportunities for PVDF‐based tactile sensors in intelligent healthcare, bioinspired robotics, and human–machine symbiosis.

Throughout the development of soft robots, shape memory alloy (SMA) actuators have received considerable attention due to their inherent advantages, such as high power-to-weight ratio, low driving voltage, and high response speed. This study presents a lattice-reinforced SMA actuator with improved response speed and increased deformation range. The SMA wires are used to drive the actuator to achieve bending, while the high elastic wire's elasticity is used to achieve recovery. The actuator is cast into a lattice structure with five connection nodes, named Lattice-N5. Lattice-N5's fast response properties are validated through finite element analysis and experiments. Compared with the actuator without lattice structure (nonlattice), lattice-N5's bending deformation increases by up to 390.59% and 204.4% under optimal (voltage of 20 V, duty ratio of 30%, and frequency of 4 Hz) and practical (voltage of 20 V, duty ratio of 20% and frequency of 1 Hz) conditions, respectively, while reaching a stable state more rapidly under a periodic actuation. Therefore, the lattice-reinforced actuator exhibits robust actuation capabilities and improved response frequencies and thus can be employed in a biomimetic jellyfish robot for underwater monitoring and detection by combining a flexible pressure sensor. Moreover, the jellyfish robot with Lattice-N5 actuators exhibits a speed improvement of 111% under the optimal condition (duty ratio of 20% and frequency of 4 Hz) and 55% under the practical condition (voltage of 20 V, duty ratio of 20% and frequency of 1 Hz) compared with the robot with the nonlattice. This study provides a simple and effective design scheme for improving the performance of SMA actuators and prompting the development of underwater soft robots.

With the widespread application of lithium batteries in electric vehicles and energy storage systems, battery-related safety and reliability issues have become increasingly prominent. Conventional monitoring methods often struggle to address dynamic changes under complex operando. In recent years, flexible sensing technology has emerged as a promising solution for battery health monitoring due to its high adaptability and conformability to complex structures. Meanwhile, empowered by artificial intelligence (AI) for data analysis, the collected data enables efficient and accurate state assessment, offering robust support for accident prevention. Against this background, this paper first explores the integrated applications of flexible sensors in battery health monitoring and their unique advantages in addressing complex battery operating conditions, while analyzing the potential of AI in battery state analysis. Subsequently, it systematically reviews mainstream flexible sensing technologies (e.g., film sensors, thermocouples, and optical fiber sensors), elucidating their mechanisms for revealing intricate internal battery processes during operation. Finally, the paper discusses AI’s role in enhancing monitoring efficiency and accuracy, and envisions future research directions and application prospects. This work aims to provide technical references for the battery health monitoring field as well as promote the application of flexible sensing technologies in improving battery system safety and reliability.

Correction for 'An ultra-sensitive iontronic pressure sensor with femtosecond-laser-engraved microstructures for machine-learning-based tactile sensing' by Yihui Lan et al., Nanoscale, 2026, 18, 5242-5254, https://doi.org/10.1039/d5nr05111h.

Flexible pressure sensors have become pivotal in the advancement of wearable electronics and underwater monitoring, particularly when augmented by artificial intelligence. Nevertheless, the development of a unified sensing platform capable of seamless operation in both health monitoring and underwater communication remains a significant challenge. To address this issue, a highly sensitive flexible iontronic pressure sensor featuring a micro-pyramidal architecture was developed. The device is fabricated using molding involving a bespoke composite ink comprising carbon nanotubes (CNTs) and ionic liquid as the sensing layer. This layer is then sandwiched between screen-printed silver electrodes. The sensor demonstrated exceptional performance metrics, including high sensitivity (370 kPa−1), rapid response and recovery times (20 ms), and outstanding reliability (about 20000 cycles). In the domain of wearable health monitoring, the sensor demonstrated its capacity to discern faint human pulse signals, facilitating the acquisition of high-fidelity pulse waveforms. Concurrently, within the domain of underwater intelligent communication, the sensor was used to detect Morse code signals, which were then accurately classified by a deep learning algorithm. This work not only validates the sensor’s high performance but also demonstrates its dual functionality, seamlessly connecting human healthcare with intelligent underwater interaction and significantly broadening the scope of flexible sensing applications.

This study introduces a dual-resonator quartz pressure sensor employing a novel stress redistribution mechanism with orthogonal force beams. Utilizing the anisotropy of AT-cut quartz, the design integrates X- and Z-resonators with force paths parallel and perpendicular to the X-axis, respectively. This configuration induces opposite pressure sensitivities, yielding a high-gain differential output. Finite element analysis guided the geometric optimization for maximum sensitivity and robustness. The fabricated device achieves a record differential sensitivity of 378.72 Hz/MPa at 25 degrees C, increasing to 413.84 Hz/MPa at 80 degrees C over 0-10 MPa. This positive temperature coefficient of sensitivity, combined with excellent linearity, low hysteresis (<0.18% FS), and high thermal stability, underscores its potential for demanding applications like downhole monitoring, advancing resonant sensor design through strategic mechanical engineering.

The cilium avoids energy loss due to bending deformation during vibration, thereby efficiently transmitting the acoustic driving force to the cross-beam. Meanwhile, a hollow cylindrical structure is adopted instead of the traditional solid one. While maintaining the same external geometry, this hollow design not only increases the effective acoustic area to enhance the acoustic driving force but also reduces the added mass of the cilium. This material–structure synergistic optimization improves the acoustic-to-mechanical transfer efficiency of the cilium in low-frequency acoustic fields, thus enhancing the device’s acoustic sensitivity in the low-frequency range. Parametric simulations are conducted using the COMSOL Multiphysics 6.3 platform to systematically optimize key geometric parameters such as the outer radius and height of the quartz cilium, and the optimal dimensions are determined. The sensitivity and directivity of the prototype are measured in the 20–1000 Hz frequency range using the standard hydrophone comparison method. Experimental results show that the quartz cilium vector hydrophone achieves a sensitivity of –179.1 dB (1 kHz, 0 dB = 1 V/μPa) at 1000 Hz. The frequency response curve exhibits good flatness in the low-frequency range and agrees well with the theoretical 6 dB per octave increase characteristic of pressure gradient sensors. Directivity tests reveal a typical figure-8 pattern at both 315 Hz and 630 Hz, with null depths exceeding 30 dB, demonstrating excellent vector detection capability. This study provides an effective approach for improving the low-frequency sensitivity of MEMS (Micro-Electromechanical System) vector hydrophones, and the designed device meets the requirements for underwater target detection with promising prospects for engineering applications.

Flexible sensors have garnered significant interest for applications in wearable electronics and aerospace monitoring. However, achieving highly sensitive and stable multi-parameter sensing on a single platform remains a key challenge due to material integration complexity and signal decoupling. In this study, we present a flexible ion-electronic wireless pressure-temperature sensor (IEPTS) capable of simultaneously detecting pressure and temperature with high performance. The sensor features a broad pressure sensing range (0–150 kPa) and high sensitivity (931.46 kPa−1), enabled by a carbon nanotube-based ionic network that forms an ion-electron co-conduction pathway. It also provides accurate temperature sensing over a wide range (10°C–94°C) with excellent linearity (up to 99.8

Sea surface temperature plays a crucial role in the exchange of heat, gases, and materials between the ocean and atmosphere, profoundly influencing global climate, marine ecosystems, and atmospheric circulation. However, temperature variations at the air-sea interface are rapid and highly unstable, being affected by multiple dynamic factors, posing significant challenges for real-time monitoring. In this work, a rapid-response flexible temperature sensor was developed using polyimide film as the substrate. Based on the thermal expansion mechanism and finite element analysis, the optimal sensor structure and material composition were determined. The sensor was fabricated via screen-printing technology, employing a acrylic copolymer and polydimethylsiloxane (PDMS) as the composite matrix, with carbon black and nickel serving as conductive fillers. A PDMS encapsulation layer was applied to enhance waterproofing performance. Within the temperature range of 0-35 degrees C, the sensor exhibited a high temperature coefficient of resistance of 4.82%/degrees C, an excellent temperature resolution of 0.05 degrees C, an ultrafast response time of 40 ms, outstanding thermal stability over more than 500 heating-cooling cycles, and strong insensitivity to external stimuli such as bending, humidity, and pressure. When integrated into a marine buoy system for testing, the sensor accurately detected temperature fluctuations, demonstrating great potential for temperature monitoring at the air-sea interface.

Dual-mode sensors with ultrahigh sensitivity, wide detection range, linearity, and stable temperature response are highly desirable for monitoring in extreme environments. Here, we report a temperature-pressure dual-mode sensor that leverages a synergistic enhancement mechanism, combining the ion pump effect of hexagonal boron nitride (h-BN) with the strain-regulated conductive pathways of few-layer graphene (FLG) to boost sensitivity. The high rigidity of h-BN and the stress-dispersing role of FLG ensure mechanical stability under high load, withstanding 11200 and 6000 cycles at 1 and 6 MPa, respectively. As a result, the device achieves a record-high sensitivity of 4771.2 kPa-1 with a detection limit up to 10 MPa. Meanwhile, the platinum serpentine electrode temperature sensor fabricated via magnetron sputtering exhibits highly linear (R2 = 0.9993) and stable response characteristics within the temperature range of -20 to 140 °C after annealing treatment, with negligible pressure interference. This sensor is successfully applied to monitor lithium-ion battery expansion and deep-sea waves, capturing high-quality time-resistance-temperature sensing data. To further validate the sensor's data utility and achieve precise prediction of battery thermal behavior, we constructed a deep learning model based on the Informer architecture. This model enables high-precision short-time temperature prediction (MAE = 4.2 °C, range accuracy = 97.36%) using the sensor-acquired data, ultimately proving the scalability of this dual-mode sensing platform in high-performance multimodal sensing under extreme conditions.

Quartz and langasite(LGS) stand as core piezoelectric materials for high-performance sensors, owing to their exceptional mechanical stability, prominent piezoelectric response, and superior adaptability to extreme operating conditions. With the growing demand for precise parameter monitoring in harsh scenarios including deep oil/gas wells, deep-sea exploration, nuclear engineering, and aerospace systems-quartz/LGS sensors have been extensively investigated for their ability to withstand temperatures up to 1200°C, pressures exceeding 100 MPa, and deliver high-precision measurement. This paper provides a comprehensive and systematic review of the multi-mode operating mechanisms of quartz/LGS sensors, covering resonant modes(thickness shear mode, double-ended tuning fork mode), surface acoustic wave(SAW) mode, bulk acoustic wave(BAW) mode, and dual-mode synergistic mechanisms. Key adaptation technologies for extreme environments are elaborated, including high-temperature material selection, high-pressure structural reinforcement, temperature/pressure compensation algorithms, and high-reliability packaging. Typical application scenarios and engineering deployment schemes are analyzed in detail for oil/gas exploration, deep-sea research, nuclear industry, and high-temperature manufacturing. Finally, current research bottlenecks are summarized, and future trends are proposed, including material innovation, mechanism breakthroughs, technology integration, and application expansion. This review offers a complete theoretical foundation and technical reference for the upgrading and industrialization of extreme-environment sensing technology.

An all-fiber dual-parameter pressure-temperature sensor with enhanced contrast and sensitivity is proposed, fabricated, and experimentally validated for gas monitoring in high-temperature environments. The sensing structure combines a Fabry-P & eacute;rot interferometer (FPI) for pressure detection and a fiber Bragg grating (FBG) for temperature measurement. A collimation-enhancement mechanism, based on the self-focusing effect of the graded-index fiber, is employed to improve signal contrast. The diaphragm-based closed-end FPI cavity is fabricated using precision mechanical cutting and arc discharge techniques. To further enhance the pressure sensitivity, the fiber end-face is treated using mechanical grinding followed by femtosecond laser roughening. The sensor's performance was evaluated at ambient conditions and under extreme conditions of 700(degrees )C and 5 MPa. At 700 C-degrees , the sensor exhibits a temperature sensitivity of 11.61 pm/degrees C and a pressure sensitivity of 46.96 nm/MPa. The full-temperature drift of the pressure sensitivity is less than 3 nm/MPa, with a maximum full-scale error of 2.95%. Owing to its high mechanical robustness and sensitivity, the proposed sensor is well suited for simultaneous gas temperature and pressure monitoring in harsh, high-temperature environments.

Sensitivity is one of the most important indicators for the high-temperature thin-film strain gauges (TFSGs), which is meaningful for the microstrain monitoring and its testing accuracy. Indium Tin Oxide (ITO) thin films have been widely used for the preparation of the TFSGs due to its excellent piezoresistivity and high melting point at elevated temperatures. However, the sensitivity of the ITO TFSGs needs to be further improved at elevated temperatures. In this work, we investigate the enhancement of the sensitivity of ITO thin films at high temperatures by controlling the conductivity via changing their thickness (3.4-10.8 mu m). The microstructure and electrical properties of the ITO thin films with various thickness were studied. Results show that the intensity of the (222) peak gradually weakened and the (400) peak progressively increased with the growth of film thickness. The influence of the crystal phase transition on the chemical state of the ITO thin films were investigated. The concentration of the oxygen vacancies and Sn4+ increased with the transition of the crystal phase in the ITO thin films. In consequence, the carrier concentration of the ITO thin films increased by 197 % with the growth of film thickness. Notably, the sensitivity of the ITO TFSGs can reach up to 27.77, which enhanced by over an order of magnitude at high temperatures. Eventually, 8.9 mu m ITO TFSG was determined to be the optimal thickness, which also exhibited excellent piezoresistive stability at 1200 degrees C.

Total hip replacement (THR) surgery has achieved significant success in alleviating pain from hip joint diseases and improving patients' quality of life. However, the challenge of precisely placing the acetabular implant during surgery can lead to complications, such as early loosening and wear of the implant. Traditionally, this critical step relies on the surgeon's experience and subjective judgment, lacking objective tools to monitor the pressure field within the acetabulum in real-time. This study presents the development of a highly sensitive micropyramid flexible sensor array, fabricated using microfine photolithography precision molding technology, for assisting pressure field monitoring in the acetabulum during THR. The compression of the pyramid microstructure results in large changes in contact area, allowing our single sensor to exhibit an ultrahigh sensitivity of 11 711.95 kPa(-1) within the 0-90-kPa pressure range, with a response/recovery time of 120/81 ms. Six independent sensors were integrated into a customized acetabular implant model, enabling the collection of pressure field data from the acetabulum. To simulate the surgical process, we modified the test platform, developed corresponding signal acquisition circuits, and a software system for real-time visualization of pressure distribution in the acetabulum, demonstrating the potential application of this system in assisting surgeons in precisely placing implants during THR surgery.

Abstract Flexible multidimensional force sensors (FWFS) have become key components in the new generation of wearable electronics, human–machine interfaces, soft robotics, and intelligent health monitoring systems. Compared with traditional uniaxial force sensors, flexible multidimensional sensors offer enhanced directional recognition capabilities, enabling real‐time detection of complex force signals—including normal, shear, and torsional forces—on nonplanar surfaces. This review summarizes recent research progress in FWFS, covering structural design strategies, performance comparisons across sensing mechanisms, and representative applications. Furthermore, it explores the role of artificial intelligence (AI) in enhancing sensor performance. First, we review development trends and typical applications of multidimensional force sensing, with particular focus on structural strategies for direction recognition and signal decoupling, such as bio‐inspired configurations and decoupled designs. Next, key performance parameters—including sensitivity, linearity, response speed, and long‐term stability—are discussed. Finally, the review highlights recent advances in applying flexible multidimensional sensors in health monitoring, human–machine interaction, and robotic tactile perception, with emphasis on AI‐enhanced systems and their advantages. Looking ahead, flexible multidimensional force sensing technologies are expected to evolve toward intelligent perception, self‐powered operation, and deep integration with machine learning, offering new pathways for the development of smart, integrated sensing platforms.

The rapid development of flexible sensor technology has made flexible sensor arrays a key research area in various applications due to their exceptional flexibility, wearability, and large-area-sensing capabilities. These arrays can precisely monitor physical parameters like pressure and strain in complex environments, making them highly beneficial for sectors such as smart wearables, robotic tactile sensing, health monitoring, and flexible electronics. This paper reviews the fabrication processes, operational principles, and common materials used in flexible sensors, explores the application of different materials, and outlines two conventional preparation methods. It also presents real-world examples of large-area pressure and strain sensor arrays. Fabrication techniques include 3D printing, screen printing, laser etching, magnetron sputtering, and molding, each influencing sensor performance in different ways. Flexible sensors typically operate based on resistive and capacitive mechanisms, with their structural designs (e.g., sandwich and fork-finger) affecting integration, recovery, and processing complexity. The careful selection of materials—especially substrates, electrodes, and sensing materials—is crucial for sensor efficacy. Despite significant progress in design and application, challenges remain, particularly in mass production, wireless integration, real-time data processing, and long-term stability. To improve mass production feasibility, optimizing fabrication processes, reducing material costs, and incorporating automated production lines are essential for scalability and defect reduction. For wireless integration, enhancing energy efficiency through low-power communication protocols and addressing signal interference and stability are critical for seamless operation. Real-time data processing requires innovative solutions such as edge computing and machine learning algorithms, ensuring low-latency, high-accuracy data interpretation while preserving the flexibility of sensor arrays. Finally, ensuring long-term stability and environmental adaptability demands new materials and protective coatings to withstand harsh conditions. Ongoing research and development are crucial to overcoming these challenges, ensuring that flexible sensor arrays meet the needs of diverse applications while remaining cost-effective and reliable.