Search Results (221)

Flexible pressure sensors serve as core sensing components for wearable health monitoring systems, electronic skins for soft robots, and flexible human–machine interaction devices. Benefiting from the interfacial electric double-layer polarization effect, iontronic sensing delivers far higher pressure response sensitivity than conventional parallel-plate capacitive sensors, endowing it with distinctive advantages in the detection of weak physiological signals. Nevertheless, current dense ionic thin-film dielectric layers suffer from limited deformation space under compression and poor low-pressure sensing capability. Mainstream high-precision micropillar arrays are fabricated via photolithography, 3D printing, and metal etching molds, which require costly equipment and complicated fabrication procedures, making large-area mass production unfeasible. Random frosted concave-convex microstructures feature disordered dimensions, leading to severe device hysteresis and narrow linear ranges, which fail to achieve ultrahigh sensitivity alongside a wide pressure detection range simultaneously. To address the aforementioned multiple bottlenecks, this paper proposes a low-cost resin template replication process to fabricate TPU-based ionic thin-film dielectric layers with ordered micropillar array microstructures. Combined with inkjet-printed silver conductive PI flexible electrodes, an iontronic flexible pressure sensor with a sandwich layered structure is constructed. Multi-dimensional investigations including microscopic morphology characterization, electromechanical sensing performance calibration, and human wearable application tests are systematically implemented to thoroughly elucidate the synergistic enhancement mechanism of the arrayed micropillars. Test results demonstrate that the effective pressure detection range of the sensor spans 0–1038 kPa, accommodating ultra-low pressures such as pulse signals as well as medium-to-high-pressure loads including joint bending. The sensitivity reaches 23.27 kPa⁻¹ within the low-pressure range of 0–200 kPa and remains stable at 3.52 kPa⁻¹ in the high-pressure range of 200–1038 kPa, with piecewise linear fitting correlation coefficients of 0.93 and 0.96 respectively. Both the response time and recovery time of the device are 40 ms, and the hysteresis error throughout the loading-unloading cycle is merely 2.62%. After 20,000 consecutive cyclic loading-unloading tests, the peak capacitance output only decays by 5.1%, verifying outstanding mechanical fatigue resistance and electrical stability. Validations in multi-scenario applications prove that the sensor can accurately capture human physiological and motion signals including radial artery pulses, laryngeal deformation induced by multi-syllable vocalization, and multi-angle bending of fingers and elbow joints, suitable for home-based health monitoring, quantitative rehabilitation training, flexible tactile interaction and other scenarios. The entire fabrication process eliminates high-precision micro-nano processing equipment such as photolithography systems, plasma etchers and 3D printers; only general chemical raw materials and conventional laboratory instruments are adopted. The reusable templates enable low manufacturing costs and large-area coating forming, offering a novel low-cost technical solution for the engineering implementation and industrialization of high-performance iontronic flexible pressure sensors. Full article

Main memory carries data outside the processor’s trust boundary, so commodity systems-on-chip (SoCs) increasingly encrypt it; yet, in-line memory encryption engine itself becomes a differential power analysis (DPA) target whose key, if recovered, unlocks all of dynamic random-access memory (DRAM). We present PACE, a page-adaptive, cache-anchored memory encryption engine for RISC-V that makes nth-order DPA resistance practical and keeps cryptographic latency off the cache eviction critical path. PACE inserts a TileLink adapter between the last-level cache and the memory port and applies, per physical page, one of four policies (plaintext/confidentiality/confidentiality+integrity/+masking-order-d) selected from RISC-V page table bits through a memory-mapped control plane. Confidentiality uses counter mode whose per-line keystream is precomputed during cache residency; integrity is tree-free at the embedded operating point via on-chip counters and tags, with a live split counter block-MAC Bonsai Merkle tree for scale-out. DPA resistance is layered: ISAP-style fresh re-keying caps the data complexity per key at $q\approx 1$, and domain-oriented masking (DOM, d + 1 shares) protects the sole key processing block to order d. We implement PACE in Chisel on a Rocket SoC (Chipyard) and evaluate it with open-source tooling. A deterministic TileLink-level harness proves ciphertext-in-memory and detects tamper/replay/splice, and the live Tier-B engine (DRAM counters and per-line message authentication codes (MACs) plus an on-chip-rooted block-MAC tree) is validated from end to end on full Rocket and BOOM SoCs and on the FPGA; the masked Ascon-p S-box is proven order-d secure (d = 1, 2) under a glitch- and transition-aware model by three independent formal tools (COCO, PROLEAD, and SILVER, the last also deciding the full composability lattice and confirming exact glitch-robust order-2 probing security), with COCO extending the exact verdict to the highest synthesized order d = 3 (secure at probing orders 1–3); a simulated trace correlation power analysis (CPA) recovers the full key from an unprotected core and is defeated by masking, with a mutual information analysis confirming the $N\propto {\sigma }^{2(d+1)}$ trace amplification law. We further realize PACE on field-programmable gate array (FPGA) silicon: the engine plus an on-chip ring oscillator power sensor is placed, routed, timing-closed at 100 MHz, and programmed on a Xilinx XC7Z020, and we drive a fixed-vs-random Test Vector Leakage Assessment (TVLA) campaign read back entirely over a JTAG (Joint Test Action Group). A multi-core configuration and a Linux control-plane driver are likewise validated. Across synthetic access patterns and named application kernels (AES, SHA-256, matrix multiplication, pointer chasing) on both in-order Rocket and out-of-order BOOM, application-level overhead is within measurement noise of plaintext for cache resident workloads (masking, in particular, is cycle-identical to plain confidentiality), and we characterize the cost of each policy, masking order, and re-keying interval, demonstrating side-channel-hardened memory encryption on open RISC-V hardware. Full article

Large-scale physical model experiments play a critical role in understanding the coupled thermo–hydro-mechanical responses during hydrate dissociation. In this study, a specially designed large-scale physical simulation apparatus (effective volume: 1178 L) was employed to investigate the depressurization-induced dissociation behavior of CO₂ hydrate, which was used as a model system to simulate the macroscopic response of hydrate-bearing sediments under controlled laboratory conditions. Key reservoir parameters—including temperature, pressure, electrical resistivity, gas production rate, and stratum displacement—were continuously monitored using an integrated array of temperature sensors, pressure transducers, electrical resistivity probes, and displacement meters. During depressurization, the system pressure decreased from 3 MPa to 1 MPa (matching the backpressure), while the internal temperature dropped from 3.5 °C to approximately 1 °C due to the endothermic dissociation of the hydrate. Gas production exhibited a three-stage evolution: an initial slow release, a rapid increase as the dissociation front propagated through the sediment, and a plateau upon completion of hydrate dissociation. Based on the measured gas production and CO₂ consumption, the hydrate saturation was estimated to be approximately 0.248. The dissociation process led to measurable sediment settlement, with a maximum vertical displacement of 88.3 mm (approximately 5.88% of the model height). Analysis of the evolution of effective stress indicates that depressurization reduced pore pressure and increased vertical effective stress by approximately 0.55 MPa, while hydrate dissociation weakened the sediment skeleton, jointly causing settlement. This study demonstrates the feasibility of using a large-scale apparatus to capture the coupled processes during hydrate dissociation. It provides benchmark experimental data for validating numerical models of hydrate-bearing sediment behavior. Further validation is required before these results can be extrapolated to CH₄ hydrate systems. Full article

Transimpedance amplifiers (TIAs) are the critical components for current-to-voltage interfaces in optical receivers, LiDAR front-ends, biomedical sensors, and unconventional applications such as magnetic-resonance receiver-coil arrays and wide-bandgap ultraviolet detectors, and their CMOS design is governed by a fundamental gain-bandwidth-noise trade-off whose structure is rarely made explicit. This review introduces a unifying framework rooted in three explicit assumptions underlying the classical shunt-feedback TIA limit: a single-pole core amplifier (A1), a resistive feedback element (A2), and the full input capacitance loading the feedback summing node (A3). Relaxing one or more of these assumptions is shown to be the common structural thread behind every class of bandwidth or noise enhancement in the recent literature, and all surveyed architectures are organized into a six-tier taxonomy, from Tier 0 designs operating within the classical limit to Tier 5 topologies that bypass all three assumptions simultaneously. This taxonomy is supplemented by an orthogonal configurability axis spanning single- and dual-control reconfigurable, variable-gain, and dynamic-range-extension designs. We further show that stability is not removed by these relaxations but migrates with the tier, from the global phase margin of the classical loop to a local regulating loop, a group-delay-flatness constraint, an input-passivity condition, or a multi-loop interaction, so that each architecture carries a predictable stability locus. The taxonomy is cross-referenced with application domains and closed-form noise-floor boundary plots parametrized by input capacitance and amplifier gain-bandwidth product, and with the CMOS technology landscape, where we argue that the most advanced node is not universally optimal and that node and topology act as complementary rather than competing levers. A single consistent figure of merit, applied uniformly to a representative set of CMOS realizations from 0.6 $\mathsf{\mu }$m to 16 nm FinFET, shows no monotonic improvement with publication year or node and is presented as a diagnostic indicator rather than an absolute ranking. The review closes with an outlook on 200 Gb/s/lane links, wide-bandgap sensor integration, and the FinFET-to-gate-all-around device transition. Full article

Traditional crack monitoring methods, relying on discrete point sensors, cannot capture the full spatiotemporal evolution of cracks. To address this limitation, this paper presents a distributed online monitoring approach using ultra-weak Fiber Bragg Grating (UWFBG) array sensing technology. A 16 m full-scale π-beam was instrumented with a grating array strain sensing system and tested under progressive mid-span loading until failure. The array successfully detected crack initiation at 848.7 kN (0.9P1) and tracked the transformation from L-shaped to U-shaped cracks, yielding a final crack count of 90 with a maximum width of 1.21 mm and length of 246.5 cm at 1791.7 kN. The strain–load curves exhibited a clear linear-to-nonlinear transition and continuous slope increase, closely matching manual observations. Quantitative correlation analysis further established a strong linear relationship between UWFBG peak strains and manually measured crack widths, with the fitting equation $\mathsf{\epsilon }=7918·\mathrm{w}-110$ and a coefficient of determination R² = 0.971, providing a specimen-specific basis for strain-based crack severity estimation that requires in-situ calibration before field application. The UWFBG array maintained stable signal acquisition throughout the entire loading process, offering superior data continuity and measurement range compared to resistive strain gauges, which suffered progressive data loss after cracking. The results demonstrate that the proposed method can provide real-time, full-field strain mapping and quantitative crack evolution monitoring, offering a powerful tool for bridge health assessment. Full article

Large sensor arrays are an increasingly popular sampling method among ecologists. To last in the field, sensor housing needs to be resistant to damage from both weather and animals. The popular AudioMoth acoustic recorder does not have integral weather-resistant housing and is deployed by users in a wide variety of protective cases. One inexpensive way to protect AudioMoths is to deploy them in plastic bags, which offer moderate weather resistance but are susceptible to chewing damage from small mammals. In this study, we test the effectiveness of commercially available mammal deterrents in preventing such chewing damage. We deployed 115 treatment-control pairs across two grids in temperate forests in Pennsylvania. Bag treatments consisted of Liquid Fence, Bonide, and a cayenne and Vaseline mixture. For all deterrents, there was no statistically significant difference in the proportion or severity of mammal chewing damage between treatments and controls. Counter to expectations, for all three treatments, more of the bags treated with a deterrent were damaged by mammal chewing than the paired control bags. Our results strongly suggest that single applications of these three deterrents have no useful effect on preventing mammal chewing damage to sensor housing in the field. Full article

Exhaled breath analysis has emerged as a promising non-invasive approach for disease diagnosis, leveraging gas sensors for their high sensitivity, portability, and real-time monitoring capabilities. Two-dimensional nanomaterials, such as graphene, transition metal dichalcogenides (TMDs), MXenes, black phosphorus, and metal–organic frameworks (MOFs), exhibit exceptional gas-sensing properties due to their atomic-scale thickness, ultra-large specific surface area, and tunable electronic structures. These characteristics enable enhanced gas adsorption and room-temperature operation, making them ideal for detecting ppb-level biomarkers like acetone, ammonia, and nitric oxide in breath. However, sensors based on pristine 2D materials face challenges including slow response/recovery kinetics, poor stability, weak humidity resistance, and limited selectivity in complex breath environments. To address these limitations, functionalization strategies have been developed to engineer material properties. Key approaches include heteroatom doping to modulate electronic band structures, heterojunction construction to facilitate charge transfer and improve selectivity, and noble metal decoration for catalytic enhancement of gas adsorption. Additionally, light irradiation has been employed to regulate the carrier concentration on the surface of sensitive materials. These strategies significantly boost sensor performance, achieving ppb-level detection limits, robust humidity resistance, and rapid response. Future directions involve integrating functionalized 2D materials into wearable, multiplexed sensor arrays for simultaneous biomarker detection, coupled with machine learning for real-time diagnostic platforms. Full article

Precise control of the water-to-cement (w/c) ratio is critical in three-dimensional concrete printing (3DCP), for which minor deviations compromise extrudability, buildability, and structural integrity. Existing non-destructive w/c (moisture) sensors have not been validated for real-time, in situ monitoring during the concrete extrusion process. This study develops and validates a four-electrode Wenner-array probe, interfaced with an LCR meter, for in situ electrical resistance measurements of fresh concrete. The system was calibrated against NaCl and KCl electrolytic solutions at resistivities of 1, 5, and 10 Ω·m and then tested on ordinary Portland cement pastes at w/c ratios of 0.40–0.60 and on a proprietary 3D-printable blend at 0.40–0.65. The results show that resistance drift remained below 1.2% under ambient temperature fluctuations, with sub-second response times. Strong nonlinear correlations (R² > 0.99) were established between electrical resistance and w/c ratio for both formulations, with resistance increasing with higher w/c ratios due to ionic dilution and decreasing over time as early-age hydration progressed. Proprietary mixtures below w/c = 0.51 exhibited insufficient pore connectivity (CV > 30%) for reliable measurement, whereas mixtures at w/c ≥ 0.51 demonstrated excellent repeatability (CV < 2.80%). Electrical resistance measurement provides a viable real-time technique for w/c determination in fresh concrete, enabling automated closed-loop control in 3DCP operations. Full article

High-entropy alloys (HEAs), composed of five or more principal elements in near-equimolar ratios, have emerged as a groundbreaking class of materials for next-generation flexible electronics. This review systematically examines the unique potential of HEAs as sensing materials, moving beyond their traditional role as structural components. We first elucidate the fundamental mechanisms—core effects including lattice distortion, sluggish diffusion, and the cocktail effect—that endow HEAs with an exceptional synergy of high strength, good ductility, tunable electrical resistivity, and superior electrocatalytic activity. Subsequently, we critically analyze the state-of-the-art strategies for processing HEA-based micro/nano structures, including mechanical alloying, wet-chemical synthesis, and non-equilibrium deposition techniques, with an emphasis on their compatibility with flexible substrates. The core of the review categorizes and discusses the latest advances in HEA-based flexible sensors for strain/stress, gas, and electrochemical (e.g., glucose, biomarkers, heavy metals) detection, highlighting the structure–property–performance relationships. Representative studies have demonstrated that HEA flexible strain sensors achieve a temperature coefficient of resistance as low as 45.59 ppm/K with no signal drift over 6000 stretching cycles; room-temperature hydrogen sensors reach a detection limit down to 31 ppb with a response time of 19 s; and non-enzymatic glucose sensors deliver a sensitivity up to 3043 μA·mM⁻¹·cm⁻². Finally, we summarize the key challenges—such as manufacturing scalability, long-term stability under dynamic deformation, and cost-effectiveness—and provide a forward-looking perspective on promising research directions, including high-throughput compositional screening, multi-functional sensor arrays, and the integration of machine learning for rational material design. Full article

Black tea quality is governed by aroma chemistry: terpene alcohols (linalool, geraniol, nerolidol), methyl salicylate, and short-chain aldehydes whose abundance and release kinetics from the polyphenol-rich leaf matrix shape perceived grade. Grade information lies not only in the average headspace concentration but in the temporal shape of volatile organic compound (VOC) release under controlled heating. Conventional electronic noses obscure this signal: they rely on multi-sensor arrays, compress each response into summary statistics, and report accuracy only at the level of individual measurements. Whether a single low-cost metal–oxide–semiconductor (MOS) gas sensor can recover grade-defining aroma chemistry, and whether waveform-level modeling can exploit it, was therefore investigated. A portable electronic nose built around a Bosch BME688 sensor recorded 90 time series, each comprising four directly measured channels (temperature, humidity, pressure, gas sensor resistance) and a derived indoor-air-quality (IAQ) proxy computed from them by the on-chip BSEC library, from 16 commercial Turkish black teas across three quality grades. Two representations were compared on the same data: a feature-based pipeline reducing 25 statistical descriptors to seven principal components for six classifiers (best F1-macro = 0.624, MLP), and a raw-waveform Multi-Scale 1D-CNN with Squeeze–Excitation and temporal self-attention (MS-CNN-Attention). Under product-grouped cross-validation, the deep model reached F1-macro = 0.811 (+30%) and graded 14 of 16 products correctly by majority vote, against 11 of 16 for the MLP, with the largest gain in the medium grade (F1: 0.52 → 0.79), where summary-statistic compression destroys the release-kinetic signal. The contributions are threefold: one programmable MOS sensor operated as a thermal-desorption profiler rather than a sensor array; a direct comparison of feature-based classical learning against raw-waveform deep learning on the same small, non-normally distributed dataset; and a product-level decision-consistency metric suited to batch screening. Pairing a low-cost MOS sensor with waveform-level modeling offers a rapid, non-destructive route to aroma-chemistry-based tea quality screening. Full article

With the growing security requirements of sensor nodes in Internet of Things (IoT) systems, conventional silicon-circuit-based physical unclonable functions (PUFs) still face limitations in circuit overhead, design complexity, and system integration. To address these challenges, this paper proposes a lightweight gas sensor PUF (GS-PUF) design based on a Ni-doped SnO₂ nanoscale gas sensor array. The proposed method exploits both the unavoidable process randomness introduced during sensor fabrication and the device-to-device electrical response variations induced by gas–material interactions as entropy sources, thereby enabling high-quality PUF response generation. At the device level, Ni-SnO₂ nanomaterials are prepared by electrostatic spray deposition (ESD), and an indirectly heated gas sensor array is constructed to enhance the sensitivity and stability of the sensing response. At the algorithmic level, a random resistance balancing algorithm based on multi-sensor combinational comparison is proposed. By randomly comparing the summed resistances of multiple sensor clusters, a 128-bit multi-bit PUF response is generated, while the uniformity and independence of the output bits are effectively improved. Experimental results demonstrate that the proposed GS-PUF exhibits excellent randomness, uniqueness, and reliability: the information entropy of the PUF responses is greater than 0.99, approaching the ideal value; the probabilities of output bits “1” and “0” are 0.4988 and 0.5012, respectively, indicating a well-balanced distribution; the inter-device uniqueness reaches 49.8%, close to the ideal value of 50%; all items in the NIST randomness test suite are passed, with all p-values exceeding 0.01 and the minimum p-value being 0.0368, confirming a high level of statistical randomness confidence. In addition, long-term measurements under fixed laboratory conditions show that the PUF response reliability remains above 96%. Compared with other sensor-based PUFs, the proposed method provides a lightweight sensing-security integration approach for IoT sensor nodes by reusing intrinsic gas-sensor response variations and avoiding an additional dedicated silicon PUF circuit. Full article

Environmental pollution constitutes an increasingly complex global challenge, largely driven by industrial expansion and the consequent release of toxic species such as Cd²⁺, Pb²⁺, Cu²⁺, Hg²⁺, Fe³⁺, As³⁺, and Rh³⁺ into natural ecosystems. These contaminants pose significant risks to environmental integrity and public health, motivating the development of analytical technologies capable of sensitive, selective, and reliable detection. In this context, graphene-based electrochemical sensors have emerged as versatile platforms for monitoring a broad range of analytes, particularly in environmental applications involving heavy-metal detection. The intrinsic physicochemical properties of graphene derivatives have enabled low detection limits, rapid response times, and tunable selectivity. Despite analytical advances, critical challenges persist regarding operational stability in complex matrices, inter-batch reproducibility, and robustness to interfering species, which continue to hinder large-scale deployment and real-world applicability. However, challenges remain regarding stability and performance in complex arrays, reproducibility, and resistance to interference, necessitating innovative strategies for functionalization and molecular recognition. This review article establishes a comparative framework based on functionalization strategies (covalent, non-covalent, and hybrid), the chemical nature of graphene (GO, rGO, and doping), and various types of polymers (conductors and insulators), using statistical metrics such as the limit of detection (LOD), linear range, working potential, stability, and interferences, employing a bibliometric analysis using the PRISMA 2020 methodology. This comparative framework enables analysis and explanation of performance trends, and the generation of design and functionalization recommendations for versatile applications, including criteria for reproducibility and sustainability. Full article

To address the demand for underwater acoustic detection with hydrostatic pressure resistance, this paper proposes a fiber-optic Fabry–Perot (F-P) underwater acoustic sensor based on micro-electromechanical system (MEMS) technology. According to the F-P interference principle, the diaphragm deforms under acoustic pressure, inducing variations in the F-P cavity length which modulate the interference spectrum and enable the measurement of underwater acoustic signals. A sensing diaphragm with a composite structure consisting of a central boss and a micro-hole array is designed, which improves the optical signal quality while reducing the influence of the pressure difference between the inner and outer surfaces of the diaphragm on sensor operation. MEMS fabrication, computer numerical control (CNC) machining, and laser fusion splicing technologies are employed to achieve batch fabrication of the sensing units and adhesive-free integration of the sensor. Experimental results show that the proposed sensor exhibits a flat frequency response within ±1.5 dB over the range of 1 kHz to 10 kHz, with an average signal-to-noise ratio (SNR) of 86.35 dB. The sensitivity reaches −181.79 dB re 1 rad/μPa at 10 kHz, with a maximum nonlinearity of 0.48% F.S., a repeatability error of 0.15% F.S. and a dynamic range of 100.83 dB. The proposed sensor features miniaturization, high consistency, hydrostatic pressure self-balancing capability, and immunity to electromagnetic interference, providing a solid foundation for hydrostatic-pressure-resistant underwater acoustic measurements in deep-sea environments. Full article

Steels remain among the most widely used structural and engineering materials in modern infrastructure, energy systems, and industrial facilities. Their long-term reliability depends critically on the early detection of corrosion damage and microstructural degradation. This review surveys recent advances in two complementary families of non-destructive evaluation (NDE) methods: magnetic techniques, including magnetic Barkhausen noise (MBN), magnetic flux leakage (MFL), eddy current testing (ECT), and magnetic hysteresis analysis; and electrochemical methods including electrochemical impedance spectroscopy (EIS), linear polarization resistance (LPR), scanning vibrating electrode technique (SVET), and electrochemical noise (EN). Recent progress in sensor miniaturization, signal processing algorithms, and multi-technique integration is reviewed. Particular attention is given to the sensitivity of these methods to microstructural changes reported in the literature, including carbide dissolution, phase transformations, temper embrittlement, and sensitization in stainless steels, as well as to the conditions under which such sensitivity has been demonstrated. The potential synergy between magnetic and electrochemical monitoring is discussed as a possible pathway toward more robust, condition-based maintenance frameworks. Challenges related to field deployment, environmental interference, calibration, and data interpretation are identified, and future directions—including machine learning-assisted analysis and multi-physics sensor arrays—are outlined. Full article

Flexible pressure sensors have been increasingly proposed for clinical monitoring applications. However, the available evidence on the technical characteristics and the biomedical applications of these technologies remains fragmented. To fill this gap, this scoping review aimed to map the available literature (i) to identify the existing flexible pressure sensor matrices proposed for biomedical applications, their technical characteristics, and usage contexts, and (ii) to determine the systems integrated into bed-based support surfaces for clinical monitoring functions. The scoping review was conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. PubMed, Scopus, and Web of Science databases were systematically searched to identify studies published between 2015 and 2025 that describe flexible pressure sensor matrices for biomedical monitoring and care applications. A total of 5021 records were screened, and 45 studies were included. Existing flexible pressure sensor matrices were mainly based on resistive and capacitive principles. Systems integrated into clinical support surfaces were primarily used for pressure distribution and posture monitoring, and spanned from experimental prototypes to commercially available technologies. A lack of technical specifications and relevant heterogeneity was observed among the studies. Flexible pressure sensors demonstrated potential for clinical monitoring, but standardized technological reporting and clinical validation protocols are needed to develop technically robust and clinically oriented pressure sensing solutions. Full article