Guoxuan Qin

Reliable detection of low concentrations of NH3 at room temperature remains challenging. Traditional metal oxide sensors usually rely on relatively high operating temperatures, while conductive polymer sensors often suffer from insufficient stability and limited signal amplification at extremely low concentrations. In this work, a silicon-based NH3 sensor with a WO3–polyaniline (PANI)/silicon nanowire arrays (SiNW) composite structure was constructed. In this structure, WO3 and PANI form n–p heterointerfaces, while the SiNW array provides a three-dimensional scaffold that facilitates gas diffusion and supports charge transport within the sensing layer. Owing to the coupled effects of the WO3–PANI heterointerface and the SiNW-supported sensing architecture, the device exhibits a distinct resistance response to NH3 at room temperature. The obtained sensor shows good selectivity, repeatability, and stability, with a detectable NH3 concentration as low as 0.1 ppb under the present testing conditions. Compared with the PANI/SiNW reference device, the WO3–PANI/SiNW sensor exhibits a stronger response and improved detection capability in the low-concentration range. The enhanced sensing performance is mainly attributed to the synergistic effects of PANI deprotonation, WO3–PANI interfacial barrier modulation, and SiNW-assisted gas diffusion and charge transport. This work provides a feasible strategy for designing low-power, highly sensitive ammonia gas sensors based on interface-modulated polymer/oxide heterostructures.

Trimethylamine (TMA), a representative volatile organic amine, is crucial for the precise and rapid evaluation of food freshness and environmental safety. However, existing gas sensors face challenges, such as low system integration and limited operational lifetime, which restrict their practical application in the Internet of Things (IoT). In this work, we fabricated a photovoltaic gas sensor by constructing a PANI:PSS/MoO3 multifunctional layer on silicon nanowire arrays. Through precise energy-band engineering and dual-heterojunction structure, we optimized the separation, transport, and transfer of photogenerated carriers, enabling self-powered TMA detection with excellent performance for the first time. Systematic characterization and electrical testing confirmed that the sensor exhibited stable photovoltaic properties. Under these conditions, the sensor achieved a detection limit for TMA as low as 10 ppb with a response time of only 19 s, placing its overall performance among the best of similar devices. Additionally, cycling tests and lifetime verification confirmed its reliable long-term operational capability. This research fills a gap in self-powered TMA detection, significantly extending the lifespan of sensing systems and broadening their application prospects, providing a potential technological reference for the development of self-sustaining IoT smart terminals.

The detection of ammonia at trace levels is helpful for tracing pollution sources in air pollution control and identifying early-stage diseases, thereby offering practical value in environmental monitoring and medical diagnosis. Although carbon nanotube/polyaniline (CNT/PANI) composites exhibit good response toward NH3, they tend to suffer from serious agglomeration during the growth process. In this work, we modified the three-dimensional structure of the substrate and successfully prepared the CNT/PANI/silicon nanowire (SiNW) ammonia gas sensor. Material characterizations confirmed that the SiNW significantly improved the dispersion of CNTs/PANI composites. Subsequently, the sensor exhibited a response amplitude of 112.8% at 1 ppm NH3 and 260.5% at 10 ppm at room temperature, which surpassed most other similar polymer-based sensors. Furthermore, the sensor exhibited a detection limit as low as 1 ppb, which is approximately one order of magnitude lower than that of most existing sensors. The results also demonstrated that the sensor possessed a fast response time and high selectivity toward NH3 detection.

Cross-modal remote sensing image retrieval (CMR-SIR) is vital for Earth observation but remains challenged by the fundamental heterogeneity gap. Existing hashing methods often struggle to reconcile fine-grained representation with semantic consistency, primarily due to resolution-induced physical degradation and spatial–spectral discrepancies. To address these issues, we propose the Frequency-Guided Mutual Distillation Network (FG-MD), a lightweight framework designed for efficient and consistent feature alignment. The proposed approach first introduces a fine-grained refinement stage featuring a Frequency Domain Full-Spectrum Perceiver (FDFSP) module and an Adaptive Dynamic Filter (ADF), which synergistically enhance high-frequency structural details and suppress environmental clutter. Subsequently, a Dual-Attention Mutual Distillation (DAMD) strategy is devised to enforce spatial-semantic consistency via symmetric collaborative learning without incurring additional inference overhead. Extensive experiments conducted across multiple benchmarks demonstrate that FG-MD consistently achieves state-of-the-art performance with only 22.05 M parameters, offering an optimal efficiency-accuracy trade-off across all evaluated datasets. Furthermore, to validate generalization, we construct the Indoor Geometric Structure (IGS) benchmark for GPS-denied UAV reconnaissance. This dataset constitutes a challenging isomorphic extension of remote sensing tasks, where FG-MD significantly outperforms competitive baselines under severe viewpoint variations.

Coptis chinensis (cc) was widely used in traditional Chinese medicine for the treatment of various diseases, and its quality evaluation directly influenced clinical efficacy and safety. Traditional analytical methods, such as chromatographic or mass spectrometric techniques, were limited by high equipment costs and complex operational procedures. Here, a gelatin (Gel) side-gated double-layer field-effect transistor (GGDL-FET) was designed for highly sensitive detection of cc. The electric double-layer (EDL) capacitance of GGDL-FET reached 12.2 μF with 2 wt. % Gel. The superposition effect of electric fields 1 and 2 (E1 and E2) enhanced the gate control capability, thus contributed to a significant increase in channel current (∼374.4%). Furthermore, berberine (BBR) as the main components of cc was first quantified, and the incorporation of BBR increased the ion concentration of Gel electrolyte as well as the EDL capacitance since the quaternary ammonium salt group in its structure produced more positive charges, which enhanced the gate controllability and led to an obvious increase in the channel current. Subsequently, cc samples with varying concentration gradients were introduced into Gel. The resulting changes of the channel current exhibited consistent behavior with BBR alone, demonstrating a concentration-dependent response. The device detected cc with concentrations of 1, 2, and 3 wt. %. Thus, the concentration of BBR in cc could be evaluated by analyzing the changing trend of channel current, which provided a reference for the quality assessment of cc.

Acetic acid gas, as an organic pollutant, poses serious hazards to both human health and the environment. Consequently, the real-time detection of low concentrations of acetic acid gas has become a matter of considerable concern. In this study, a bioelectronic sensor was synthesized by directly coupling N-terminal cysteine-modified olfactory receptor-derived peptide with thioester-functionalized single-walled carbon nanotubes through chemical linkage, and its performance was experimentally tested. More importantly, to further enhance its performance, polystyrene microsphere templating was employed during synthesis, this improvement significantly improved the overall performance of the sensor compared to the original process, and then characterization and gas sensitivity tests were carried out. The results revealed that the sensor exhibited extremely high sensitivity, with a detection limit 1 order of magnitude lower than that of the sensor fabricated without the template, reaching 1 ppt at room temperature. This detection limit is 2-3 orders of magnitude lower than that of conventional devices. Moreover, the sensor demonstrated excellent selectivity, stability, and rapid response characteristics.

With the rapid development of nanotechnology, silicon nanowire (SiNW) array gas sensors have shown great potential for gas detection due to their high sensitivity, fast response, and excellent selectivity. In this study, we fabricated a flexible SiNW array gas sensor and measured its performance in acetone gas detection under various conditions, including different acetone gas concentrations (ranging from 0.1 to 200 ppm), humidity levels, and bending conditions. To further investigate the sensor’s performance, we developed a multiphysics finite element model using COMSOL software. The model simulation results were in good agreement with the experimental data. Experimental and modeling results showed that the main factors influencing sensor performance were the changes in nanowire morphology, diffusion dynamics, and adsorption, while the underlying mechanisms were discussed. This study provides helpful theoretical support for the design and optimization of flexible SiNW array gas sensors, offering insights for the development of highly sensitive and durable flexible gas sensors.

Prostate-specific antigen (PSA) is the best serum biomarker for prostate cancer (PCa), and the detection of PSA concentration can be used to assess the risk of malignancy. Given the current lack of effective treatment options for PCa, early detection and intervention are particularly important. To address this, we developed a novel electronic biosensor aimed at highly sensitive detection of PSA. The core materials of this sensor consist of the receptor material, PSA-affinity peptides, and the support material, single-walled carbon nanotubes. These materials are cost-effective, can operate at room temperature, and exhibit good stability, which aids in optimizing the sensor’s performance and stability. We attached the carbon nanotubes to a gold fork electrode and successfully fabricated the device by chemically linking the peptides to the carbon nanotubes. PSA was subsequently detected through the binding of PSA molecules to specific peptide sequences in standard solution. The sensor achieved a detection limit as low as 10⁻¹³ μg μL⁻¹, which is lower than that of currently used detection methods, demonstrating exceptional sensitivity. This biosensor offers advantages such as low cost, high efficiency, and strong specificity, indicating its broad application prospects in medical diagnostics, particularly in PCa screening.