Search Results (1,367)

We propose a strain-optimized design strategy for lattice-matched InAs_1−xSb_x/Al_1−yIn_ySb Type-I quantum wells (QWs) that emit across the near-to mid-infrared spectrum (2–5 µm). By combining elastic strain energy minimization with band offset calculations, we identify Type-I alignment for Sb contents (x ≤ 0.40) and In contents (0.10 < y ≤ 1). At the same time, Type-II dominates at higher Sb compositions (x ≥ 0.50). Using the transfer matrix method under the effective mass approximation, we demonstrate precise emission tuning via QW thickness (L_W) and compositional control, achieving a wavelength coverage of 2–5 µm with <5% strain-induced energy deviation. Our results provide a roadmap for high-efficiency infrared optoelectronic devices, addressing applications in sensing and communications technologies. Full article

Accurate measurement of wall shear stress (WSS) is essential for both fundamental and applied fluid dynamics, where it governs boundary-layer behavior, drag generation, and the performance of flow-control systems. Yet, existing WSS sensing methods remain limited by low spatial resolution, complex instrumentation, or the need for user-dependent calibration. This work introduces a method based on artificial intelligence (AI) and Oil-Film Interferometry, referred to as AI-OFI, that transforms a classical optical technique into an automated and sensor-like platform for local WSS detection. The method combines the non-intrusive precision of Oil-Film Interferometry with modern deep-learning tools to achieve fast and fully autonomous data interpretation. Interference patterns generated by a thinning oil film are first segmented in real time using a YOLO-based object detection network and subsequently analyzed through a modified VGG16 regression model to estimate the local film thickness and the corresponding WSS. A smart interrogation-window selection algorithm, based on 2D Fourier analysis, ensures robust fringe detection under varying illumination and oil distribution conditions. The AI-OFI system was validated in the high-Reynolds-number Long Pipe Facility at the Centre for International Cooperation in Long Pipe Experiments (CICLoPE), showing excellent agreement with reference pressure-drop measurements and conventional OFI, with an average deviation below 5%. The proposed framework enables reliable, real-time, and operator-independent wall shear stress sensing, representing a significant step toward next-generation optical sensors for aerodynamic and industrial flow applications. Full article

In recent years, electrochemical pressure (ECP) sensors with self-powered and both dynamic and static pressure detection capabilities have received widespread attention. To improve pressure sensing performances while reducing the thickness of conventional sandwich structure ECP sensors, we propose an ECP sensor with a simple electrode coplanar structure. Specifically, it consists of Cu/Zn foil electrodes and LiCl/polyvinyl alcohol (PVA) modified filter paper. Among them, the Cu/Zn coplanar electrodes are used for redox reactions, the LiCl provides conductive ions, and the PVA is used to provide a humid environment to promote the ionization and conduction of LiCl. The rough surface microstructure of the filter paper is used to enhance the pressure sensing performances of the sensor. The results show that the ECP sensor with an electrode coplanar structure can spontaneously output current in the pressure range of 0.4–100 kPa, with sensitivities of 0.273 kPa⁻¹ (0.6–20 kPa) and 0.036 kPa⁻¹ (20–100 kPa). Specifically, compared to ECP sensors with a sandwich structure, it has a wider response range and higher sensitivity. Through the current response, morphological characterizations, and redox reactions, the pressure sensing mechanism is elucidated. Furthermore, the proposed ECP sensor can be used for respiratory state recognition combined with machine learning. This research provides a new approach for developing a high-performance ECP sensor with a simple electrode coplanar structure. Full article

The detection of trace nitrogen dioxide (NO₂) is critical for environmental monitoring and industrial safety. Among various sensing technologies, chemiresistive sensors based on semiconducting metal oxides are prominent due to their high sensitivity and fast response. However, their application is hindered by inherent limitations, including low selectivity and elevated operating temperatures, which increase power consumption. Two-dimensional metal oxysulfides have recently attracted attention as room-temperature sensing materials due to their unique electronic properties and fully reversible sensing performance. Meanwhile, their combination with optoelectronic gas sensing has emerged as a promising solution, combining higher efficiency with minimal energy requirements. In this work, we introduce non-layered 2D indium oxysulfide (In₂S_xO_3−x) synthesized via a two-step process: liquid metal printing of indium followed by thermal annealing of the resulting In₂O₃ in a H₂S atmosphere at 300 °C. The synthesized material is characterized by a micrometer-scale lateral dimension with 6.3 nm thickness and remaining n-type semiconducting behavior with a bandgap of 2.53 eV. It demonstrates a significant response factor of 1.2 toward 10 ppm NO₂ under blue light illumination at room temperature. The sensor exhibits a linear response across a low concentration range of 0.1 to 10 ppm, alongside greatly improved reversibility, selectivity, and sensitivity. This study successfully optimizes the application of 2D metal oxysulfide and presents its potential for the development of energy-efficient NO₂ sensing systems. Full article

Safe and efficient coal mining faces a global challenge in predicting sudden surface subsidence whose mechanisms remain unclear. This study, centered on deep coal seams in China’s Ordos Basin, examines the risk of abrupt subsidence controlled by high-positioned, ultra-thick, and weakly cemented key strata. We adopt an integrated “observation–experiment–model” paradigm. First, we construct a spatial decoupling model to analyze errors in 1D SBAS-InSAR monitoring, leading to a refined 2D method that reduces the three-dimensional monitoring error from 50 mm to under 20 mm. Based on this, the subsidence basin’s boundary angles are accurately determined as 52.3°–58.6° (strike) and 44.3°–48.2° (dip). Second, a large-scale physical simulation experiment visualizes the complete process of overburden failure up to the breaking of high-level key strata. Finally, by coupling remote sensing observations with experimental phenomena, a theoretical model is built to quantify the mechanical behavior of key strata, revealing the critical width-to-depth ratios for the rupture of the Yan’an Formation (0.21–0.27), Zhiluo Formation (0.53–0.82), and Zhidan Group (1.22–1.34). The research not only delineates surface subsidence morphology under special geological conditions but also answers the core questions of why subsidence occurs and when mutation may happen, thereby laying a theoretical foundation for a comprehensive early-warning model for mining areas worldwide. Full article

Experimental and numerical investigations of the alternating current (AC) susceptibility, $\mathsf{\chi }\left(H\right) ~ \mathrm{d}M/\mathrm{d}H,$ examined multigrain La_0.66Sr_0.34MnO₃ (LSMO) thin films (thickness d = 250 nm) grown by radio-frequency (RF) magnetron sputtering on lattice-mismatched yttria-stabilized zirconia YSZ(001) substrates. The films exhibit a columnar structure comprising two types of grains, with (001)- and (011)-oriented planes of a pseudocubic lattice aligned parallel to the film surface. Field- and angle-dependent AC susceptibility measurements at 78 K reveal characteristic peak- and tip-like anomalies, attributed to contributions from grains with three distinct directions of easy magnetization axes within the film plane. Numerical modeling based on the transverse susceptibility theory for single-domain ferromagnetic grains, incorporating first- and second-order anisotropy constants, corroborates the experimental findings and elucidates the role of different grain types in magnetization switching and AC susceptibility response. This study provides a quantitative determination of the three in-plane easy magnetization axes in LSMO/YSZ(001) films and clarifies their influence on the magnetization dynamics of multigrain thin films. The demonstrated control over multigrain LSMO/YSZ(001) thin films with distinct in-plane easy magnetization axes and well-characterized AC susceptibility suggests potential applications in magnetic memory, spintronic devices, and precision magnetic sensing. Full article

We investigate optical bistability (OB) in a hybrid system comprising a semiconductor quantum dot (SQD), a metallic nanoshell (MNS), and a cell membrane within the framework of the multipole approximation. Bistability phase diagrams plotted in the system’s parameter subspaces demonstrate that, in the weak exciton–phonon coupling regime, dynamic switching of bistable states among no-channel, single-channel, and dual-channel configurations can be achieved via precise modulation of the MNS’s dielectric shell thickness. Especially, a critical sensing threshold is identified: the absorption peak disappears and a bistable effect emerges when only 1.82% of normal cells undergo malignant transformation. Furthermore, the bistable region exhibits a gradual broadening trend with an increasing proportion of cancerous cells, yielding a quantitative and ultra-sensitive readout that underpins a highly accurate strategy for early cancer diagnosis. These findings not only deepen our fundamental understanding of bistability regulation in hybrid quantum-plasmonic systems interfaced with biological materials but also offer valuable insights for the development of next-generation optical switches and biomedical sensing platforms. Full article

Crop root development, and in turn crop growth, is strongly influenced by soil strength and the mechanical impedance of compacted layers, which restrict root elongation and exploration. Because the depth and thickness of compacted layers vary across a field, their identification is essential for site-specific tillage and sustainable root-zone management. A sensing approach that can support future real-time identification of compacted layers after soil-specific calibration, which would enable variable-depth tillage, reducing mechanical impedance and improving energy-use efficiency while maintaining crop yields. This study aimed to develop and evaluate prediction models that can support future real-time identification of compacted soil layers using soil electrical conductivity (EC) and moisture content as non-destructive indicators. A sandy clay soil (48.6% sand, 29.3% clay, 22.1% silt) was tested in a soil-bin laboratory under controlled conditions at three moisture levels (13, 18, and 22% db.) and six depth layers (C1–C6, 0–30 cm) identified from the penetration-resistance profile to measure penetration resistance, shear resistance, and EC. Penetration and shear resistance increased toward the most resistant depth layer and decreased with increasing moisture content, whereas EC generally increased with both depth layer and moisture content. Linear regression models relating penetration resistance ($R^2=0.893$) and shear resistance ($R^2=0.782$) to EC and moisture content were developed and evaluated. Field validation in a paddy field of similar texture showed that predicted penetration resistance differed from measured values by 3–6% across the three compaction treatments evaluated. Root length density and root volume decreased with increasing machine-induced compaction, confirming the agronomic relevance of the modeled patterns and supporting the suitability of the proposed indicators. Together, these results demonstrate that EC and moisture content can potentially be used as non-destructive proxies for compacted-layer identification and provide a calibration basis for future on-the-go sensing systems to support site-specific, variable-depth tillage in agricultural fields. Full article

In this report, a thickness-driven, aggregation–structure–transport optimum in sonicated poly(3-hexylthiophene) (P3HT) FETs was investigated. Mobility peaks at ~10–20 nm, coincident with a minimum in the photoluminescence (PL) vibronic ratio $I_{0-0}/I_{0-1}$ (strong H-aggregate interchain coupling) and X-ray diffraction sharpening of the (100) lamellar peak with slightly reduced d-spacing, indicate tighter π–π stacking and larger crystalline coherence. Absorption analysis (Spano model) is consistent with this enhanced interchain order. The mobility maximum arises from an optimal balance: J-aggregate–like intrachain planarity supports along-chain transport, while H-aggregates provide interchain connectivity for efficient hopping. Below this thickness, insufficient interchain coupling limits transport; above it, over-aggregation and disorder introduce traps and weaken gate control. The sharp rise in threshold voltage beyond the critical thickness indicates more trap states or fixed charges forming within the film bulk. As a result, a larger gate bias is needed to deplete the channel (remove excess holes) and switch the device off. These results show that electrical gating can be tuned via solution processing (sonication) and film thickness—guiding the design of P3HT devices for photovoltaics and sensing. Full article

This paper presents a practical thermal control strategy to enhance the output performance of oxide-based all-solid-state batteries (ASSBs), which typically exhibit low ionic conductivity at room temperature. A lightweight polyimide (PI) film heater was designed, fabricated, and integrated into the cell stack to locally maintain the optimal operating temperature range (≈65–75 °C) for electrolyte activation. Unlike previous studies limited to liquid or sulfide-based batteries, this work demonstrates the direct integration and coupled numerical–experimental validation of a PI film heater within oxide-based ASSBs. The proposed design achieves high heating efficiency (~92%) with minimal thickness (<100 μm) and long-term stability, enabling reliable and scalable thermal management. Finite-element simulations and experimental verification confirmed that the proposed heater achieved rapid and uniform heating with less than a 10 °C temperature deviation between the cell and heater surfaces. These findings provide a foundation for smart battery management systems with distributed temperature sensing and feedback control, supporting the development of high-performance and reliable solid-state battery platforms. Full article

In this work, a quasi-D-shaped photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) biosensor is proposed and numerically investigated using the finite element method (FEM) implemented in COMSOL Multiphysics version 6.2 for the detection of cancer cells with different refractive indices. The biosensor has a coating of plasmonic material gold (Au) and a polymer coat of polymethyl methacrylate (PMMA). The effects of plasmonic material thickness and air hole dimensions on key sensing parameters, including confinement loss (CL), wavelength sensitivity (WS), and amplitude sensitivity (AS), are systematically analyzed. The results revealed that increasing plasmonic thickness beyond its optimum value significantly raises CL while reducing sensitivity due to reduced penetration depth of the evanescent field. Similarly, variations in the geometrical dimensions of the air holes (±10%) also affect the sensor response, emphasizing the importance of precise structural optimization. For the optimized design the proposed biosensor exhibits high performance with a maximum WS of 31,000 nm/RIU for MDA-MB-231 cells under x-polarization and 29,500 nm/RIU under y-polarization. The corresponding resolutions achieved are as low as 3.22 × 10⁻⁶ RIU and 3.38 × 10⁻⁶ RIU, respectively, with AS exceeding 9000 RIU⁻¹. The WS, AS, and other sensing parameters obtained from our sensor are relatively higher than some of the PCF–SPR sensors reported recently. These numerical results demonstrate that the optimized quasi-D-shaped PCF–SPR biosensor exhibits enhanced sensitivity to refractive index (RI) variations associated with cancerous cells, suggesting its suitability for early detection. Full article

Air pollution is an important environmental issue that affects social development and human life. Atmospheric fine particulate matter (PM_2.5) is the primary pollutant affecting the air quality of most cities in the authors’ country. It can cause severe haze, reduce air visibility and cleanliness, and affect people’s daily lives and health. Therefore, it has become a primary research object. Ground monitoring and satellite remote sensing are currently the main ways to obtain PM_2.5 data. Satellite remote sensing technology has the advantages of macro-scale, dynamic, and real-time functioning, which can make up for the limitations of the uneven distribution and high cost of ground monitoring stations. Therefore, it provides an effective means to establish a mathematical model—based on atmospheric aerosol optical thickness data obtained through satellite remote sensing and PM_2.5 concentration data measured by ground monitoring stations—in order to estimate the PM_2.5 concentration and temporal and spatial distribution. This study takes the Yangtze River Delta region as the research area. Based on the measured PM_2.5 concentration data obtained from 184 ground monitoring stations in 2023, the newly released sixth version of the MODIS aerosol optical depth product obtained via the US Terra and Aqua satellites is used as the main prediction factor. Dark-pixel AOD data with a 3 km resolution and dark-blue AOD data with a 10 km resolution are combined with the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis meteorological, land use, road network, and population density data and other auxiliary prediction factors, and XGBoost and LSTM models are used to achieve high-precision estimation of the spatiotemporal changes in PM_2.5 concentration in the Yangtze River Delta region. Full article

A novel two-in-one sensor for both carbon dioxide and hydrogen detection has been obtained based on a hybrid heterostructure. It consists of a 30 nm thick TiO₂ nanocrystalline film grown by atomic layer deposition (ALD), thermally annealed at 610 °C, and subsequently coated with bimetallic AgAu nanoparticles and covered with a PV4D4 nanolayer, which was thermally treated at 430 °C. Two types of gas response behaviors have been registered, as n-type for hydrogen gas and p-type semiconductor behavior for carbon dioxide gas detection. The highest response for carbon dioxide has been registered at an operating temperature of 150 °C with a value of 130%, while the highest response for hydrogen gas was registered at 350 °C with a value of 230%, although it also attained a relatively good gas selectivity at 150 °C. It is considered that a thermal annealing temperature of 610 °C is better for the properties of TiO₂ nanofilms, since it enhances gas sensor sensitivity too. Polymer coating on top is also believed to contribute to a higher influence on selectivity of the sensor structure. Accordingly, to our previous research where PV4D4 has been annealed at 450 °C, in this research paper, a lower temperature of 430 °C for annealing has been used, and thus another ratio of cyclocages and cyclorings has been obtained. Knowing that the polymer acts like a sieve atop the sensor structure, in this study it offers increased selectivity and sensitivity towards carbon dioxide gas detection, as well as maintaining a relatively increased selectivity for hydrogen gas detection, which works as expected with Ag and Au bimetallic nanoparticles on the surface of the sensing structure. The results obtained are highly important for biomedical and environmental applications, as well as for further development of the sensor industry, considering the high potential of two-in-one sensors. A carbon dioxide detector could be used for assessing respiratory markers in patients and monitoring the quality of the environment, while hydrogen could be used for both monitoring lactose intolerance and concentrations in cases of therapeutic gas, as well as monitoring the safe handling of various concentrations. Full article

In this paper, the combined use of Ground Penetrating Radar (GPR) and a Terrestrial Laser Scanner (TLS) is illustrated to highlight multiple advantages arising from the integration of these two distinct Non-Destructive Testing (NDT) techniques in the investigation of a historical wall. In particular, thanks to the TLS point cloud, a precise evaluation of the medium’s thickness, as well as its irregularities, was carried out. Based on this accurate geometrical constraint, a first-order velocity model, to be used for a time-to-depth conversion and for a post-stack GPR data migration, was computed. Moreover, a joint visualization of both datasets (GPR and TLS) was achieved in a novel tridimensional workspace. This solution provided a more straightforward and efficient way of testing the reliability of the combined results, proving the efficiency of the proposed method in the estimation of a velocity model, especially in comparison to conventional GPR methods. This demonstrates how the integration of different remote sensing methodologies can yield a more solid interpretation, taking into account the uncertainties related to the geometrical irregularities of the external wall’s surface and the inner structure generating complex GPR signatures. Full article

Asymmetric and symmetric magnetoelectric (ME)-laminated composites with magnetostrictive layer FeNi and piezoelectric layer PZT are prepared. The longitudinal resonance ME voltage coefficient in the symmetric composite is approximately 1.57 times that in the asymmetric composite with same constituents due to the flexural deformation and asymmetric stress distribution in the asymmetric structure. By bonding an additional high-permeability FeSiB, combining FeSiB with FeNi forms magnetization-graded ferromagnetic materials. A stronger maximum ME voltage coefficient, a dual-peak phenomenon, and a self-bias ME effect are observed. The maximum ME voltage coefficients for asymmetric and symmetric composites reach 3.10 V/Oe and 5.67 V/Oe by adjusting the thickness of the FeCuNbSiB layer. The maximum zero-bias ME voltage coefficients for asymmetrical and symmetrical composite materials reach 2.19 V/Oe at 25 µm thickness of FeSiB and 2.87 V/Oe at 75 µm thickness of FeSiB. Such high performances enable the ME composites to possess ideal sensing and make them promising for self-bias current sensor applications. Full article