This work presents a semi-analytical framework that predicts the collectable charge yield from hypervelocity impacts by coupling four physics-based modules: (i) equation-of-state-driven Hugoniot solutions with impedance matching, (ii) energy-threshold-based phase zoning to delineate the vapor/plasma source region, (iii) Thomas-Fermi average-atom ionization for the free-electron inventory under warm dense matter conditions, and (iv) a screening-limited escape formulation based on a generalized Debye-Thomas-Fermi length. Validated against dust-accelerator measurements for Fe projectiles impacting Al, Fe, and Cu targets over 10-42 km/s, the model reproduces measured charge-yield magnitude, velocity scaling, and material ordering with RMSEs typically below 0.3 in log10(Q/m). The collected yield is governed by two competing factors: the spatial extent of the vaporized region, which sets the electron source strength, and early-time electrostatic screening, which reduces the collectable fraction by 2-3 orders of magnitude relative to the screening-free limit. Velocity-range-out tests demonstrate robust extrapolation beyond the calibration window, with reliable predictions obtainable from as few as three data points-outperforming conventional power-law fitting in data-limited regimes. The model combines physical transparency with computational efficiency, providing a practical tool for payload calibration, on-orbit signal interpretation, and rapid assessment of impact-induced electrical transients.

The growing population of space debris has become a significant threat to the reliability and stability of solar arrays, as evidenced by multiple reported anomalies and failures associated with space debris impacts over the past decades. Compared with rigid panels, flexible solar arrays employ novel materials, devices, and structures, leading to distinct damage behaviors and degradation mechanisms under hypervelocity impacts. In this study, the damage evolution and electrical performance degradation of flexible solar arrays under hypervelocity impacts were investigated by combining numerical simulations and experimental studies. The developed semi-refined model effectively reproduced the damage evolution under different impact velocities and was validated by experiments, achieving RMSE and MRE values of 0.56 mm2 and 2.01% for the simulated perforation areas, respectively. An in-situ measurement system was developed to characterize impact-induced plasma and electrical degradation. Under comparable impact conditions, the electron temperature and electron density of the impact-induced plasma generated by the flexible solar array were 32.6% and 69.7% lower, respectively, than the corresponding values for the rigid panel. The impact-induced power degradation mechanisms were further elucidated. Computed tomography revealed the mechanism of short-circuit failure caused by sub-millimeter debris impacts, and the Burt model indicated a higher short-circuit failure risk under oblique impacts than under normal impacts. These findings provide new insights into the multiscale space debris-induced damage mechanisms of flexible solar arrays and establish an evaluation framework for reliability assessment and fault diagnosis.

Nano-thermite energetic films were suited to microscale laser ignition, but weak NIR absorption and low energy-use efficiency still limited practical use. Herein, we addressed these limitations by integrating Ti3C2 into flexible Al/Bi2O3 films via Direct Ink Writing (DIW). Experimental characterizations and theoretical calculations (Gibbs free energy, Bader charge analysis) indicated that Ti3C2 acted as a multifunctional regulator: it enhanced NIR absorption via localized surface plasmon resonance (LSPR), accelerated heat conduction, and tailors thermite reactions via a three-stage pathway (preheating, reaction and product transfer). Ultimately, by tuning the Ti3C2 content, the laser ignition threshold was reduced by 60.8 % and the photothermal conversion efficiency was increased to 41.43 % at 10 wt%, the reaction onset temperature was decreased by 40 degrees C and the maximum flame propagation/pressurization performance was achieved at 1 wt%, and the total heat release was nearly tripled at 5 wt%, indicating a comprehensive optimization of the combustion behavior. This work established a Ti3C2 paradigm for coupling photothermal conversion with chemical energy release, enabling low-threshold, high-response micro-igniters and miniaturized devices.

In order to satisfy the demands of high-power applications, the desire to improve electromechanical properties of piezoelectric ceramics has become increasingly urgent. A conventional ternary ceramic system 0.05Pb(Mn1/3Sb2/ 3)O3-xPbZrO3-(0.95-x)PbTiO3 (x = 0.45-0.49) (0.05PMS-xPZ-(0.95-x)PT) was studied through regulating the ratios of rhombohedral (R) and tetragonal (T) phases in this research. The phase compositions, microstructures, electromechanical properties and thermal stability of ceramics were characterized. The 0.05PMS-0.47PZ-0.48PT ceramics near the morphotropic phase boundary (MPB) reveals remarkable comprehensive properties (d33 = 418 pC/N, Qm = 1762, FOM = d33* Qm = 7.37 & times; 105 pC/N, Tc = 331 degrees C, tans = 0.28% (at 25 degrees C), epsilon r = 1606, kp = 0.62). Compared with the undoped PMS-PZT research reported before, the FOM is improved by 57.5%. Additionally, it also exhibits excellent thermal stability that from 25 degrees C to 150 degrees C, the variation of d33 is less than 5%. The outstanding comprehensive properties are primarily ascribed to the optimal ratio of the R and T phases which is 19/81 and the pinning effect of defect dipoles. The XPS and PFM result directly proved the presence of defect dipoles and exhibited the structures of domains. The strong "defect dipole-strain cooperative pinning" in T phase rich MPB yield high Qm when the d33 is enhanced at the same time. The results of this research especially the high FOM, low tans and excellent thermal stability indicate that the 0.05PMS-0.47PZ-0.48PT ceramics could be a promising alternative for the productions of piezoelectric devices working in a large temperature range in high-power fields.

Pickering emulsions offer high stability and biocompatibility, making them promising for food applications. The preparation of stabilizers using deep eutectic solvents (DES) supports green chemistry principles. This study compared cellulose nanofiber (CNF) prepared using two DES-based methods: L-CNF, obtained chemically with malic acid/choline chloride, and G-CNF, produced physically by glycerol/choline chloride ball milling, with microcrystalline cellulose (MCC) as the control. L-CNF exhibited the smallest size (82.8 ± 2.0 nm), highest surface charge (-24.5 ± 0.4 mV), and lowest interfacial tension (16.57 ± 0.45 mN·m-1). When combined with 1.0 wt% soy protein isolate (SPI) at 0.4 wt% L-CNF, fine droplets and a strong viscoelastic network formed, resulting in excellent freeze-thaw and storage stability. At a 3:7 oil-to-water ratio, creaming was minimized, antioxidant performance improved, and creaming index remained 19.5% after 6 months of simulated light exposure. MCC and G-CNF showed weaker stabilization, highlighting the importance of DES preparation in emulsion design.

The widely used aromatic polyamide (PA) membrane elements are susceptible to degradation caused by chlorine and that by chlorine dioxide (ClO2) in a slower manner, when either chlorine or ClO2 was employed for the membrane biofouling-control purposes. Physicochemical properties and filtration performances of a fully aromatic PA membrane (NF 90) after ClO2 treatment for 96 h at neutral pH were investigated in this study. Results indicate that ClO2 treatment increased the membrane pore size and the surface roughness, implying disruption of membrane cross-linking. Halogen incorporation, which is usually the case for chlorination, was not observed for ClO2 treatment of up to 250 mg/L (Cl-2 equivalent). The attenuated total reflection-Fourier transform infrared analysis results indicated the occurrence of amide bond breakage and the addition of carboxyl groups after oxidation. Results showed that the 10 and 50 mg/L treatment decreased zeta potential by > 3 mV and contact angle by > 5.3(degrees), confirming the hydrolysis of PA membrane. The oxidized PA membrane surface became more permeable: water permeability increased by up to 63.3%; and the solute permeability increased by 71.6% and 285% for charged and neutral solutes, respectively. Amide bond breakage by hydrolysis is proposed as the primary degradation mechanism for PA by ClO2 at neutral pH. This study provides novel insights into ClO2 and PA oxidation processes at pH 7 and membranes biofouling control in reverse osmosis and nanofiltration at representative conditions.

Despite the promising performance of deep reinforcement learning (DRL)-based energy management systems (EMSs) for electrified vehicles, persistent safety concerns regarding control actions hinder their real-world deployment. This article proposes a safe DRL-based EMS for hybrid electric vehicles (HEVs) that guarantee zero safety violations during both training and deployment. A model-based safety layer is developed with prior knowledge to filter unsafe actions with minimal disruption to agent exploration. This safety metric evaluation is embedded into the reward function via a Lagrangian relaxation (LR) method, enabling adaptive penalization of constraint violations and prompting efficient policy learning. A safe soft actor-critic (SSAC) EMS is then trained under stochastic conditions, including random initial battery state-of-charge (SOC) and multimodal driving cycles. The approach is validated through simulation and battery-in-the-loop (BIL) experiments. The proposed reward formulation accelerates safety-aware policy learning by 38.5% compared to conventional methods. In BIL tests, SSAC-EMS achieves over 95% fuel efficiency relative to the offline dynamic programming (DP) benchmark under unseen driving cycles and initial SOCs, with actions consistently respecting safety constraints. Compared to the adaptive equivalent consumption minimization strategy (AECMS), SSAC-EMS improves fuel economy by 6%-10% while delivering more stable SOC regulation and smoother engine operation.

Low conductivity, slow ion-diffusion, and limited reactive sites are common problems in electrocatalysts and electrode materials. In this study, a complex NiTe-CoTe heterojunction with abundant Te vacancies embedded in N, P, and F co-doped hollow carbon nanorods (NiTe1-x-CoTe1-x/NPFC) was fabricated via a simple ionic liquid-assisted hydrothermal method and calcination. NiTe1-x-CoTe1-x/NPFC shows excellent activity (80.1 and 108.4 mV overpotentials at 10/100 mA cm-1) for the hydrogen evolution reaction in 1.0 M KOH solution. Moreover, NiTe1-x-CoTe1-x/NPFC exhibits an excellent energy density of 57.9 Wh kg-1 at an extremely high power density of 15.90 kW kg-1 in a flexible solid-state supercapacitor, revealing its outstanding performance. Mechanistic insights from synchrotron XANES, in situ spectroscopy, and DFT calculations elucidate the interfacial electron transfer pathways, dynamic water dissociation behavior during HER, reversible phase transition mechanisms during energy storage, and the optimization of OH-/H* adsorption energy. Overall, this study will facilitate the design of telluride heterojunctions with tellurium-rich vacancies as well as N, P, and F doped carbon composites, which can be applied to other electrode materials and electrocatalysts. (sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)N/P/F(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)NiTe-CoTe(sic)(sic)(sic)(sic)(sic)(sic)(sic)(NiTe1-x-CoTe1-x/NPFC).(sic)(sic)(sic)(sic)1.0 M KOH(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(10/100 mA cm-1(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)80.1(sic)108.4 mV).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),NiTe1-x-CoTe1-x/NPFC(sic)15.90 kW kg-1(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)57.9 Wh kg-1(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)OH-/H*(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)N/P/F(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

Indoor localization is crucial for applications such as navigation, asset tracking, and emergency response. Fingerprint-based methods that use RSSI are widely adopted; however, they fail under large environmental changes. Unmanned Vehicles (UVs) equipped with high precision sensors are able to collect fingerprints, serving as a promising way by forming a Vehicular Crowdsensing (VCS) campaign. In this paper, we propose “BRAVE”, a Bayesian RL Approach for VCS under Environment changing, while introducing a new metric “Calibration Benefit” to explicitly quantify how effectively a learned trajectory updates those regions of the fingerprint database that have changed and matter most for localization. Specifically, we propose a spatial-temporal Bayesian Network(BN) for change detection, a region rearrangement method for fewer restarts, and an optimistic strategy to balance the exploration and exploitation trade-offs in optimizing calibration benefit. Extensive results on two real-world datasets from SML Center (Shanghai) and Haopu Fashion City (Shanghai) demonstrate that BRAVE outperforms eight baselines and the derived dataset has better localization accuracy compared with the original dataset.

In the advanced automobile industry, widespread air pollution in the vehicle cabin significantly affects the health of drivers and passengers. Although the category and concentration of gaseous pollutants have been widely researched, the interior and exterior factors cause variations in the composition and concentration of vehicle cabin-air pollutants. Meanwhile, the latest vehicle cabin-air quality standards of some nations and organizations are limited and outdate, incapably to guide the following research on cabin-air pollutants. Therefore, it is necessary to conduct a systematic review of the characteristics of vehicle cabin-air pollutants and evaluate the cabin-air quality standards of typical nations and organizations. This article summarized the composition and concentration range of the gaseous pollutants in the vehicle cabin and identified the prior-treated substrates based on their carcinogenicity and toxicity. Meanwhile, this review analyzed how interior and exterior factors affect the vehicle cabin-air environment, and specifying what the dynamic change of air pollutants means to the improvement of air quality standards. Furthermore, this article provided a comparison of indoor air quality standards and vehicle cabin-air quality standards of some nations and organizations, acting solid evidence of the scientific basis of these standards. This research could provide solid guidelines for improving the screening and evaluation of vehicle cabin-air and decreasing the health risks to inhabitants.

The limited theoretical capacity and rate performance of graphite-based anodes are increasingly struggling to meet the growing demands of electric vehicles, aircraft, and smart grids. Combining SiOx with graphite is recognized as an effective strategy to enhance the comprehensive battery performance. However, the inherently low initial coulombic efficiency and sluggish lithiation kinetics of SiOx significantly hinder its advantages and practical applications. This work constructs a novel double-core-shelled G@Ni2SiO4-Ni@C material by in situ growth of Ni2SiO4 nanolayers (<15 nm thick) and Ni(OH)2 nanoplates (<8 nm), followed by pyrolytic carbon encapsulation of pitch. SEM, TEM, EDS, XRD, XPS, and TGA provide an adequate characterization of the formation trajectory. Benefiting from the unique double core-shell structure and Ni catalysis, G@Ni2SiO4-Ni@C exhibits superior lithium storage performance, with an initial coulombic efficiency of 87.2% at 500 mA/g, much higher than that of the Ni-free sample (63.9%); the reversible capacity after 1000 cycles is 585.6 mAh/g (1.57 times the theoretical capacity of graphite), with a capacity retention of 115.8%. Ex-situ XPS and density functional theory calculations reveal the role of Ni in activating Li-Si-O and Li-O bonds and enhancing interfacial electronic transport, thereby enabling the release of more Li+ ions and improving rate performance.

Conventional transdermal delivery systems are constrained by inherent trade-offs among penetration efficiency, bioactive potency, and skin biocompatibility. To overcome these limitations, here we show a supramolecular Janus eutectic engineered from D-panthenol and α-(-)-bisabolol (SPB). This carrier-free system effectively integrates autonomous permeation with multimodal therapeutic functions. SPB demonstrates synergistic enhancement of panthenol transdermal delivery while markedly improving the biocompatibility of bisabolol, alongside multiplex anti-irritation and pro-repair efficacy—a combination unattainable by its individual components or physical mixtures. Mechanistic investigations indicate that the supramolecular architecture modulates the active transport pathway and antagonizes the TRPV1 receptor. This work provides a practical strategy for designing biofunctional materials that intrinsically unify delivery, efficacy, and safety. Transdermal delivery systems are constrained by a trade off in penetration efficiency bioactivity. Here, the authors report on A supramolecular eutectic of D-panthenol and bisabolol that overcomes the trade-offs, achieving synergistic transdermal efficacy and skin repair that physical mixtures cannot replicate

Deep reinforcement learning (DRL)-based energy management strategies (EMSs) have gained significant popularity in improving the performance of electrified vehicles. Typically, these EMSs are trained and validated in simulated environments. However, this article reveals that the environment's fidelity significantly impacts DRL-based EMSs' performance. Specifically, the EMSs optimized within low-fidelity environments (LFEs)-prevalent in literature yet lacking detailed powertrain dynamics-suffer a performance drop of 2%-3% in energy economy when tested in high-fidelity environments (HFEs) that incorporate powertrain dynamics. To address it, a DRL-based hierarchical energy management framework for multimode power-split hybrid electric vehicles (HEVs) is proposed. It recognizes powertrain dynamics and facilitates transfer learning techniques to bridge the performance gap between LFEs and HFEs. In the upper level of this framework, a DRL agent determines the optimal timing to activate the hybrid mode and the optimal engine operation. The lower level optimizes the torque distribution between two electric motors for all-electric modes. Simulation results demonstrate that the proposed DRL-based EMS, enhanced by transfer learning, reduces training time by approximately 40% compared with the trained-from-scratch EMS within an HFE. Moreover, the proposed EMS achieves 98% energy economy of the optimal benchmark, addressing the noted performance degradation and exhibiting consistent performance in adaptability tests.

Vision-Language Model (VLM) is a kind of multi-modality deep learning model that aims to fuse visual information with language information to enhance the understanding and analysis of visual content. VLM was originally used to integrate multi-modality information and improve task accuracy. Then, VLM was further developed in combination with zero-shot and few-shot learning to solve the problem of insufficient medical labels. At present, it is the technical basis of the popular medical general large model. Its role is no longer limited to simple information fusion. This paper makes a comprehensive review for the development and application of VLM-based medical image analysis technology. Specifically, this paper first introduces the basic principle and explains the pre-training and fine-tuning framework. Then, the research progress of medical image classification, segmentation, report generation, question answering, image generation, large model and other application scenarios is introduced. This paper also summarizes seven main characteristics of medical image VLM, and analyzes the specific embodiment of these characteristics in each task. Finally, the challenges, potential solutions and future directions in this field are discussed. VLM is still in a rapid development in the field of medical image analysis, and a continuously updated repository of papers and code has been built, it is available at https://github.com/XiangQA-Q/VLM-in-MIA.

Simulation of hypervelocity dust impact generated plasma has been based on experimental fitting, ignoring the impact behavior process, resulting in a disadvantage using at velocity beyond fitting range. Aming on improve simulation model of the impact plasma generation, this article establishes a forward simulation paradigm from the theory of impact behavior to plasma diffusion. By using the higher-order wave velocity and material velocity relationship, as well as the phase transition equation of state, the research model establish a fine simulation extend impact condition upto 1000 GPa, and achieves a consistent description of the impact behavior to the impact ionization process. The model demonstrates a promising correspondence with experimental results, as in close proximity to the magnitude and comparable exponential growth patterns.

This article presents a novel approach to battery thermal management control in electric vehicles (EVs), focusing on the establishment of a power loss model that incorporates temperature and aging effects on internal resistance, thereby enabling accurate estimation of battery power loss for optimized battery thermal management systems (BTMS). In addition, this article introduces a BTMS design capable of both heating and cooling, aiming to maintain optimal battery temperature and enhance battery efficiency and longevity. The proposed methodology includes an offline optimization layer to improve battery longevity and BTMS energy efficiency and an online control layer to maintain a safe battery temperature operation. The adaptability of this BTMS design for real-time applications in various climates is achieved by integrating discharge rate (c-rate) information from the drive cycle. This results in a two-level, driving-aware BTMS control system tailored to varying driving patterns specific to commuter applications. Consequently, this research significantly advances EV battery thermal management by addressing key challenges such as reducing power loss estimation error by up to 28%, optimizing temperature regulation, improving power efficiency by up to 7 kJ for different drive cycles, and enhancing battery aging by more than 3% per life cycle, while ensuring adaptability to various driving patterns for commuters.

Alternating-current poling (ACP) is becoming a mainstream method because of its stronger ability in promoting the piezoelectric performance of ferroelectric single crystals than that of direct-current poling (DCP). A novel approach was developed by incorporating alternating-current poling and direct-current poling as modified alternating-current poling (MACP). According to the comparison of performance differences between AC-poled and DC-poled single crystals, the properties of MACP single crystals under specific conditions were systematically investigated. The improvement of single crystal performance by MACP is manifested by the multi-peak increase in piezoelectric coefficient (d33) and relative dielectric permittivity (ε33T/ε0), and the coupling factor (kt) value under higher DC bias is higher than that under DC polarization, rather than a direct superposition of DCP and ACP. Two optimal polarization windows were found: 0.2–0.25 kV/mm and 0.35–0.6 kV/mm. Compared with DCP, MACP increases the d33, ε33T/ε0 and kt, of single crystals by up to 45.67%, 21.62%, and 24.54%, respectively. This significant performance improvement, combined with its complexity, provides a new direction for customizing the performance of single crystals.

The growing demand for safe and sustainable cosmetics has led to a marked inclination toward natural extracts and peptides as raw materials. In this study, we developed a sustainable system with multiple antiaging effects by combining peony extract (PE) and acetyl hexapeptide-8 (AHP8) to simultaneously treat static and dynamic wrinkles, as well as skin dullness. As the poor skin permeability of AHP8 limited its efficacy, we used a bioactive ionic liquid derived from betaine and malic acid (MA) ([Bet][MA]) as a permeation enhancer. In vitro and in vivo zebrafish experiments indicated that [Bet][MA] not only significantly enhances transdermal and cellular penetration, but also exerts synergistic anti-aging effects. While being biosafe, [Bet][MA] significantly increased the transdermal permeation, skin retention, and cellular uptake of AHP8. Theoretical calculations revealed that [Bet][MA] improved the anti-wrinkle and whitening efficacies of AHP8 and PE through supramolecular interactions; it modulated their electron cloud distribution and molecular polarity and thus intensified their affinity to target proteins. The supramolecular PE/AHP8/[Bet][MA] system demonstrated excellent radical- and reactive oxygen species-scavenging capability, collagen production, and tissue repair capability while concurrently inhibiting tyrosinase activity, motion signaling, and inflammation. The study findings pave the way for sustainable and multifunctional skincare solutions.

Currently, the improvement in energy efficiency of catalysts for Zn-air batteries (ZABs) is seriously hindered by kinetic retardation. In this study, an ionic liquid was employed to generate sulfur vacancies, nitrogen/fluorine atoms, and a high concentration of single-atom Sb on a layered ZnIn2S4 substrate via a one-step synthesis process. These components were uniformly loaded onto porous carbon (SbSANF-ZnIn2S4-x/PC). The sulfur vacancies and nitrogen/fluorine atoms altered the surface charge distribution of ZnIn2S4-x and created an ideal coordination environment for the adsorption of single-atom Sb, enhancing the reactions in oxygen evolution/reduction reactions (OER/ORR) and ZABs. During testing, SbSANF-ZnIn2S4-x/PC demonstrated a half-wave potential of 0.892 V in ORR and an overpotential of 0.319 V in OER. When assembled into ZABs, it showed a specific capacity of 812.1 mAh g(-1) and a power density of 186.2 mW cm(-2). Overall, this study presents a promising one-step synthesis approach for creating a highly efficient electrocatalyst with single-metal atoms, non-metal atoms, and vacancies.

Biosensors based on field-effect transistor (FET) are extensively utilized in biomedical engineering for their capability to achieve rapid and label-free detection of targets. However, the extremely low concentration level of biomarkers, crucial for human health, put forward higher requirements for biosensors. Developing stable and reliable biosensors with high sensitivity for biomarker detection remains challenging. In this study, we report a highly sensitive MoS2-FET biosensor for the cytokine IFN-gamma. Surface etching of the MoS2 channel using a reactive ion etching system increases reactive sites for biological molecules on the channel surface, thereby enhancing the detection performance of the biosensor. The MoS2-FET biosensor functionalized with aptamer demonstrates high sensitivity and selectivity for IFN-gamma detection (limit of detection is 5.98 x 10-5nM). Notably, the signal responses of the MoS2-FET biosensor are higher than that of the MoS2-FET biosensor without Ar etching and graphene-FET biosensor. Additionally, this paper analyzes the relationship between the modification density of probe molecules and the biosensor's detection signal, establishing a theoretical foundation for further enhancing the sensor's detection performance. Experimental results confirm that the highly sensitive MoS2-FET biosensor provides an effective testing platform for the biomarkers with low concentrations, crucial for disease prevention and early diagnosis.