Search Results (1,088)

Soil organic carbon (SOC) plays a critical role in climate regulation, soil fertility, and ecosystem resilience, making its accurate spatial quantification essential for sustainable land management and greenhouse gas (GHG) reporting. However, mapping SOC in heterogeneous agroforestry systems remains challenging due to vegetation cover and landscape complexity. In this study, we develop and evaluate a hybrid bare soil modelling- Digital Soil Mapping supported by ML framework to generate high-resolution soil properties predictions in Mediterranean agroforestry systems (Extremadura, Spain). A dual modelling approach was implemented, combining (i) Bare Soil modelling using Sentinel-2 multi-temporal reflectance composites and (ii) Digital Soil Mapping (DSM) supported by environmental covariates (climate, terrain, vegetation) following the SCORPAN framework. Machine learning models, namely Quantile Regression Forests (QRF) and Extreme Gradient Boosting (XGBoost), were applied and optimised using automated hyperparameter tuning (FLAML). A total of 107 LUCAS topsoil samples and 36 complementary points from the Forest ICP Level I were used for calibration and validation, with a 70/30 train–test split. Results show that Sentinel-2-based modelling can effectively capture SOC spatial variability in bare soil conditions, while DSM improves predictions in vegetated areas. Model performance reached R² values up to 0.76 (QRF, pH) and RMSE as low as 0.03 (XGBoost, N), with uncertainty quantified using the Prediction Interval Ratio (PIR) and performance further supported by RPIQ values up to 3.15. However, prediction accuracy remains sensitive to vegetation structure and sample density. The proposed framework provides a scalable and uncertainty-aware approach for SOC mapping, supporting Tier-3 GHG inventories and emerging Monitoring, Reporting, and Verification (MRV) systems. The results highlight the importance of integrating multi-source datasets and hybrid modelling strategies for reliable SOC estimation in complex landscapes. Full article

The development of biocompatible materials has gained traction due to the increasing clinical demands for customizable and functional medical devices. Chitosan, a deacetylated derivative of chitin, is a naturally occurring biopolymer with strong antimicrobial properties, immunocompatibility, and structural adaptability, making it a promising candidate for biomedical applications. Through mechanisms such as crosslinking, ionic bonding, gas formation, and UV radiation, the mechanical properties and stimulus responses of chitosan-based hydrogels can be tailored for drug delivery at specific sites or under specific pH, light, or electrical conditions. Beyond drug delivery, chitosan hydrogels have shown considerable potential for vascular tissue repair. The porous structure of chitosan allows patient specific vascular scaffolding to be created that promotes the recovery rate veins and stenting procedures. Thermally sensitive hydrogels can deliver drugs to target regions to further assist in vascular healing. Furthermore, recent developments with composite polymers and coatings engineered to self-assemble within veins provide scaffolds for vascular tissue growth. This manuscript reviews chitosan hydrogel fabrication methods and their corresponding materials properties, with particular emphasis on drug delivery to vascular tissues. Furthermore, relevant findings from clinical trials are summarized to support the potential of chitosan hydrogels for future clinical use. Challenges of chitosan hydrogels, such as insufficient mechanical strength, high degradation rates, and complex manufacturing, remain as areas for research break-through. Full article

With the shift in advanced packaging toward 3D integration and flexible electronics, it is becoming critical to produce high-quality silicon nitride films under low thermal budgets. To overcome the limitations of low-temperature deposition, this study compares two gas mixtures—SiH₄/NH₃/N₂ and SiH₄/N₂—in plasma-enhanced chemical vapor deposition of silicon nitride coatings. We systematically evaluated how the NH₃ precursor affects deposition kinetics, chemical bonds, non-uniformity, optical properties, and internal stress at different RF powers and electrode gaps. The test results show that NH₃, with its lower dissociation energy, avoids the high activation barrier associated with pure N₂ plasma, leading to a higher reactive nitrogen flux and a doubled deposition rate. In the SiH₄/NH₃/N₂ system, raising RF power from 300 W to 900 W reduced hydrogen content from 23.58% to 12.25%. This suppression of hydrogen promoted structural densification, shifting the mechanical stress from 173.3 MPa to −989.7 MPa. At a larger electrode gap of 19 mm, NH₃’s better diffusion characteristics offset the electric field sensitivity typical of N₂ systems, reducing large-area film non-uniformity by 28.7% compared to a 13 mm gap. This work offers a practical, mass-production-friendly approach for depositing robust, low-hydrogen, highly uniform silicon nitride films at low temperatures. 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

In gas-condensate reservoirs, the phase behavior of reservoir fluids is inherently dynamic during pressure depletion. When the rate of external pressure decline exceeds the intrinsic relaxation rate governing phase equilibrium, the system deviates from thermodynamic equilibrium and exhibits pronounced non-equilibrium effects. These transient behaviors significantly influence fluid properties; meanwhile, conventional equilibrium models neglect phase transition lag, resulting in inaccurate phase behavior and biased production predictions. In this study, a non-equilibrium dynamic phase transition model is developed to quantitatively couple the pressure depletion rate with the relaxation kinetics of the system. This model, established based on controlled non-equilibrium phase transition experiments performed on the condensate-gas fluid investigated in this work, provides an analytical framework for describing the temporal evolution of phase behavior under dynamic conditions. Model validation through integrated experimental measurements and numerical simulations shows good agreement between calculated and measured results for the studied condensate-gas system, with average relative errors below 5%. Results reveal that accelerated pressure depletion strengthens non-equilibrium effects. At a rate of 15 MPa/h, the relative volume and retrograde condensate saturation decrease by 9.09% and 5.38%, respectively, while condensate recovery improves by 13.85%. Moreover, the characteristic relaxation time toward equilibrium exhibits a strong dependence on the depletion rate, increasing as the depletion rate rises. This work provides an experimentally constrained analytical framework for describing rate-dependent non-equilibrium phase behavior during pressure depletion and for interpreting its impact on condensate recovery in the specific condensate-gas system studied. Although the governing framework may be transferable to other rate-sensitive hydrocarbon systems after fluid-specific recalibration, the parameterized analytical model and validation presented in this study are limited to the investigated condensate-gas fluid, and its applicability to other hydrocarbon fluid types remains to be evaluated in future studies. Full article

The volumetric mass transfer coefficient ($k_{L}a$) governs the design, operation, and scale-up of aerobic bioprocesses, yet its dependence on reactor geometry, impeller design, operating conditions, and fluid properties limits prediction by empirical correlations. Machine learning (ML) improves accuracy but faces two barriers in bioprocess practice: selecting the best model among many candidates requires expertise, and small, highly multicollinear data make models chosen based on test error alone prone to overfitting. Using a browser-based, no-code platform, we trained 14 regression algorithms under an identical pipeline on a published $k_{L}a$ dataset, and introduced a composite objective, the generalization-penalized error (GPE), which is the test RMSE plus the absolute train–test RMSE gap. Minimizing GPE rather than test RMSE expanded the top statistically equivalent group to include not only boosting ensembles but also simpler, interpretable models, indicating that black-box models hold no clear advantage once train–test consistency is assessed. Sensitivity analysis showed that tree models produce discontinuous responses, whereas algebraic learning via elastic net (ALVEN) yields smooth surfaces. Shapley additive explanations (SHAP) and an ontology graph, interpreted by a retrieval-augmented language-model agent, identified rotational speed and gas flow rate as dominant, reproducing the established mass transfer mechanism. The framework offers a reproducible, interpretable, expertise-light route to bioprocess model selection. Full article

The Chang 8 tight oil reservoir in the Xifeng area of the Ordos Basin is characterized by poor reservoir properties, making conventional water flooding ineffective for efficient reservoir development. CO₂ flooding is therefore considered an important approach for enhancing oil recovery in tight reservoirs. However, suitable development strategies for direct CO₂ injection in undeveloped reservoir areas remain insufficiently understood. In this study, compositional numerical simulation combined with a single-factor sensitivity analysis was employed to investigate the effects of key parameters, including well pattern configuration, fracturing parameters, injection–production strategy, and gas injection modes. The results indicate that an inverted nine-spot well pattern with vertical well injection and vertical well production, a well spacing of 500 m, and a row spacing of 200 m can achieve relatively favorable areal and vertical sweep performance. A fracture half-length of 80 m, fracture widths of 0.003–0.005 m, and fracturing treatment before initial production help balance early-stage productivity and gas channeling control. Maintaining an injection rate of 0.03–0.04 PV/a, an oil production rate of 2–3 m³/d, and a bottomhole flowing pressure of 13–14 MPa is beneficial for maintaining reservoir energy and stabilizing displacement-front propagation. Based on neighboring field development experience, switching from continuous CO₂ injection to water–alternating–gas (WAG) injection during the mid-development stage can improve mobility control and enlarge the CO₂ swept volume. Under the current geological model and simulation conditions, the recommended development strategy predicts a recovery factor of 35.43% over a 30-year production period. The results provide reasonable parameter ranges and an engineering reference for direct CO₂ flooding development in the Chang 8 tight oil reservoir and similar reservoirs. Full article

During the operation of underground natural gas storage, drastic wellbore temperature and pressure fluctuations impose complex and variable loads on cement sheaths. This impairs cement sheath sealing integrity, triggers fluid leakage along interfacial gaps and continuous annular pressure rise, severely threatening the operational safety of gas storage injection–production wells. Based on the analysis of potential gas leakage paths in injection–production wells of underground gas storage, a calculation model for annulus pressure buildup induced by cement sheath leakage of gas storage wells is established with consideration of influencing factors, including formation pressure, annulus temperature, and cement property parameters. Model verification indicates that the maximum relative error of the test well is 9.20%, the average relative error is 2.64%, the mean absolute error (MAE) is 0.08 MPa, and the average root-mean-square error (RMSE) is 0.09 MPa. Calculations for field case wells are performed to quantitatively predict the variation in annulus pressure, followed by sensitivity analysis on the annulus pressure buildup of the studied wells. Formation pressure and cement permeability act as core controlling factors, positively correlating with annular pressure. In contrast, temperature exerts a relatively minor influence on annulus pressure. Optimized cementing design and reduced cement permeability can effectively mitigate leakage-induced annular pressure. The proposed model and findings offer reliable theoretical support for annular pressure management and safe long-term operation of gas storage wells. Full article

Characteristic gas-based detection technology can facilitate the warning of lithium-ion battery thermal runaway with a high accuracy at an early stage. Microelectromechanical system (MEMS) metal–oxide–semiconductor (MOS) gas sensors have advantages of a low cost, a high accuracy, and low power consumption; therefore, they are ideal candidates for the lithium-ion battery thermal-runaway warning. MEMS MOS gas sensors are composed of a micro-hotplate and gas-sensitive materials. The micro-hotplate component strongly influences the device’s mechanical and thermal properties. Initially, we used COMSOL to optimize the micro-hotplate component. Then, we fabricated the device based on the optimal micro-hotplate. Next, gas-sensitive materials made of ZnO and ZnO-Au were deposited on the micro-hotplate by radio-frequency magnetic sputtering. The self-made and commercial MEMS MOS sensors were integrated to form an electronic nose. The as-made electronic nose can classify hydrogen, ethylene, acetylene, methane, carbon monoxide, and ethanol with a maximum accuracy of 99.4% using gas response data acquired over only 20 s. The reported work can provide a solution for an early and accurate lithium-ion battery thermal runaway warning. Full article

Gallium oxide (Ga₂O₃) is emerging as a promising material for X-ray detectors due to its high sensitivity, high melting point, and stable physicochemical properties. However, intrinsic background shallow donors in raw materials hinder the preparation of high-resistance intrinsic crystals, making doping essential to tailor electrical properties. This study grew Ti³⁺-doped β-Ga₂O₃ single crystals via the Edge-defined Film-fed Growth (EFG) method using Ti₂O₃ as a dopant, achieving high resistivity and a moderate reduction in bandgap. High-resolution X-ray diffraction (HRXRD) showed a rocking curve full width at half maximum (FWHM) of 96.50 arcsec. Compared with the unintentionally doped (UID) crystal, the bandgap exhibited a slight reduction, decreasing from 4.76 eV to 4.59 eV. In the infrared transmission spectra, the onset wavelength of the decrease in transmittance for the Ti³⁺: β-Ga₂O₃ crystal showed a distinct redshift relative to that of the UID crystal, indicating effective suppression of free electrons within the crystal. X-ray photoelectron spectroscopy (XPS) revealed that Ti³⁺ incorporation minimally affected the valence states of Ga and O or the Ga/O ratio, with no significant shift in valence band maximum (EVBM). A metal–semiconductor–metal (MSM) structured X-ray detector fabricated on polished Ti³⁺: β-Ga₂O₃ (100) substrate with Ti/Au electrodes exhibited a peak sensitivity of 943.16 μC/(Gy·cm²) at 40 V bias and 2.944 μGy/s dose rate, surpassing the upper sensitivity limit reported for semi-insulating doping bulk β-Ga₂O₃ detectors. The rise and fall times were 0.23 s and 0.30 s, respectively, with a minimum detectable limit (MDL) of 164.26 nGy/s, demonstrating its potential for high-performance X-ray detection applications. Full article

Emerging metallic radionuclides are expanding theranostic capabilities in nuclear medicine by improving diagnostic sensitivity, enabling dosimetry, and matched theranostic approaches. ¹⁴⁹Tb, ⁴⁴Sc, ⁵²Mn, ²⁰³Pb, and ⁵⁵Co offer distinct nuclear decay properties, including extended half-lives, variable positron emissions, and prompt γ-photons that may influence quantitative imaging performance. Cyclotron and generator routes integrating enriched targets and optimized separations support clinical-scale supply, while advances in chelation chemistry improve in vivo stability and imaging performance. Preclinical and early clinical data demonstrate that ¹⁴⁹Tb provides intrinsic α-therapy and PET imaging capability for theranostic use, ⁴⁴Sc enables extended imaging relative to ⁶⁸Ga, supporting delayed imaging and improved tumor-to-background contrast for peptide-based radiopharmaceuticals and theranostic applications. ⁵²Mn supports prolonged biological tracking for antibody- and engineered-protein-targeted studies, whereas ²⁰³Pb serves as a diagnostic surrogate for ²¹²Pb based α-therapy (via ²¹²Bi). ⁵⁵Co PET imaging supports the development and evaluation of ^58mCo Auger electron therapy. Current challenges include limited global availability of highly enriched targets, management of long-lived radioactive by-products, and the need for standardized dosimetry and regulatory pathways to ensure reproducibility and safety. Ongoing developments in automated target handling, optimized separations, next-generation chelators, and harmonized regulation may facilitate broader clinical translation. Full article

This paper presents the design, fabrication, and characterization of a sub-milliwatt graphene-based micro thermal conductivity detector (µTCD) that utilizes a suspended multilayer graphene (MLG) bridge to sense volatile organic compounds (VOCs) in the gas phase based on their thermal transport properties. The graphene bridge is transferred onto a silicon chip with integrated microchannels using a photolithography-free process. By incorporating microchannel designs, this approach enables precise transfer of suspended MLG dimensions without conventional patterning steps. A key innovation of this work lies in the use of an ultra-low thermal mass suspended graphene architecture, which significantly increases temperature rise per unit input power, thereby enhancing sensitivity per unit power compared to conventional metal-based TCDs. The fabricated µTCD successfully produces chromatograms of multiple VOC species, closely matching those obtained using a standard flame ionization detector (FID). The device demonstrates an estimated limit of detection (LOD) of 190 ppm while consuming an average power of 151 µW under DC operation. Full article

Thermal transient testing (TTT) is an essential technique for characterizing electronic systems, including packaged devices, modules, and subassemblies. These tests serve two closely related purposes: first, they enable determination of peak operating temperatures under various power conditions; on the other hand, they allow extraction of partial thermal resistances within the tested structure and identification of structural details near the active devices. The latter objective has become increasingly challenging with the advent of wide bandgap devices featuring extremely low on-state resistance, such as GaN HEMTs. This paper first identifies the temperature-sensitive electrical parameters and heater structures relevant for TTT of semiconductor devices. It then narrows the focus on GaN power devices and analyzes how external series resistances, originating from HEMT packages and the associated printed circuit boards, affect thermal impedances and structure functions. To remove the influence of these external resistances, which distort the extracted thermal descriptors, an analytical correction methodology has been developed. The proposed approach is validated through measurements performed on real devices. The results demonstrate that the method successfully restores the intrinsic thermal properties of the devices, yielding more accurate and physically meaningful thermal characteristics. Full article

In this study, metal (copper, nickel, cobalt, chromium)-decorated ZnO nanorods are successfully grown on glass substrates via a hydrothermal synthesis method to test their electrical and gas-sensing properties. SEM images revealed the formation of metal nanoparticles surrounding the ZnO nanorods. To confirm that these structures originated from the metal nanoparticles, EDX analysis was performed, and the presence of metal nanoparticles was validated. XRD analysis indicated that the crystal structure of the ZnO nanorods was hexagonal, and shifts in the (002) plane were observed due to metal nanoparticle doping. ZnO nanorods functionalized with metal nanoparticles were tested at 200 °C against various gases (hydrogen, ethanol, chloroform) and at different gas concentrations. The time-dependent variation in current was observed when ZnO nanorods functionalized with metal elements were exposed to hydrogen gas at test concentrations ranging from 1000 ppm to 5000 ppm at 200 °C. The results demonstrated a clear correlation between the rate of current change and hydrogen concentration, with higher concentrations resulting in faster responses. Additionally, the sensitivity of ZnO nanorods with decorated metal nanoparticles to ethanol and chloroform gases at concentrations ranging from 1000 ppm to 5000 ppm, as well as their sensor responses to different gases at 200 °C, were also measured. Full article

Achieving a circular and climate-neutral bioeconomy by 2050 requires not only high-quality recycling but also the large-scale integration of renewable carbon from biomass and atmospheric CO₂ into material systems. Plastics represent the world’s largest and most rapidly growing carbon sink, positioning them as a critical intervention point for replacing fossil-based feedstocks with renewable alternatives. Because plastic packaging is one of the most visible material streams encountered by consumers in daily life, a transition toward sustainable, recyclable bioplastics has the potential to deliver both meaningful environmental benefits and strong societal impact, accelerating public awareness and acceptance of renewable carbon solutions. Poly(ethylene furanoate) (PEF)—a fully bio-based polyester synthesized from plant-derived 2,5-furandicarboxylic acid (FDCA) and monoethylene glycol (MEG)—offers a promising pathway toward more sustainable packaging due to its superior mechanical strength and gas-barrier performance relative to polyethylene terephthalate (PET). This study presents a cradle to grave life cycle assessment (LCA) of PEF resin production and PEF bottle applications, using industrially relevant, at-scale process data covering biomass feedstock conversion, polymer synthesis, packaging manufacture, use phase, and end of life. Bottle applications were selected as a focal point due to their technical maturity, commercial relevance, and suitability for direct comparison with incumbent PET systems. The results indicate that PEF can reduce greenhouse gas emissions by up to 71% and fossil resource depletion by 26% compared to PET at the resin level when biogenic carbon uptake is included. Moreover, the material’s enhanced functional properties enable lightweight, recyclable bottle designs with carbon footprint reductions of up to 88% for 500 mL formats under a baseline recycling rate scenario of 72%, with the remaining share directed to municipal solid-waste incineration with energy recovery. Sensitivity analyses reveal that virgin PEF maintains environmental advantages over PET even when PET incorporates high levels of recycled content, highlighting the complementary roles of renewable carbon and circular material strategies. Prospective scenario modeling underscores the importance of sustainable feedstock selection and process electrification, with sucrose-based routes offering the largest potential for further decarbonization. Overall, the findings demonstrate that PEF is a scalable biopolymer capable of delivering substantial climate benefits while supporting circularity objectives. By targeting a highly visible consumer application—plastic packaging—this transition amplifies the societal impact of adopting renewable carbon materials. The study provides actionable insights for policymakers, industry stakeholders, and sustainability practitioners working to advance a more resilient, renewable, and consumer-recognizable plastics economy. Full article