Diamond demonstrates significant application potential in electronic devices owing to its excellent properties, yet its practical application is often limited by interface challenges in precisely controlling its interfacial electronic properties. This study demonstrates that surface termination engineering serves as a potential strategy for effectively modulating the electron affinity (EA) of diamond, thereby tuning the band offsets and Schottky barrier heights (SBHs) at its interfaces. By constructing 24 distinct diamond termination models, the EA of diamond can be tuned from -3.95 to 2.71 eV, governed by the combined effects of surface dipole moment and gap states. Furthermore, the terminated diamond forms a charge-blocking layer at the heterojunction interface, thereby largely preserving the original band positions. Consequently, a linear modulation of the band offset from 0.58 to 4.34 eV is accomplished by integrating beta-Ga2 O3 with 12 different diamond terminations. For metal/diamond contacts, an SBH adjustment from -0.78 to 2.14 eV is achieved at Pt/diamond interfaces by employing different terminations. Notably, the introduction of surface-state-free terminations effectively suppresses metal-induced gap states, thereby achieving significant Fermi-level depinning. This work elucidates the underlying mechanism of termination-induced EA tuning and establishes a paradigm for quantitative band offset and SBH control, providing critical guidance for the rational design of high-performance diamond-based devices. (c) 2026 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.
Large Language Models (LLMs) are rapidly transforming intelligent healthcare and medicine. However, their successful clinical deployment depends on reliable and explainable medical reasoning rather than surface-level text generation. This survey reviews LLM reasoning in medicine. It covers foundational datasets, training-time optimization, test-time reasoning, collaborative agents, and reasoning evaluation. We distinguish two complementary design axes. Individual-model optimization improves the reasoning behavior of a model or module through supervised fine-tuning, reinforcement-based fine-tuning, or test-time control. Collaborative-agent design specifies how one or more such modules exchange evidence, invoke tools, and aggregate decisions at the system level. Collaborative-agent design does not replace individual-model optimization. Contemporary agent systems commonly compose prompted or individually trained modules, including SFT- and GRPO-optimized planners, routers, and aggregators. This compositional view clarifies both the promise and the current limitations of agents. Structured collaboration can support transparency, error recovery, and heterogeneous evidence integration in workflow-oriented tasks. However, it does not provide an inherent advantage over a strong single LLM on narrowly scoped questions. Combining individual-model optimization with collaborative-agent design offers substantial potential for advancing future medical intelligence.
Abstract Enhancing the durability of bituminous pavements requires effective antiaging additives for bitumen. However, the unclear differences in microstructure and performance enhancement among various additives hinder their optimization and application. This study evaluates the effects of four antiaging additives on bitumen performance and aging resistance: antioxidant (AO), ultraviolet absorber (UVA), their combination (UVA+AO), and a novel zinc oxide/expanded vermiculite composite (ZnO/EV). Results show that unlike UVA and AO, which undergo structural changes in bitumen, ZnO/EV maintains structural stability and demonstrates superior ultraviolet absorption (about 20% higher than UVA) and thermal stability. These superior intrinsic properties translate into enhanced performance for ZnO/EV modified bitumen. ZnO/EV significantly increases bitumen stiffness and elastic response in the unaged state, improving resistance to permanent deformation while maintaining excellent low-temperature flexibility. Critically, ZnO/EV provides consistently superior short- and long-term aging resistance across all tested conditions, markedly reducing aging-induced changes (e.g., softening point increment, viscosity aging index). In contrast, the common additives show limitations: UVA can impair short-term aging resistance, AO provides only moderate improvement, and the UVA+AO compound fails to synergize effectively, underperforming ZnO/EV. This study conclusively demonstrates that ZnO/EV significantly outperforms conventional antiaging additives in both enhancing bitumen’s key performance properties and providing robust, multicondition aging resistance, highlighting its strong potential for durable pavement applications.
Strategically transmitting harvestable photons and reflecting non-useful photons are essential for photovoltaic (PV) efficiency improvement and temperature reduction. However, it remains a considerable challenge to develop spectrally selective thin-film structures that can maximize PV lifetime energy yield (EY) while maintaining structural simplicity and adequate manufacturability. Herein, a neural network surrogate-assisted genetic algorithm (NNSGA) framework is proposed to facilitate the design of spectrally selective structures. By incorporating spectral utilization weight (SUW) of PV modules, the optimization is guided toward a more effective search direction. Optimal thin-film structures under different design weights are identified using NNSGA with a large population by further leveraging the surrogate model for accelerated prediction. The results reveal that, by adopting SUW, high-performance structures with superior above-bandgap transmittance and below-bandgap reflectance can be designed. Additionally, an extra PDMS top layer degrades the spectral selectivity while introducing an additional heat source, resulting in non-beneficial or deteriorated performance, despite the emissivity compensation. Furthermore, owing to the inherently high transmittance of the air/glass interface, weight of transmission waveband (TWB) must exceed 0.8 to maintain the current, and the operating temperature can only be reduced by about 2.30 °C, with approximately 0.52% efficiency loss under specific working conditions. Moreover, weight of TWB equal to 0.9 can maximize the performance of silicon PV modules. The 25-year cumulative EY can be improved by about 0.94%, mainly due to increased current rather than temperature reduction, where the lifetime EY of silicon PV modules can be enhanced by approximately 3.40% when thermal degradation is accounted for.
Efficient thermal management is paramount for enhancing the power density and operational longevity of proton exchange membrane fuel cells. This study systematically investigates twelve feasible coupled coolant-reactant flow-direction configurations within the same three-stage segmented cooling-channel geometry featuring straight, wavy, and tapered sections. We propose a robust data-driven framework that integrates high-fidelity physical modeling, Bayesian surrogate modeling, and multi-objective genetic algorithms to decouple complex thermo-fluid mechanisms. Case 12 is identified as the best-performing flow-direction topology, reducing the average temperature uniformity index by 45.7% relative to Case 8 based on ten Latin-hypercube-sampled coolant velocity-temperature difference combinations under identical geometric and operating conditions. The subsequent optimization determines a synergistic operating window with a velocity of 1.989 m/s and a temperature difference of 6.109 K, yielding an additional 14.53% enhancement in thermal uniformity while sustaining a high current density. The thermo-hydraulic synergistic mechanism involves reshaping the thermal boundary layer via induced secondary Dean vortices and spatial acceleration while successfully avoiding diminishing returns. This work provides a systematic design framework for coordinated flow-orientation and operating-parameter optimization in proton exchange membrane fuel cell thermal management systems.
