Browse Articles

High temperature Nb-Si alloys using data science: optimization of fracture toughness and high-temperature strength

Abstract High temperature Nb-Si based alloys face a critical challenge: achieving adequate room-temperature fracture toughness ( > 18 MPa·m 1/2 ) for processing while maintaining high-temperature strength, properties that typically compete with each other. Here, we overcome this inherent trade-off through machine learning-guided alloy design, employing a three-step feature screening strategy to identify 6 key descriptors from 200 initial features. SHAP analysis reveals how melting enthalpy and atomic radius mismatch control property outcomes, enabling targeted multi-objective optimization via NSGA-II algorithm. The optimized Nb-12.26Si-21.35Ti-1.98Al-1.96Cr-0.51Hf-4.34Zr-4.35 V alloy achieves an as-cast fracture toughness of 18.92 MPa·m 1/2 while maintaining 322 MPa strength at 1250 °C, surpassing all reported as-cast Nb-Si alloys. Microstructural analysis shows that the superior properties originate from the dispersed distribution of nanoscale γ′-Nb 5 Si 3 phase and crack deflection at phase boundaries with 67.6% lattice mismatch. Our results demonstrate that combining machine learning techniques with mechanistic understanding can accelerate the discovery of high temperature materials.

Accurate orange yield estimation using a novel dataset, fine-tuned deep learning models, and vision-LLM benchmarking

Structural evolution of iron oxides melts at Earth’s outer-core pressures

Abstract Oxygen and other light elements comprise up to 5 wt% of the Earth’s outer-core, and may significantly influence its physical properties and the operation of the geodynamo. Here we report in situ X-ray diffraction measurements of Fe, Fe + 4.5 FeO (atomic proportion), and Fe 2 O 3 melts at 177-440 GPa, achieved using laser-driven shock compression at an x-ray free-electron laser. The melts exhibit Fe-O coordination numbers between 4.0(0.4) and 4.5(0.4), indicating predominantly four-fold coordination environments. These coordination states are significantly smaller than those of Fe-bearing lower-mantle phases such as bridgmanite and ferropericlase. Shorter Fe-Fe interatomic distances in compressed iron oxide melts drive the denser packing relative to ambient melts, while the structural differences between Fe + 4.5 FeO and Fe 2 O 3 melts under shock indicate that the oxidation state modulates oxygen solubility in liquid Fe. At 177 GPa ( ~ 380 km below the core-mantle boundary) and 3800 K, Fe 2 O 3 melts exhibit higher Fe-O coordination, suggesting that local variations in oxygen content could contribute to the stratification in the uppermost outer-core inferred from seismological and geomagnetic observations.

Federated generative adversarial network with hybrid transformer-GRU and explainable AI for financial fraud detection

Reversible hydrogen storage in reactive hydride composites under 400 K

Abstract Hydrogen storage remains a key challenge for widescale adoption of hydrogen as an energy vector. Lightweight complex hydrides offer high storage densities but suffer from hydrogen release/cyclability above the temperatures required for practical use. Here, we report on discoveries in ternary Reactive Hydride Composites (RHCs). We systematically tuned the LiBH₄ content in the well-established Mg(NH₂)₂ - LiH framework, achieving reversible hydrogen release at temperatures starting below 393 K and a capacity of 3.1 wt%; a decrease of 100 K compared to the Mg(NH₂)₂ - LiH system.This is a crucial step towards the use of complex hydride-based hydrogen carriers for stationary and onboard hydrogen storage applications. We demonstrate a reversible RHC within the utilisation range of low-grade waste heat from a fuel cell, alongside offering insight into the reaction pathways in these RHCs to inform the design of future materials.

Fuzzy robust model predictive fault tolerant control in wind turbine based on ST-SMO and PMIO

Abstract Conventional wind turbine maintenance relies on post-failure diagnosis, yet sustained degraded operation remains critical. This paper proposes a fault-tolerant model predictive control (MPC) framework with switching between a super-twisting sliding mode observer (ST-SMO) and a proportional multiple integral (PMI) dual observer system. In the observation layer, the PMI observer estimates unmeasured states and various faults, while the ST-SMO specifically compensates for high-order pitch angle faults. A Takagi-Sugeno (T-S) fuzzy logic based on the $$\nu$$ -gap metric coordinates the two observers. Adaptive penalty terms in the MPC layer compensate deviations via a linear parameter-varying model. Multi-scenario case studies validate the framework under load-range transitions and simultaneous multi-fault conditions. Compared with single-observer FTC methods and conventional MPC, the proposed framework improves maximum power tracking accuracy by 18% under sensor faults, suppresses drivetrain torsional torque fluctuation by 50% under cross-load switching, and reduces tower bending moment damage equivalent load (DEL) by 19.63% under multi-fault conditions. It innovatively integrates dual observers with T-S fuzzy logic and hard-soft combined LPV switching, achieving synergistic optimization of fault tolerance, fatigue load mitigation, and active power maximization for megawatt-class wind turbines under multi-fault coupling and cross-load transitions.

Intracellular iron homeostasis-regulated epigenetic reprogramming contributes to −7/del(7q) leukemia

A regime-aware framework for runoff prediction in ungauged basins via self-supervised learning of hydrometeorological drivers

Stabilizing 1.93-eV ultrawide-bandgap perovskites for efficient triple-junction solar cells

Population-based incidence trends and surgery-associated survival among patients with synchronous lung metastases across solid tumors from 2010 to 2022

Spin-controlled enantioselective near-infrared photocatalysis with chiral MgO/Co3O4 nanoparticles

Integrated technical and tactical demands during peak match demands in soccer players

Phase engineering of atomically thin magnetic chromium tellurides via molecular beam epitaxy

Stabilization of two dimensional switched systems with unstable modes based on the weighted average dwell time strategy

Dynamic acoustic-to-categorical representations of phonemes and prosody along ventral and dorsal speech streams

Abstract Phonemes and prosodic contours are fundamental elements of speech used to convey complementary meanings. Perceiving these elements requires mapping variable acoustic cues onto discrete categories along ventral and dorsal speech streams. While traditional models make clear predictions, exactly where and when this acoustic-to-categorical mapping occurs remains unclear. Using magnetoencephalography and behavioural psychophysics, combined with time-resolved representational similarity and multivariate transfer entropy analyses, we show how phonemes and prosody propagate along the dual streams and how their categorical representations are gradually formed. Contrary to theoretical predictions, acoustic and categorical representations occur in parallel, rather than serially, across time and space for both elements. Moreover, prosody categories extend further along both streams than phoneme categories, with differently weighted contributions of posterior temporal areas. These results highlight a shared principle of parallel acoustic and categorical processing, yet partially distinct abstraction mechanisms for phonemes and prosody, key to access the multilayered meaning of speech.

Performance evaluation of TCP congestion control variants across application workloads in cloud based networks

Arginine methyltransferase PRMT1 equipoises trophoblast development to prevent early pregnancy loss

Correction: Hybrid intelligent RSM–ANN modeling and optimization of precision turning of CK45 steel for calibration devices

A unifying equation for fermentation sustainability across the titer-rate-yield landscape

Abstract Industrial fermentation is central to the sustainable production of fuels and chemicals, yet commercial viability of emerging technologies hinges on improving fermentation titer, rate, and yield (TRY). How these metrics shape system cost remains difficult to generalize due to complex interactions among feedstocks, fermentation, separations, catalytic upgrading, waste management, and facility design. Here, we systematically map theoretical fermentation performance spaces (formed by all potential TRY combinations) for 32 representative biomanufacturing facilities—spanning distinct choices for feedstocks, fermentation regimes and products, separations, and catalytic upgrading—by simulating and evaluating them (via techno-economic analysis, TEA) under uncertainty (600,000 Monte Carlo simulations) and across TRY combinations (7500 TRY combinations for each of 32 configurations). Across this wide design and thermodynamic simulation space, we find the relationship between fermentation TRY and system cost is captured by a simple, generalizable mathematical equation (R 2 of 0.992 − 1.000 across our simulations; 0.954 − 1.000 when validated against prior studies that used different tools). We use this equation to elucidate key drivers that shape cost sensitivity to fermentation performance, generating widely applicable insights. By demonstrating a unifying relationship governs the impact of fermentation on biomanufacturing economics, this work establishes a foundation for agile, holistically predictive, resource-efficient strategies to prioritize fermentation research and development needs and accelerate commercialization of emerging biomanufacturing technologies.

Closed-loop constraint model for emergency care in county medical alliances: grounded theory study in western China’s underdeveloped multiethnic region

Abstract Increasing emergency medical service (EMS) capacity within integrated delivery systems is essential for universal health coverage, particularly in low- and middle-income countries. However, in underdeveloped ethnic regions of western China, developing EMS capacity within county-level medical alliances (CLMAs) remains a critical challenge. Using classic grounded theory, we conducted semistructured interviews with 47 health care professionals from 11 CLMAs across Guangxi, a representative underdeveloped, multiethnic, mountainous region. Systematic three-level coding of 575 statements revealed 57 initial concepts, 15 categories, and four core dimensions: institutional deficiencies (root cause), inefficient coordination (key bottleneck), resource shortcomings (direct manifestation), and service efficacy constraints (final outcome). These dimensions form a closed-loop constraint model reinforced by reverse feedback. Crucially, service efficacy constraints—specifically, poor emergency care quality and collective public cognitive bias—do not merely represent outcomes but actively reinforce the institutional deficiencies that generated them, trapping the system in a low-level equilibrium. This finding explains why piecemeal interventions fail. Effective strengthening requires simultaneously targeting all four dimensions to disrupt the negative cycle, a transferable strategy for integrated health systems facing analogous constraints worldwide.