Results 111 to 120 of about 4,642 (256)

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

Advanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao, Yiming Ma, Baihao Shao, Molly M. Stevens   +3 more
wiley   +1 more source

Fundamentals of Thermal Transport and Energy Conversion in Ultra‐High Temperature Ceramics: From Microscale Mechanisms to Macroscopic Properties

Advanced Science, EarlyView.
This review critically examines thermal transport and radiative properties of ultra‐high temperature ceramics for hypersonic flight, advanced nuclear systems, and next‐generation energy conversion devices. It explores phonon–photon–electron interactions, microstructural engineering, thermoelectric conversion, and machine learning‐accelerated multiscale
Zhipeng Pei, Yue Li, Jiayu Xing, Yue Zhu, Ru Zhang, Huan Wu, Zihao Qin, Gang Pei, Man Li   +8 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

GreenMix-pareto: Uncertainty-aware, physics-guided multi-objective optimization of low-carbon concrete mix designs

Ain Shams Engineering Journal
Concrete mix design increasingly requires balancing mechanical performance with climate and resource impacts. Most existing data-driven studies either optimize a single target (often strength) or report point predictions without calibrated uncertainty ...
Tarek Salem Abdennaji, Amel Ksibi, Aymen Flah, Vandna Batra, Rupesh Kumar Tipu   +4 more
doaj   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Use of empirical likelihood to calibrate auxiliary information in partly linear monotone regression models. [PDF]

Stat Med, 2014
Chen B, Qin J.
europepmc   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

Quantum Photothermal Self‐Monitoring Fiber Probes for In Vivo Photothermal Therapy

Advanced Science, EarlyView.
A miniaturized quantum photothermal fiber probe based on a metal/polymer/glass composite optoelectronic fiber that simultaneously guides lightwave and microwave was developed for the first time. The probe achieves enhanced photothermal conversion (13°C/mW, 25°C–120°C range) while providing real‐time self‐monitoring with 0.2°C thermal resolution at the ...
Wanjun Li, Ruixiao Hu, Jie Mao, Jin Wo, Yunsong Zhang, Liang Chen, Ying Liu, Zhibo Li, Yongxin Lin, Minghui Du, Yaofei Chen, Libing Zhou, Tuan Guo   +12 more
wiley   +1 more source

Impurity Tolerance in LiFePO4 Cathodes: Contrasting Structural, Electronic, and Electrochemical Roles of Residual Ni and Cr

Advanced Science, EarlyView.
Impurity tolerance in LiFePO4 cathodes varies strongly with impurity type and content. Low Ni levels are accommodated within the lattice with minimal structural disruption, whereas higher Ni contents introduce antisite disorder. In contrast, Cr impurities segregate from the LiFePO4 framework, blocking lithium‐ion pathways and leading to inferior ...
Minjin Kim, Hyerin Jeon, Jinhee Lee, Jinsub Choi   +3 more
wiley   +1 more source