Results 191 to 200 of about 1,081,152 (292)

In-situ ceramic nanoparticle assembly within wood microstructure for strong, tough, and resilient ceramic wood. [PDF]

Nat Commun
Du F, Tian Y, Niu Z, Cai K, Duan J, Guo H, Yang R, Zhang Y, Marquez JA, Zeng H, Liu X, Wang Q, Tao C, Ma H, Li T.   +14 more
europepmc   +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

Synthesis of poly(4HB-co-PhLA) and poly(3HB-co-4HB-co-PhLA) as sustainable hot-melt adhesives using engineered Escherichia coli. [PDF]

Nat Commun
Kang M, Lee Y, Kim GB, Lee SY.
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

Structure-Property Relationships in Urea-Formaldehyde Bonded Napier Grass Composites: Influence of Lignocellulosic Chemistry on Interfacial Interaction and Thermal Stability. [PDF]

ACS Omega
Bairwan RD, Ying GY, Abdullah CK, Jeffri NI, Mohamad Khalid MSF, Edrus SSOA, Mohammad Rawi NF.   +6 more
europepmc   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Reconstitution of woody biomass framework via dual-functional lignin engineering toward efficient and salt-resistant solar desalination. [PDF]

Nat Commun
Wang B, He Y, Yang Z, Sun Q, Zhang X, Shen X, Wen JL, Chen C, Yuan TQ.   +8 more
europepmc   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Aqueous lignin adhesive for high-performance wood bonding. [PDF]

Sci Adv
Zhou X, Wang Y, Hu S, Ou R, Qi H, Lu F, Ralph J, Yue F.   +7 more
europepmc   +1 more source

Phase‐Resolved Dual Control of Phenol Photodissociation at the Air–Water Interface From Structure‐Resolved Statistics

Advanced Science, EarlyView.
Faster phenol photolysis at the air–water interface arises from two cooperative factors: a more favorable initial microenvironment for solvent‐side electron stabilization, which lowers CI access, and a more labile hydrogen‐bond network, which more readily reorganizes to stabilize the dark‐state intermediate.
Qiang Yin, Jialing Shi, Jinping Zhao, Chengjun Li, Yongbo Xie, Benkun Tan, Da Wang, Ziyun Wang, Yu Mao   +8 more
wiley   +1 more source