Results 91 to 100 of about 3,858 (249)

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Thermal degradation of pinus caribe wood treated with CCA salts

Revista Técnica de la Facultad de Ingeniería, 2004
En este trabajo se reporta el estudio comparativo de la degradación térmica de la albura de Pinus caribaea var hondurensis tratada (PCHT) con sales de cromo-cobre-arsénico (CCA) como preservante, a dos niveles de retención de 4.4 Kg/m³ y de 12.6 Kg/m³,con la madera PCH sin tratamiento (PCHST).
Toro, M.E., Rincón, A., Torres, C
openaire   +4 more sources

Deciphering Short‐Range Order in 2D Transition Metal Dichalcogenides: From Origin to Multi‐Scale Property Modulation

Advanced Science, EarlyView.
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu, Linggang Zhu, Jian Zhou, Zhimei Sun   +3 more
wiley   +1 more source

Engineering Microbial Particles for Next‐Generation Biomedical Platforms

Advanced Science, EarlyView.
Microbe‐derived particles (MDPs), which include extracellular vesicles, outer membrane vesicles, inclusion bodies, polysaccharide particles, and virus‐like particles, represent a rapidly expanding category of bioinspired nanomaterials. With their natural origin, intrinsic biocompatibility, and highly programmable functionality, MDPs serve as a ...
Yuting Li, Yunjie Lu, Ziyan Huang, Jianjiang Chen, Yanbin Liu, Lei Qin, Chao Wang, Yumin Wu   +7 more
wiley   +1 more source

Functional Disorder at the Neural Interface: How Disordered Nanostructures Promote Proper Growth and Differentiation in In Vitro Neural Cultures

Advanced Science, EarlyView.
This work provides a practical guide for neuroengineers to design advanced neural interfaces, embracing and tailoring the concept of functional disorder. By bridging 2D and 3D in vitro models, this work highlights how non‐periodic, spatially heterogeneous, multiscale nanotopography can enable more physiologically relevant platforms for studying neural ...
F. Maita, E. Palmieri, I. Lucarini, L. Montaina, L. Maiolo   +4 more
wiley   +1 more source

Decay Resistance Variability of European Wood Species Thermally Modified by Industrial Process [PDF]

Pro Ligno, 2017
Thermal modification is now considered as a new ecofriendly industrial wood modification process improving mainly the material decay resistance and its dimensional stability.
Kevin CANDELIER, Luc PIGNOLET, Sylvain LOTTE, Alban GUYOT, Benjamin BOUSSEAU, Etienne CUNY, Marie-France THEVENON   +6 more
doaj  

Multidimensional and Multifunctional Laser‐Induced Graphene (LIG) for Point‐of‐Care and Wearable Biosensing, Theranostics, and Bioactive Interfaces Toward Personalized Healthcare and Regenerative Medicine

Advanced Science, EarlyView.
Multidimensional laser‐induced graphene (LIG) spanning from 0D to 3D architectures is comprehensively reviewed for multifunctional biomedical platforms, including biosensing, theranostics, and bioactive interface applications, which highlights its potentials for point‐of‐care diagnostics, wearable health monitoring, smart drug delivery, and tissue ...
Li Zhang, Yurou Yuan, Xiaohong Ding, Wing Cheung Mak   +3 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

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

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