Results 81 to 90 of about 1,839 (214)
Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction
Advanced Science, EarlyView.We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen +3 more
wiley +1 more source
Degradation Pathways of Silicon‐Based Anodes in Lithium‐Ion Batteries
Advanced Energy Materials, EarlyView.Silicon‐based anodes undergo degradation through five primary pathways: (1) mechanical and structural deterioration of the active material, (2) loss of electrode integrity and electrical contact, (3) mechanical instability of the solid electrolyte interphase (SEI), characterized by repetitive fracture and deformation, (4) chemical instability of the ...
Yoon Jeong Choi +3 more
wiley +1 more source
, 2022 In fluid flow simulation, the multi-continuum model is a useful strategy. When the heterogeneity and contrast of coefficients are high, the system becomes multiscale, and some kinds of reduced-order methods are demanded.
Mai, Tina +2 more
core +1 more source
A Generalized Multiscale Finite Element Method for poroelasticity problems I: Linear problems
Journal of Computational and Applied Mathematics, 2016 arXiv admin note: text overlap with arXiv:1309.6030 by other ...
Donald L. Brown, Maria V. Vasilyeva
openaire +3 more sources
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
Advanced Energy Materials, EarlyView.In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Some Applications of the Generalized Multiscale Finite Element Method [PDF]
, 2018 Many materials in nature are highly heterogeneous and their properties can vary at different scales. Direct numerical simulations in such multiscale media are prohibitively expensive and some types of model reduction are needed.
Fu, Shubin
core
Advanced Energy Materials, EarlyView.Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
A Generalized Finite Element Method for Linear Thermoelasticity [PDF]
, 2017 We propose and analyze a generalized finite element method designed for linear quasistatic thermoelastic systems with spatial multiscale coefficients.
Persson, Anna +6 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source
, 2019 In this research, we develop an online enrichment framework for goal-oriented adaptivity within the generalized multiscale finite element method for flow problems in heterogeneous media.
Pollock, Sara +2 more
core +1 more source