Results 11 to 20 of about 44 (43)

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

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, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Sports Activity Recognition Using Textile‐Based Sensor Fusion and Complex‐Valued Residual Convolutional Neural Networks

Advanced Intelligent Systems, EarlyView.
Motion artifacts in electrocardiographic signals, conventionally dismissed as noise, are shown to encode discriminative activity information. A smart t‐shirt fusing textile strain sensors with textile ECG electrodes, processed through a complex‐valued residual network, recognizes 12 sport activities.
Nada Al‐azzawi, Munire Sibel Cetin, Asli Tuncay Atalay, Ozgur Atalay, Gökhan Ince   +4 more
wiley   +1 more source

Compact Manifolds With Unbounded Nilpotent Fundamental Groups and Positive Ricci Curvature

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT It follows from the work of Kapovitch and Wilking that a closed manifold with nonnegative Ricci curvature has a uniformly almost nilpotent fundamental group. Leftover questions and conjectures, have asked if in this context the fundamental group is actually uniformly almost abelian. The main goal of this work is to construct examples (Mk9,gk)$(
Elia Bruè, Aaron Naber, Daniele Semola
wiley   +1 more source

Predicting Functional Diversity Within Enzyme Families: A Practical Perspective

ChemBioChem, Volume 27, Issue 19, 14 October 2026.
Integrating machine learning into enzyme discovery requires navigating the trade‐offs between data quantity and quality. This article provides a best‐practice framework for developing robust predictors, focusing on mitigating bias in biochemical datasets, implementing systematic “cold‐drug” validation strategies, and utilizing explainable artificial ...
Nika Sokolova, Kristina Haslinger
wiley   +1 more source

A Multi‐Scale Computational Framework for Anti‐Persister Tuberculosis Drug Discovery

Chemical Biology &Drug Design, Volume 108, Issue 4, October 2026.
This review presents an integrated QSAR–scaffold design–docking–MD framework for discovering anti‐persister tuberculosis agents active in dormant granuloma‐like conditions. By targeting Mtb bioenergetics and prioritising dual NDH‐2/cytochrome bd oxidase inhibition, the workflow advances rational design of candidates with higher resistance barriers ...
Said Moshawih, Anguraj Moulishankar, Chee Yan Choo, Khang Wen Goh, Chrismawan Ardianto, Azam Che Idris, Long Chiau Ming   +6 more
wiley   +1 more source

A conversation with James V. Zidek

Canadian Journal of Statistics, Volume 54, Issue 3, September 2026.
Abstract This article documents a series of exchanges between the authors and the senior Canadian statistician Jim Zidek in early 2026. The interview traces his life trajectory, surveying his principal contributions to statistics while offering insights into his motivations, successes, and challenges.
Christian Genest, Nancy E. Heckman
wiley   +1 more source

AI‐Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox‐Active Molecules to Polymer Electrolytes

Macromolecular Materials and Engineering, Volume 311, Issue 9, September 2026.
AI is reshaping the design and modeling of organic electrochemical energy materials, from redox‐active molecules to polymer electrolytes. Progress across data‐driven prediction, machine‐learning interatomic potentials, generative models, and agentic workflows is assessed, while persistent challenges in data quality, polymer representation, validation ...
Zhan‐Yun Zhang, Giannis Savvas, Jichen Li, Yue Zhou, Thanh Trung Le, Daniel Brandell, Rocío Mercado, Chao Zhang   +7 more
wiley   +1 more source

Mixture‐Quantitative Structure–Property Relationship Approaches for Jet Fuel‐Component Blends: A Review

Molecular Informatics, Volume 45, Issue 9, September 2026.
A literature review of QSPR approaches to predict jet fuel properties. It exposes the fundamental principles of QSPR and illustrates pure‐compound QSPR through examples of applications for jet fuel components. Mixture‐QSPR (M‐QSPR) modeling specificities are addressed: mixtures representation, design of descriptors for mixtures, and impact on internal ...
Erik Yeghyan, Benoit Creton, Mickaël Matrat, Gilles Marcou   +3 more
wiley   +1 more source