Results 211 to 220 of about 4,674,723 (297)

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

LIF signaling pathway regulates the heterogeneous Sox2 transcriptional dynamics in mESCs. [PDF]

Sci Rep
Jin G, Porello EAL, Zhang J, Vidal JA, Lim B.   +4 more
europepmc   +1 more source

Modular design and supervisory control for enhanced economic resilience in continuous pharmaceutical manufacturing

AIChE Journal, EarlyView.
Abstract Conventional continuous plants use fixed‐capacity equipment, resulting in high capital risk and suboptimal performance under fluctuating demands. To address these, this study proposes an integrated framework for modular process design and supervisory control capable of adapting to demand uncertainty for long‐term economic viability.
T. Asrav, M. Alvarado‐Morales, G. Sin
wiley   +1 more source

Dynamics of soliton propagation: bifurcation, chaos, and quantitative insights into the modified Camassa-Holm equation. [PDF]

Sci Rep
Alam MN, Ahmed SF, Ismael HF, Firdi MD, Badruddin IA, Javed S.   +5 more
europepmc   +1 more source

Machine learning–driven design of catalytic processes for sulfur dioxide oxidation: Lessons from the trenches

AIChE Journal, EarlyView.
Abstract Despite the growing use of ML in chemical engineering, the catalytic conversion of sulfur dioxide (SO2) to sulfur trioxide (SO3) remains underexplored from a data‐driven modeling perspective. This study evaluates an integrated workflow for literature‐derived SO2 oxidation data, combining data curation, preprocessing assessment, machine ...
Farough Agin, Jules Thibault, Clémence Fauteux‐Lefebvre   +2 more
wiley   +1 more source

Noisy galvanic vestibular stimulation improves postural stability under virtual reality perturbation by enhancing vestibular processing and multisensory integration. [PDF]

J Neuroeng Rehabil
Xie H, Li Y, Hao Z, Zhao L, Chien JH, Wang C.   +5 more
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Soliton structures and dynamical characteristics of fractional nonlinear waves in the classical Boussinesq framework. [PDF]

Sci Rep
Rimu NN, Islam MA, Dey P.
europepmc   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source