Results 221 to 230 of about 142,307 (303)

Thermodynamics of finite-time processes: Final report, 1986--89

, 1989
Not Available
openalex   +2 more sources

Reaction kinetics model in liquid and solid phases and its parameterization for room temperature sodium–sulfur battery

AIChE Journal, EarlyView.
Abstract A multipore, multiphase, continuum model is assembled for the first time for room temperature sodium–sulfur (RT Na–S) batteries, with Na+ ion transport and redox reactions in the liquid electrolyte phase and semisolid phase of precipitates softened by the electrolyte solvent, as guided by molecular dynamics simulations in this study ...
Hakeem A. Adeoye, Allan Foster, John F. Watts, Constantina Lekakou   +3 more
wiley   +1 more source

Way More than the Sum of Their Parts: From Statistical to Structural Mixtures. [PDF]

Entropy (Basel)
Crutchfield JP.
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Optimizing optimal transport: Role of final distributions in finite-time thermodynamics [PDF]

Kakuji Tojo, Rihito Nagase, Ken Funo, Takahiro Sagawa   +3 more
openalex   +1 more source

Flexible Memory: Progress, Challenges, and Opportunities

Advanced Intelligent Discovery, EarlyView.
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan, Sen Chen, Minghui Guo, Ziliang Cui, Yujie Du, Jing Liu   +5 more
wiley   +1 more source

Quantum thermalization must occur in translation-invariant systems at high temperature. [PDF]

Nat Commun
Pilatowsky-Cameo S, Choi S.
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Theoretical Considerations for Patient-Specific Modeling Based on Observable State Variables. [PDF]

J Biomech Eng
Ateshian GA, Deiters S, Weiss JA.
europepmc   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source