Results 91 to 100 of about 1,129,295 (286)
Internal Temperature Evolution Metrology and Analytics in Li‐Ion Cells
Advanced Functional Materials, EarlyView.This study investigates the non‐linear evolution of internal temperatures across diverse operating conditions, highlighting the disparities between internal and external measurements and the resulting thermal asymmetries. The coupled thermo‐electrochemical modeling framework provides a comprehensive analysis of various heat generation modes, examining ...
Anuththara S. J. Alujjage +5 more
wiley +1 more source
Publisher's Note: Machine learning
, 2018 Yi Zhang, Roger G. Melko, Eun-Ah Kim
openalex +1 more source
Sampling Algorithms in Statistical Physics: A Guide for Statistics and Machine Learning
Statistical ScienceWe discuss several algorithms for sampling from unnormalized probability distributions in statistical physics, but using the language of statistics and machine learning. We provide a self-contained introduction to some key ideas and concepts of the field, before discussing three well-known problems: phase transitions in the Ising model, the melting ...
Faulkner, Michael F. +1 more
openaire +5 more sources
Machine learning and conventional statistics: making sense of the differences
Knee Surgery, Sports Traumatology, Arthroscopy, 2022 Christophe Ley +5 more
semanticscholar +1 more source
Structurally Colored Physically Unclonable Functions with Ultra‐Rich and Stable Encoding Capacity
Advanced Functional Materials, Volume 35, Issue 12, March 18, 2025.This study reports a design strategy for generating bright‐field resolvable physically unclonable functions with extremely rich encoding capacity coupled with outstanding thermal and chemical stability. The optical response emerges from thickness‐dependent structural color formation in ZnO features, which are fabricated by physical vapor deposition ...
Abidin Esidir +8 more
wiley +1 more source
Advanced Functional Materials, EarlyView.This study examines how manufacturing uncertainties in Curie temperatures (1.5–2°C) affect multilayer active magnetic regenerators (AMR). While increasing the number of magnetocaloric layers boosts cooling power, performance degrades due to temperature variations.
Urban Tomc +6 more
wiley +1 more source
Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications
Advanced Functional Materials, EarlyView.Quantum emitters in hexagonal boron nitride have emerged as a promising candidate for quantum information science. This review examines the fundamentals of these quantum emitters, including their level structures, defect engineering, and their possible chemical structures.
Thi Ngoc Anh Mai +8 more
wiley +1 more source
Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery
Advanced Functional Materials, EarlyView.This study provides an efficient approach to train a machine learning model by merging heterogeneous literature data to predict suitable polymers for siRNA delivery. Without the need for extensive laboratory synthesis, the machine learning enabled a virtual screening and successfully predicted a polymer that is validated for effective gene silencing in
Felix Sieber‐Schäfer +10 more
wiley +1 more source
Advanced Functional Materials, EarlyView.By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto +8 more
wiley +1 more source