Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Quantitative Risk Assessment of Hepatitis E Virus from Shellfish Consumption Among Chinese Residents Using Monte Carlo Simulation. [PDF]
Xie Q +6 more
europepmc +1 more source
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan +3 more
wiley +1 more source
Feasibility of public CPR training kiosks to increase bystander resuscitation: a Monte Carlo simulation study. [PDF]
Ohle R +5 more
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
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
Authors' response to comment on evaluation of high dose post-dialytic versus daily beta-lactam dosing in hemodialysis patients using Monte Carlo simulation. [PDF]
Lewis SJ +6 more
europepmc +1 more source
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
Monte Carlo Simulation on Adiabatic Ensembles and a Genetic Algorithm. [PDF]
Silva Fernandes FMS.
europepmc +1 more source
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Limitations of blood supply and walking blood bank implementation in Forward Resuscitative Surgical Detachments during large-scale combat operations: A Monte Carlo simulation model. [PDF]
Nye K +20 more
europepmc +1 more source

