Advances in Early Warning of Thermal Runaway in Lithium‐Ion Battery Energy Storage Systems
Advanced Sensor Research, EarlyView.This review presents a comprehensive analysis of cutting‐edge sensing technologies and strategies for early detection and warning of thermal runaway in lithium‐ion battery energy storage systems. It discusses the factors inducing thermal runaway, the evolution mechanism, and the detectable characteristic signals, along with advancements in ...
Duzhao Han +3 more
wiley +1 more source
The optimization and impact of public sports service quality based on the supervised learning model and artificial intelligence. [PDF]
Sci RepYan Y.
europepmc +1 more source
Optical Microfiber Biomedical Sensors: Classification, Applications, and Future Perspectives
Advanced Sensor Research, EarlyView.This review delves deeply into the various types of optical microfiber biosensors, grounded firmly in their fundamental principles, and underscores their indispensable roles in pushing forward biomedical advancements. It examines the latest advancements, challenges faced by these biosensors in practical applications, future directions, breakthroughs ...
Lili Liang +5 more
wiley +1 more source
Collaborative optimization of truck scheduling in container terminals using graph theory and DDQN. [PDF]
Sci RepCheng S +5 more
europepmc +1 more source
Machine Learning‐Driven Multi‐Objective Optimization of Microchannel Reactors for CO₂ Conversion
Advanced Sustainable Systems, EarlyView.This study introduces a novel method that combines CFD, RSM, and ML to improve a microreactor's performance utilizing the Sabatier reaction. A range of ML models is assessed, and the best one is selected to predict optimal reactor conditions. ML shows the ability to predict performance in just milliseconds, leading to a decrease in computational time ...
Sandeep Kumar +2 more
wiley +1 more source
Advanced Theory and Simulations, EarlyView.By substituting lattice sites in 16 binary prototypes, over 27 000 boron‐based ternary compounds are studied, revealing 155 stable candidates. The analysis identifies 31 compounds with superior hardness and elastic moduli compared to their binary counterparts.
Adam Carlsson +2 more
wiley +1 more source
Efficient Training of Neural Network Potentials for Chemical and Enzymatic Reactions by Continual Learning. [PDF]
J Chem Theory ComputLei YK, Yagi K, Sugita Y.
europepmc +1 more source
An Analysis of Elusive Relationships in Floating Zone Growth Using Data Mining Techniques
Advanced Theory and Simulations, EarlyView.Ultra‐pure silicon single‐crystals can be grown by the Floating Zone (FZ) method. This study investigates intricate relationships between process stability measures and multiple growth parameters by applying data mining techniques on FZ simulations. Regression Trees identified multivariate relationships that help explaining complex interactions between
Lucas Vieira +3 more
wiley +1 more source
Atom-based machine learning for estimating nucleophilicity and electrophilicity with applications to retrosynthesis and chemical stability. [PDF]
Chem SciRee N +3 more
europepmc +1 more source
Crystal Structure Prediction of Cs–Te with Supervised Machine Learning
Advanced Theory and Simulations, EarlyView.High‐throughput density functional theory calculations combined with machine learning models are employed to predict stable Cs– Te binary crystals. By systematically evaluating various structural descriptors and learning algorithms, the superiority of models based on atomic coordination environments is revealed.
Holger‐Dietrich Saßnick +1 more
wiley +1 more source