Results 181 to 190 of about 110,857 (196)

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source

Analysis of Machine Learning-Based Investigation Into Multivariate Factors of Team Performance in Serious Games: Cross-Sectional Retrospective Study.

JMIR Serious Games
Abdul-Rahman GG, de Lange F, Zwitter A, Haleem N.   +3 more
europepmc   +1 more source

Resolving Oxidative and Corrosive Calendar‐Aging via Electrolyte Engineering for Stable Lithium Metal Batteries

Advanced Energy Materials, EarlyView.
A weakly solvating ether solvent, 1,2‐dimethoxypropane (DMP), is proposed for use in localized high‐concentration electrolytes (LHCEs) for lithium metal batteries (LMBs). These DMP‐based LHCEs simultaneously suppress lithium metal corrosion and cathode degradation—two interrelated processes that accelerate calendar aging of LMBs.
Jisub Kim, Ihnkyung Jung, Kyunam Lee, Insu Hwang, Minkwan Kim, Eunseok Park, Dongmin Park, Hayoung Park, Yonggoon Jeon, Gaeun Park, Hyo Chul Ahn, Jihoon Oh, Jungwon Park, Ali Coskun, Jang Wook Choi   +14 more
wiley   +1 more source

<i>Vitess 3.8</i>: a modernized framework for Monte Carlo neutron tracing simulations. [PDF]

J Appl Crystallogr
Robledo JI, Violini N, Beule F, Voigt J, Zakalek P, Lieutenant K.   +5 more
europepmc   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Automated workflow for genotyping individual transposon library variants. [PDF]

BMC Methods
Alejaldre L, Anhel AM, Grozinger L, Goñi-Moreno Á.   +3 more
europepmc   +1 more source

Taskblaster: a generic framework for automated computational workflows.

Digit Discov
Larsen AH, Kuisma MJ, Boland TM, Nilsson FA, Thygesen KS.   +4 more
europepmc   +1 more source

A curated resource of chemolithoautotrophic genomes and marker genes for CO₂ fixation pathway prediction. [PDF]

Sci Data
Kawashima S, Okabeppu Y, Miyazawa S, Ichikawa N, Nagazumi H, Nishihara Y, Nakazato T, Goto S, Kurokawa K, Ishii M, Mori H.   +10 more
europepmc   +1 more source

textToKnowledgeGraph: generation of molecular interaction knowledge graphs using large language models for exploration in Cytoscape. [PDF]

Bioinformatics
James F, Pratt D, Churas C, Luna A.
europepmc   +1 more source

A Major Update and Improved Validation Functionality in the mwtab Python Library and the Metabolomics Workbench File Status Website. [PDF]

Metabolites
Thompson PT, Moseley HNB.
europepmc   +1 more source