Results 191 to 200 of about 489,759 (365)

The High‐Altitude Adaptation Characteristics of Microbiota‐Host Cross‐Talk in Yak Gastrointestinal Track

open access: yesAdvanced Science, EarlyView.
In this study, a single‐cell atlas of 117,019 yak gastrointestinal cells across 54 subtypes identified HNF4A and SREBF2 as key transcription factors targeting MYO6 gene. Cross‐species and multi‐omics analyses reveals epithelial cells as key regulators that, through interactions with microbes, particularly Bacillus, facilitate flexible energy supply and
Chun Huang   +12 more
wiley   +1 more source

Uncertainty‐Quantified Primary Particle Size Prediction in Li‐Rich NCM Materials via Machine Learning and Chemistry‐Aware Imputation

open access: yesAdvanced Science, EarlyView.
This study demonstrates a machine learning framework that predicts the primary particle size of Lithium‐rich Nickel‐Cobalt‐Manganese (Li‐rich NCM) materials from synthesis conditions, even with incomplete literature data. By combining chemistry‐aware imputation with uncertainty‐quantified modeling, it identifies sintering temperature and time as ...
Benediktus Madika   +6 more
wiley   +1 more source

A Complete Density Correction using Normalizing Flows (CDC-NF) for CMIP6 GCMs. [PDF]

open access: yesSci Data
Fang S   +4 more
europepmc   +1 more source

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

open access: yesAdvanced 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   +7 more
wiley   +1 more source

Leveraging historical trials to predict Fusarium head blight resistance in spring wheat breeding programs. [PDF]

open access: yesPlant Genome
Brault C   +8 more
europepmc   +1 more source

Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency

open access: yesAdvanced Energy Materials, EarlyView.
This perspective highlights how machine learning accelerates sustainable energy materials discovery by integrating quantum‐accurate interatomic potentials with property prediction frameworks. The evolution from statistical methods to physics‐informed neural networks is examined, showcasing applications across batteries, catalysts, and photovoltaics ...
Kwang S. Kim
wiley   +1 more source

Home - About - Disclaimer - Privacy