Results 191 to 200 of about 6,209,447 (296)

Elemental and Thermochemical Analyses of Materials after Electrical Discharge Machining in Water: Focus on Ni and Zn. [PDF]

open access: yesMaterials (Basel), 2021
Grigoriev SN   +5 more
europepmc   +1 more source

Physics‐Guided Descriptors Enable Data‐Efficient Prediction of Battery Coulombic Efficiency

open access: yesAdvanced Science, EarlyView.
This work integrates multiscale simulations with data‐driven approaches to predict Coulombic efficiency (CE). Multiscale simulations of battery systems are performed to extract Physics‐Guided descriptors and construct a dataset. Machine learning models trained on this dataset are then subjected to interpretable analysis to identify the most influential
Qintao Sun   +9 more
wiley   +1 more source

Structural Polymorphism of polyG Inclusions Revealed by In Situ Cryo‐Electron Tomography

open access: yesAdvanced Science, EarlyView.
Correlative cryo‐electron tomography in primary cortical neurons and NIID mouse brain tissue reveals that polyG inclusions are interconnected ribbon‐like assemblies rather than canonical amyloid fibrils. Multiple compartment‐specific ribbon states show distinct 26S proteasome accessibility, while cytoplasmic ribbons contact and deform ER‐like ...
Yunwen Qian   +12 more
wiley   +1 more source

Human‐Guided Bayesian Optimization Enables High‐Throughput Laser Annealing of Mesoporous SiOx Anodes for Lithium‐Ion Batteries

open access: yesAdvanced Science, EarlyView.
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park   +3 more
wiley   +1 more source

A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks

open access: yesAdvanced Science, EarlyView.
Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais   +32 more
wiley   +1 more source

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