Results 171 to 180 of about 1,354,041 (282)

Phase Fraction Modulation Enhances Li+/Na+ Diffusion Disparity in Spent LiFePO4 Cathodes for Efficient Lithium Extraction from Brine

open access: yesAdvanced Science, EarlyView.
A direct cascaded utilization strategy for spent LiFePO4 batteries efficiently extracts lithium from brine, embodying the “urban mining” concept. Phase fraction modulation revealed its significant impact on local bond lengths of crystal structure and the Li/Na diffusion energy barrier, identifying the best material (Li0.19FePO4) for lithium extraction.
Ruiqi Yin   +7 more
wiley   +1 more source

Spatially Selective Solvation Chemistry by Local Charge Enrichment for Stable Potassium‐Metal Anodes

open access: yesAdvanced Science, EarlyView.
A MoC/NC functional intermediate medium preferentially interacts with KFSI to reconstruct the interfacial solvation structure and form a KF‐rich inorganic SEI. The synergistic integration of the electronically insulating SEI and MoC/NC suppresses electron tunneling, enables fast and balanced K+/electron transport, and promotes uniform K deposition for ...
Lu‐Kang Zhao   +9 more
wiley   +1 more source

Interactive process mining of cancer treatment sequences with melanoma real-world data. [PDF]

open access: yesFront Oncol, 2023
Wicky A   +7 more
europepmc   +1 more source

Environmental Insights and Sustainability Opportunities for Scaled‐Up MXene Production Without Etching

open access: yesAdvanced Science, EarlyView.
Through a systematic and comprehensive analysis of the environmental impacts for the emerging MXene synthesis pathways, this study presents process transformation and optimization opportunities for low‐carbon MXene production from laboratory to industrial scales.
Yushuai Huang   +6 more
wiley   +1 more source

Leveraging process mining for modeling progression trajectories in amyotrophic lateral sclerosis. [PDF]

open access: yesBMC Med Inform Decis Mak, 2023
Tavazzi E   +7 more
europepmc   +1 more source

Decoupling Intrinsic Molecular Efficacy From Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery

open access: yesAdvanced Science, EarlyView.
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang   +5 more
wiley   +1 more source

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