Calendering‐Dependent Electrochemical and Cost‐Energy Tradeoffs in Layered – Olivine Blend Cathodes
Advanced Energy Materials, EarlyView.Blends comprised of LiNi0.9Mn0.05Co0.05O2 (NMC) and LiMn0.7Fe0.3PO4 (LMFP) are investigated to assess the performance – cost tradeoffs. Their rate‐capability benefit is retained only under uncalendered‐to‐moderately calendered states. Although blends reduce voltage decay and improve energy retention, they do not deliver measureable improvement in ...
Huyen T. K. Nguyen, Arumugam Manthiram
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Operational Markov matrix formulation for structures in continuum plasma models. [PDF]
Sci RepPanday N, Sharma D.
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Agribusiness, EarlyView.ABSTRACT The US hemp market is a new and nascent industry that has been devoid of research for about half a century. This study examined the effects of exogenous shock on price at each phase of the value chain—Farm (hemp biomass), and its impact on prices at other phases of the value chain—Intermediary Processor (crude cannabidiol hemp) and Final ...
Solomon Odiase +2 more
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Semi-Analytical Investigation into the Balanced Performance of Thick-Walled Fiber-Reinforced Flexible Pipes. [PDF]
Materials (Basel)You J, Zhao Y, Zhang B.
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A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
Advanced Intelligent Discovery, EarlyView.The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
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Serviceability Moment Capacity of Bolted Endplate Minor-Axis Connections in Prefabricated Steel Frames: Role of Column Web Yielding and Numerical Verification. [PDF]
Materials (Basel)Aosimanjiang A, Chen M, Wang Z, Huang Q.
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Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
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Controlling Spatio-Temporal Sequences of Neural Activity by Local Synaptic Changes. [PDF]
J NeurosciWernecke HO, Lehr AB, Kumar A.
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Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
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Fault-Tolerant Private Information Retrieval via Threshold Distributed Point Functions. [PDF]
Entropy (Basel)Yuan D, Liu X, Liu B.
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