Machine Learning-Assisted Prediction of State of Health in Lithium Metal Batteries with Electrochemical Impedance Spectroscopy. [PDF]
Small SciThis study investigates the artificial intelligence‐driven method for predicting the state of health of lithium metal batteries based on electrochemical impedance spectroscopy (EIS) data. Four machine learning algorithms achieve accuracy exceeding 95%, identifying phase shift as a critical feature for prediction and establishing a connection between ...
Yoon J +7 more
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Unraveling Defect-Dependent Conductivity-Type Switching in CuFe<sub>2</sub>O<sub>4</sub> for Enhanced Photoelectrocatalytic Reduction of Benzaldehyde. [PDF]
ACS Appl Mater InterfacesHuang YC +5 more
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DiMA: sequence diversity dynamics analyser for viruses. [PDF]
Brief BioinformTharanga S +8 more
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Seawater Corrosion Resistance of Zr-Ti Combined Deoxidized Martensitic Stainless Steel. [PDF]
Materials (Basel)Wu Q +9 more
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Effective electrochemical synthesis of ferrate(vi) utilizing a porous iron foam anode and its application in the removal of azo dye reactive red 24. [PDF]
RSC AdvNguyen TVA +5 more
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Feasibility Study of Photoelectrochemical Sensing of Glucose and Urea Using BiVO4 and BiVO4/BiOCl Photoanodes. [PDF]
Sensors (Basel)Skruodiene M +4 more
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Microstructure and Release Behavior of Alginate-Natural Hydrocolloid Composites: A Comparative Study. [PDF]
Polymers (Basel)Sıçramaz H +4 more
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