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To unlock the full potential of lithium metal batteries, a deep understanding of lithium metal reactivity and its solid electrolyte interphase is essential. Correlative imaging, combining focused ion beam and electron microscopy offers a…

Rechargeable lithium metal batteries (LMBs) with an ultrahigh theoretical energy density have attracted more and more attentions for their crucial applications of portable electronic devices, electric vehicles, and smart grids. However, the…

Materials Science · Physics 2024-10-22 Yanchen Fana , Xiang Chenb , Dominik Legut , Qianfan Zhang

We present a structural and magnetic study on two batches of polycrystalline LiNi$_{0.8}$Mn$_{0.1}$Co$_{0.1}$O$_2$ (commonly known as Li NMC 811), a Ni-rich Li ion battery cathode material, using elemental analysis, X-ray and neutron…

Materials Science · Physics 2021-01-19 P. Mukherjee , J. A. M. Paddison , C. Xu , Z. Ruff , A. R. Wildes , D. A. Keen , R. I. Smith , C. P. Grey , S. E. Dutton

We explore LiNiO2-based cathode materials with two-element substitutions by an ab initio simulation based materials informatics (AIMI) approach. According to our previous study, a higher cycle performance strongly correlates with less…

Materials Science · Physics 2020-08-20 Tomohiro Yoshida , Ryo Maezono , Kenta Hongo

Magnesium-ion batteries hold promise as future energy storage solution, yet current Mg cathodes are challenged by low voltage and specific capacity. Herein, we present an AI-driven workflow for discovering high-performance Mg cathode…

Materials Science · Physics 2025-06-11 Wenjie Chen , Zichang Lin , Xinxin Zhang , Hao Zhou , Yuegang Zhang

Conventional wisdom of materials modelling stipulates that both chemical composition and crystal structure are integral in the prediction of physical properties. However, recent developments challenge this by reporting accurate…

Materials Science · Physics 2022-06-29 Siyu Isaac Parker Tian , Aron Walsh , Zekun Ren , Qianxiao Li , Tonio Buonassisi

A novel non-destructive methodology for operando observation of ion intercalation and the state of charge on battery electrodes is presented based on spectroscopic ellipsometry (SE). The potentiality of this technique for performing…

Applied Physics · Physics 2021-05-28 A. Morata , V. Siller , F. Chiabrera , M. Nunez , R. Trocoli , M. Stchakovskyb , A. Tarancon

Adaptive finite element methods are a powerful tool to obtain numerical simulation results in a reasonable time. Due to complex chemical and mechanical couplings in lithium-ion batteries, numerical simulations are very helpful to…

Numerical Analysis · Mathematics 2024-04-17 Raphael Schoof , Lennart Flür , Florian Tuschner , Willy Dörfler

We have employed first-principles electronic structure calculations to examine the hypothetical (but plausible) oxide spinel, LiCr2O4 with the d^{2.5} electronic configuration. The cell (cubic) and internal (oxygen position) structural…

Materials Science · Physics 2009-11-10 Markus Lauer , Roser Valenti , H. C. Kandpal , Ram Seshadri , .

Lithium-ion batteries are the major type of battery used in a variety of everyday applications, including electric vehicles (EVs), mobile devices, and energy storage systems. Predicting the Remaining Useful Life (RUL) of Li-ion batteries is…

Signal Processing · Electrical Eng. & Systems 2026-01-01 Sel Ly , Rufan Yang , Ninad Dixit , Hung Dinh Nguyen

Atomistic simulations of liquid alloys face the challenge of correctly modeling basic thermodynamic properties. In this work we present an interatomic potential for the Li-Pb system, as well as a study of physical properties of Li-Pb…

Materials Science · Physics 2015-06-17 Alberto Fraile , Santiago Cuesta-López , Alfredo Caro , Daniel Schwen , J. Manuel Perlado

We demonstrate the ability of large language models (LLMs) to perform material and molecular property regression tasks, a significant deviation from the conventional LLM use case. We benchmark the Large Language Model Meta AI (LLaMA) 3 on…

Materials Science · Physics 2026-04-22 Ryan Jacobs , Maciej P. Polak , Lane E. Schultz , Hamed Mahdavi , Vasant Honavar , Dane Morgan

The application of machine learning in materials presents a unique challenge of dealing with scarce and varied materials data - both experimental and theoretical. Nevertheless, several state-of-the-art machine learning models for materials…

The discovery and optimization of materials for specific applications is hampered by the practically infinite number of possible elemental combinations and associated properties, also known as the `combinatorial explosion'. By nature of the…

Computation and Language · Computer Science 2025-06-11 Lei Zhang , Markus Stricker

The lithium manganese oxide spinel Li$_x$Mn$_2$O$_4$, with $0\leq x\leq 2$, is an important example for cathode materials in lithium ion batteries. However, an accurate description of Li$_x$Mn$_2$O$_4$ by first-principles methods like…

Materials Science · Physics 2020-05-20 Marco Eckhoff , Peter E. Blöchl , Jörg Behler

The development of materials science is undergoing a shift from empirical approaches to data-driven and algorithm-oriented research paradigm. The state-of-the-art platforms are confined to inorganic crystals, with limited chemical space,…

Materials Science · Physics 2025-07-08 Jifeng Wang , Jiazhe Ju , Ying Wang

The electrochemical performance of the spinel LiNi0.5Mn1.5O4, a high-voltage positive electrode material for Li-ion batteries, is influenced by the transition metal arrangement in the octahedral network, leading to disordered (Fd m S.G.)…

Higher loading of active electrode materials is desired in batteries, especially those based on conversion reactions, for enhanced energy density and cost efficiency. However, increasing active material loading in electrodes can cause…

Machine Learning · Computer Science 2024-12-30 Vidushi Sharma , Andy Tek , Khanh Nguyen , Max Giammona , Murtaza Zohair , Linda Sundberg , Young-Hye La

In the dynamic and rapidly advancing battery field, alloy anode materials are a focal point due to their superior electrochemical performance. Traditional screening methods are inefficient and time-consuming. Our research introduces a…

Materials Science · Physics 2024-09-17 Xingyue Shi , Linming Zhou , Yuhui Huang , Yongjun Wu , Zijian Hong

Introduction: Computational modeling has rapidly advanced over the last decades, especially to predict molecular properties for chemistry, material science and drug design. Recently, machine learning techniques have emerged as a powerful…

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