English
Related papers

Related papers: Predicting Crystal Structures and Ionic Conductivi…

200 papers

Machine learning interatomic potentials (MLIPs) enable large-scale atomistic simulations but remain challenged in describing mixed-valence materials where charge ordering strongly influences thermodynamic stability. Here we investigate the…

We use rigorous group-theoretic techniques and molecular dynamics to investigate the connection between structural symmetry and ionic conductivity in the garnet family of solid Li-ion electrolytes. We identify new ordered phases and…

The sustainable utilization of lithium-ion batteries (LIBs) is crucial to the global energy transition and carbon neutrality, yet data scarcity and heterogeneity remain major barriers across remanufacturing, reusing, and recycling. This…

Machine Learning · Computer Science 2025-09-29 Shengyu Tao

The lithium bis(trifluoromethylsulfonyl)azanide-triglyme electrolyte plays a critical role in the performance of lithium-ion batteries. However, its solvation structure and transport properties at the atomic scale remain incompletely…

Materials Science · Physics 2025-04-01 Chenyang Cao , Liyi Bai , Shuo Cao , Ye Su , Yanzhou Wang , Zheyong Fan , Ping Qian

Lithium-based disordered rocksalts (LDRs), which are an important class of cathodes for advanced Li-ion batteries, represent a complex chemical and configurational space for conventional density functional theory (DFT)-based high-throughput…

Materials Science · Physics 2024-06-21 Vijay Choyal , Nidhish Sagar , Gopalakrishnan Sai Gautam

Liquid electrolytes are critical components of next-generation energy storage systems, enabling fast ion transport, minimizing interfacial resistance, and ensuring electrochemical stability for long-term battery performance. However,…

This paper reviews some selected approaches to the description of transport properties, mainly electroconductivity, in crystalline and disordered metallic systems. A detailed qualitative theoretical formulation of the electron transport…

Statistical Mechanics · Physics 2011-09-27 A. L. Kuzemsky

Combining high-throughput first-principles calculations and experimental measurements, we have identified a novel family of fast lithium-ion chalcogenide conductors in Li$_2$BMQ$_4$ (2114, B = Ca, Sr and Ba; M = Si, Ge and Sn; Q = O, S and…

Lithium ion batteries often contain transition metal oxides like Li$_{x}$Mn$_2$O$_4$ ($0\leq x\leq2$). Depending on the Li content different ratios of Mn$^\text{III}$ to Mn$^\text{IV}$ ions are present. In combination with electron hopping…

Materials Science · Physics 2022-01-25 Marco Eckhoff , Knut Nikolas Lausch , Peter E. Blöchl , Jörg Behler

Accurate prediction of the Remaining Useful Life (RUL) is essential for enabling timely maintenance of lithium-ion batteries, impacting the operational efficiency of electric applications that rely on them. This paper proposes a RUL…

Machine Learning · Computer Science 2026-02-03 Khoa Tran , Tri Le , Bao Huynh , Hung-Cuong Trinh , Vy-Rin Nguyen , T. Nguyen-Thoi , Vin Nguyen-Thai

Solid-state ion conductors (SSICs) have emerged as a promising material class for electrochemical storage devices and novel compounds of this kind are continuously being discovered. High-throughout approaches that enable a rapid screening…

Universal machine-learning interatomic potentials (uMLIPs) have become powerful tools for accelerating computational materials discovery by replacing expensive first-principles calculations in crystal structure prediction (CSP). However,…

Materials Science · Physics 2026-02-04 Yuqi An , Zhenbin Wang

Crystal structure optimization is fundamental to materials modeling but remains computationally expensive when performed with density-functional theory (DFT). Machine-learning (ML) approaches offer substantial acceleration, yet existing…

Materials Science · Physics 2026-03-26 Ziduo Yang , Wei Zhuo , Huiqiang Xie , Xiaoqing Liu , Lei Shen

Oxide Li-conducting solid-state electrolytes (SSEs) offer excellent chemical and thermal stability but typically exhibit lower ionic conductivity than sulfides and chlorides. This motivates the search for new oxide materials with enhanced…

Materials Science · Physics 2025-10-02 Seungwoo Hwang , Jiho Lee , Seungwu Han , Youngho Kang , Sungwoo Kang

The rapid development of computational materials science powered by machine learning (ML) is gradually leading to solutions to several previously intractable scientific problems. One of the most prominent is machine learning interatomic…

Materials Science · Physics 2025-05-27 Xiao Fu , Jing Xu , Qifan Yang , Xuhe Gong , Jingchen Lian , Liqi Wang , Zibin Wang , Ruijuan Xiao , Hong Li

The optimization of the electrode manufacturing process is important for upscaling the application of Lithium Ion Batteries (LIBs) to cater for growing energy demand. In particular, LIB manufacturing is very important to be optimized…

Machine Learning · Computer Science 2023-07-13 Marc Duquesnoy , Chaoyue Liu , Vishank Kumar , Elixabete Ayerbe , Alejandro A. Franco

Electrolytes play a critical role in designing next-generation battery systems, by allowing efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyte interfaces. In this work, we develop a differentiable…

Disordered rocksalt (DRX) Li3V2O5 is a promising candidate for anode in rechargeable lithium-ion batteries because of its ideal low voltage, high rate capability, and superior cycling stability. Herein, we presents a comprehensive study of…

Materials Science · Physics 2022-08-31 Xingyu Guo , Chi Chen , Shyue Ping Ong

Designing materials with targeted lattice thermal conductivity (LTC) demands electronic-level insight into chemical bonding. We introduce two bonding descriptors, namely normalized negative integrated crystal orbital Hamilton populations…

Materials Science · Physics 2025-12-12 Mohammed Al-Fahdi , Riccardo Rurali , Jianjun Hu , Christopher Wolverton , Ming Hu

Traditional approaches to identify ion-transport pathways often presume equal probability of occupying all hopping sites and focus entirely on finding the lowest migration barrier channels between them. Although this strategy has been…

Materials Science · Physics 2023-01-27 Shashwat Anand , Tina Chen , Gerbrand Ceder