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Related papers: Machine-Learning-Guided Insights into Solid-Electr…

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Zirconia (ZrO2) and hafnia (HfO2) are leading candidates for replacing SiO2 as the gate insulator in CMOS technology. Amorphous versions of these materials (a-ZrO2 and a-HfO2)) can be grown as metastable phases on top of a silicon buffer;…

Materials Science · Physics 2009-11-11 Davide Ceresoli , David Vanderbilt

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are…

Chemical Physics · Physics 2025-07-15 Ademola Soyemi , Tibor Szilvasi

The PEO3:LiCF3SO3 polymer electrolyte has attracted significant research due to its enhanced stability at the lithium/polymer interface of high conductivity polymer batteries. Experimental studies have shown that, depending on the…

Materials Science · Physics 2015-10-21 Sha Xue , Yingdi Liu , Hongli Dang , Yaping Li , Dale Teeters , Daniel W. Crunkleton , Sanwu Wang

Following a recent proposal by Burrard-Lucas et al. [unpublished, arXiv: 1203.5046] we intercalated FeSe by Li in liquid ammonia. We report on the synthesis of new LixFe2Se2(NH3)y phases as well as on their magnetic and superconducting…

Superconductivity · Physics 2012-09-28 E. -W. Scheidt , V. R. Hathwar , D. Schmitz , A. Dunbar , W. Scherer , V. Tsurkan , J. Deisenhofer , A. Loidl

Computational modeling is vital for the fundamental understanding of processes in Li-ion batteries. However, capturing nanoscopic to mesoscopic phase thermodynamics and kinetics in the solid electrode particles embedded in realistic…

Effective passivation of lithium metal surfaces, and prevention of battery-shorting lithium dendrite growth, are critical for implementing lithium-metal-anodes for batteries with increased power densities. Nanoscale surface heterogeneities…

Materials Science · Physics 2017-10-03 Kevin Leung , Katherine L. Jungjohann

This article presents a novel empirical study for the estimation of the State of Charge (SOC) of a lithium-ion (Li-ion) battery which uses a deep learning model with three hidden layers. We model a series of ten vehicle drive cycles that…

Signal Processing · Electrical Eng. & Systems 2020-11-20 Alexandre Barbosa de Lima , Maurício B. C. Salles , José Roberto Cardoso

High-kappa dielectrics for insulating layers are a current key ingredient of microelectronics. X2O3 sesquioxide compounds are among the candidates. Here we show for a typical material of this class, ScO3, that the relatively modest…

Materials Science · Physics 2009-11-13 Pietro Delugas , Vincenzo Fiorentini , Alessio Filippetti

Lithium--sulfur (Li/S) batteries are regarded as one of the most promising energy storage devices beyond lithium-ion batteries because of their high energy density of 2600 Wh/kg and an affordable cost of sulfur. Meanwhile, some challenges…

Li$_{10}$Ge(PS$_6$)$_2$ (LGPS) is a highly concentrated solid electrolyte, in which Coulombic repulsion between neighboring cations is hypothesized as the underlying reason for concerted ion hopping, a mechanism common among superionic…

Materials Science · Physics 2022-11-29 Gavin Winter , Rafael Gómez-Bombarelli

With the rapid advancement of machine learning techniques for materials simulations, machine-learned force fields (MLFFs) have become a powerful tool that complements first-principles calculations by enabling high-accuracy molecular…

Materials Science · Physics 2026-01-16 Zicun Li , Huanjing Gong , Ruijuan Xiao , Xinguo Ren

Benefiting from the significantly improved energy density and safety, all-solid-state lithium batteries (ASSLBs) are considered one of the most promising next-generation energy technologies. Their practical applications, however, are…

Materials Science · Physics 2024-12-18 Yun An , Taiping Hu , Quanquan Pang , Shenzhen Xu

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 formation of passivating films is a common aging phenomenon, for example in weathering of rocks, silicon, and metals. In many cases, a dual-layer structure with a dense inner and a porous outer layer emerges. However, the origin of this…

Computational Physics · Physics 2022-12-01 Lars von Kolzenberg , Martin Werres , Jonas Tetzloff , Birger Horstmann

Among the 'beyond Li-ion' battery chemistries, nonaqueous Li-O$_2$ batteries have the highest theoretical specific energy and as a result have attracted significant research attention over the past decade. A critical scientific challenge…

Lithium-ion battery performance is strongly influenced by the ionic conductivity of the electrolyte, which depends on the speed at which Li ions migrate across the cell and relates to their solvation structure. The choice of solvent can…

The miscibility of Au and Li exhibits a potential application as an adhesion layer and electrode material in secondary batteries. Here, to explore alloying properties, we constructed a neural network potential (NNP) of Au-Li binary systems…

Materials Science · Physics 2021-03-31 Koji Shimizu , Elvis F. Arguelles , Wenwen Li , Yasunobu Ando , Emi Minamitani , Satoshi Watanabe

During the first charge-discharge cycle, silicon-based batteries show an important capacity loss because of the formation of the solid electrolyte interphase (SEI) and morphological changes due to expansion-contraction sequence upon…

Uncontrollable dendrites growth during electrochemical cycles leads to low Coulombic efficiency and critical safety issues in Li metal batteries. Hence, a comprehensive understanding of the dendrite formation mechanism is essential for…

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