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Li-CO$_2$ batteries are promising energy storage systems due to their high theoretical energy density and CO$_2$ fixation capability, relying on reversible Li$_2$CO$_3$/C formation during discharge/charge cycles. We present a multiscale…

The rapid expansion of electric vehicles has intensified the need for accurate and efficient diagnosis of lithium-ion batteries. Parameter identification of electrochemical battery models is widely recognized as a powerful method for…

Machine Learning · Computer Science 2025-10-29 Hojin Cheon , Hyeongseok Seo , Jihun Jeon , Wooju Lee , Dohyun Jeong , Hongseok Kim

The increasing need for portable and large-scale energy storage systems requires development of new, long lasting and highly efficient battery systems. Solid state NMR spectroscopy has emerged as an excellent method for characterizing…

Chemical Physics · Physics 2023-07-10 Shira Haber , Michal Leskes

The high-throughput (HT) computational method is a useful tool to screen high performance functional materials. In this work, using the deformation potential method under the single band model, we evaluate the carrier relaxation time and…

Materials Science · Physics 2019-12-24 Tiantian Jia , Zhenzhen Feng , Shuping Guo , Xuemei Zhang , Yongsheng Zhang

Conversion cathode materials are gaining interest for secondary batteries due to their high theoretical energy and power density. However, practical application as a secondary battery material is currently limited by practical issues such…

Conventional generative models for materials discovery are predominantly trained and validated using data from Density Functional Theory (DFT) with approximate exchange-correlation functionals. This creates a fundamental bottleneck: these…

Artificial Intelligence · Computer Science 2026-04-30 Mahule Roy

The ability to rapidly develop materials with desired properties has a transformative impact on a broad range of emerging technologies. In this work, we introduce a new framework based on the diffusion model, a recent generative machine…

Dielectric structures composed of many inclusions that manipulate light in ways the bulk materials cannot are commonly seen in the field of metamaterials. In these structures, each inclusion depends on a set of parameters such as location…

Computational Physics · Physics 2019-03-05 Boaz Blankrot , Clemens Heitzinger

The rate capability of layered lithium nickel manganese cobalt oxide (NMC) cathode materials plays a decisive role in high-power applications such as fast charging, necessitating a detailed understanding of lithium-ion diffusion. However,…

Materials Science · Physics 2026-05-20 Jian He , Constantijn H. J. A. van de Wetering , Rolande W. Nolsen , Nongnuch Artrith

The design of novel cathode materials for Li-ion batteries would greatly benefit from accurate first-principles predictions of structural, electronic, and magnetic properties as well as intercalation voltages in compounds containing…

Materials Science · Physics 2022-11-03 Iurii Timrov , Francesco Aquilante , Matteo Cococcioni , Nicola Marzari

The physical and chemical characteristics of cathodes used in batteries are derived from the lithium-ion phosphate cathodes crystalline arrangement, which is pivotal to the overall battery performance. Therefore, the correct prediction of…

Materials Science · Physics 2025-09-16 Yogesh Yadav , Sandeep K Yadav , Vivek Vijay , Ambesh Dixit

Graphyne, a single atomic layer structure of the carbon six-member rings connected by one acetilenic linkage, is a promising anode of rechargeable batteries. In this paper, a first-principle study has been carried out on graphyne as a new…

Materials Science · Physics 2021-05-24 E. Shomali , I. Abdolhosseini Sarsari , F. Tabatabaei , MR. Mosaferi , N. Seriani

We develop a mathematical framework to analyze electrochemical impedance spectra in terms of a distribution of diffusion times (DDT) for a parallel array of random finite-length Warburg (diffusion) or Gerischer (reaction-diffusion) circuit…

Chemical Physics · Physics 2018-03-21 Juhyun Song , Martin Z. Bazant

This paper introduces a comprehensive unified framework for constructing multi-view diffusion geometries through intertwined multi-view diffusion trajectories (MDTs), a class of inhomogeneous diffusion processes that iteratively combine the…

Machine Learning · Computer Science 2025-12-02 Gwendal Debaussart-Joniec , Argyris Kalogeratos

Machine learning (ML) techniques have rapidly found applications in many domains of materials chemistry and physics where large data sets are available. Aiming to accelerate the discovery of materials for battery applications, in this work,…

Materials Science · Physics 2019-05-24 Rajendra P. Joshi , Jesse Eickholt , Liling Li , Marco Fornari , Veronica Barone , Juan E. Peralta

We have studied low-temperature magnetic properties as well as high-temperature lithium ion diffusion in the battery cathode materials LixNi1/3Co1/3Mn1/3O2 by the use of muon spin rotation/relaxation. Our data reveal that the samples enter…

Materials Science · Physics 2015-06-22 M. Mansson , H. Nozaki , J. M. Wikberg , K. Prsa , Y. Sassa , M. Dahbi , K. Kamazawa , K. Sedlak , I. Watanabe , J. Sugiyama

Understanding energy transport in semiconductors is critical for design of electronic and optoelectronic devices. Semiconductor material properties such as charge carrier mobility or diffusion length are commonly measured in bulk crystals…

Density functional theory (DFT) is a powerful computational method used to obtain physical and chemical properties of materials. In the materials discovery framework, it is often necessary to virtually screen a large and high-dimensional…

Materials Science · Physics 2024-08-06 Şener Özönder , H. Kübra Küçükkartal

Organic electrode-active materials (OAMs) not only enable a variety of charge and storage mechanisms, but are also safer for the environment and of lower cost compared to materials in commonly used lithium-ion batteries. Cross-linked…

Materials Science · Physics 2025-02-27 L. Dodell , M. Neumann , M. Osenberg , A. Hilger , G. Studer , B. Esser , I. Manke , V. Schmidt

The inverse design of materials with specific desired properties, such as high-temperature superconductivity, represents a formidable challenge in materials science due to the vastness of chemical and structural space. We present a guided…