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Honeycomb layered oxides are a novel class of nanostructured materials comprising alkali or alkaline earth metals intercalated into transition metal slabs. The intricate honeycomb architecture and layered framework endows this family of…

Materials Science · Physics 2021-10-01 Godwill Mbiti Kanyolo , Titus Masese

Layered lithium intercalating transition metal (TM) oxides are promising cathode materials for Li-ion batteries. Here we scrutinize the recently developed strongly constrained and appropriately normed (SCAN) density functional method to…

Materials Science · Physics 2018-12-31 Arup Chakraborty , Mudit Dixit , Dan T. Major

Potassium-ion ($\rm K$-ion) rechargeable batteries; considered to be lucrative low-cost battery options for large-scale and capacious energy storage systems, have been garnering tremendous attention in recent years. However, due to the…

Carbon fiber composite can be a potential candidate for replacing metal-based battery enclosures of current electric vehicles (E.V.s) owing to its better strength-to-weight ratio and corrosion resistance. However, the strength of carbon…

We discover many new crystalline solid materials with fast single crystal Li ion conductivity at room temperature, discovered through density functional theory simulations guided by machine learning-based methods. The discovery of new solid…

Materials Science · Physics 2019-04-22 Austin D. Sendek , Ekin D. Cubuk , Evan R. Antoniuk , Gowoon Cheon , Yi Cui , Evan J. Reed

Intercalation materials are promising candidates for reversible energy storage and are, for example, used as lithium-battery electrodes, hydrogen-storage compounds, and electrochromic materials. An important issue preventing the more…

Materials Science · Physics 2022-04-12 Ananya Renuka Balakrishna

The performance of all-solid-state battery (ASSB) cathodes strongly depends on their microstructure. Optimizing the cathode morphology can therefore enhance effective macroscopic properties such as ionic and electronic conductivity. The…

Designing molecules that must satisfy multiple, often conflicting objectives is a central challenge in molecular discovery. The enormous size of chemical space and the cost of high-fidelity simulations have driven the development of machine…

Machine Learning · Statistics 2025-12-22 Madhav R. Muthyala , Farshud Sorourifar , Tianhong Tan , You Peng , Joel A. Paulson

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…

It is challenging to parameterize the force field for calcium ions (Ca2+) in calcium-binding proteins because of their unique coordination chemistry that involves the surrounding atoms required for stability. In this work, we observed wide…

Biomolecules · Quantitative Biology 2021-08-03 Pengzhi Zhang , Jaebeom Han , Piotr Cieplak , Margaret. S. Cheung

Physics-based electrochemical battery models derived from porous electrode theory are a very powerful tool for understanding lithium-ion batteries, as well as for improving their design and management. Different model fidelity, and thus…

Liquid metal batteries (LMBs) are a promising grid-scale storage device however, the scalability of this technology and its electrochemical performance is limited by mass transport overpotentials. In this work, a numerical model of a…

Fluid Dynamics · Physics 2024-10-15 Declan Finn Keogh , Mark Baldry , Victoria Timchenko , John Reizes , Chris Menictas

We present high-quality reference data for two fundamentally important groups of molecular properties related to a compound's utility as a lithium battery electrolyte. The first property is energy changes associated with charge excitations…

Despite ongoing efforts aimed at increasing energy density in all-solid-state-batteries, the optimal composite cathode morphology, which requires minimal volume change, small void development, and good interfacial contact, remains a…

In this paper, we introduce an approach for the prediction of capacity for over 100,000 spinel compounds relevant for battery materials, from which we propose the 20 most promising candidate materials. In the design of batteries, selecting…

Materials Science · Physics 2022-03-17 Scott R. Broderick , Kaito Miyamoto , Krishna Rajan

Materials discovery is a computationally intensive process that requires exploring vast chemical spaces to identify promising candidates with desirable properties. In this work, we propose using quantum-enhanced machine learning algorithms…

Developing new metal hydrides is a critical step toward efficient hydrogen storage in carbon-neutral energy systems. However, existing materials databases, such as the Materials Project, contain a limited number of well-characterized…

Machine Learning · Computer Science 2026-01-30 Xiyuan Liu , Christian Hacker , Shengnian Wang , Yuhua Duan

Hybrid or organic plastic crystals have the potential as lead-free alternatives to conventional inorganic ferroelectrics. These materials are gaining attention for their multiaxial ferroelectricity, above-room-temperature Curie…

We predict a quantum phase transition in fcc Ca under hydrostatic pressure. Using density functional theory, we find at pressures below 80 kbar, the topology of the electron charge density is characterized by nearest neighbor atoms…

Materials Science · Physics 2015-03-17 Travis E. Jones , Mark E. Eberhart , Dennis P. Clougherty

Crystal structures are indispensable across various domains, from batteries to solar cells, and extensive research has been dedicated to predicting their properties based on their atomic configurations. However, prevailing Crystal Structure…

Neural and Evolutionary Computing · Computer Science 2024-06-24 Hannah Janmohamed , Marta Wolinska , Shikha Surana , Thomas Pierrot , Aron Walsh , Antoine Cully