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Related papers: Accelerated search for new ferroelectric materials

200 papers

Molybdenum clusters, characterised by their unique structure and intriguing catalytic properties, have gained significant attention in recent years. In several existing studies density functional theory (DFT) methods have been used to find…

Materials Science · Physics 2023-10-03 Yao Wei , Lev Kantorovich

Moir\'e-twisted materials have garnered significant research interest due to their distinctive properties and intriguing physics. However, conducting first-principles studies on such materials faces challenges, notably the formidable…

Materials Science · Physics 2024-04-10 Ting Bao , Runzhang Xu , He Li , Xiaoxun Gong , Zechen Tang , Jingheng Fu , Wenhui Duan , Yong Xu

Geometric information such as the space groups and crystal systems plays an important role in the properties of crystal materials. Prediction of crystal system and space group thus has wide applications in crystal material property…

Materials Science · Physics 2021-05-18 Yuxin Li , Rongzhi Dong , Wenhui Yang , Jianjun Hu

Practical density functional theory (DFT) owes its success to the groundbreaking work of Kohn and Sham that introduced the exact calculation of the non-interacting kinetic energy of the electrons using an auxiliary mean-field system.…

Chemical Physics · Physics 2023-11-17 P. del Mazo-Sevillano , J. Hermann

An integrated data-driven approach combined with a high-throughput framework based on first-principles calculations was used to discover novel rare-earth-free permanent magnets, focusing on binary alloys. Compounds were screened…

Materials Science · Physics 2025-07-03 Junaid Jami , Nitish Bhagat , Amrita Bhattacharya

Density functional theory (DFT) has become a standard tool for the study of point defects in materials. However, finding the most stable defective structures remains a very challenging task as it involves the solution of a multimodal…

Materials Science · Physics 2020-11-16 Marco Arrigoni , Georg K. H. Madsen

We report a high throughput computational search for two-dimensional ferroelectric materials. The starting point is 252 pyroelectric materials from the computational 2D materials database (C2DB) and from these we identify 64 ferroelectric…

Unlike covalent two-dimensional (2D) materials like graphene, 2D metals have non-layered structures due to their non-directional, metallic bonding. While experiments on 2D metals are still scarce and challenging, density-functional theory…

Materials Science · Physics 2023-01-06 Kameyab Raza Abidi , Pekka Koskinen

Melting is a high temperature process that requires extensive sampling of configuration space, thus making melting temperature prediction computationally very expensive and challenging. Over the past few years, I have built two methods to…

Materials Science · Physics 2022-04-12 Qi-Jun Hong

Modeling ferroelectric materials from first principles is one of the successes of density-functional theory, and the driver of much development effort, requiring an accurate description of the electronic processes and the thermodynamic…

Materials Science · Physics 2022-10-26 Lorenzo Gigli , Max Veit , Michele Kotiuga , Giovanni Pizzi , Nicola Marzari , Michele Ceriotti

The landscape of condensed matter physics is facing an unprecedented data surge driven by high-throughput ab initio workflows and rapidly expanding experimental datasets. Traditional first-principles methods such as Density Functional…

Mesoscale and Nanoscale Physics · Physics 2026-04-20 Mahyar Hassani-Vasmejani , Hosein Alavi-Rad , Meysam Bagheri Tagani

Density functional theory (DFT) is a fundamental method for simulating quantum chemical properties, but it remains expensive due to the iterative self-consistent field (SCF) process required to solve the Kohn-Sham equations. Recently, deep…

Computational Physics · Physics 2025-10-23 Seongsu Kim , Nayoung Kim , Dongwoo Kim , Sungsoo Ahn

A central problem of materials science is to determine whether a hypothetical material is stable without being synthesized, which is mathematically equivalent to a global optimization problem on a highly non-linear and multi-modal potential…

Applications · Statistics 2023-05-02 Arvind Krishna , Huan Tran , Chaofan Huang , Rampi Ramprasad , V. Roshan Joseph

Piezoelectric materials are widely used in all kinds of industries such as electric cigarette lighters, diesel engines and x-ray shutters. However, discovering high-performance and environmentally friendly (e.g. lead-free) piezoelectric…

Materials Science · Physics 2022-02-09 Jeffrey Hu , Yuqi Song

In this study, we formulate a density functional theory (DFT) for systems of labeled particles, considering a two-dimensional bead-spring lattice with a magnetic dipole on every bead as a model for ferrogels. On the one hand, DFT has been…

Soft Condensed Matter · Physics 2019-07-22 Segun Goh , René Wittmann , Andreas M. Menzel , Hartmut Löwen

We demonstrate a machine learning-based approach which predicts the properties of crystal structures following relaxation based on the unrelaxed structure. Use of crystal graph singular values reduces the number of features required to…

Materials Science · Physics 2024-02-15 Ethan P. Shapera , Dejan-Krešimir Bučar , Rohit P. Prasankumar , Christoph Heil

In this concept paper, the development of strategies for the integration of first-principles methods with crystallographic database mining for the discovery and design of novel ferroelectric materials is discussed, drawing on the results…

Materials Science · Physics 2012-10-24 Joseph W. Bennett , Karin M. Rabe

Ferroelectric materials can switch their polarization in response to an applied electric field. In this work, ferroelectricity at the single molecule level is proposed and investigated using density functional theory (DFT) calculations.…

Applied Physics · Physics 2017-05-30 Xinfeng Quan , Geoffrey R. Hutchison

Most of the FFT methods available for homogenization of the mechanical response use the strain/deformation gradient as unknown, imposing their compatibility using Green's functions or projection operators. This implies the allocation of…

Computational Engineering, Finance, and Science · Computer Science 2019-08-27 Sergio Lucarini , Javier Segurado

We propose a method for crystal structure prediction based on a new structure generation algorithm and on-lattice machine learning interatomic potentials. Our algorithm generates the atomic configurations assigning atomic species to sites…

Materials Science · Physics 2023-06-08 Vadim Sotskov , Alexander V. Shapeev , Evgeny V. Podryabinkin