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Related papers: The Computational 2D Materials Database: High-Thro…

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We develop a materials descriptor based on the electronic density of states and investigate the similarity of materials based on it. As an application example, we study the Computational 2D Materials Database that hosts thousands of…

Materials Science · Physics 2022-01-07 Martin Kuban , Santiago Rigamonti , Markus Scheidgen , Claudia Draxl

We address the problem of predicting the zero-temperature dynamical stability (DS) of a periodic crystal without computing its full phonon band structure. Here we report the evidence that DS can be inferred with good reliability from the…

2D materials find promising applications in next-generation devices, however, large-scale, low-defect, and reproducible synthesis of 2D materials remains a challenging task. To assist in the selection of suitable substrates for the…

Materials Science · Physics 2021-12-08 Tara M. Boland , Arunima K. Singh

Combinatorial and guided screening of materials space with density-functional theory and related approaches has provided a wealth of hypothetical inorganic materials, which are increasingly tabulated in open databases. The OPTIMADE API is a…

The large-scale search for high-performing candidate 2D materials is limited to calculating a few simple descriptors, usually with first-principles density functional theory calculations. In this work, we alleviate this issue by extending…

Materials Science · Physics 2020-07-07 Victor Venturi , Holden Parks , Zeeshan Ahmad , Venkatasubramanian Viswanathan

The last decade has seen intense research in materials with reduced dimensionality. The low dimensionality leads to interesting electronic behavior due to electronic confinement and reduced screening. The investigations have to a large…

Materials Science · Physics 2019-03-27 Peter Mahler Larsen , Mohnish Pandey , Mikkel Strange , Karsten Wedel Jacobsen

Conventionally, high-throughput computational materials searches start from an input set of bulk compounds extracted from material databases, and this set is screened for candidate materials for specific applications. In contrast, many…

Materials Science · Physics 2023-04-11 Rachel Woods-Robinson , Matthew K. Horton , Kristin A. Persson

By performing high-throughput first-principles calculations combined with a semiempirical van der Waals dispersion correction, we have screened 74 direct- and 185 indirect-gap two dimensional (2D) nonmagnetic semiconductors from near 1000…

Mesoscale and Nanoscale Physics · Physics 2022-12-12 Vei Wang , Gang Tang , Ren-Tao Wang , Ya-Chao Liu , Hiroshi Mizuseki , Yoshiyuki Kawazoe , Jun Nara , Wen-Tong Geng

Owing to the fascinating physical characteristics of two-dimensional (2D) materials and their heterostructure, much effort has been devoted to exploring their basic physical properties as well as discovering other novel 2D materials.…

Materials Science · Physics 2020-07-13 Seungjun Lee , Young-Kyun Kwon

The discovery of novel substrate materials has been dominated by trial and error, opening the opportunity for a systematic search. To identify stable crystal surfaces, we generate bonding networks for materials from the Materials Project…

Materials Science · Physics 2021-03-31 Joshua T. Paul , Alice Galdi , Christopher Parzyck , Kyle Shen , Richard G. Hennig

We search for novel two-dimensional materials that can be easily exfoliated from their parent compounds. Starting from 108423 unique, experimentally known three-dimensional compounds we identify a subset of 5619 that appear layered…

Modification of physical properties of materials and design of materials with on-demand characteristics is at the heart of modern technology. Rare application relies on pure materials--most devices and technologies require careful design of…

Machine learning (ML) models utilizing structure-based features provide an efficient means for accurate property predictions across diverse chemical spaces. However, obtaining equilibrium crystal structures typically requires expensive…

Materials Science · Physics 2021-04-22 Yunxing Zuo , Mingde Qin , Chi Chen , Weike Ye , Xiangguo Li , Jian Luo , Shyue Ping Ong

We describe a first open-access database of experimentally investigated hybrid organic-inorganic materials with two-dimensional (2D) perovskite-like crystal structure. The database includes 515 compounds, containing 180 different organic…

Two-dimensional materials have attracted considerable attention due to their remarkable electronic, mechanical and optical properties, making them prime candidates for next-generation electronic and optoelectronic applications. Despite…

Two-dimensional (2D) materials are frequently associated with the sheets which form bulk layered compounds bonded by van der Waals (vdW) forces. The anisotropy and weak interaction between the sheets have also been the main criteria in the…

Materials Science · Physics 2022-01-24 Rico Friedrich , Mahdi Ghorbani-Asl , Stefano Curtarolo , Arkady V. Krasheninnikov

Two-dimensional (2D) materials have disrupted materials science due to the development of van der Waals technology. It enables the stacking of ultrathin layers of materials characterized by vastly different electronic structures to create…

The field of two-dimensional (2D) materials has grown dramatically in the last two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computation applications. These…

Materials informatics offers a promising pathway towards rational materials design, replacing the current trial-and-error approach and accelerating the development of new functional materials. Through the use of sophisticated data analysis…

Materials Science · Physics 2018-05-17 Cormac Toher , Corey Oses , Stefano Curtarolo

Understanding excitonic effects in two-dimensional (2D) materials is critical for advancing their potential in next-generation electronic and photonic devices. In this study, we introduce a machine learning (ML)-based framework to predict…

Materials Science · Physics 2025-12-02 Ahsan Javed , Sajid Ali