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Computational Discovery of New 2D Materials Using Deep Learning Generative Models

https://doi.org/10.1021/acsami.1c01044
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Outgoing claims: the papers this work cites, builds on, or argues with.

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The Earth Mover's Distance as a Metric for Image Retrieval
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Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials
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Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds
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Magnetic 2D materials and heterostructures
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Structure prediction drives materials discovery
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2DMatPedia, an open computational database of two-dimensional materials from top-down and bottom-up approaches
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High-throughput Identification and Characterization of Two-dimensional Materials using Density functional theory
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Smart inverse design of graphene-based photonic metamaterials by an adaptive artificial neural network
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A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu
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Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
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The Elastic Behaviour of a Crystalline Aggregate
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Computational methods for 2D materials: discovery, property characterization, and application design
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The Computational 2D Materials Database: high-throughput modeling and discovery of atomically thin crystals
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Ab initio molecular dynamics for liquid metals
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Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium
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Projector augmented-wave method
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Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set
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From ultrasoft pseudopotentials to the projector augmented-wave method
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Necessary and sufficient elastic stability conditions in various crystal systems
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Discovering two-dimensional topological insulators from high-throughput computations
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Phonons and related crystal properties from density-functional perturbation theory
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Prediction of Flatband Potentials at Semiconductor‐Electrolyte Interfaces from Atomic Electronegativities
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SMACT: Semiconducting Materials by Analogy and Chemical Theory

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