2DMatPedia, an open computational database of two-dimensional materials from top-down and bottom-up approaches

Nature·Jun 12

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A database called 2DMatPedia has been created, focusing on two-dimensional materials. The database is being utilized in various studies that apply machine learning and other computational approaches to understand and predict properties of these materials. Research using 2DMatPedia appears to cover a range of topics, including electronic band structures, superlubric heterostructures, and thermodynamic stability.

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Deep learning approach to genome of two-dimensional materials with flat electronic bands

Nature·Jun 8

Continuous chiral distances for two‐dimensional lattices - Bright - 2023 - Chirality

Wiley Online Library·Jun 21

Domain features-informed two-step machine learning: accelerating the search for superlubric heterostructures

Nature·Mar 3

Hole-doping induced ferromagnetism in 2D materials

Nature·Nov 10

From bulk effective mass to 2D carrier mobility accurate prediction via adversarial transfer learning

Nature·Jun 25

Elf autoencoder for unsupervised exploration of flat-band materials using electronic band structure fingerprints

Nature·Jan 17

High-throughput ab initio design of atomic interfaces using InterMatch

Nature·Dec 1

Predicting thermodynamic stability of inorganic compounds using ensemble machine learning based on electron configuration

Nature·Jan 2

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