Substrate-aware computational design of two-dimensional materials | npj Computational Materials

Nature·Aug 21

✦ NabkaNews BriefAuto-summarized from multiple outlets · verify with the source

Researchers are exploring the computational design of two-dimensional materials, with a focus on various aspects such as substrate awareness, spin qubit coherence time, and epitaxial growth. Studies are also investigating the application of machine learning and physics-informed methods to understand and optimize the properties of these materials. The research appears to be multidisciplinary, incorporating concepts from materials science, physics, and computer science to advance the field of two-dimensional materials.

Full coverage

Strategies to search for two-dimensional materials with long spin qubit coherence time

Nature·Nov 26

AQCat25: unlocking spin-aware, high-fidelity machine learning potentials for heterogeneous catalysis

Nature·Apr 27

Mechanisms of the epitaxial growth of two-dimensional polycrystals

Nature·May 12

2D computational photodetectors enabling multidimensional optical information perception

Nature·Jul 23

Theoretical prediction and shape-controlled synthesis of two-dimensional semiconductive Ni

Nature·Jul 8

Physics-informed Bayesian optimization suitable for extrapolation of materials growth

Nature·Feb 15

Towards understanding structure–property relations in materials with interpretable deep learning

Nature·Dec 7

Machine learning and data-driven methods in computational surface and interface science

Nature·Jul 1

View original report at Nature ↗

Fetching the latest headlines…