High throughput calculations for a dataset of bilayer materials.
Ranjan Kumar BarikLilia M WoodsPublished in: Scientific data (2023)
Bilayer materials made of 2D monolayers are emerging as new systems creating diverse opportunities for basic research and applications in optoelectronics, thermoelectrics, and topological science among others. Herein, we present a computational bilayer materials dataset containing 760 structures with their structural, electronic, and transport properties. Different stacking patterns of each bilayer have been framed by analyzing their monolayer symmetries. Density functional theory calculations including van der Waals interactions are carried out for each stacking pattern to evaluate the corresponding ground states, which are correctly identified for experimentally synthesized transition metal dichalcogenides, graphene, boron nitride, and silicene. Binding energies and interlayer charge transfer are evaluated to analyze the interlayer coupling strength. Our dataset can be used for materials screening and data-assisted modeling for desired thermoelectric or optoelectronic applications.
Keyphrases
- density functional theory
- molecular dynamics
- high throughput
- transition metal
- public health
- electronic health record
- room temperature
- gold nanoparticles
- big data
- machine learning
- mass spectrometry
- molecular dynamics simulations
- ionic liquid
- deep learning
- reduced graphene oxide
- artificial intelligence
- transcription factor
- dna binding