66 datasets found

The AIMD dataset generated from a melt-quench ab initio molecular dynamics (AIMD) protocol for Hafnium dioxide (HfO2)

The Fe/N2 dataset consists of molecular dynamics simulations of a nitrogen molecule adsorbing on an iron (Fe) <111> surface at high temperature (T = 700 K) and breaking in...

The Cu/formate dataset is a collection of molecular dynamics simulations of the dehydrogenation reaction of formate on a copper (Cu) <110> surface.

The OC20 dataset is a large dataset of ab initio calculations aimed at estimating adsorption energies on catalytic surfaces.

The dataset used to train the CGCNN model to visualize the compositional and structural similarities between elemental boron.

The dataset used to train the CGCNN model to visualize the compositional and structural similarities between perovskite crystals.

The MatSci-NLP dataset is a collection of materials science text for NLP tasks.

The HoneyBee dataset is a collection of instructions for materials science tasks.

The dataset used in this paper is a collection of thin-film libraries with lateral-gradient laser spike annealing (lg-LSA) experiments.

The dataset contains in situ radiation experiment videos providing real-time observation of defect generation and evolution under extreme conditions.

The dataset used comprises of about 1000 screened singlet fission molecules from previous literature

A dataset with 996 entries, including up to 7 variables regarding both the manufacturing process and environmental conditions for more than 180 days.

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk...

The dataset used for investigating NMC cathode manufacturing parameters.

The dataset used in this paper is a collection of metal-organic frameworks (MOFs) with simulated CO2 adsorption data.

The JARVIS-DFT database is a collection of density functional theory (DFT) data for various materials.

Crystal structure generation and property optimization

Crystal structure generation and property optimization

Crystal structure generation and property optimization

Gathering 3D material microstructural information is time-consuming, expensive, and energy-intensive. Acquisition of 3D data has been accelerated by developments in serial...