Welcome to the D3TaLES Database!
This is an open-access database of mineable data for Liquid-based Energy Storage (LES) materials. It contains curated
experimental and computational data generated by the D3TaLES project researchers and gathered from the relevant literature.
Computation
Properties computed with quantum chemical methods like density functional theory.
1e+07
Core hours
used to fill this database
Experiment
Data from laboratory and robotic experimentation
38
Users
uploading experiments
Literature Scraping
Data gathered from the relevant literature through natural language processing.
1979
Abstracts
scraped from the literature
Machine Learning
Properties predicted with a variety of machine learning models.
38434
Molecules
for training machine learning models
updated 2023-01-16
