Open research towards the discovery of room-temperature superconductors.
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Literature review of databases with materials and . See literature review on ML models which utilize these datasets:
This post will focus on the methods available to predict/derive of a material. We want to be able to build a pipeline where we can go beyond the available (and experimental) Tc data and train a model
Temperature ramping AIMD simulation of NaCL (mp-22851), taken from 0 K to 300 K over 10ps.
We had this idea before too, but cool to see Claude agrees. A lot of what we're trying to accomplish with this project requires a room temperature material. As comprehensive as Materials Project may be, it's all at 0 K. Who knows how many of these materials are actually stable at room temp, or the kinds of structural changes they'd undergo at higher temperatures.
Claude says:
For high-temperature trajectories paired with Materials Project structures, there are a few relevant datasets though they're somewhat limited:
The AIMD (Ab Initio Molecular Dynamics) database from NREL - however this mainly focuses on specific material families like perovskites.
The High-Throughput AIMD dataset from CMU contains some temperature-dependent trajectories, but it's fairly specialized to certain material classes.
NOMAD Archives has some MD trajectories, but they're not systematically linked to Materials Project IDs.
There isn't a comprehensive, systematic dataset that takes Materials Project structures and provides their high-temperature trajectories. This is actually a significant gap in available data - having validated high-temperature behavior for Materials Project entries would be extremely valuable for the community.