2025-01-03
2025-01-03
Superconductivity typically emerges from strong interactions between electrons and vibrations in the crystal lattice (phonons). These interactions can lead to electron pairing, enabling resistance-fre
Try to compare MLIP vs DFT calculations if possible
Visualize how the lattice changes with temperature
See if we can estimate stability
Take materials we know to decompose at certain temps and replicate that in silico
Derive ionic diffusion coefficients for super-ionic conductors.
If the results match the GNoME findings, attempt to model a known a superconductor or HEA and compare the MLIP simulation findings with AIMD or other physics based molecular dynamics models.
2025-01-10
Looking into fine-tuning MLIP models. Most are trained on GGA-PBE (and sometimes with Hubbard U correction) but there are other levels of theory that may be better suited to superconductivity research. The MatterSim paper demonstrates fine-tuning on other methods with relatively small amounts of data.
ORB paper and tools talks about training with D3 corrections, and the benefit of training the model at the level of theory you want instead of adding corrections as an independent step, especially considering some of the computational requirements for said corrections.
2025-01-17
Looking into studying optical and topological properties of superconductors around their critical temperature. Developing some theories about the mechanisms underlying the different pairing mechanisms we see in different classes of superconductor, potentially getting closer to a unified theory.
Superconductivity typically emerges from strong interactions between electrons and vibrations in the crystal lattice (phonons). These interactions can lead to electron pairing, enabling resistance-fre
Try to compare MLIP vs DFT calculations if possible
Visualize how the lattice changes with temperature
See if we can estimate stability
Take materials we know to decompose at certain temps and replicate that in silico
Derive ionic diffusion coefficients for super-ionic conductors.
If the results match the GNoME findings, attempt to model a known a superconductor or HEA and compare the MLIP simulation findings with AIMD or other physics based molecular dynamics models.
2025-01-10
Looking into fine-tuning MLIP models. Most are trained on GGA-PBE (and sometimes with Hubbard U correction) but there are other levels of theory that may be better suited to superconductivity research. The MatterSim paper demonstrates fine-tuning on other methods with relatively small amounts of data.
ORB paper and tools talks about training with D3 corrections, and the benefit of training the model at the level of theory you want instead of adding corrections as an independent step, especially considering some of the computational requirements for said corrections.
2025-01-17
Looking into studying optical and topological properties of superconductors around their critical temperature. Developing some theories about the mechanisms underlying the different pairing mechanisms we see in different classes of superconductor, potentially getting closer to a unified theory.