400 .cif files of candidate structures property condition generated by MatterGen where tc = 298.15K
Interactive plot of predicted vs. true Tc on the evaluation set.
Visualizing the counts of materials in the training and evaluation dataset by their Tc. First bin is non-superconductors, the rest are ranges of 20 K increments.
Using the 256 dimensional latent space output from the Orb model, we visualize the 3DSC(MP) dataset using UMAP with direction from Tc labels. Hover a point to see Tc, formula, and Material Project identifier.
Using the 256 dimensional latent space output from the Orb model, we visualize the 3DSC(MP) dataset using t-SNE and UMAP. The UMAP projection has been given the target for learning a manifold that keeps similar Tc materials close together.
Authors introduce Orb, a family of universal interatomic potentials for atomistic modeling of materials. Orb models are 3-6 times faster than existing universal potentials, stable under simulation for a range of out of distribution materials and, upon release, represented a 31% reduction in error over other methods on the Matbench Discovery benchmark. https://arxiv.org/abs/2410.22570
Authors present MatterSim, a deep learning model actively learned from large-scale first-principles computations, for efficient atomistic simulations at first-principles level and accurate prediction of broad material properties across the periodic table, spanning temperatures from 0 to 5000 K and pressures up to 1000 GPa. https://arxiv.org/abs/2405.04967
Not exactly the most rigorous test, but this side-by-side comparison shows the difference between running MD locally (M2 Macbook Air) and on a proper server (g4dn.2xl with T4 GPU). Each log is actually 100 simulation steps too.
Molecular dynamics simulation temperature ramping NaCl 3x3x3 supercell from 0 K to 300 K
Molecular dynamics simulation temperature ramping H2O 3x3x3 supercell from 0 K to 300 K
Simulating ice into water
Langevin temperature ramp over 10ps from 0 K to 300 K on a 3x3x3 supercell of NaCl
Langevin temperature ramp over 10ps from 0 K to 300 K on a 3x3x3 supercell of NaCl
https://next-gen.materialsproject.org/materials/mp-22851
Visualization created using .traj outputs of ASE MD simulation
Since the announcement in 2011 of the Materials Genome Initiative by the Obama administration, much attention has been given to the subject of materials design to accelerate the discovery of new materials that could have technological implications. Although having its biggest impact for more applied materials like batteries, there is increasing interest in applying these ideas to predict new superconductors. This is obviously a challenge, given that superconductivity is a many body phenomenon, with whole classes of known superconductors lacking a quantitative theory. Given this caveat, various efforts to formulate materials design principles for superconductors are reviewed here, with a focus on surveying the periodic table in an attempt to identify cuprate analogues. https://arxiv.org/abs/1601.00709
Tibetan-style vajra/dorje. Based on references from https://www.himalayanart.org/search/set.cfm?setID=563.
Authors make use of a new optical device to drive metallic K3C60 with mid-infrared pulses of tunable duration, ranging between one picosecond and one nanosecond. The same superconducting-like optical properties observed over short time windows for femtosecond excitation are shown here to become metastable under sustained optical driving, with lifetimes in excess of ten nanoseconds.