GitHub - OrderN/CONQUEST-release: Full public release of large scale and linear scaling DFT code CONQUEST Full public release of large scale and linear scaling DFT code CONQUEST - OrderN/CONQUEST-release

Version 1.5 of Conquest, the large-scale and linear scaling DFT code has been released.

* Interface to the ELPA library
* Surface dipole correction
* Correct O(N) stress and forces
* pDOS and band densities with MSSF
* LibXC 7.0
* Bug fixes

github.com/OrderN/CONQU...

Interesting article showing that the highest frequency for phonons in materials is set by fundamental constants of nature (and suggesting that the same is true for the maximum possible superconducting temperature) @ioppublishing.bsky.social

iopscience.iop.org/article/10.1...

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials We present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalyt...

Interesting new test set for machine-learning potentials, highlights the importance of going beyond energy and force matching: pubs.acs.org/doi/10.1021/...