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"GAMESS seems to have an old academic user base and a stable code for most traditional calculations" GAMESS has been in development since the 1970s and split into GAMESS(US) and GAMESS(UK) in 1981, whereas MOLCAS has been in development since the 1980s and Psi4 is much newer. However, I would not focus too much on the age of the software. The ...


8

I don't think this is something that you can model accurately in an ab initio manner, as there is no good method for predicting the thermal conductivity of amorphous materials yet, let alone materials that are both amorphous and have macroscopic inhomogeneities. IMHO the way to go is to collect experimental thermal conductivity data on soil samples with ...


5

Our Method We have created a machine learning model for estimating the thermal conductivity of any soil, which we have made publicly available at soilconductivity.com. Our model is significantly more accurate than any other existing method that we are aware of (MAE of around 0.08 W/mK), besides direct physical measurement of the soil, of course. (here is a ...


4

MoleView Super lightweight Developed based on standard plotting library (Matplotlib) Very easy to install pip install moleview All-in-one command moleview your_file.xyz More info: https://github.com/moleview/moleview


4

I also remember finding it difficult to navigate the landscape of atomistic simulation engines as a Ph.D. student. While there are very extensive lists on Wikipedia, I often found it difficult to understand which of these codes actually are in broad use and for what purpose. This was one of the motivations for me creating the atomistic.software collection, ...


3

AiiDA plugin for Quantum ESPRESSO The aiida-quantumespresso plugin contains fairly advanced parsing capabilities of the output of various QE executables, all written in Python. See the parsers subdirectory. Part of the parsing is interleaved with AiiDA-specific data structures but you should be able to reuse much in other contexts as well.


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