python Low Energy Electron Analysis SuitE
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Updated
Jun 22, 2017 - Python
python Low Energy Electron Analysis SuitE
Post-processing scripts for VASP output files, with focus on gnuplot formats
Atomic crystal structures for Julia
This provides the files needed and detailed process (instructions) to install the wien2k 14.2 in Linux.
Source of the short paper titled "Proposal of Automatic Extraction Framework of Superconductors related Information from Scientific literature"
GPU-accelerated Quantum ESPRESSO using CUDA FORTRAN
V2DB (Virtual 2D Materials Database): the code for generating and predicting the novel 2D materials by virtual screening.
Plot MICRESS data with Python (gnuplot, Matplotlib, Plotly)
This repository contains the Python code for generating the (ABAQUS Explicit v6.14) CAE files associated with the research paper titled "Nature-Inspired Cellular Structure Design for Electric Vehicle Battery Compartment: Application to Crashworthiness" with doi:10.3390/app10134532
Calculating the pseudo spin phase transition in metal halide perovskites
A tool for visualizing MD data
An interactive web app for bioplastic material properties data. We plot material properties for bioplastics properly
Python package providing some useful tools when dealing with molecules and materials under periodic boundary conditions and uniform grids. This is a mirror of https://gitlab.com/ales.genova/pbcpy
Density functional theory: Quantum Espresso & Projected Electronic Band Structure
All data and analyses to reproduce my ice material science research, as published in Penn Science: Furman and Goldsby, 2021.
Using the regression models in a real thermodynamic system. We have applied two supervised algorithms, Linear regression, and K-Nearest Neighbors to predict the composition values at various eta values.
Predict molecular chemical properties using deep learning model
We share in this repository some codes and data used during our research about glass property prediction and the design of new glasses.
The Alchemist uses a pool of optimization algorithms and machine learning models to search for viable glass compositions for a given glass transition temperature (Tg) value.
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