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Warning

Quandarium is a work in process. It doesn't reach its first stable version yet and its source code is changing every week. Use at your own risk.

Quandarium

This package present several tools to deal with Quantum Chemistry (QC) data of molecular systems (non-periodic):

  • Extraction from QC calculations;
  • Molecular analysis, seuch as effective coordination bonds and exposed area;
  • AtoMF (Atomic to Molecular Featurization);
  • Correlation analysis and correlation significance analysis with bootstrap.

Install:

First, download the package:

cd 
git clone https://github.com/johnatanmucelini/Quandarium.git

Then, add the following lines at the top of your python code:

import sys
sys.path.append('~/Quandarium/')
import quandarium as qd

Usage:

I will improve this section further.

Requirements:

The following python packages are prerequisites:

  • numpy
  • scipy
  • pandas
  • atomic simulation environment
  • scikit-learn
  • matplotlib
  • seaborn

If you employ Anaconda package management, you can install the packages with the following commands:

conda install pandas numpy scipy matplotlib seaborn scikit-learn
conda install -c conda-forge ase

References:

The following papers have employed this package:

  1. Methane dehydrogenation on 3d 13-atom transition-metal clusters: A density functional theory investigation combined with Spearman rank correlation analysis. Fuel, 2020, 275, 117790. DOI: 10.1016/j.fuel.2020.117790

  2. Ab Initio Insights Into the Formation Mechanisms of 55-Atom Pt-Based Core-Shell Nanoalloys. The Journal of Physical Chemistry, 2020, 124, 1, 1158-1164. DOI: 10.1021/acs.jpcc.9b09561

  3. Ab initio insights into the structural, energetic, electronic, and stability properties of mixed CenZr15-nO30 nanoclusters, Physical Chemistry Chemical Physics, 2019, 21, 26637-26646. DOI: 10.1039/C9CP04762J

Cite us:

Please, if you employed the Quandarium package, cite us:

Correlation-Based Framework for Extraction of Insights from Quantum Chemistry Databases: Applications for Nanoclusters. Journal of Chemical Information and Modeling, 2021, 61 (3), 1125-1135. DOI: 10.1021/acs.jcim.0c01267

Contact

Fell free to contact me by email: