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---
title: 'MacroDensity: Understanding The Electrostatic Potential and Electron Density Landscapes within Systems of Quantum Mechanical Simulations'
tags:
- Python
- Density Functional Theory
- DFT
- electrostatic potentials
- electron density
- ab initio
- vasp
authors:
- name: Calysta A. Tesiman
orcid: 0009-0008-7784-4320
equal-contrib: true
affiliation: "1, 2" # (Multiple affiliations must be quoted)
- name: Author Without ORCID
equal-contrib: true # (This is how you can denote equal contributions between multiple authors)
affiliation: 2
- name: Author with no affiliation
corresponding: true # (This is how to denote the corresponding author)
affiliation: 3
- given-names: Ludwig
dropping-particle: van
surname: Beethoven
affiliation: 3
affiliations:
- name: Lyman Spitzer, Jr. Fellow, Princeton University, USA
index: 1
- name: Institution Name, Country
index: 2
- name: Independent Researcher, Country
index: 3
date: 13 August 2017
bibliography: paper.bib

---

# Summary

Summary

# Statement of need

When assessing the potential utility of novel semiconducting devices (p-n juntions,
heterostructures, surface terminations) through simulation, an understanding of the
variation in the electrostatic potential and electron density across the system is key.
However, extraction and useful presentation of this data from the raw output of the
simulation can prove cumbersome and often requires the use of visualisation software followed
by manual data extraction. This can result in bottlenecks in high throughput screening projects,
where the same data extraction procedure is repeatedly applied to large databases of candidate structures.

To address this, ``MacroDensity`` was developed to simplify the data extraction and visualisation processes.
By using the landscape of electrostatic potentials and electronic density within a system seperated by grid points,
it becomes trivial to produce meaningful analysis and plots for visualisation.

# MacroDensity

MacroDensity is a set of Python modules developed to read and analyse electrostatic potentials and electron
density data from electronic structure calculations derived from Density Functional Theory (DFT). The package
allows users to read from VASP LOCPOT [@vasp], CHGCAR files, FHI-AIMS [@fhi_aims] , *.cube file, and GULP *.out
file and format the data into physically meaningful quantities, which can then be plotted for user interpretation.

(MOVE ME TO ANOTHER SECTION)
#The code has been used to rapidly generate data for these publications: 1,2, amongst others.#

The package formats datasets containing information about a system's lattice parameters electron density, and
electrostatic potentials. ``MacroDensity`` contains some high-level tools and functions to calculate
the planar and macroscopic average (as defined in Jackson's Electrodynamics [@Jackson:1999]), the spherical average
around a user-defined point, and calculates band energy offsets, deformation potential, and volume changes of a system.
``MacroDensity`` can also calculate the localised potential around a certain atomic nucleus of a system. The approach
to calculating this on site (Hartree) potential is similar to calculating the Madelung potential. this is useful for
electron energy level predictions [@aron:2014].

# Citations

Citations to entries in paper.bib should be in
[rMarkdown](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html)
format.

If you want to cite a software repository URL (e.g. something on GitHub without a preferred
citation) then you can do it with the example BibTeX entry below for @fidgit.

For a quick reference, the following citation commands can be used:
- `@author:2001` -> "Author et al. (2001)"
- `[@author:2001]` -> "(Author et al., 2001)"
- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)"

# Figures

Figures can be included like this:
![Caption for example figure.\label{fig:example}](figure.png)
and referenced from text using \autoref{fig:example}.

Figure sizes can be customized by adding an optional second parameter:
![Caption for example figure.](figure.png){ width=20% }

# Acknowledgements

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