diff --git a/JOSSpaper/JOSSpaper.md b/JOSSpaper/JOSSpaper.md index 47dc700..7080495 100644 --- a/JOSSpaper/JOSSpaper.md +++ b/JOSSpaper/JOSSpaper.md @@ -43,19 +43,19 @@ bibliography: JOSSpaper.bib # Summary -We report a Python package to simplify the analysis of electrostatic potentials and electron density of crystals. Macrodensity can read volumetric output files from the first-principles materials modelling codes VASP (LOCPOT format) and FHI-AIMS (cube format), as well as the classical electrostatic potentials from GULP (standard output). The code consists of functions that calculate and plot planar macroscopic and spherical averages, as well as calculating conduction and valence band alignments over a user-defined vector or plane. As a result, this code has been used to aid the data analysis and generation for several publications [@Butler:2014;@Walsh:2013]. +We report a Python package to simplify the analysis of electrostatic potentials and electron density of crystals. Macrodensity can read volumetric output files from the first-principles materials modelling codes VASP and FHI-AIMS, as well as the classical electrostatic potentials from GULP. The code can calculate and plot planar, macroscopic, and spherical averages, as well as calculate conduction and valence band alignments over a user-defined vector or plane. As a result, this package has been used to aid the data analysis and generation for several publications [@Butler:2014;@Walsh:2013]. # Statement of need To assess the potential utility of novel semiconducting devices (like p-n junctions, heterostructures, surface terminations), it is key to understand how the electrostatic potential and electron density change across the system [@Politzer:2002]. However, analysing this data from the raw output of simulations can prove cumbersome and often requires manually extracting data and using visualisation software. 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. -The general approach for processing electrostatic potential and electron density data as well as its translation to a grid mesh is discussed in @Butler:2014. Withing the framework of Kohn-Sham density functional theory, this approach samples the spherical averages over points within the system onto a matrix, where our raw data is generated. To process this data appropriately, ``MacroDensity`` was developed to simplify the data extraction and visualisation processes. By defining planes or vectors along the landscape of electrostatic potentials and electronic density matrix, it becomes straightforward to produce meaningful analysis and visualisation plots across a user-defined area. +The general approach for processing electrostatic potential and electron density data as well as its translation to a grid mesh is discussed in @Butler:2014. Within the framework of Kohn-Sham density functional theory, this approach samples the spherical averages over points within the system onto a matrix, where our raw data is generated. To process this data appropriately, ``MacroDensity`` was developed to simplify the data extraction and visualisation processes. By defining planes or vectors along the landscape of electrostatic potentials and electronic density matrix, it becomes straightforward to produce meaningful analysis and visualisation plots across a user-defined area. # 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) [@Kohn:1996]. The package allows users to read from VASP [@vasp] LOCPOT and CHGCAR files, FHI-AIMS [@fhi_aims] (cube file), and GULP [@Gale1997] (standard output files) and format the data into physically meaningful quantities, which can then be plotted for user interpretation. +``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) [@Kohn:1996]. The package allows users to read from VASP LOCPOT and CHGCAR files [@vasp], FHI-AIMS cube files [@fhi_aims], and GULP standard output files [@Gale1997] and format the data into physically meaningful quantities, which can then be plotted for user interpretation. -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 and plot the planar and macroscopic average as defined in Jackson's Electrodynamics [@Jackson:2003] (Figure 1a). The determination of the lattice vector settings and how the macroscopic averaging is calculated in this package is best described from the work of @Peressi:1998. +The package formats datasets containing information about a system's lattice parameters, electron density, and electrostatic potentials. ``MacroDensity`` contains some high-level functions to calculate and plot the planar and macroscopic averages as defined in Jackson's Electrodynamics [@Jackson:2003] (Figure 1a). The determination of the lattice vector settings and how the macroscopic averaging is calculated in this package is best described from the work of @Peressi:1998. \begin{equation} \label{eq:Planar-average} diff --git a/JOSSpaper/JOSSpaper.pdf b/JOSSpaper/JOSSpaper.pdf index c340ffe..b5932cb 100644 Binary files a/JOSSpaper/JOSSpaper.pdf and b/JOSSpaper/JOSSpaper.pdf differ