CITATION.cff

# Citation File Format (cff).
# See https://citation-file-format.github.io/

cff-version: "1.2.0"
message: "If you use this software, please cite it using these metadata."

# Keep project metadata in sync with `pyproject.toml`!
type: "software"
title: "transfer_Li"
abstract: "Transfer Li ions from cathode to anode in MD simulations."
authors:
  - given-names: "Andreas"
    family-names: "Thum"
    alias: "andthum"
    email: "coding.andthum@e.mail.de"
    tel: "+49 251 83-29179"
    fax: "+49 251 83-29159"
    affiliation: "University of Münster, Institute for Physical Chemistry"
    address: "Corrensstraße 28/30"
    city: "Münster"
    post-code: 48149
    country: "DE"
    region: "North Rhine-Westphalia"
    orcid: "https://orcid.org/0000-0002-2262-8507"
contact:
  - given-names: "Andreas"
    family-names: "Thum"
    email: "coding.andthum@e.mail.de"
identifiers:
  - description: "The concept DOI of the software."
    type: "doi"
    value: "10.5281/zenodo.10155117"
url: "https://github.com/andthum/transfer_Li"
repository-code: "https://github.com/andthum/transfer_Li"
license: "MIT"
license-url: "https://mit-license.org/"
keywords:
  - "Python Scripts"
  - "Science"
  - "Scientific Computing"
  - "Computational Science"
  - "Materials Science"
  - "Molecular Simulation"
  - "Molecular Modeling"
  - "Molecular Mechanics"
  - "Molecular Dynamics"
  - "Molecular Dynamics Simulations"
  - "Gromacs"
  - "MDAnalysis"
  - "NumPy"

# Keep references in sync with pyproject.toml.
references:
  - type: "software"
    title: "MDTools"
    abstract: "Scripts to prepare and analyze molecular dynamics simulations."
    authors:
      - given-names: "Andreas"
        family-names: "Thum"
      - given-names: "Len"
        family-names: "Kimms"
      - name: "All Contributors to MDTools"
    url: "https://github.com/andthum/mdtools"
    repository-code: "https://github.com/andthum/mdtools"
    license: "GPL-3.0-or-later"
    license-url: "https://www.gnu.org/licenses/gpl-3.0.html"
    keywords:
      - "Scripts Collection"
      - "Python Scripts"
      - "Science"
      - "Scientific Computing"
      - "Computational Science"
      - "Computational Biology"
      - "Computational Chemistry"
      - "Computational Physics"
      - "Materials Science"
      - "Molecular Simulation"
      - "Molecular Modeling"
      - "Molecular Mechanics"
      - "Molecular Dynamics"
      - "Molecular Dynamics Simulation"
      - "Trajectory Analysis"
      - "MDAnalysis"
      - "NumPy"
      - "Python3"
      - "GPLv3"

  - type: "software"
    title: "MDAnalysis"
    abstract: >-
      MDAnalysis is a Python library to analyze molecular dynamics simulations.
    authors:
      - given-names: "Naveen"
        family-names: "Michaud-Agrawal"
      - name: "The MDAnalysis Core Developer Team"
      - name: "All Contributors to MDAnalysis"
    url: "https://www.mdanalysis.org"
    repository-code: "https://github.com/MDAnalysis/mdanalysis"
    license: "GPL-2.0-or-later"
    license-url: "https://www.gnu.org/licenses/gpl-2.0.html"
    keywords:
      - "python"
      - "science"
      - "chemistry"
      - "biophysics"
      - "molecular-dynamics"
      - "computational-chemistry"
      - "molecular-simulation"
      - "analysis"
      - "trajectory-analysis"

  - type: "proceedings"
    title: >-
      MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics
      Simulations
    abstract: >-
      MDAnalysis (http://mdanalysis.org) is a library for structural and
      temporal analysis of molecular dynamics (MD) simulation trajectories and
      individual protein structures. MD simulations of biological molecules
      have become an important tool to elucidate the relationship between
      molecular structure and physiological function. Simulations are performed
      with highly optimized software packages on HPC resources but most codes
      generate output trajectories in their own formats so that the development
      of new trajectory analysis algorithms is confined to specific user
      communities and widespread adoption and further development is delayed.
      MDAnalysis addresses this problem by abstracting access to the raw
      simulation data and presenting a uniform object-oriented Python interface
      to the user. It thus enables users to rapidly write code that is portable
      and immediately usable in virtually all biomolecular simulation
      communities. The user interface and modular design work equally well in
      complex scripted work flows, as foundations for other packages, and for
      interactive and rapid prototyping work in IPython / Jupyter notebooks,
      especially together with molecular visualization provided by nglview and
      time series analysis with pandas. MDAnalysis is written in Python and
      Cython and uses NumPy arrays for easy interoperability with the wider
      scientific Python ecosystem. It is widely used and forms the foundation
      for more specialized biomolecular simulation tools. MDAnalysis is
      available under the GNU General Public License v2.
    authors:
      - given-names: "Richard J."
        family-names: "Gowers"
      - given-names: "Max"
        family-names: "Linke"
      - given-names: "Jonathan"
        family-names: "Barnoud"
      - given-names: "Tyler John Edward"
        family-names: "Reddy"
      - given-names: "Manuel N."
        family-names: "Melo"
      - given-names: "Sean L."
        family-names: "Seyler"
      - given-names: "Jan"
        family-names: "Domanski"
      - given-names: "David L."
        family-names: "Dotson"
      - given-names: "Sebastien"
        family-names: "Buchoux"
      - given-names: "Ian M."
        family-names: "Kenney"
      - given-names: "Oliver"
        family-names: "Beckstein"
    editors:
      - given-names: "Sebastian"
        family-names: "Benthall"
      - given-names: "Scott"
        family-names: "Rostrup"
    conference:
      name: "Proceedings of the 15th Python in Science Conference"
      city: "Austin"
      region: "Texas"
      country: "US"
    year: 2016
    pages: 98-105
    doi: "10.25080/Majora-629e541a-00e"
    url: "https://www.osti.gov/biblio/1565806"
    keywords:
      - "software"
      - "molecular dynamics simulations"
      - "science"
      - "chemistry"
      - "physics"
      - "biology"

  - type: "article"
    title: >-
      MDAnalysis: A toolkit for the analysis of molecular dynamics simulations
    abstract: >-
      Abstract MDAnalysis is an object-oriented library for structural and
      temporal analysis of molecular dynamics (MD) simulation trajectories and
      individual protein structures. It is written in the Python language with
      some performance-critical code in C. It uses the powerful NumPy package
      to expose trajectory data as fast and efficient NumPy arrays. It has been
      tested on systems of millions of particles. Many common file formats of
      simulation packages including CHARMM, Gromacs, Amber, and NAMD and the
      Protein Data Bank format can be read and written. Atoms can be selected
      with a syntax similar to CHARMM's powerful selection commands. MDAnalysis
      enables both novice and experienced programmers to rapidly write their
      own analytical tools and access data stored in trajectories in an easily
      accessible manner that facilitates interactive explorative analysis.
      MDAnalysis has been tested on and works for most Unix-based platforms
      such as Linux and Mac OS X. It is freely available under the GNU General
      Public License from http://mdanalysis.googlecode.com.
    authors:
      - given-names: "Naveen"
        family-names: "Michaud-Agrawal"
      - given-names: "Elizabeth J."
        family-names: "Denning"
      - given-names: "Thomas B."
        family-names: "Woolf"
      - given-names: "Oliver"
        family-names: "Beckstein"
    journal: "Journal of Computational Chemistry"
    volume: 32
    number: 10
    pages: "2319-2327"
    year: 2011
    doi: "10.1002/jcc.21787"
    url: "https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.21787"
    keywords:
      - "molecular dynamics simulations"
      - "analysis"
      - "proteins"
      - "object-oriented design"
      - "software"
      - "membrane systems"
      - "Python programming language"

  - type: "software"
    title: "NumPy"
    abstract: "The fundamental package for scientific computing with Python."
    authors:
      - name: "All Contributors to NumPy"
    url: "https://numpy.org"
    repository-code: "https://github.com/numpy/numpy"
    license: "BSD-3-Clause"
    license-url: "https://opensource.org/licenses/BSD-3-Clause"
    keywords:
      - "python"
      - "numpy"
      - "closember"

  - type: "article"
    title: "Array programming with NumPy"
    abstract: >-
      Array programming provides a powerful, compact and expressive syntax for
      accessing, manipulating and operating on data in vectors, matrices and
      higher-dimensional arrays. NumPy is the primary array programming library
      for the Python language. It has an essential role in research analysis
      pipelines in fields as diverse as physics, chemistry, astronomy,
      geoscience, biology, psychology, materials science, engineering, finance
      and economics. For example, in astronomy, NumPy was an important part of
      the software stack used in the discovery of gravitational waves and in
      the first imaging of a black hole. Here we review how a few fundamental
      array concepts lead to a simple and powerful programming paradigm for
      organizing, exploring and analysing scientific data. NumPy is the
      foundation upon which the scientific Python ecosystem is constructed. It
      is so pervasive that several projects, targeting audiences with
      specialized needs, have developed their own NumPy-like interfaces and
      array objects. Owing to its central position in the ecosystem, NumPy
      increasingly acts as an interoperability layer between such array
      computation libraries and, together with its application programming
      interface (API), provides a flexible framework to support the next decade
      of scientific and industrial analysis.
    authors:
      - given-names: "Charles R."
        family-names: "Harris"
      - given-names: "K. Jarrod"
        family-names: "Millman"
      - given-names: "Stéfan J."
        family-names: "van der Walt"
      - given-names: "Ralf"
        family-names: "Gommers"
      - given-names: "Pauli"
        family-names: "Virtanen"
      - given-names: "David"
        family-names: "Cournapeau"
      - given-names: "Eric"
        family-names: "Wieser"
      - given-names: "Julian"
        family-names: "Taylor"
      - given-names: "Sebastian"
        family-names: "Berg"
      - given-names: "Nathaniel J."
        family-names: "Smith"
      - given-names: "Robert"
        family-names: "Kern"
      - given-names: "Matti"
        family-names: "Picus"
      - given-names: "Stephan"
        family-names: "Hoyer"
      - given-names: "Marten H."
        family-names: "van Kerkwijk"
      - given-names: "Matthew"
        family-names: "Brett"
      - given-names: "Allan"
        family-names: "Haldane"
      - given-names: "Jaime Fernández"
        family-names: "del Río"
      - given-names: "Mark"
        family-names: "Wiebe"
      - given-names: "Pearu"
        family-names: "Peterson"
      - given-names: "Pierre"
        family-names: "Gérard-Marchant"
      - given-names: "Kevin"
        family-names: "Sheppard"
      - given-names: "Tyler"
        family-names: "Reddy"
      - given-names: "Warren"
        family-names: "Weckesser"
      - given-names: "Hameer"
        family-names: "Abbasi"
      - given-names: "Christoph"
        family-names: "Gohlke"
      - given-names: "Travis E."
        family-names: "Oliphant"
    journal: "Nature"
    volume: 585
    number: 7825
    pages: "357-362"
    year: 2020
    month: 9
    publisher:
      name: "Springer Science and Business Media LLC"
    doi: "10.1038/s41586-020-2649-2"
    url: "https://doi.org/10.1038/s41586-020-2649-2"