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<title>
Materials-Science-Workflows.html
</title>
</head>
<body>
<header style="font-size:2.0em;
font-weight:600;
letter-spacing:1px;
color:#f10ea2;
margin-bottom:1.0em;
text-align:center;
padding-top:40px;"> <!--MH: adjust position of the header text-->
PC<sup>2</sup> presents <!--MH: Put header title here and color is defined just few lines above-->
</header>
<div class="card">
<div id="page">
<div id="main">
<div id="main-header">
<!-- <div id="breadcrumb-section">
<ol id="breadcrumbs">
<li>
<span>
<a href="index.html">
PC2 presents
</a>
</span>
</li>
</ol>
</div> -->
<h1 id="title-heading">
<span id="title-text">
Materials Science Workflows
</span>
</h1>
<img src="./logos/pc2_logo_2.png" alt="PC2 Logo" class="in-card-logo">
</div>
<div id="content">
<div id="main-content">
<p>
<strong>
Introduction:
</strong>
</p>
<p>
In the rapidly evolving field of materials science (including physics, chemistry,
nanotechnology, and data science), computational workflows have become indispensable for
automating, managing, and analyzing complex simulations to accelerate materials
discovery and design. These workflows, ranging from flexible simulation environments to
robust high-throughput automation systems, enable researchers to efficiently handle
atomistic calculations, such as density functional theory (DFT), molecular dynamics
(MD), and machine learning (ML)/artificial intelligence (AI) driven predictions.
Open-source workflow systems provide modular, scalable solutions that integrate with
popular computational codes and support diverse applications, from small-scale studies
to large-scale materials screening. The following table summarizes the prominent
open-source workflows, detailing their field of application, development teams,
supported simulations, and key features. This compilation serves as a guide for
researchers to select the most suitable workflow for their computational needs,
fostering reproducible, data-driven advancements in materials science.
</p>
<p>
<br />
</p>
<p>
<strong>
Motivation:
</strong>
</p>
<p>
Computational workflows are critical because they streamline repetitive tasks, reduce
human error, and enable the processing of vast datasets, which are essential for
discovering new materials with tailored properties. By automating simulations and
ensuring data provenance, these tools enhance reproducibility, accelerate research
cycles, and facilitate collaboration across disciplines. In an era of big data and
AI-driven discovery, workflows empower researchers to tackle complex challenges—such as
designing sustainable energy materials or advanced semiconductors—efficiently and
cost-effectively, making them vital for scientific and technological breakthroughs.
</p>
<p>
<br />
</p>
<p>
<strong>
Purpose:
</strong>
</p>
<p>
This table compiles prominent open-source and free to use computational workflows to
guide researchers in selecting tools that best fit their simulation needs, whether for
small-scale prototyping or large-scale high-throughput screening. It provides a concise
overview of each workflow's applications, supported simulations, scalability, and unique
features, enabling users to compare options and adopt solutions that enhance
productivity and reproducibility. Designed for materials scientists, physicists,
chemists, and data scientists, this resource aims to foster data-driven advancements by
promoting accessible, community-supported tools.
</p>
<p>
<br />
</p>
<!--------------------------------------------------------->
<div class="content-layout">
<div class="content-left">
<p>
<strong>
Key Term Definitions:
</strong>
</p>
<div class="expander">
<div role="heading">
<button aria-expanded="false" type="button" onclick="toggleThisExpander(this)">
Workflow
</button>
</div>
<div class="expander-content" role="region" style="display: none;">
<p>
A workflow is a structured sequence of computational tasks and processes designed
to conduct simulations and analyses systematically. It involves steps such as setup,
execution, and post-processing of simulations, ensuring efficiency, reproducibility,
and accuracy in scientific research.
<a href="https://www.ibm.com/think/topics/workflow" rel="nofollow">
IBM - Workflow
</a>
</p>
</div>
</div>
<div class="expander">
<div role="heading">
<button aria-expanded="false" type="button" onclick="toggleThisExpander(this)">
High-throughput
</button>
</div>
<div class="expander-content" role="region" style="display: none;">
<p>
High-throughput refers to the automated process of screening and analyzing
a large number of samples or materials or data points efficiently and
systematically. In various scientific contexts, such as in genomics,
pharmaceuticals, and materials science, high-throughput techniques allow
researchers to conduct experiments and collect data on a massive scale,
accelerating the discovery and analysis processes. High-throughput
screening (HTS), for example, is a method used in drug discovery to
quickly assess the biological or biochemical activity of a large number
of compounds.
<a href="https://en.wikipedia.org/wiki/High-throughput_screening" rel="nofollow">
High-Throughput Screening - Wikipedia
</a>
</p>
</div>
</div>
<div class="expander">
<div role="heading">
<button aria-expanded="false" type="button" onclick="toggleThisExpander(this)">
FAIR Principles
</button>
</div>
<div class="expander-content" role="region" style="display: none;">
<p>
FAIR principles are basically a set of guidelines designed to ensure data is
Findable, Accessible, Interoperable, and Reusable (FAIR), promoting
efficient
data sharing and reproducibility in scientific research, particularly in
materials science and other data-driven fields.
<a href="https://www.go-fair.org/fair-principles/" rel="nofollow">
FAIR Principles - GO FAIR
</a>
</p>
</div>
</div>
<div class="expander">
<div role="heading">
<button aria-expanded="false" type="button" onclick="toggleThisExpander(this)">
Data Provenance
</button>
</div>
<div class="expander-content" role="region" style="display: none;">
<p>
Data provenance, often referred to as data lineage, is the documentation of
the origin, movement, and transformation of data throughout its
lifecycle—from
creation or capture to storage, analysis, and ultimately, final use or
sharing.
It provides a record of where data comes from, how it is processed, and what
happens to it over time. This information is crucial for ensuring data
integrity, reproducibility, and trustworthiness.
<a href="https://en.wikipedia.org/wiki/Data_lineage#Data_provenance" rel="nofollow">
Data Provenance - Wikipedia
</a>
</p>
</div>
</div>
<div class="expander">
<div role="heading">
<button aria-expanded="false" type="button" onclick="toggleThisExpander(this)">
Big Data
</button>
</div>
<div class="expander-content" role="region" style="display: none;">
<p>
Big Data refers to extremely large and complex datasets that cannot be
effectively processed or analyzed using traditional data processing tools
and methods. It is characterized by the "3 Vs" (Volume, Velocity, Variety)
and often extended to include Veracity and Value.
<a href="https://en.wikipedia.org/wiki/Big_data" rel="nofollow">
Wikipedia - Big Data
</a>
</p>
</div>
</div>
<div class="expander">
<div role="heading">
<button aria-expanded="false" type="button" onclick="toggleThisExpander(this)">
Meta Data
</button>
</div>
<div class="expander-content" role="region" style="display: none;">
<p>
Metadata is data that provides information about other data, describing
its characteristics, structure, or context to facilitate its management,
discovery, and use. Often referred to as "data about data," metadata
includes details such as the data's source, format, size, creation date,
author, location, or permissions.
<a href="https://en.wikipedia.org/wiki/Metadata" rel="nofollow">
Wikipedia - Metadata
</a>
</p>
</div>
</div>
</div>
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<div style="font-size: 0.9em; color: #8ea9b9; margin-top: 4px;">
Figure: Workflow (
<a href="https://www.alamy.de/stockfoto-halber-kopf-menschliche-gehirn-idee-konzept-138145776.html"
style="color: #8ea9b9; text-decoration: none;"
target="_blank"
rel="noopener noreferrer">
credit
</a>
)
</div>
</div> -->
</div>
<p>
<br />
</p>
<p>
<br />
</p>
<div>
</div>
<div class="fullwidth-table-outer">
<table>
<colgroup>
<col />
<col />
<col />
<col />
<col />
<col />
<col />
<col />
<col />
<col />
</colgroup>
<tbody>
<tr>
<th data-highlight-colour="#ff8f73" scope="col">
Name
</th>
<th data-highlight-colour="#ff8f73" scope="col">
Field/Area
</th>
<th data-highlight-colour="#ff8f73" scope="col">
Scale of Workflows
</th>
<th data-highlight-colour="#ff8f73" scope="col">
Supported Simulations
</th>
<th data-highlight-colour="#ff8f73" scope="col">
Key Tools/Features
</th>
<th data-highlight-colour="#ff8f73" scope="col">
Tutorials/Resources
</th>
<th data-highlight-colour="#ff8f73" scope="col">
Responsible Group
</th>
<th data-highlight-colour="#ff8f73" scope="col">
Institute/Affiliation
</th>
<th data-highlight-colour="#ff8f73" scope="col">
Active
</th>
<th data-highlight-colour="#ff8f73" scope="col">
Description
</th>
</tr>
<tr>
<td data-highlight-colour="#abf5d1">
<div>
<p>
<strong title="">
<a href="https://wiki.fysik.dtu.dk/ase/" rel="nofollow">
ASE
</a>
</strong>
</p>
<p>
<strong title="">
<a href="https://wiki.fysik.dtu.dk/ase/" rel="nofollow">
<span>
<img src="./logos/112820663.png" alt="ASE logo" width="43" />
</span>
</a>
</strong>
</p>
</div>
</td>
<td data-highlight-colour="#abf5d1">
Atomistic Simulations
</td>
<td data-highlight-colour="#abf5d1">
Small-scale (e.g., single molecules) to large-scale high-throughput
computations
</td>
<td data-highlight-colour="#abf5d1">
DFT, MD, NEB, Transport, Structure Optimization, Thermochemistry, Phonon
calculations using all the major First Principles codes
</td>
<td data-highlight-colour="#abf5d1">
<a href="https://wiki.fysik.dtu.dk/ase/python.html#what-is-python"
rel="nofollow" title="">
Python interfaces,
</a>
<a href="https://wiki.fysik.dtu.dk/ase/ase/calculators/calculators.html#module-ase.calculators"
rel="nofollow" title="">
ASE Calculators,
</a>
<a href="https://wiki.fysik.dtu.dk/ase/ase/optimize.html#module-ase.optimize"
rel="nofollow" title="">
Structure optimization,
</a>
<a href="https://wiki.fysik.dtu.dk/ase/ase/visualize/visualize.html#module-ase.visualize"
rel="nofollow" title="">
Visualization,
</a>
<a href="https://wiki.fysik.dtu.dk/ase/ecosystem.html" rel="nofollow" title="">
ASE echosystem,
</a>
<a href="https://wiki.fysik.dtu.dk/ase/ase/ase.html" rel="nofollow" title="">
other ASE modules
</a>
</td>
<td data-highlight-colour="#abf5d1">
<p>
<a href="https://ase-workshop-2023.github.io/tutorial/" rel="nofollow">
Tutorials-ASE
</a>
</p>
<p>
<a href="https://www.youtube.com/watch?v=DhAMoJv8M_o" rel="nofollow">
Video-Tutorials
</a>
</p>
<p>
<br />
</p>
</td>
<td data-highlight-colour="#abf5d1">
ASE Developers including
<a href="https://orbit.dtu.dk/en/persons/ask-hjorth-larsen" rel="nofollow"
title="">
Ask Hjorth Larsen
</a>
</td>
<td data-highlight-colour="#abf5d1">
<a href="https://www.dtu.dk/english/" rel="nofollow" title="">
DTU, Denmark
</a>
and others
</td>
<td data-highlight-colour="#abf5d1">
Yes
</td>
<td data-highlight-colour="#abf5d1">
An open-source Python library for setting up, manipulating, running,
visualizing, and analyzing atomistic simulations.
</td>
</tr>
<tr>
<td data-highlight-colour="#fff0b3">
<div>
<p>
<strong title="">
<a href="https://www.aiida.net/" rel="nofollow">
AiiDA
</a>
</strong>
</p>
<p>
<br />
</p>
<p>
<a href="https://www.aiida.net/" rel="nofollow">
<span>
<img src="./logos/112820664.png" alt="AiiDA logo" width="84" />
</span>
</a>
</p>
</div>
</td>
<td data-highlight-colour="#fff0b3">
High-Throughput Simulations, Workflow Management
</td>
<td data-highlight-colour="#fff0b3">
Medium-scale to large-scale high-throughput workflows
</td>
<td data-highlight-colour="#fff0b3">
DFT, MD, High-Throughput Materials Screening, Monte Carlo Simulations,
Machine-Learning Potential Calculations, Supports all major materials
science codes
</td>
<td data-highlight-colour="#fff0b3">
<a href="https://aiidateam.github.io/aiida-registry/" rel="nofollow" title="">
AiiDA plungins,
</a>
<a href="https://aiida.readthedocs.io/projects/aiida-core/en/stable/topics/workflows/index.html"
rel="nofollow" title="">
Worksflow,
</a>
<a href="https://aiida.readthedocs.io/projects/aiida-core/en/stable/topics/provenance/index.html"
rel="nofollow" title="">
Provenance,
</a>
<a href="https://www.aiidalab.net/" rel="nofollow" title="">
AiiDAlab,
</a>
</td>
<td data-highlight-colour="#fff0b3">
<p>
<a href="https://aiida-tutorials.readthedocs.io/en/latest/" rel="nofollow">
Tutorials-AiiDA
</a>
</p>
<p>
<a href="https://www.youtube.com/watch?v=RtdXXWFLvF8&list=PL19kfLn4sO_-e_A9lVYb_NBNcwoVvUP6V"
rel="nofollow">
Video-Tutorials
</a>
</p>
<p>
<a href="https://www.youtube.com/watch?v=t6kNLwkGMP0" rel="nofollow">
Hands-on-video
</a>
</p>
</td>
<td data-highlight-colour="#fff0b3">
AiiDA Team, led by Prof.
<a href="https://people.epfl.ch/nicola.marzari?lang=en" rel="nofollow" title="">
Nicola Marzari
</a>
and
<a href="https://www.psi.ch/en/lms/people/giovanni-pizzi" rel="nofollow"
title="">
Giovanni Pizzi
</a>
</td>
<td data-highlight-colour="#fff0b3">
<a href="https://www.epfl.ch/en/" rel="nofollow" title="">
École Polytechnique Fédérale de Lausanne (EPFL), Switzerland
</a>
</td>
<td data-highlight-colour="#fff0b3">
Yes
</td>
<td data-highlight-colour="#fff0b3">
An open-source Python framework for managing, automating, and preserving
computational materials science workflows with full data provenance.
</td>
</tr>
<tr>
<td data-highlight-colour="#abf5d1">
<div>
<p>
<strong title="">
<a href="https://github.com/materialsproject/jobflow"
rel="nofollow">
JobFlow
</a>
</strong>
</p>
<p>
<br />
</p>
<p>
<a href="https://github.com/materialsproject/jobflow" rel="nofollow">
<span>
<img src="./logos/112820659.png" alt="JobFlow" width="70" />
</span>
</a>
</p>
</div>
</td>
<td data-highlight-colour="#abf5d1">
Materials science, Computational Chemistry and Physics, and
High-throughput Computing
</td>
<td data-highlight-colour="#abf5d1">
Medium-scale to large-scale high-throughput workflows locally or on HPC
</td>
<td data-highlight-colour="#abf5d1">
DFT, MD, Machine learning-based property predictions, High-throughput
materials screening, Custom workflows for user-defined computational
tasks
</td>
<td data-highlight-colour="#abf5d1">
<a href="https://github.com/materialsproject/jobflow" rel="nofollow" title="">
Job and Flow Objects, Dynamic Workflows, Database Integration,
Tutorials and Support
</a>
</td>
<td data-highlight-colour="#abf5d1">
<p>
<a href="https://materialsproject.github.io/jobflow/tutorials.html"
rel="nofollow">
Tutorials-JobFlow
</a>
</p>
<p>
<br />
</p>
</td>
<td data-highlight-colour="#abf5d1">
Materials Project team including Alex Ganose, Anubhav Jain, Gian-Marco
Rignanese
</td>
<td data-highlight-colour="#abf5d1">
<a href="https://www.lbl.gov/" rel="nofollow" title="">
Lawrence Berkeley National Laboratory (LBNL),
</a>
<a href="https://www.berkeley.edu/" rel="nofollow" title="">
University of California, Berkeley,
</a>
<a href="https://www.uclouvain.be/en" rel="nofollow" title="">
UCLouvain,
</a>
<a href="https://ucsd.edu/" rel="nofollow" title="">
UC San Diego,
</a>
</td>
<td data-highlight-colour="#abf5d1">
Yes
</td>
<td data-highlight-colour="#abf5d1">
<p>
An open-source Python library for creating and executing
computational workflows. It allows users to define dynamic and
complex workflows to accelerate computational materials science.
</p>
</td>
</tr>
<tr>
<td data-highlight-colour="#fff0b3">
<div>
<p>
<strong title="">
<a href="https://atomate.org/" rel="nofollow">
Atomate
</a>
</strong>
</p>
<p>
<br />
</p>
<p>
<a href="https://atomate.org/" rel="nofollow">
<span>
<img src="./logos/112820662.png" alt="Atomate logo" width="81" />
</span>
</a>
</p>
</div>
</td>
<td data-highlight-colour="#fff0b3">
High-Throughput Materials Discovery, Workflow Automation
</td>
<td data-highlight-colour="#fff0b3">
Single material simulations to large-scale high-throughput campaigns
</td>
<td data-highlight-colour="#fff0b3">
DFT, Elastic Property Calculations, BoltzTraP, Dielectric Properties,
NEB, XAS and EELS spectra, Equation of State, Piezoelectric tensor,
Ferroelectricity
</td>
<td data-highlight-colour="#fff0b3">
<a href="https://atomate.org/#workflows" rel="nofollow" title="">
Atomate Workflow
</a>
</td>
<td data-highlight-colour="#fff0b3">
<p>
<a href="https://atomate.org/#documentation-tutorials" rel="nofollow">
Tutorials-Atomate
</a>
</p>
<p>
<a href="https://atomate.org/creating_workflows.html" rel="nofollow">
Create-Customize-Workflow
</a>
</p>
</td>
<td data-highlight-colour="#fff0b3">
Atomate Development Team lead by
<a href="https://bids.berkeley.edu/people/anubhav-jain" rel="nofollow" title="">
Anubhav Jain
</a>
</td>
<td data-highlight-colour="#fff0b3">
<a href="https://www.lbl.gov/" rel="nofollow" title="">
Lawrence Berkeley National Laboratory (LBNL),
</a>
<a href="https://www.berkeley.edu/" rel="nofollow" title="">
University of California, Berkeley
</a>
</td>
<td data-highlight-colour="#fff0b3">
Yes
</td>
<td data-highlight-colour="#fff0b3">
An open-source Python framework for automating high-throughput materials
science simulations, built on Pymatgen, custodian and FireWorks, with a
focus on pre-built, reproducible workflows.
</td>
</tr>
<tr>
<td data-highlight-colour="#abf5d1">
<div>
<p>
<strong title="">
<a href="https://pymatgen.org/" rel="nofollow">
Pymatgen
</a>
</strong>
</p>
<p>
<br />
</p>
<p>
<a href="https://pymatgen.org/" rel="nofollow">
<span>
<img src="./logos/112820655.png" alt="Pymatgen logo" width="85" />
</span>
</a>
</p>
</div>
</td>
<td data-highlight-colour="#abf5d1">
Materials Informatics and Materials Analysis
</td>
<td data-highlight-colour="#abf5d1">
Analysis and preprocessing of small to large-scale high-throughput