Award Abstract # 2229690
POSE: Phase I: A Path to Sustaining a New Open-Source Ecosystem for Materials Science (OSEMatS)

NSF Org: TI
Translational Impacts
Recipient: THE PENNSYLVANIA STATE UNIVERSITY
Initial Amendment Date: September 9, 2022
Latest Amendment Date: September 9, 2022
Award Number: 2229690
Award Instrument: Standard Grant
Program Manager: Richard Dawes
rdawes@nsf.gov
 (703)292-7486
TI
 Translational Impacts
TIP
 Directorate for Technology, Innovation, and Partnerships
Start Date: September 15, 2022
End Date: February 29, 2024 (Estimated)
Total Intended Award Amount: $300,000.00
Total Awarded Amount to Date: $300,000.00
Funds Obligated to Date: FY 2022 = $300,000.00
History of Investigator:
  • Zi-Kui Liu (Principal Investigator)
  • ShunLi Shang (Co-Principal Investigator)
Recipient Sponsored Research Office: Pennsylvania State Univ University Park
201 OLD MAIN
UNIVERSITY PARK
PA  US  16802-1503
(814)865-1372
Sponsor Congressional District: 15
Primary Place of Performance: Pennsylvania State Univ University Park
201 Old Main
University Park
PA  US  16802-1503
Primary Place of Performance
Congressional District:
15
Unique Entity Identifier (UEI): NPM2J7MSCF61
Parent UEI:
NSF Program(s): POSE
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s): 211Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.084

ABSTRACT

This project is funded by Pathways to Enable Open-Source Ecosystems (POSE) which seeks to harness the power of open-source development for the creation of new technology solutions to problems of national and societal importance. OSEMatS aims to scope preparatory activities to enable the growth of existing open-source materials research tools into a sustainable and robust Open-Source Ecosystem (OSE) that will have broad and lasting scientific and societal impacts. OSEMatS stems from the team?s nonprofit Materials Genome Foundation (MGF) incorporated in 2018 for ?promoting computational approaches in science and engineering through organizing workshops and supporting the development of computational tools and databases?. The existing open-source tools on GitHub developed by the team are PyCalphad and ESPEI (Extensible Self-optimizing Phase Equilibria Infrastructure) for the modeling and applications of thermodynamics, which is the most fundamental component of materials science and engineering, through the calculation of phase diagram (CALPHAD) method which is the backbone of the Integrated Computational Materials Engineering (ICME) and Materials Genome Initiative (MGI). An advisory council will be established within the MGF and will include key contributors and stakeholders associated with PyCalphad and related projects, as well as external subject matter experts in open-source governance. The near-term goal of OSEMatS is to develop and execute a strategic plan for a sustainable PyCalphad and ESPEI OSE using an organized and intentional approach through joint efforts between MGF and The Pennsylvania State University (PSU). The long-term vision of OSEMatS seeks to promote the computational thermodynamics library PyCalphad as a foundational component of scientific computing within materials science, supporting a robust portfolio of associated software projects and user cases to enable the integrated computational-experimental fundamental research and data-driven discovery and inverse-design of materials with emergent functionalities.

OSEMatS will engage in several planning and outreach activities with the goal of devising a path to sustainability. OSEMatS will (i) empower its user community to become contributors, mentors, and technical leaders through interactive workshops; (ii) ensure a low barrier for onboarding of new projects by providing access to MGF organizational resources commensurate with transparent success criteria and periodic evaluation processes; and (iii) organize outreach activities and events within OSEMatS in a manner consistent with a commitment to inclusion, diversity, equity, and accessibility (IDEA). To organize outreach activities coherently, the team incorporated the nonprofit MGF in 2018, aiming to search for a sustainability model to continue the development of OSE in alignment with the POSE program for the creation and maintenance of infrastructure needed for efficient and secure operation of the OSEMatS. PyCalphad and ESPEI have demonstrated their global impacts on computational materials science for universities, national laboratories, and commercial companies. The POSE program will provide necessary support to kickstart a path to sustainability for OSEMatS, based on the open-source PyCalphad and ESPEI, along with many new ones on the way from the PI?s group and in the community through increased coordination of developer contributions and a more focused route to impactful technologies. OSEMatS will enable better fundamental understanding of materials and efficient discovery and design of advanced materials to benefit our society. The team will actively engage students in these activities via various educational and outreach programs at PSU as done in the past such as the Summer Research Opportunity Program for high school students, the Women in Science and Engineering Research program, and student chapters of various professional societies.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Liu, Zi-Kui "Quantitative predictive theories through integrating quantum, statistical, equilibrium, and nonequilibrium thermodynamics" Journal of Physics: Condensed Matter , v.36 , 2024 https://doi.org/10.1088/1361-648X/ad4762 Citation Details
Liu, Zi-Kui "Thermodynamics and its prediction and CALPHAD modeling: Review, state of the art, and perspectives" Calphad , v.82 , 2023 https://doi.org/10.1016/j.calphad.2023.102580 Citation Details
Olson, G.B. and Liu, Z.K. "Genomic materials design: CALculation of PHAse Dynamics" Calphad , v.82 , 2023 https://doi.org/10.1016/j.calphad.2023.102590 Citation Details
Paz Soldan Palma, Jorge and Gong, Rushi and Bocklund, Brandon J. and Otis, Richard and Poschmann, Max and Piro, Markus and Shahbazi, Shayan and Levitskaia, Tatiana G. and Hu, Shenyang and Smith, Nathan D. and Wang, Yi and Kim, Hojong and Liu, Zi-Kui and S "Thermodynamic modeling with uncertainty quantification using the modified quasichemical model in quadruplet approximation: Implementation into PyCalphad and ESPEI" Calphad , v.83 , 2023 https://doi.org/10.1016/j.calphad.2023.102618 Citation Details
Sun, Hui and Pan, Bo and Yang, Zhening and Krajewski, Adam M and Bocklund, Brandon and Shang, Shun-Li and Li, Jingjing and Beese, Allison M and Liu, Zi-Kui "MaterialsMap: A CALPHAD-based tool to design composition pathways through feasibility map for desired dissimilar materials, demonstrated with resistance spot welding joining of Ag-Al-Cu" Materialia , v.36 , 2024 https://doi.org/10.1016/j.mtla.2024.102153 Citation Details
Sun, Hui and Shang, Shun-Li and Gong, Rushi and Bocklund, Brandon J. and Beese, Allison M. and Liu, Zi-Kui "Thermodynamic modeling of the Nb-Ni system with uncertainty quantification using PyCalphad and ESPEI" Calphad , v.82 , 2023 https://doi.org/10.1016/j.calphad.2023.102563 Citation Details

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

The proposed Open-Source Ecosystem for Materials Science (OSEMatS) aims to scope preparatory activities to enable the growth of existing open-source materials research tools into a sustainable and robust Open-Source Ecosystem (OSE) that will have broad and lasting scientific and societal impacts. In this project, the performed researches and the gained achievements are as follows:

  1. Generation of the OSEMatS; see the included software tools in software.phaseslab.org
  2. Empowerment of the OSEMatS user community through the Materials Genome Foundation (MGF) workshops; see details and the associated YouTube videos summarized in: https://materialsgenomefoundation.org/workshop
  3. Development and distribution of open-source software packages
    1. Development of pycalphad, ESPEI, pySIPFENN
    2. New tools introduced such as (i) nimCSO (nimComposition Space Optimization) for high-performance tool implementing several methods for selecting components (data dimensions) in compositional datasets, which optimize the data availability and density for applications; (ii) nimplex (nimplex.phaseslab.org) implements several simplex-specific methods and, critically, introduces a novel algorithm for constructing compositional graphs orders of magnitude faster.
    3.  MaterialsMap (https://github.com/PhasesResearchLab/MaterialsMap) is Python package for mapping properties, manufacturing feasibility, and desirability. We focus on guiding materials design graphically while proving an API to underlying methods, so that others can utlize it as an engine behind their tools, like machine learning (ML) based alloy design.
    4. Open-source textbook created for materials science, as demonstrated by the book of “computational thermodynamics of materials” at https://github.com/materialsgenomefoundation/nobook
    5. Six journal articles have been published as shown in the Products section and two articles have been submitted and were in arXiv. They are: (i) Adam M. Krajewski, Arindam Debnath, Allison M. Beese, Wesley F. Reinhart, and Zi-Kui Liu, nimCSO: A Nim package for Compositional Space Optimization, March 2024: arXiv: abs/2403.02340, (ii) Adam M. Krajewski, Allison M. Beese, Wesley F. Reinhart, and Zi-Kui Liu, Efficient Generation of Grids and Traversal Graphs in Compositional Spaces towards Exploration and Path Planning Exemplified in Materials, February 2024. arXiv: abs/2402.03528
    6. One PhD student (Adam M. Krajewski) was graduated in May 2024. 

Last Modified: 06/26/2024
Modified by: Shunli Shang

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