980
PrOMMiS: Applying Novel Modeling Methods to Accelerate
Critical Minerals Research, Development, Demonstration, and
Deployment (RD3)
Thomas Tarka, Andrew Lee,
Miguel Zamarripa-Perez, Brandon Paul,
Alejandro Garciadiego, Alison Fritz
National Energy Technology Laboratory
Alexander Dowling
University of Notre Dame
Carl Laird, Chrysanthos Gounaris, Ana Torres
Carnegie Mellon University
Debangsu Bhattacharyya
West Virginia University
John Siirola
Sandia National Laboratory
Daniel Gunter, Keith Beattie
Lawrence Berkeley National Laboratory
Nick Sahinidis
Georgia Institute of Technology
ABSTRACT: The Process Optimization and Modeling for Minerals Sustainability (PrOMMiS) Initiative is
a process modeling and optimization toolkit designed to de-risk and compress the “discovery to deployment”
timeline for critical mineral and material (CMM) production technologies. It includes (1) model and cost
libraries for simulation, optimization, and techno-economic analysis of mineral processing technologies
(2) optimization capabilities for screening process configurations to identify the most promising flowsheets
(3) optimization-under-uncertainty approaches to produce designs that are robust to process variability and
(4) uncertainty quantification capabilities to maximize knowledge gained from budget- and schedule-constrained
experimental campaigns.
These tools extend capabilities developed within the Institute for the Design of Advanced Energy Systems
(IDAES) Framework which have been successfully leveraged by other Department of Energy research areas with
a “deploy now” mandate, notably carbon capture technologies, or requiring novel platforms for complex opti-
mization problems and fast decision-making. This open-source, integrated platform (IDAES-IP) is distributed
as a core modeling framework (IDAES-CMF). It is designed for ease of adaptation to address a wide range of
scientific applications and implements modern software development and release practices.
INTRODUCTION
There is a global consensus on the need to address climate
change through a worldwide transition to clean energy
technologies and other mitigation strategies. A number
of nations have pledged actions which range from tripling
global capacity of renewable energy, committing $13.9 bil-
lion to the Green Climate Fund (GCF)—dedicated to
funding projects which address climate change—and
addressing emissions through cohesive strategies involving
transparent trade and investment policies supporting clean

Previous Page Next Page

Extracted Text (may have errors)

980
PrOMMiS: Applying Novel Modeling Methods to Accelerate
Critical Minerals Research, Development, Demonstration, and
Deployment (RD3)
Thomas Tarka, Andrew Lee,
Miguel Zamarripa-Perez, Brandon Paul,
Alejandro Garciadiego, Alison Fritz
National Energy Technology Laboratory
Alexander Dowling
University of Notre Dame
Carl Laird, Chrysanthos Gounaris, Ana Torres
Carnegie Mellon University
Debangsu Bhattacharyya
West Virginia University
John Siirola
Sandia National Laboratory
Daniel Gunter, Keith Beattie
Lawrence Berkeley National Laboratory
Nick Sahinidis
Georgia Institute of Technology
ABSTRACT: The Process Optimization and Modeling for Minerals Sustainability (PrOMMiS) Initiative is
a process modeling and optimization toolkit designed to de-risk and compress the “discovery to deployment”
timeline for critical mineral and material (CMM) production technologies. It includes (1) model and cost
libraries for simulation, optimization, and techno-economic analysis of mineral processing technologies
(2) optimization capabilities for screening process configurations to identify the most promising flowsheets
(3) optimization-under-uncertainty approaches to produce designs that are robust to process variability and
(4) uncertainty quantification capabilities to maximize knowledge gained from budget- and schedule-constrained
experimental campaigns.
These tools extend capabilities developed within the Institute for the Design of Advanced Energy Systems
(IDAES) Framework which have been successfully leveraged by other Department of Energy research areas with
a “deploy now” mandate, notably carbon capture technologies, or requiring novel platforms for complex opti-
mization problems and fast decision-making. This open-source, integrated platform (IDAES-IP) is distributed
as a core modeling framework (IDAES-CMF). It is designed for ease of adaptation to address a wide range of
scientific applications and implements modern software development and release practices.
INTRODUCTION
There is a global consensus on the need to address climate
change through a worldwide transition to clean energy
technologies and other mitigation strategies. A number
of nations have pledged actions which range from tripling
global capacity of renewable energy, committing $13.9 bil-
lion to the Green Climate Fund (GCF)—dedicated to
funding projects which address climate change—and
addressing emissions through cohesive strategies involving
transparent trade and investment policies supporting clean

Help

Destination page number Search scope Search Text

loading

XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 981
energy. (United Nations, 2023) (The White House, 2023)
The increased demand for clean energy technologies to sup-
port the transition has already resulted a significant growth
in mineral demand, a trend which is projected to continue
and accelerate, particularly if efforts to meet Sustainable
Development Scenarios (SDS) for climate mitigation con-
tinue to remain a priority. (International Energy Agency,
2023) (International Energy Agency, 2024)
The U.S. Government (USG) has recognized the
strategic need for critical minerals and materials (CMM)
in the context of energy security, onshoring clean energy
technology manufacturing, and securing CMM supply
chains. The U.S. Department of Energy (DOE) strat-
egy to addresses that need has included over a decade of
research and development efforts into diversifying supply,
developing substitutes, and improving reuse and recycling.
(U.S. Department of Energy, 2021) Recent policies such
as the Infrastructure Investment and Jobs Act (IIJA) and
the Inflation Reduction Act (IRA) have accelerated and
expanded these efforts, dedicating tens of billions of dollars
to critical minerals and clean energy technology research,
with an increased focus placed on rapidly demonstrating
and deploying the technologies which will establish domes-
tic CMM supply chains. (Congressional Research Service,
2023) (Congressional Research Service, 2023)
The urgency of the establishing domestic CMM sup-
ply chains along with the size of the investment has led the
DOE to seek was to accelerate and de-risk these research,
development, demonstration, and deployment (RD3)
efforts. One recently successful effort in this area—accel-
erating RD3—has been the development of the Institute
for Design of Advanced Energy Systems (IDAES) frame-
work. The IDAES Integrated Platform (IDAES-IP) is an
open-source, multi-scale modeling framework which was
designed to provide a robust, configurable platform for
“advanced optimization-based decision-making”: equa-
tion oriented (EO) modeling with support for screening
process designs, determining optimal operating parameters
and configurations, and reducing risk of scale-up through
uncertainty quantification (UQ) and the scientific design of
experiments (SDoE). (Lee, et al., 2021) The IDAES Core
Modeling Framework (IDAES-CMF) is python-based, and
provides a flexible platform that is easily applied to other
application-areas, providing a suite of solvers, libraries for
unit operations and thermophysical property models, and
support for superstructure-based optimization. (Lee, et al.,
2021)
This paper describes the Process Optimization
and Modeling for Minerals Sustainability (PrOMMiS)
Initiative, which extends the IDAES-CMF framework to
modeling CMM systems. PrOMMiS is focused on ampli-
fying the impact of DOE RD3 in the CMM space with an
initial focus on accelerating and de-risking projects enter-
ing the pilot- and demonstration-scale. It builds upon over
a decade of research into both process optimization and
modeling, as well as CMM research funded by the DOE’s
Office of Fossil Energy and Carbon Management (FECM)
and within the Advanced Materials and Manufacturing
Technologies Office (AMMTO)-funded Critical Materials
Innovation Hub (CMI). The approach followed in develop-
ing PrOMMiS will be explored, and several early examples
of applying PrOMMiS are summarized.
APPROACH &METHODOLOGY
PrOMMiS development has been driven by the urgent need
to support DOE-funded CMM RD3 efforts, particularly
projects currently entering the pilot- and demonstration-
scale of development. Modeling needs include (1) process
modeling and cost libraries for simulation, multi-criteria
optimization, and techno-economic analysis (2) optimi-
zation capabilities for process configuration screening and
to identify promising flowsheets (3) optimization-under-
uncertainty approaches to produce designs that are robust
to process variability, and (4) uncertainty quantification
capabilities to inform and maximize knowledge gained
from budget- and schedule-constrained pilot campaigns
and experiments.
Consequently, three guiding principles were estab-
lished to focus the project team:
• Rapidly establish the capability by leveraging existing
projects and learning by doing
• Ensure long-term impact: flexible, foundational plat-
form developed with input from key stakeholders
• Maximize support and integration with other CMM
research portfolios and modeling efforts
Further guidance was received from FECM’s Office
of Resource Sustainability (who funds the initiative) that
efforts should not be limited to the unconventional CMM
resources and processing pathways which are the focus of
FECM research, but instead should include projects and
feedstocks within the AMMTO and CMI purview, notably
recycling and reuse.
Approach
To reinforce the project urgency and focus team efforts, a
goal was set to establish a working process flowsheet for
mineral processing within the first year of the project. This
was deemed feasible based on the flexibility and capabili-
ties of IDAES-CMF, the existence of relevant project data,

Previous Page Next Page

Extracted Text (may have errors)

XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 981
energy. (United Nations, 2023) (The White House, 2023)
The increased demand for clean energy technologies to sup-
port the transition has already resulted a significant growth
in mineral demand, a trend which is projected to continue
and accelerate, particularly if efforts to meet Sustainable
Development Scenarios (SDS) for climate mitigation con-
tinue to remain a priority. (International Energy Agency,
2023) (International Energy Agency, 2024)
The U.S. Government (USG) has recognized the
strategic need for critical minerals and materials (CMM)
in the context of energy security, onshoring clean energy
technology manufacturing, and securing CMM supply
chains. The U.S. Department of Energy (DOE) strat-
egy to addresses that need has included over a decade of
research and development efforts into diversifying supply,
developing substitutes, and improving reuse and recycling.
(U.S. Department of Energy, 2021) Recent policies such
as the Infrastructure Investment and Jobs Act (IIJA) and
the Inflation Reduction Act (IRA) have accelerated and
expanded these efforts, dedicating tens of billions of dollars
to critical minerals and clean energy technology research,
with an increased focus placed on rapidly demonstrating
and deploying the technologies which will establish domes-
tic CMM supply chains. (Congressional Research Service,
2023) (Congressional Research Service, 2023)
The urgency of the establishing domestic CMM sup-
ply chains along with the size of the investment has led the
DOE to seek was to accelerate and de-risk these research,
development, demonstration, and deployment (RD3)
efforts. One recently successful effort in this area—accel-
erating RD3—has been the development of the Institute
for Design of Advanced Energy Systems (IDAES) frame-
work. The IDAES Integrated Platform (IDAES-IP) is an
open-source, multi-scale modeling framework which was
designed to provide a robust, configurable platform for
“advanced optimization-based decision-making”: equa-
tion oriented (EO) modeling with support for screening
process designs, determining optimal operating parameters
and configurations, and reducing risk of scale-up through
uncertainty quantification (UQ) and the scientific design of
experiments (SDoE). (Lee, et al., 2021) The IDAES Core
Modeling Framework (IDAES-CMF) is python-based, and
provides a flexible platform that is easily applied to other
application-areas, providing a suite of solvers, libraries for
unit operations and thermophysical property models, and
support for superstructure-based optimization. (Lee, et al.,
2021)
This paper describes the Process Optimization
and Modeling for Minerals Sustainability (PrOMMiS)
Initiative, which extends the IDAES-CMF framework to
modeling CMM systems. PrOMMiS is focused on ampli-
fying the impact of DOE RD3 in the CMM space with an
initial focus on accelerating and de-risking projects enter-
ing the pilot- and demonstration-scale. It builds upon over
a decade of research into both process optimization and
modeling, as well as CMM research funded by the DOE’s
Office of Fossil Energy and Carbon Management (FECM)
and within the Advanced Materials and Manufacturing
Technologies Office (AMMTO)-funded Critical Materials
Innovation Hub (CMI). The approach followed in develop-
ing PrOMMiS will be explored, and several early examples
of applying PrOMMiS are summarized.
APPROACH &METHODOLOGY
PrOMMiS development has been driven by the urgent need
to support DOE-funded CMM RD3 efforts, particularly
projects currently entering the pilot- and demonstration-
scale of development. Modeling needs include (1) process
modeling and cost libraries for simulation, multi-criteria
optimization, and techno-economic analysis (2) optimi-
zation capabilities for process configuration screening and
to identify promising flowsheets (3) optimization-under-
uncertainty approaches to produce designs that are robust
to process variability, and (4) uncertainty quantification
capabilities to inform and maximize knowledge gained
from budget- and schedule-constrained pilot campaigns
and experiments.
Consequently, three guiding principles were estab-
lished to focus the project team:
• Rapidly establish the capability by leveraging existing
projects and learning by doing
• Ensure long-term impact: flexible, foundational plat-
form developed with input from key stakeholders
• Maximize support and integration with other CMM
research portfolios and modeling efforts
Further guidance was received from FECM’s Office
of Resource Sustainability (who funds the initiative) that
efforts should not be limited to the unconventional CMM
resources and processing pathways which are the focus of
FECM research, but instead should include projects and
feedstocks within the AMMTO and CMI purview, notably
recycling and reuse.
Approach
To reinforce the project urgency and focus team efforts, a
goal was set to establish a working process flowsheet for
mineral processing within the first year of the project. This
was deemed feasible based on the flexibility and capabili-
ties of IDAES-CMF, the existence of relevant project data,

XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 963
herein to any specific commercial product, process, or ser-
vice by trade name, trademark, manufacturer, or otherwise
does not necessarily constitute or imply its endorsement,
recommendation, or favoring by the USA Government
or any agency thereof. The views and opinions of authors
expressed herein do not necessarily state or reflect those of
the USA Government or any agency thereof.
REFERENCES
Bourricaudy, Ernesto, Niels Verbaan, James Brown, Ronald
Molnar, and Sunil Jayasekera. 2016. “Commissioning
of a mini REE SX Pilot Plant at SGS Minerals-Lakefield
Site.” Pp. 978–79 in IMPC. Canadian Institute of
Mining, Metallurgy and Petroleum.
Chen, Ziying, Zhan Li, Jia Chen, Parashuram Kallem,
Fawzi Banat, and Hongdeng Qiu. 2022. “Recent
Advances in Selective Separation Technologies of Rare
Earth Elements: A Review.” Journal of Environmental
Chemical Engineering 10(1):107104. doi: 10.1016
/J.JECE.2021.107104.
Chi-Linh Do-Thanh, Huimin Luo, and Sheng Dai. 2023.
“A Perspective on Task-Specific Ionic Liquids for the
Separation of Rare Earth Elements.” RSC Sustainability.
doi: 10.1039/D3SU00007A.
Fernández, Ruben García, and J. Ignacio García
Alonso. 2008. “Separation of Rare Earth Elements
by Anion-Exchange Chromatography Using
Ethylenediaminetetraacetic Acid as Mobile Phase.”
Journal of Chromatography A 1180(1–2):59–65. doi:
10.1016/J.CHROMA.2007.12.008.
Inoue, Yoshinori, Hiroki Kumagai, Yoshiko Shimomura,
Toshiro Yokoyama, and Toshishige M. Suzuki. 1996.
“Ion Chromatographic Separation of Rare-Earth
Elements Using a Nitrilotriacetate-Type Chelating
Resin as the Stationary Phase.” Analytical Chemistry
68(9):1517–20. doi: 10.1021/AC950783K/ASSET
/IMAGES/LARGE/AC950783KF00005.JPEG.
Kaim, Vishakha, Jukka Rintala, and Chao He. 2023.
“Selective Recovery of Rare Earth Elements from
E-Waste via Ionic Liquid Extraction: A Review.”
Separation and Purification Technology 306:122699.
doi: 10.1016/J.SEPPUR.2022.122699.
Koermer, Scott Carl, Christopher A. Noble, Robert B.
Gramacy, Nino S. Ripepi, Emily A. Sarver, and Paul
F. Ziemkiewicz. 2022. “Bayesian Methods for Mineral
Processing Operations.”
Larochelle, Tommee, and Henry Kasaini. 2016. “Predictive
Modeling of Rare Earth Element Separation by
Solvent Extrraction Using METSIM.” Pp. 978–79 in
IMPC 2016: XXVIII International Mineral Processing
Congress. Canadian Institute of Mining, Metallurgy
and Petroleum.
Meloy, T.P. 1983. “Analysis and Optimization of Mineral
Processing and Coal-Cleaning Circuits—Circuit
Analysis.” International Journal of Mineral Processing
10(1):61–80. doi: 10.1016/0301-7516(83)90033-9.
Noble, Aaron, and Gerald H. Luttrell. 2014. “The Matrix
Reduction Algorithm for Solving Separation Circuits.”
Minerals Engineering 64:97–108. doi: 10.1016
/j.mineng.2014.05.024.
Noble, Aaron, Gerald H. Luttrell, and Seyed Hassan Amini.
2019. “Linear Circuit Analysis: A Tool for Addressing
Challenges and Identifying Opportunities in Process
Circuit Design.” Mining, Metallurgy and Exploration
36(1):159–71. doi: 10.1007/s42461-018-0031-9.
Seisenbaeva, Gulaim A. 2020. “Molecular Recognition
Approach to REE Extraction, Separation, and
Recycling.” Minerals, Metals and Materials Series 57–66.
doi: 10.1007/978-3-030-36758-9_6/FIGURES/6.
Turgeon, K., C. Bazin, J.F. Boulanger, L. Whitty-Léveillé,
and D. Larivière. 2016. “Material Balancing and
Estimation of Equilibrium Constants: Application
to Solvent Extraction Tests of Rare Earth Elements.”
Pp. 978–79 in IMPC 2016 -28th International Mineral
Processing Congress. Vols. 2016-Sept.
Turgeon, Keven, Jean François Boulanger, and Claude
Bazin. 2023. “Simulation of Solvent Extraction
Circuits for the Separation of Rare Earth Elements.”
Minerals 13(6):714. doi: 10.3390/min13060714.
Williams, M.C., D.W. Fuerstenau, and T.P. Meloy. 1986.
“Circuit Analysis—General Product Equations
for Multifeed, Multistage Circuits Containing
Variable Selectivity Functions.” International
Journal of Mineral Processing 17(1–2):99–111. doi:
10.1016/0301-7516(86)90048-7.

Previous Page Next Page

Extracted Text (may have errors)

XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 963
herein to any specific commercial product, process, or ser-
vice by trade name, trademark, manufacturer, or otherwise
does not necessarily constitute or imply its endorsement,
recommendation, or favoring by the USA Government
or any agency thereof. The views and opinions of authors
expressed herein do not necessarily state or reflect those of
the USA Government or any agency thereof.
REFERENCES
Bourricaudy, Ernesto, Niels Verbaan, James Brown, Ronald
Molnar, and Sunil Jayasekera. 2016. “Commissioning
of a mini REE SX Pilot Plant at SGS Minerals-Lakefield
Site.” Pp. 978–79 in IMPC. Canadian Institute of
Mining, Metallurgy and Petroleum.
Chen, Ziying, Zhan Li, Jia Chen, Parashuram Kallem,
Fawzi Banat, and Hongdeng Qiu. 2022. “Recent
Advances in Selective Separation Technologies of Rare
Earth Elements: A Review.” Journal of Environmental
Chemical Engineering 10(1):107104. doi: 10.1016
/J.JECE.2021.107104.
Chi-Linh Do-Thanh, Huimin Luo, and Sheng Dai. 2023.
“A Perspective on Task-Specific Ionic Liquids for the
Separation of Rare Earth Elements.” RSC Sustainability.
doi: 10.1039/D3SU00007A.
Fernández, Ruben García, and J. Ignacio García
Alonso. 2008. “Separation of Rare Earth Elements
by Anion-Exchange Chromatography Using
Ethylenediaminetetraacetic Acid as Mobile Phase.”
Journal of Chromatography A 1180(1–2):59–65. doi:
10.1016/J.CHROMA.2007.12.008.
Inoue, Yoshinori, Hiroki Kumagai, Yoshiko Shimomura,
Toshiro Yokoyama, and Toshishige M. Suzuki. 1996.
“Ion Chromatographic Separation of Rare-Earth
Elements Using a Nitrilotriacetate-Type Chelating
Resin as the Stationary Phase.” Analytical Chemistry
68(9):1517–20. doi: 10.1021/AC950783K/ASSET
/IMAGES/LARGE/AC950783KF00005.JPEG.
Kaim, Vishakha, Jukka Rintala, and Chao He. 2023.
“Selective Recovery of Rare Earth Elements from
E-Waste via Ionic Liquid Extraction: A Review.”
Separation and Purification Technology 306:122699.
doi: 10.1016/J.SEPPUR.2022.122699.
Koermer, Scott Carl, Christopher A. Noble, Robert B.
Gramacy, Nino S. Ripepi, Emily A. Sarver, and Paul
F. Ziemkiewicz. 2022. “Bayesian Methods for Mineral
Processing Operations.”
Larochelle, Tommee, and Henry Kasaini. 2016. “Predictive
Modeling of Rare Earth Element Separation by
Solvent Extrraction Using METSIM.” Pp. 978–79 in
IMPC 2016: XXVIII International Mineral Processing
Congress. Canadian Institute of Mining, Metallurgy
and Petroleum.
Meloy, T.P. 1983. “Analysis and Optimization of Mineral
Processing and Coal-Cleaning Circuits—Circuit
Analysis.” International Journal of Mineral Processing
10(1):61–80. doi: 10.1016/0301-7516(83)90033-9.
Noble, Aaron, and Gerald H. Luttrell. 2014. “The Matrix
Reduction Algorithm for Solving Separation Circuits.”
Minerals Engineering 64:97–108. doi: 10.1016
/j.mineng.2014.05.024.
Noble, Aaron, Gerald H. Luttrell, and Seyed Hassan Amini.
2019. “Linear Circuit Analysis: A Tool for Addressing
Challenges and Identifying Opportunities in Process
Circuit Design.” Mining, Metallurgy and Exploration
36(1):159–71. doi: 10.1007/s42461-018-0031-9.
Seisenbaeva, Gulaim A. 2020. “Molecular Recognition
Approach to REE Extraction, Separation, and
Recycling.” Minerals, Metals and Materials Series 57–66.
doi: 10.1007/978-3-030-36758-9_6/FIGURES/6.
Turgeon, K., C. Bazin, J.F. Boulanger, L. Whitty-Léveillé,
and D. Larivière. 2016. “Material Balancing and
Estimation of Equilibrium Constants: Application
to Solvent Extraction Tests of Rare Earth Elements.”
Pp. 978–79 in IMPC 2016 -28th International Mineral
Processing Congress. Vols. 2016-Sept.
Turgeon, Keven, Jean François Boulanger, and Claude
Bazin. 2023. “Simulation of Solvent Extraction
Circuits for the Separation of Rare Earth Elements.”
Minerals 13(6):714. doi: 10.3390/min13060714.
Williams, M.C., D.W. Fuerstenau, and T.P. Meloy. 1986.
“Circuit Analysis—General Product Equations
for Multifeed, Multistage Circuits Containing
Variable Selectivity Functions.” International
Journal of Mineral Processing 17(1–2):99–111. doi:
10.1016/0301-7516(86)90048-7.