Public Abstract

DE-SC0024382: Coarse-Grained Molecular Studies of CO2 storage in Gas Hydrates

Award Status: Active

Institution: Louisiana State University and A&M College, Baton Rouge, LA
UEI: ECQEYCHRNKJ4
DUNS: 075050765

Most Recent Award Date: 08/26/2023
Number of Support Periods: 1
PM: Wilk, Philip

Current Budget Period: 09/01/2023 - 08/31/2024
Current Project Period: 09/01/2023 - 08/31/2026
PI: Olorode, Olufemi

Supplement Budget Period: N/A

Public Abstract

Coarse-Grained Molecular Studies of CO2 Storage in Gas Hydrates Olufemi Olorode, Louisiana State University (Principal Investigator) The escalating global concern surrounding carbon footprints necessitates innovative carbon sequestration strategies. To this end, various researchers have performed laboratory experiments and molecular simulations to evaluate the potential of storing CO2 in natural gas hydrates (NGH) while simultaneously producing methane (CH4). Some have also proposed that CO2 could be stored below the gas hydrate stability zone (GHSZ), where it would rise through water-saturated rocks to form solid CO2 hydrates, effectively trapping CO2 in the subsurface when it reaches the GHSZ. This research seeks to advance the understanding of the kinetics of trapping CO2 as hydrates in GHSZs or in the vast amounts of NGH in the subsurface and permafrost using coarse-grained molecular dynamics (MD). To study the kinetics of CO2 hydrate formation in systems much larger than those explored in existing literature, we will use coarse-grained models and physics-encoded message-passing neural networks (PeHMPNN). We will extend and calibrate the monoatomic water model to study systems with more than two types of molecules, including CO2, water, and promoters. Using experimental design and response surface modeling techniques, we will develop a workflow to search for the optimal pair interaction parameters for these multi-component systems. To ensure that our simulations represent the kinetics of CO2 sequestration as hydrates in nature, we will estimate the area-normalized hydrate formation rate and compare this to corresponding experimental data in the literature. The proposed coarse-grained and deep-learning methods will allow us to simulate systems of over one million molecules and generate statistically significant results. We anticipate that our estimation of area-normalized hydrate formation rates from these large-scale MD simulations will match experimental results and provide deeper insights into the kinetics of CO2 hydrate formation with and without promoters. This will consequently facilitate the search for optimum CO2 hydrate promoters. In conclusion, the proposed research studies, methodologies, and tools will facilitate the development of clean energy technologies to safely, efficiently, and commercially store gases like CO2, hydrogen, and CH4 as hydrates in the subsurface or permafrost. In addition to advancing scientific knowledge in this critical area, the proposed research will help support a principal investigator whose demographic is underrepresented in the energy sciences and engineering.

Coarse-Grained Molecular Studies of CO2 Storage in Gas Hydrates
Olufemi Olorode, Louisiana State University (Principal Investigator)

The escalating global concern surrounding carbon footprints necessitates innovative carbon sequestration strategies. To this end, various researchers have performed laboratory experiments and molecular simulations to evaluate the potential of storing CO2 in natural gas hydrates (NGH) while simultaneously producing methane (CH4). Some have also proposed that CO2 could be stored below the gas hydrate stability zone (GHSZ), where it would rise through water-saturated rocks to form solid CO2 hydrates, effectively trapping CO2 in the subsurface when it reaches the GHSZ. This research seeks to advance the understanding of the kinetics of trapping CO2 as hydrates in GHSZs or in the vast amounts of NGH in the subsurface and permafrost using coarse-grained molecular dynamics (MD).

To study the kinetics of CO2 hydrate formation in systems much larger than those explored in existing literature, we will use coarse-grained models and physics-encoded message-passing neural networks (PeHMPNN). We will extend and calibrate the monoatomic water model to study systems with more than two types of molecules, including CO2, water, and promoters. Using experimental design and response surface modeling techniques, we will develop a workflow to search for the optimal pair interaction parameters for these multi-component systems. To ensure that our simulations represent the kinetics of CO2 sequestration as hydrates in nature, we will estimate the area-normalized hydrate formation rate and compare this to corresponding experimental data in the literature.

The proposed coarse-grained and deep-learning methods will allow us to simulate systems of over one million molecules and generate statistically significant results. We anticipate that our estimation of area-normalized hydrate formation rates from these large-scale MD simulations will match experimental results and provide deeper insights into the kinetics of CO2 hydrate formation with and without promoters. This will consequently facilitate the search for optimum CO2 hydrate promoters. In conclusion, the proposed research studies, methodologies, and tools will facilitate the development of clean energy technologies to safely, efficiently, and commercially store gases like CO2, hydrogen, and CH4 as hydrates in the subsurface or permafrost. In addition to advancing scientific knowledge in this critical area, the proposed research will help support a principal investigator whose demographic is underrepresented in the energy sciences and engineering.