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At least 1,081 records · Page 60

Techno-Economic Screening Analysis of CO2 Removal Through Enhanced Weathering

Terrestrial enhanced weathering has emerged as a technology of interest due to its simplicity, low energy requirement, and potentially low capital investment requirement. Due to the novelty of this technology, there is limited literature exploring the techno-economics of the process. This presentation reports on a screening techno-economic analysis that examines the impact of key factors that influence terrestrial enhanced weathering performance and cost. Two cases are considered for analysis, based on the material used: (1) Naturally occurring mined igneous rock (2) Industrial waste materials (like biomass ash or cement kiln dust) The analysis considers locating the terrestrial enhanced weathering system in the Midwestern United States, because of proximity to alkaline materials, availability of farmland, and appropriate ambient conditions for weathering. For the igneous rock case, the size of the system is based on the average amount of igneous rock available from a single mine—250,000 tonnes/year. For the industrial waste case, the size of the system is based on the amount of suitable waste material produced by an industrial hub—150,000 tonnes/year.

Leptinsky, Sarah↗

Effect of Support on Iron-Based Catalyst Toward CO2-Free H2 Production From Methane Pyrolysis

The global demand for low-emission hydrogen production is increasing rapidly due to the potential for hydrogen to substitute conventional fossil fuels in energy related applications. Among all the current practical technologies – Steam Reforming of Methane (SMR), Water Electrolysis, and Methane Pyrolysis – methane pyrolysis has the potential to produce economical- and near-zero-emission hydrogen because the reaction produces a solid carbon by-product that can be monetized to offset production costs. However, this route is not without research challenges, and the selective formation of high-value carbon remains a critical issue. Supported nickel, iron, and cobalt, have been widely investigated for methane pyrolysis. Although iron-based catalysts are less active than Ni, iron catalysts offer less resistance to coke formation, are inexpensive, and have a longer lifetime. One area not sufficiently explored is the effect of support materials other than Al2O3 for the iron-based catalysts. Therefore, in this study we investigated a detailed variation of support material to study their influence on the catalytic performance. Moreover, this study offers a fair comparison because all catalytic materials were synthesized and studied under identical conditions, allowing a direct comparison of the obtained results; this is important because results reported in different publications in literature are often not comparable, due to very different reaction conditions.

Aireddy, Divakar Reddy↗

Machine Developing a Transferable Framework for CO2-Stimulated Geothermal Energy Enhancement: A Case Study

Poster presented at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. In this poster, we present innovative technologies to image key features, including CO₂-stimulated fracture imaging, CO₂ fluid sweep imaging and heat transfer and exchange imaging by leveraging multiple datasets and applying advanced AI/ML, multi-level data analytics, and data/information fusion to better understand the geothermal reservoir for enhanced recovery.

Liu, Guoxiang↗

Deep Learning-based Parameterization of Complex 3D CO2 Saturation Data in Large-scale Geological Carbon Storage

In deep learning (DL), dimension reduction plays a pivotal role in improving training efficiency and minimizing overfitting, especially when working with complex datasets like three-dimensional (3D) saturation data. In the context of geological carbon storage (GCS), 3D saturation data introduces unique challenges due to its sparse nature and sharp transitions at plume boundaries, known as shock fronts. To tackle these challenges, we developed a novel DL framework that combines dimension reduction with advanced 3D reconstruction techniques. Our approach utilizes latent variables derived from 2D average saturation fields to efficiently capture the essential features of high-dimensional data while reducing the number of variables. This enhances both the robustness and accuracy of DL models, making the framework more practical for real-world applications. By offering a tailored solution for modeling complex 3D saturation dynamics, this framework holds significant potential for environmental monitoring, energy storage, and other geological applications.

Wang, Hongsheng [University of Texas at Austin]↗

Solid State Additive Manufacturing of Oxide Dispersion Strengthened-FeCrAl Alloy Components for High-Temperature Supercritical CO2 Power Cycle Applications

In this research, material extrusion additive manufacturing (MEAM) has been explored as an SSAM method for fabrication of 3-D components using ODS-FeCrAl alloy. MEAM-printed 3-D parts go through a series of process steps, e.g., chemical treatment, thermal treatment etc. in order to create a high density fully metallic part. Final 3-D part quality is associated with various process steps, e.g., filament fabrication, print design, and thermal treatment optimization. In MEAM, a metal powder loaded filament is used for printing 3-D shapes. Composition of the filament is very important since it provides shape retention at low-to-medium temperature. There are a few commercially available metallic alloy filaments. However, FeCrAl alloy filaments are not commercially available. In this project, we came up with a method to fabricate high quality composite FeCrAl filaments that could be used for MEAM printing. Subsequently, we have optimized MEAM print methods to fabricate samples that are larger than 10 mm, by using a modular print design approach. Finally, we have been able to optimize the chemical and high temperature heat treatment steps to achieve very high density (>98%) in sintered MEAM-printed products.

36 MATERIALS SCIENCE↗

Theoretical study of CO2 capture mechanisms of SrO and Sr(OH)2.nH2O (n=0,1,8)

<span style="font-family: Roboto; font-size: 11pt;">In this presentation, the adsorption reactions of CO</span><sub style="font-family: Roboto; font-size: 11pt;">2</sub><span style="font-family: Roboto; font-size: 11pt;"> on SrO surfaces and its hydrated counterparts are examined. The predicted energies of CO</span><sub style="font-family: Roboto; font-size: 11pt;">2</sub><span style="font-family: Roboto; font-size: 11pt;"> adsorption on follows the order of increasing H</span><sub style="font-family: Roboto; font-size: 11pt;">2</sub><span style="font-family: Roboto; font-size: 11pt;">O content. The carbonation on the monohydrate surface is barrierless, whereas the CO</span><sub style="font-family: Roboto; font-size: 11pt;">2</sub><span style="font-family: Roboto; font-size: 11pt;"> reaction on the Sr(OH)</span><sub style="font-family: Roboto; font-size: 11pt;">2</sub><span style="font-family: Roboto; font-size: 11pt;"> and the octahydrate surfaces follows pathways with finite activation barriers. The thermodynamics of bulk reaction is also addressed.</span>

computational science and engineering↗

Developing a Prototype Methodology to Rank CO2-EOR Wells and Assess Their Reuse Potential for Geologic Carbon Sequestration

This study presents a prototype methodology for evaluating the reuse potential of Class II CO₂-enhanced oil recovery (CO₂-EOR) wells as Class VI wells for geologic carbon sequestration. The approach focuses on assessing wellbore construction materials—casing, cement, tubing, and packers—based on U.S. Environmental Protection Agency (EPA) Class VI well conversion guidelines. Utilizing Python scripts and JSON representations, the methodology automates checks on digitized Texas Railroad Commission (TRRC) data to rank wells based on regulatory and integrity criteria. Key factors include casing integrity, cementing techniques, tubing compatibility, and packer selection. Due to limitations in digitized data, manual verification is required for certain sections. Future enhancements include incorporating non-digitized data via web scraping and machine learning. This research provides a practical framework for well owners and regulators, supporting informed decision-making for sustainable CO₂ storage.

carbon sequestration↗

Final Report for FE0032098: Improving the cost-effectiveness of algal CO2 utilization by synergistic integration with power plant and wastewater treatment operations

The overall goal of this project was to demonstrate an engineering-scale open raceway pond algae cultivation system (approximately 180 m²), including the integration of technologies that utilized carbon dioxide (CO₂) from a coal-fired power plant and wastewater-derived nutrient inputs for cost-effective and environmentally friendly biomass production. The key advantages associated with the innovative algae cultivation system and its integration with wastewater treatment functions, as described herein, had been demonstrated in previous bench- and pilot-scale work by the project team partners. This project combined those approaches to maximize practical benefits and available synergies, resulting in a significant reduction in the net cost of producing algal biomass products. The primary target algal species for the project was Spirulina, which served as a high-protein content ingredient for food and animal feed. Spirulina was selected because it had already been approved by the FDA, was in use as a food ingredient, and commanded prices of up to $30/kg. It had a typical protein content of 50–75%, comparable to other high-protein concentrates, featured high digestibility without requiring pretreatment, and offered a high conversion ratio in animal feed applications. In addition, Spirulina had a relatively high content of the blue pigment phycocyanin, which could be extracted as a high-value co-product prior to using the remaining biomass for nutritional purposes.

Schideman, Lance [University of Illinois]↗

Descriptors for Cu facets for CO2 reduction reaction activity

Computation screening is crucial for designing efficient electrochemical catalysts for carbon dioxide (CO2R) reduction to valuable hydrocarbons and oxygenates. Herein, leveraging density functional theory calculations of the CO adsorption energy ΔE_CO on seventeen Cu terminations, we discover a strong linear correlation between ΔE_CO and the recently experimentally measured CO2R electrochemical currents (ACS Catal. 2022, 12, 11, 6578–6588). Examining the ab initio thermodynamics of the early critical intermediates CO*, COH*, and CHO*, we find that CO* → CHO* is the thermodynamically preferred step, and notably shows a volcano trend with the experimental currents where the maximum CO2R current corresponds to the moderate CHO* formation energy. Importantly, we show that increasing the step and kink density of the Cu termination not only enhances CO adsorption strength but also modulates the CO* → CHO* pathway, as respectively exemplified in the (941) and (741) facets. We also explain why (741) is exceptional with high CO2R activity as measured experimentally due to its relatively low activity toward the hydrogen evolution reaction compared with the other Cu surfaces. Beyond the general CO adsorption energy that only shows a linear trend with CO2R activity, we show that the reaction CO* → CHO* free energy is a descriptor that displays a volcano relationship with the overall CO2R activity on Cu facets.

machine learning↗