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At least 955 records · Page 53

Integration of pH Control into Chi.Bio Reactors and Demonstration with Small-Scale Enzymatic Poly(ethylene terephthalate) Hydrolysis

Small-scale bioreactors that are affordable and accessible would be of major benefit to the research community. In previous work, an open-source, automated bioreactor system was designed to operate up to the 30 mL scale with online optical monitoring, stirring, and temperature control, and this system, dubbed Chi.Bio, is now commercially available at a cost that is typically 1–2 orders of magnitude less than commercial bioreactors. In this work, we further expand the capabilities of the Chi.Bio system by enabling continuous pH monitoring and control through hardware and software modifications. For hardware modifications, we sourced low-cost, commercial pH circuits and made straightforward modifications to the Chi.Bio head plate to enable continuous pH monitoring. For software integration, we introduced closed-loop feedback control of the pH measured inside the Chi.Bio reactors and integrated a pH-control module into the existing Chi.Bio user interface. We demonstrated the utility of pH control through the small-scale depolymerization of the synthetic polyester, poly(ethylene terephthalate) (PET), using a benchmark cutinase enzyme, and compared this to 250 mL bioreactor hydrolysis reactions. The results in terms of PET conversion and rate, measured both by base addition and product release profiles, are statistically equivalent, with the Chi.Bio system allowing for a 20-fold reduction of purified enzyme required relative to the 250 mL bioreactor setup. Through inexpensive modifications, the ability to conduct pH control in Chi.Bio reactors widens the potential slate of biochemical reactions and biological cultivations for study in this system, and may also be adapted for use in other bioreactor platforms.

09 BIOMASS FUELS↗

Anomaly detection in the Zwicky Transient Facility DR3

We present results from applying the SNAD anomaly detection pipeline to the third public data release of the Zwicky Transient Facility (ZTF DR3). The pipeline is composed of three stages: feature extraction, search of outliers with machine learning algorithms, and anomaly identification with followup by human experts. Our analysis concentrates in three ZTF fields, comprising more than 2.25 million objects. A set of four automatic learning algorithms was used to identify 277 outliers, which were subsequently scrutinized by an expert. From these, 188 (68 per cent) were found to be bogus light curves – including effects from the image subtraction pipeline as well as overlapping between a star and a known asteroid, 66 (24 per cent) were previously reported sources whereas 23 (8 per cent) correspond to non-catalogued objects, with the two latter cases of potential scientific interest (e.g. one spectroscopically confirmed RS Canum Venaticorum star, four supernovae candidates, one red dwarf flare). Moreover, using results from the expert analysis, we were able to identify a simple bi-dimensional relation that can be used to aid filtering potentially bogus light curves in future studies. We provide a complete list of objects with potential scientific application so they can be further scrutinised by the community. These results confirm the importance of combining automatic machine learning algorithms with domain knowledge in the construction of recommendation systems for astronomy. Our code is publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

Stardust Network Measurement Components (esnet-stardust-components) v1

This software contains a set of components that allow us to measure and analyze the use and performance of computer networks using existing off the shelf Open Source components organized into a scalable and extensible system. The components were developed for and used within ESnet's Stardust Measurement Environment. The components are used to collect, process and display network measurement data in an architecture that employs a combination of Elasticsearch, Logstash and Grafana. The advantage of this approach is we can tailor system behavior to our analytical needs and expand its capability with new types of network measurement without waiting for a commercial vendor to support our fairly niche use cases. Additionally we have existing collaborations within our community that came about from prior research efforts that will benefit from the release of this software so that others can also contribute features.

Balas, Edward↗

Carbon monoxide chemistry of α-V70I Mo-nitrogenase: Evidence from EPR- and IR-monitored photolysis – or, what a difference a methyl makes

A critical step in the global nitrogen cycle is the conversion of dinitrogen into biologically accessible ammonia. In Nature this is accomplished by the nitrogenase (N 2 ase) family of enzymes. Carbon monoxide (CO) has long been known as an inhibitor of dinitrogen reduction by N 2 ase, but it can also be a substrate of the enzyme, when it is catalytically reduced to hydrocarbons. Understanding the CO interactions with N 2 ases are thus relevant to both dinitrogen fixation and Fischer-Tropsch-like chemistry. Here, in this work, the interaction of CO with the α-V70I variant of Azotobacter vinelandii MoFe N 2 ase was investigated using electron paramagnetic resonance (EPR) and infrared (IR) monitored photolysis of bound CO under cryogenic conditions. This was supplemented by further analysis of stopped-flow Fourier transform IR (SF-FT-IR) data under turnover conditions. The α-V70I variant adds a single methyl group close to the FeMo-cofactor active site, and the results show that this inhibits and slows, but does not substantially chemically change, the binding of CO to the FeMocofactor. The EPR spectra of both the hi-CO and lo-CO states closely resemble those from the wild-type enzyme. Similarly, the SF-FT-IR spectra of CO inhibited α-V70I and wild-type enzyme are strikingly similar, showing only small shifts in band energies which allow better interpretation of the published wild-type spectra. The extra carbon does, however, impact and inhibit the photochemical release and migration of CO at cryogenic temperatures, resulting in novel CO-bound species. These include a product species, termed Lo-1*, which may involve CO photochemically migrating on the FeMo-cofactor.

Carbon monoxide↗

Modeling fission product diffusion in TRISO fuel particles with BISON

Diffusion of fission products in intact TRISO particles depends on particle geometry, fission product source rates, time, temperature, and temperature-dependent diffusion coefficients. Simulating this diffusion process requires models for source rates and diffusion coefficients, plus computation of the temperature field if not prescribed. In addition, simulation quality depends on discretization of the geometry, appropriate time stepping, and the accuracy of the solution method. In this paper, we explore the simulation of fission product diffusion in TRISO fuel particles using the finite element method via the fuel performance code Bison. Recent material model development has occurred in Bison for each material present in tri-structural isotropic (TRISO) fuel particles: the buffer, inner pyrolytic carbon, silicon carbide, and outer pyrolytic carbon layers, as well as the fuel kernel. Also, new mesh generation and fission product release fraction capabilities have been added. Diffusion capabilities are shown to converge to the correct solution via formal verification tests. A large number of code benchmarking problems are also given, with good results, showing that Bison’s computed release fractions closely match those of other software tools. Finally, a significant validation effort is detailed in which fission product release, measured as part of the AGR-1 capsule experiments, is compared to Bison outputs. Bison outputs compare very well to the experimental data and to PARFUME results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Consequence analyses of sabotage-induced radiological releases in high-temperature helium-cooled prismatic microreactors

Here, this study analyzes the radiological dose consequences of sabotage-induced accidents at three high-temperature helium-cooled prismatic microreactors (HTPMs) with thermal power ratings of 1, 10, and 50 MWt. Each HTPM employs uranium oxycarbide tristructural isotropic fuel enriched to 19.75 wt% high-assay low-enriched uranium. Simulations were conducted to estimate reactor core inventory at the point of fuel discharge––when the effective multiplication factor reduced to less than 1––representing peak radionuclide inventory. Postulated sabotage scenarios leading to reactor shutdown were analyzed at two intervals: immediately post-shutdown (0 h) and 3 days after shutdown using the SCALE code for radionuclide inventories and the RASCAL tool for dose consequences. Results show that although HTPMs benefit from inherent safety features and robust fuel design, radiological consequences scale with reactor power because of increased source term inventories. Smaller microreactors exhibited proportionally lower dose consequences. To support the economic and regulatory feasibility of microreactor deployment, this study emphasizes the value of a risk-informed, performance-based approach, as supported by regulations like 10 CFR Parts 100 and 53 in the United States. Microreactor developers should perform site-specific assessments of potential sabotage or low-probability, high-consequence events, especially when considering minimal on-site or full off-site emergency response.

Consequence↗

A unified large language model–based framework for heterogeneous PV image diagnosis

With advances in imaging technologies, modern photovoltaic (PV) systems generate large volumes of heterogeneous image data, including visible, electroluminescence (EL), and infrared (IR) images. Existing PV image analysis models, particularly deep learning approaches, are typically task-specific and lack cross-modality generalization. To address this limitation, this paper proposes an open-source large language model (LLM)–based unified framework for heterogeneous PV image diagnostics. Through task-aware diagnostic prompting, the framework enables analysis of visible, EL, and IR images within a single pipeline, supporting both zero-shot and few-shot inference and binary and multiclass classification. It is compatible with state-of-the-art multimodal LLMs, including ChatGPT, Gemini, Claude, Qwen, and CLIP. The framework is evaluated on PV module condition classification (clean, soiling, snow, hail, and bird droppings) using visible images, cell crack detection using EL images, and hotspot detection using IR images. GPT-5.1 in few-shot mode achieves the best performance, with classification accuracy exceeding 97.3%. Open-source models such as Qwen and CLIP also deliver competitive results on visible images (around 90% accuracy), though their performance is more limited on EL and IR modalities. On the full ELPV dataset, the framework achieves 83.5% zero-shot accuracy, within 2.8% of the supervised CNN baseline, confirming scalability to larger benchmarks. Practical aspects such as reproducibility, response latency, and confidence estimation are systematically analyzed. The framework operates across PV image modalities without modality- or task-specific training, making it well suited as a rapid pre-screening tool to support downstream detailed diagnostics. A benchmark dataset of diverse labeled PV images is also released.

Li, Baojie↗

Emissions from Heated Terpenoids Present in Vaporizable Cannabis Concentrates

Vaporizable cannabis concentrates (VCCs) consumed as a liquid (vaping) or a waxy solid (dabbing) are becoming increasingly popular. However, their associated emissions and impacts have not been fully described. Mixtures containing different proportions of 12 VCC terpenoids and high MW compounds were heated at 100-500 °C inside a room-sized chamber to simulate emissions. Terpenoids, thermal degradation byproducts, and ultrafine particles (UFPs) were quantified in the chamber air. Air samples contained over 50% of emitted monoterpenes and less than 40% of released sesquiterpenes and terpene alcohols. Eleven degradation byproducts were quantified, including acrolein (1.3-3.9 μg m -3 ) and methacrolein (2.0 μg m -3 ). A large amount of UFPs were released upon heating and remained airborne for at least 3 h. The mode diameter increased from 80 nm at 100 °C to 140 nm at 500 °C, and particles smaller than 250 nm contributed to 90% of PM 1.0 . Here, the presence of 0.5% of lignin, flavonoid, and triterpene additives in the heated mixtures resulted in a threefold increase in the particle formation rate and PM 1.0 concentration, suggesting that these high-molecular-weight compounds enhanced aerosol inception and growth. Predicted UFP emission rates in typical consumption scenarios (6 × 10 11 -2 × 10 13 # min -1 ) were higher than, or comparable with, other common indoor sources such as smoking and cooking.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advancing Development of Emissions Detection (Final Report)

This document is the final report to the U.S. Department of Energy (DOE for contract DE-FE0031873) awarded to Colorado State University (CSU). CSU and partners at Harrisburg University of Science and Technology, University of Texas Arlington, and University of Texas at Austin organized several testing rounds to provide knowledge focused on advancing the detection capabilities of emissions monitoring devices. With this funding opportunity the research group began by establishing the Advancing the Development of Emission Detection (ADED) program, with the goal focused on enhancing the accuracy, reliability, and field applicability of methane detection technologies. This effort aimed to address the critical challenges of identifying and quantifying methane emissions while enabling industry stakeholders to meet regulatory compliance and environmental sustainability goals. The program engaged with industry, government, and technology stakeholders to promote adoption and consensus on testing techniques for methane detection solutions. Methane, a potent greenhouse gas, contributes significantly to global warming, and the oil and natural gas (O&G) sector is a primary source of methane emissions. Regulatory measures such as leak detection and repair (LDAR) programs have been implemented to address emissions. However, traditional LDAR approaches, reliant on handheld and component-level measurements, are resource-intensive. To address these limitations and move with evolving regulations, advanced methane technologies are emerging. These solutions include ground-based sensors, mobile systems (e.g., drones, vehicles, and aircraft), and satellite-based platforms. They offer innovative capabilities for autonomous monitoring, larger spatial coverage, and emission quantification using methods such as tracer gas techniques and inverse modeling with Gaussian plume analysis. The ADED program began with creating protocols for methane controlled release (CR) testing these continuous monitoring (CM) and survey technologies that detect and monitor methane emissions at O&G facilities. The protocols were then implemented throughout testing of CM and survey devices at CSU’s Methane Emissions Technology Evaluation Center (METEC) facility from 2021 through 2024. As apart of the protocol, solutions that tested under the ADED program installed their solutions at METEC, documented their system under test, and provided detection reports to the METEC team for analysis. The METEC team would provide the solutions with analyzed reports of their emissions and ground truth data of the releases conducted during their testing session. Under the ADED program, CMs were also tested at O&G facilities for a six week test run of challenge release (ChR) releases. The findings from the ADED program underscore the critical role of collaborative research and innovation in tackling methane emissions, offering a pathway for the oil and gas sector to achieve significant environmental and economic benefits. Results from METEC testing saw improvement of performance and accuracy across all solutions over the extent of the ADED experiments. The results also showed a variance in CM solution performance between CRs and ChRs. That variance pushed the team to further analyze the differences between CR testing environments and field conditions. With the drive from regulations and that variance in field conditions, the ADED team began designing a new CR testing protocol and additions to the METEC testing facility. The METEC team is furthering the progress made through the ADED program with awarded funding from DE-FE0032276. This funding pushes the development of METEC’s addition with new equipment, allowing for an updated facility layout. METEC still facilitates for traditional facilities, with a legacy pad, while expanding an new design based on how O&G infrastructure has Final Report - Contract Number: DE-FE0031873 been changed over the last decade. Throughout the ADED program the team has also been working with international partners to ensure staying in the trend globally. International partners have been essential in moving the new protocol forward to implement into CR testing at the METEC facility in Spring 2025.

42 ENGINEERING↗

Femtosecond diffraction studies of the sodium chloride phase diagram under laser shock compression

The phase diagram of sodium chloride (NaCl) under laser shock compression has been studied at Linac Coherent Light Source (LCLS) at the x-ray free-electron laser facility. Both solid–solid (B1 → B2) and solid–liquid (B2 → liquid) transitions have been observed along the Hugoniot over nanosecond time scales. By combining structural measurements through in situ x-ray diffraction, pressure determination through velocimetry, and a thermal equation-of-state, the shock-compressed data are used to constrain the phase diagram of NaCl. Transformation into the B2 phase is found to occur at 28(2) GPa, and B2–liquid coexistence is observed between 54(4) and 66(6) GPa, with near full melt at 66(6) GPa. Late-time pressure release from an initial shocked B2-state results in a B2 → B1 back transformation. Our results show agreement with previous static compression data, suggesting that the time scale for melting is very rapid and that equilibrium states in NaCl are being accessed over nanosecond time scales. Finally, a multiphase equation-of-state description of NaCl incorporated into a one-dimensional hydrocode is used to interpret pressure and temperature evolution over these rapid time scales.

36 MATERIALS SCIENCE↗

Geochemical, Biological, and Clumped Isotopologue Evidence for Substantial Microbial Methane Production Under Carbon Limitation in Serpentinites of the Samail Ophiolite, Oman

In hyperalkaline (pH > 10) fluids that have participated in low-temperature (<150°C) serpentinization reactions, the dominant form of C is often methane (CH 4 ), but the origin of this CH 4 is uncertain. To assess CH 4 origin in serpentinite aquifers within the Samail Ophiolite, Oman, we determined fluid chemical compositions, analyzed taxonomic profiles of fluid-hosted microbial communities, and measured isotopic compositions of hydrocarbon gases. We found that 16S rRNA gene sequences affiliated with methanogens were widespread in the aquifer. We measured clumped isotopologue ( 13 CH 3 D and 12 CH 2 D 2 ) relative abundances less than equilibrium, consistent with substantial microbial CH 4 production. Furthermore, we observed an inverse relationship between dissolved inorganic C concentrations and δ 13 C CH 4 across fluids bearing microbiological evidence of methanogenic activity, suggesting that the apparent C isotope effect of microbial methanogenesis is modulated by C availability. An additional source of CH 4 is evidenced by the presence of CH 4 -bearing fluid inclusions in the Samail Ophiolite and our measurement of high δ 13 C values of ethane and propane, which are similar to those reported in studies of CH 4 -rich inclusions in rocks from the oceanic lithosphere. In addition, we observed 16S rRNA gene sequences affiliated with aerobic methanotrophs and, in lower abundance, anaerobic methanotrophs, indicating that microbial consumption of CH 4 in the ophiolite may further enrich CH 4 in 13 C. We conclude that substantial microbial CH 4 is produced under varying degrees of C limitation and mixes with abiotic CH 4 released from fluid inclusions. This study lends insight into the functioning of microbial ecosystems supported by water/rock reactions.

58 GEOSCIENCES↗

Methane fluxes in tidal marshes of the conterminous United States

Abstract Methane (CH 4 ) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre‐industrial times. Wetlands account for a large share of global CH 4 emissions, yet the magnitude and factors controlling CH 4 fluxes in tidal wetlands remain uncertain. We synthesized CH 4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH 4 emissions. This effort included creating an open‐source database of chamber‐based GHG fluxes ( https://doi.org/10.25573/serc.14227085 ). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH 4 m −2 year −1 , with a median of 3.9 g CH 4 m −2 year −1 , and only 25% of sites exceeding 18 g CH 4 m −2 year −1 . The highest fluxes were observed at fresh‐oligohaline sites with daily maximum temperature normals (MATmax) above 25.6°C. These were followed by frequently inundated low and mid‐fresh‐oligohaline marshes with MATmax ≤25.6°C, and mesohaline sites with MATmax >19°C. Quantile regressions of paired chamber CH 4 flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m −2 s −1 at sulfate concentrations >4.7 ± 0.6 mM, porewater salinity >21 ± 2 psu, or surface water salinity >15 ± 3 psu. Across sites, salinity was the dominant predictor of annual CH 4 fluxes, while within sites, temperature, gross primary productivity (GPP), and tidal height controlled variability at diel and seasonal scales. At the diel scale, GPP preceded temperature in importance for predicting CH 4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH 4 fluxes, with pulsed releases of stored CH 4 at low to rising tide. This study provides data and methods to improve tidal marsh CH 4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories.

54 ENVIRONMENTAL SCIENCES↗

JSPEC: A Program for IBS and Electron Cooling Simulation

JSPEC (JLab Simulation Package on Electron Cooling) is an open-source C++ program developed at Jefferson Lab to simulate the evolution of the ion beam under the intrabeam scattering effect and/or the electron cooling effect. JSPEC includes various models of the ion beam, the electron beam, and the friction force, aiming to reflect the latest advances in the field and to provide a useful tool to the community. JSPEC has been benchmarked against other cooling simulation codes and experimental data. It has been used to support the cooler design for JLEIC, an earlier JLab design for the Electron-Ion Collider. A Python wrapper of the C++ code, pyJSPEC, for Python 3.x environment has also been developed and released. It allows users to run JSPEC simulations in a Python environment and makes it possible for JSPEC to collaborate with other accelerator and beam modeling programs, as well as plentiful Python tools in data visualization, optimization, machine learning, etc. In this report, we introduce the features of JSPEC, with a focus on the latest development, and demonstrate how to use JSPEC and pyJSPEC with sample codes and numerical examples.

Accelerator Physics↗

Unique nanotechnology converts carbon dioxide to valuable products

Carbon capture and management are increasing challenges associated with global warming. Current commercial-scale carbon dioxide (CO 2 ) capture technologies are associated with a heavy economic penalty – they require at least one-third of the plant’s steam and power to operate. The objective of this project was to develop and test an innovative nanotechnology that can utilize CO 2 , from coal-based power systems or other industrial sources, as the primary feedstock to produce commercially valuable products to potentially offset the cost of CO 2 capture. The scope of this project includes conversion of CO 2 to nanomaterials using two unique amino acids in synthetic flue gases and the completion of a process design and techno-economic and lifecycle analyses to demonstrate the economic feasibility and environmental impact of the developed technology. The International Energy Agency predicts that fossil fuels will continue to play a significant role in meeting global energy demand. The goal of the research is to lead to an affordable and transformational CO 2 capture and reuse technology that will reduce the release of CO 2 thereby reducing global climate variability and its enormous impact on our daily lives.

01 COAL, LIGNITE, AND PEAT↗

Recommended Updates to Solubility Controls for Modeling Leaching of Technetium, Uranium, Neptunium, Plutonium, and Iodine from the Residual Waste Layer of Closed Savannah River Site High Level Waste Tanks

The objective of this report is to relate waste leaching experiments by the Savannah River National Laboratory (SRNL) to performance assessment modeling of release of several radionuclides from residual waste in closed high-level waste tanks. SRNL leached residual waste from Tanks 18F and 12H with solutions simulating the modeled evolution of pore fluids in residual waste layers of closed tanks through various stages of grout degradation. Tc-99, uranium isotopes, Np-237, plutonium isotopes, and I-129 were analyzed in the leachate multiple times over 90 days.

07 ISOTOPE AND RADIATION SOURCES↗

Influence of clay mineral weathering on green rust formation at iron-reducing conditions

Green rusts (GR) are important drivers for trace metal and nutrient cycling in suboxic environments. We investigated whether green rusts would incorporate aluminum (Al) or other elements from naturally-formed clay minerals containing easily-weatherable clay minerals (e.g. mica, interlayered clays). We isolated the clay minerals from a Matapeake silt loam soil by removal of silt and sand, organic matter, and reducible oxides to study mechanisms of interaction between Fe(II) and soil-sourced clay minerals. We conducted batch Fe(II) sorption experiments at multiple near-neutral pHs (6.5–7.5) and reaction times (2h–365 days). Mineral transformations were characterized by selective extractions, X-ray diffraction (XRD), and Fe X-ray absorption spectroscopy (XAS) analyzed by shell-fitting and linear combination fitting (LCF) with natural and synthetic standards. Clay mineral fraction contained a mixture of quartz, kaolinite, interlayered vermiculite, mica, and chlorite with significant structural Fe (2.6% wt). Uptake of Fe(II) increased with pH and kinetics were rapid until 5 days, followed by slow continuous Fe(II) uptake. Citrate-bicarbonate desorption kinetics from Fe(II) sorbed clay released more Al and silicon (Si) compared with unreacted soil clay fraction whereas magnesium (Mg) and potassium (K) were unaffected. Citrate-bicarbonate extracted Fe contained more Fe(II) than an ideal GR with an Fe(II)/Fe(III) molar ratio of 5.50. Analysis of the Fe EXAFS by both LCF and shell fitting was best modeled as a combination of Fe(III)-clay reduction to Fe(II) and precipitation of GR and Fe(II)-Al LDH. After 7 days of Fe(II) sorption, LCF identified 55.2% total Fe in clay, 33.4% GR(Cl) and 11.4% Fe(II)-Al LDH. Further, these results provide novel evidence of Fe(II)-Al LDHs precipitating on naturally-formed soil clay minerals as a minor phase to GR. The geochemical implications are that GRs formed in soils and sediments should be considered to have Al and Si as well as Mg substitutions affecting their structure and reactivity.

58 GEOSCIENCES↗

Geothermal Fault Zone and Fluid Imaging through Joint Airborne ZTEM and Ground MT Data Inversion Analysis

This project has aimed to achieve detailed electrical resistivity resolution at geothermal reservoir scales by combining airborne natural electromagnetic (EM) field surveying (ZTEM) with ground magnetotelluric (MT) measurements to approximate an airborne MT geophysical method. MT alone is relatively expensive and may have permitting challenges in sensitive areas. Airborne ZTEM field data contains only the magnetic field, requires a background assumption, and has been limited to relatively high frequencies, thus suffering uniqueness problems. Based on proto-type 2D simulations, ZTEM ambiguities may be reduced through formal incorporation with possibly sparse ground MT soundings, which we pursued in full 3D for this project. The methodology was tested at the high-temperature Roosevelt Hot Springs geothermal system, Utah, which was considered advantageous given the near total exposure of crystalline reservoir rocks across the project area. ZTEM and ground MT survey data were acquired in 2017, subcontracted to outside parties with which we have worked in the past. These included 80 remote-referenced tensor MT soundings over the Mineral Mountains and adjacent Roosevelt Hot Spring producing geothermal system. These MT stations abut later coverage of a similar number of MT stations taken for the Utah FORGE project providing excellent total data aperture to re-solve structure beneath both project areas better than either set alone. The airborne ZTEM survey covered 704 line kilometers in E-W flight lines with a 250 m line spacing. Although this survey was timed during a maintenance-related shutdown of power production at the Roosevelt Hot Springs, other noise sources difficult to identify but including two high-voltage state-scale transmission lines compromised the ZTEM survey badly leading to unusable responses. Thus, with DOE management concurrence, the project proceeded to emphasize inversion and interpretation of the joint SubTER-FORGE MT data sets with regard to the Roosevelt Hot Springs reservoir recharge and to deep heat sources for both it and the Utah FORGE EGS project area. We also investigated the joint ZTEM-MT sampling concept with data sets from the Eleven Mile Canyon prospect area donated by the U.S. Navy (A. Sabin, PoC). Inversion of the SubTER-FORGE MT data using the HexMT 3D finite element algorithm reveals a large, low-resistivity anomaly extending sub-vertically through the depth range of the crust beneath the western Mineral Mountains. The steep conductive zone connects in the lower crust to a more tabular conductor characteristic of much of the Great Basin that generally is ascribed to current mafic magmatic underplating, hybridization and fluid release. The location of the resolved anomaly relative to the recent (0.5-0.8 Ma) eruptive centers of the Mineral Mountains implicates it as remnants of the magma body which fed these centers. This structure appears to be currently feeding heat and fluids upward into the Roosevelt Hot Springs hydrothermal system, as well as heat laterally to the FORGE project area. Separate and joint inversion models were carried out for the donated Eleven Mile Canyon MT-ZTEM data set to demonstrate concept. ZTEM only inversion showed two main alteration zones in the western portion of the project area known from geological mapping. Joint inversion including an E-W profile of MT soundings sharpened these features considerably. It also resolved in much greater detail the graben related normal faulting structure of the central project area which lies at depths exceeding the sensitivity of ZTEM alone. The sparse number of MT da-ta relative to the ZTEM required upweighting the former by a factor of several, but an exact procedure awaits future research. Our final impression is that sparse MT data can improve resolution of the subsurface over that of ZTEM alone. However, well sampled MT data are to be preferred and offer the simplicity of interpreting just one data type, and possess the superior resolution capability coming with the electric field everywhere, and from their high bandwidth.

15 GEOTHERMAL ENERGY↗

FEED Study of Carbon Capture Inc. DAC and CarbonCure Utilization Using United States Steel's Gary Works Waste Plant

The University of Illinois Urbana-Champaign (UIUC) is spearheading a front-end engineering design (FEED) study of a Direct Air Capture and Utilization System (DACUS) that can remove 5,000 tonnes/yr net CO2 from ambient air, utilizing it in the production of concrete. The designed system, if built, would be larger than any currently existing DAC collector. Such carbon negative technologies are critical to meeting the goals of the DOE’s program to accelerate climate-critical technology. DAC is a promising new technology for reducing the greenhouse gas in the atmosphere but is expensive, partly due to the energy required to capture and then release CO2 during the process. By integrating CarbonCapture Technologies Inc. DAC collector at United States Steel's Gary Works and utilizing steel plant's waste heat, energy, and location so energy & transportation costs can be minimized. CarbonCapture has developed an innovative DAC system using novel adsorbents to cost- effectively capture CO2. The captured, liquified CO2 will be trucked to ready-mix concrete plants across Illinois, Indiana, & Wisconsin, where CarbonCure will inject it into concrete during the mixing process. The carbon dioxide reacts with concrete, mineralizing into calcium carbonate (CaCO3), sequestering the CO2 into the concrete, and reducing the amount of cement, the manufacturing of which is among the major sources of CO2 emissions. This FEED study demonstrates a full CO2 value chain for DACUS from industrial facilities. It also provided an opportunity to assess the impact of this holistic approach on job creation, regional economic impact, and environmental justice.

Carbon management, ccus, carbon capture, utilizati↗