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At least 415 records · Page 23

R&D Outcomes of Surrogate Environmental Swipe Manufacturing Technique Method Development for Arms Control and Treaty Verification Applications

The analysis of environmental samples is a critical component of nuclear compliance verification and safeguards activities. While the associated particle analyses have benefitted from recent advances in the production of actinide-bearing particulates with uniform and well-characterized particle size, material phase, and isotopic ratios to serve as reference materials for calibration and interlaboratory comparisons, there is an outstanding need for surrogate environmental samples, which resemble field-collected samples, with the aforementioned reference particulates to support future nuclear compliance verification exercises and method development. This effort seeks to leverage the recent advances in tailored reference particle production to generate surrogate environmental swipe samples via parallel production techniques (direct and indirect) which are uniquely suited to the hydrothermal and aerosol-based synthesis routes developed at PNNL and SRNL, respectively. PNNL’s hydrothermal particle production method was used to generate surrogate reference particles for the indirect production of test swipes.

54 ENVIRONMENTAL SCIENCES↗

Development of a Sulfur Tolerant CHG Process (CRADA 442) (Final Report)

The Pacific Northwest Laboratory (PNNL) has developed the Catalytic Hydrothermal Gasification (CHG) technology, which can convert low-value organics dispersed in aqueous streams, such as the aqueous phase byproduct from hydrothermal liquefaction (HTL) of wet wastes, to a mixture of methane, H 2 , and CO 2 . The current CHG catalyst, ruthenium (Ru) on a graphite substrate, was selected for its effectiveness as a reducing catalyst. However, the target waste aqueous feedstock, the HTL aqueous phase from wet wastes, such as sewage sludge, contains a fair amount of sulfur in both organic and inorganic forms. Like many other reduced metal catalysts, Ru is deactivated or poisoned by exposure to sulfur, among other contaminants. In general, a deactivated Ru catalyst cannot be reactivated or restored except by removing and returning it for remanufacturing. Therefore, there is an urgent need for a sulfur-resistant catalyst to enable CHG processing of the HTL aqueous waste stream. PNNL, with support from SoCalGas CRADA, has developed a sulfur resistant CHG catalyst and demonstrated a stable CHG process for converting HTL aqueous phases from wet wastes. Here, we report the major accomplishments of the project: • We have demonstrated that sulfided Ru based catalysts is stable during CHG of HTL aqueous waste stream, with a requirement of activity improvement. • We have developed a new catalyst, with 0.5-2 wt.% Ru loading, showing better activity compared to the baseline 6.7 wt.% RuSx/C catalyst. • With the new catalysts, the single-pass COD reduction is approximately 60% and two-pass COD reduction can reach approximately 85%. • The process is robust in terms of being effective across a wide range of organic species in the feedstock. • Techno-economic analysis was conducted to evaluate the economic impact of catalyst advancement and identify further improvement requirements. This type of catalyst shows great potential to be efficient and robust for CHG with low catalyst cost.

03 NATURAL GAS↗

Land of Opportunity: Potential for Renewable Energy on Federal Lands

Renewable energy (RE) in the United States has historically been deployed primarily on private lands, but the growing interest in RE development, generally across the country and specifically on federal lands, raises questions about the potential for RE on public lands. This study seeks to estimate RE technical potential on federal lands and project the amount of RE to be developed on federal lands under decarbonization scenarios for the contiguous United States. The study applied a combination of high-resolution geospatial analysis and power sector modeling and relied on multiple partner federal agencies and land administrators from the Bureau of Land Management, the U.S. Fish and Wildlife Service, the U.S. Forest Service, the U.S. Department of Defense, and the U.S. Department of Energy. In our reference siting access case, we estimate 44 million acres of federal land across the contiguous United States is potentially suitable for UPV development, which corresponds to a capacity technical potential of 5,750 gigawatts (GW) (Figure ES-1). Federal land area available for wind development is similar to UPV but wind’s generating capacity technical potential is lower (875 GW). The technical potential is estimated for two geothermal technologies, hydrothermal and enhanced geothermal systems (EGS), both of which have a smaller amount of federal land available for development (12 and 27 million acres, respectively). However, in terms of capacity, the technical potential for EGS (975 GW) is approximately equal to wind’s technical potential and there is an estimated 130 GW of hydrothermal potential. We also developed cases with more-limited land available for UPV and wind (for federal and non-federal lands) resulting in 96% reduction of wind capacity potential and 70% reduction for UPV. In a case with additional constraints applied to non-federal lands only (Limited Private), the overall (federal and non-federal) technical potential declines but the share of that technical potential on federal lands is higher than in the other siting cases. The technical potential is the maximum amount that could be developed, but only a small fraction would be developed or needed in the future. Across seven scenarios that achieve 100% carbon-free electricity by 2035, we estimate 26 GW to 270 GW of RE capacity could be deployed on federal lands by 2035. The three central scenarios have 51–84 GW of RE deployed by 2035 and requiring about 500,000 to 1,000,000 acres of total land area. Direct land consumption is less than total land use required, thus enabling co-use opportunities. The large technical potential estimates and the increasing deployment projections from the collection of scenarios show the opportunities for RE development on federal lands. Capturing these opportunities-while minimizing conflicts with other land uses, federal department or agency missions, and public interest, and simultaneously maximizing the economic, grid, and social value of the projects-would require collaborative planning among federal land administrators, grid planners, project developers, the public, and other stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.

15 GEOTHERMAL ENERGY↗

PIE-Enabled Study of Aqueous Corrosion & Zr Hydriding in Cr-Coated Cladding: M3GV-23PN0101132

Chromium-coated zirconium alloy cladding is under investigation as an accident-tolerant fuel (ATF) concept to extend performance to higher burnups via improved oxidation resistance and reduced hydrogen pickup. However, hydrothermal corrosion behavior and hydrogen transport mechanisms governing in-service hydriding of these coatings remain poorly understood. In a collaborative study between Pacific Northwest National Laboratory (PNNL), Idaho National Laboratory (INL), and the University of Huddersfield, cold spray (CS) and physical vapor deposition (PVD) Cr-coated Optimized ZIRLO™ cladding samples were characterized after exposure to PWR-simulated water chemistry under both in-core (neutron irradiation) and out-of-core (aqueous-only) conditions at the MIT Research Reactor. Multi-scale characterization was performed independently at PNNL and INL to evaluate coating integrity, microstructural evolution, Cr/Zr interface chemistry, and hydride formation. Both laboratories observed a consistent divergence in hydriding behavior: out-of-core CS Cr-coated cladding exhibited elevated hydride concentrations exceeding those of uncoated cladding, whereas in-core CS samples showed substantially suppressed hydriding. In-core specimens also displayed irradiation-specific features, including nanoscale voids within the Cr coating and radiation-induced segregation clusters in the Zr substrate. CS coatings retained an interdiffusion-free Cr/Zr bond with no intermetallic layer, whereas PVD coatings exhibited inferior quality with visible cracks and pores. An automated image-based hydride quantification method systematically overestimated bulk hydrogen content relative to inert gas fusion measurements, underscoring the need for standardized sample preparation and reference standards. Interpretation of hydride nucleation and growth is complicated by the open inner-diameter of the specimens, which provides additional hydrogen pathways. The results motivate further foundational studies to support predictive models of hydrothermal corrosion and hydrogen transport in unirradiated and irradiated Cr-coated cladding.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Andrieslombaardite, RhSbS, a new platinum-group mineral from the platiniferous Onverwacht Pipe, Republic of South Africa

A hundred years after the discovery of the Merensky Reef in 1924, it is appropriate to present the new mineral andrieslombaardite in honour of Andries Frederik Lombaard who was instrumental in its discovery. Andrieslombaardite, RhSbS, was first described as an unknown mineral from placer deposits associated with the Tulameen Alaskan-Uralian type complex, British Colombia, Canada (Raicevic and Cabri, 1976) but has since been reported from several other deposits including the platiniferous Driekop, Mooihoek, and Onverwacht pipes in the eastern Bushveld Complex, South Africa. The mineral and the name were approved by the Commission on New Minerals Nomenclature and Classification (CNMNC) of the International Mineralogical Association (IMA no. 2022-076) based on data in the co-type samples from Onverwacht and a co-type sample from the Yubdo stream, Birbir River, Ethiopia. Andrieslombaardite in the Onverwacht sample is a single 8 x 20 μm grain attached to laurite in a matrix of altered silicate and Fe-oxyhydroxide minerals. In the Yubdo samples, there are many grains of pale brownish gray andrieslombaardite up to 25 x 55 μm in size, included in Pt-Fe alloys, some associated with erlichmanite, and others attached to bornite and chalcopyrite. The reflectance values (R%) measured in air and in oil at the COM wavelengths are 48.3 and 33.0 (470 nm), 49.3 and 34.0 (546 nm), 51.0 and 35.9 (589 nm), and 51.8 and 36.7 (650 nm). The colour values x, y, Y, λd, and Pe in air are 0.317, 0.322, 50.3, 580, and 3.2, and in oil are 0.319, 0.324, 35.6, 579, and 4.5. The composition of andrieslombaardite is ideally RhSbS, but it contains variable amounts of Fe, Pt, Pd, and Ir that may substitute for Rh. The mineral is cubic with unit-cell dimensions of a = 6.0278(4) Å, V = 219.01(6) Å 3 and Z = 4. It was synthesised at 400 and 550°C using stoichiometric elemental amounts. It is a member of the cobaltite group. The mineralisation of the intrusive dunite pipes was probably introduced at high temperatures, under magmatic conditions. The primary assemblages were to a certain degree overprinted and redistributed by low-temperature hydrothermal fluids. The Pt-Fe alloys from Yubdo containing PGM inclusions such as andrieslombaardite in the Yubdo-Alaskan-type complex were formed at some post-magmatic stage owing to PGE remobilisation during hydrothermal or metamorphic episodes.

58 GEOSCIENCES↗

Solar enhanced oxygen evolution reaction with transition metal telluride

The photo-enhanced electrocatalytic method of oxygen evolution reaction (OER) shows promise for enhancing the effectiveness of clear energy generation through water splitting by using renewable and sustainable source of energy. However, despite benefits of photoelectrocatalytic (PEC) water splitting, its uses are constrained by its low efficiency as a result of charge carrier recombination, a large overpotential, and sluggish reaction kinetics. Here, we illustrate that Nickel telluride (NiTe) synthesized by hydrothermal methods can function as an extremely effective photo-coupled electrochemical oxygen evolution reaction (POER) catalyst. In this study, NiTe was synthesized by hydrothermal method at 145°C within just an hour of reaction time. In dark conditions, the NiTe deposited on carbon cloth substrate shows a small oxygen evolution reaction overpotential (261 mV) at a current density of 10 mA cm –2 , a reduced Tafel slope (65.4 mV dec -1 ), and negligible activity decay after 12 h of chronoamperometry. By virtue of its enhanced photo response, excellent light harvesting ability, and increased interfacial kinetics of charge separation, the NiTe electrode under simulated solar illumination displays exceptional photoelectrochemical performance exhibiting overpotential of 165 mV at current density of 10 mA cm -2 , which is about 96 mV less than on dark conditions. In addition, Density Functional Theory investigations have been carried out on the NiTe surface, the results of which demonstrated a greater adsorption energy for intermediate -OH on the catalyst site. Since the -OH adsorption on the catalyst site correlates to catalyst activation, it indicates the facile electrocatalytic activity of NiTe owing to favorable catalyst activation. DFT calculations also revealed the facile charge density redistribution following intermediate -OH adsorption on the NiTe surface. This work demonstrates that arrays of NiTe elongated nanostructure are a promising option for both electrochemical and photoelectrocatalytic water oxidation and offers broad suggestions for developing effective PEC devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrophobic Lightweight Cement with Thermal Shock Resistance and Thermal Insulating Properties for Energy-Storage Geothermal Well Systems

This study assessed the possibility of using polymethylhydrosiloxane (PMHS)-treated fly ash cenospheres (FCS) for formulating a thermally insulating and thermal shock (TS)-resistant cementitious blend with calcium aluminate cement. To prevent FCS degradation in an alkaline cement environment at high temperatures, the cenospheres were pre-treated with sodium metasilicate to form silanol and aluminol groups on their surface. These groups participated in a dehydrogenation reaction with the functional ≡Si–H groups within PMHS with the formation of siloxane oxygen-linked M-FCS (M: Al or Si). At high hydrothermal temperatures of 175 and 250 °C, some Si–O–Si and SiCH 3 bonds ruptured, causing depolymerization of the polymer at the FCS surface and hydroxylation of the raptured sites with the formation of silanol groups. Repolymerization through self-condensation between the silanol groups followed, resulting in the transformation of siloxane to low crosslinked silicon-like polymer as a repolymerization-induced product (RIP) without carbon. The RIP provided adequate protection of FCS from pozzolanic reactions (PR), which was confirmed by the decline in zeolites as the products of PR of FCS. Cements with PMHS-treated FCS withstood both hydrothermal and thermal temperature of 250 °C in TS tests, and they also showed improved compressive strength, toughness, and water repellency as well as decreased thermal conductivity. The lubricating properties of PMHS increased the fluidity of lightweight slurries.

15 GEOTHERMAL ENERGY↗

Metalliferous Coals of Cretaceous Age: A Review

Critical elements in coal and coal-bearing sequences (e.g., Li, Sc, V, Ga, Ge, Se, Y and rare earth elements, Zr, Nb, Au, Ag, platinum group elements, Re, and U) have attracted great attention because their concentrations in some cases may be comparable to those of conventional ore deposits. The enrichment of critical elements in coals, particularly those of Carboniferous-Permian and Cenozoic ages, have generally been attributed to within-plate (plume-related) volcanism and associated hydrothermal activity. However, Cretaceous coals are not commonly rich in critical elements, with the exception of some (e.g., Ge and U) in localised areas. This paper globally reviewed metalliferous coals from Siberia, the Russian Far East, Mongolia, South America, the United States and Mexico, Canada (Alberta and British Columbia), China, Africa, and Australasia (Victoria, Queensland, New South Wales, South Australia, Northern Territory, New Zealand, Nelson, West Coast, Canterbury, Otago, and Southland). The world-class Ge-U or Ge deposits in North China, Mongolia, and Siberia are the only commercially significant representatives of the Cretaceous metalliferous coals, which are related to bio-chemical reduction of oxidized meteoric, hydrothermal, or sea waters by organic matter of the peat bogs. The common Cretaceous coals worldwide are generally not rich in critical elements because intensive igneous activity led to extensive acidification of terrestrial and marine waters, which are responsible for the low coal metallogenesis during the Cretaceous period, especially the Early Cretaceous time.

58 GEOSCIENCES↗

Robotic Planning under Uncertainty in Spatiotemporal Environments in Expeditionary Science

In the expeditionary sciences, spatiotemporally varying environments -- hydrothermal plumes, algal blooms, lava flows, or animal migrations -- are ubiquitous. Mobile robots are uniquely well-suited to study these dynamic, mesoscale natural environments. We formalize expeditionary science as a sequential decision-making problem, modeled using the language of partially-observable Markov decision processes (POMDPs). Solving the expeditionary science POMDP under real-world constraints requires efficient probabilistic modeling and decision-making in problems with complex dynamics and observational models. Previous work in informative path planning, adaptive sampling, and experimental design have shown compelling results, largely in static environments, using data-driven models and information-based rewards. However, these methodologies do not trivially extend to expeditionary science in spatiotemporal environments: they generally do not make use of scientific knowledge such as equations of state dynamics, they focus on information gathering as opposed to scientific task execution, and they make use of decision-making approaches that scale poorly to large, continuous problems with long planning horizons and real-time operational constraints. In this work, we discuss these and other challenges related to probabilistic modeling and decision-making in expeditionary science, and present some of our preliminary work that addresses these gaps. We ground our results in a real expeditionary science deployment of an autonomous underwater vehicle (AUV) in the deep ocean for hydrothermal vent discovery and characterization. Our concluding thoughts highlight remaining work to be done, and the challenges that merit consideration by the reinforcement learning and decision-making community.

Preston, Victoria↗

Faraday rotators of terbium oxyhydroxide

Terbium-based Faraday rotators, optical isolators incorporating the Faraday rotators, and methods for forming the Faraday rotators are described. Formation methods include hydrothermal growth methods for forming monolithic single crystals of TbO(OH) as Faraday rotator materials. TbO(OH) can also be used as a starting material in a hydrothermal growth method to form monolithic single crystals of Tb x Yb 2-x O 3 , in which x is between about 0.05 and about 1 or terbium aluminum garnet TAG for use as a Faraday rotator in an optical isolator.

Kolis, Joseph William↗

Chapter 11: Biochar Production

In production of biochar, thermochemical processes that can be used to treat biomass include pyrolysis, gasification, hydrothermal processing, and combustion. Each of these processes is defined by specific operating conditions (e.g., temperature, presence of oxygen) and feedstock requirements for optimal conversion to the product of primary interest. Each process results in varying fractions of gaseous, liquid, and solid products. Though other publications have emphasized the gaseous bio-energy products of such processes (e.g., bio-oil, synthesis gas or "syngas") with biochar as a co-product, in this discussion, we focus primarily on biochar as the In production of biochar, thermochemical processes that can be used to treat biomass include pyrolysis, gasification, hydrothermal processing, and combustion. Each of these processes is defined by specific operating conditions (e.g., temperature, presence of oxygen) and feedstock requirements for optimal conversion to the product of primary interest. Each process results in varying fractions of gaseous, liquid, and solid products. Though other publications have emphasized the gaseous bio-energy products of such processes (e.g., bio-oil, synthesis gas or "syngas") with biochar as a co-product, in this discussion, we focus primarily on biochar as the main product, with heat and electrical energy as co-products of secondary interest. The reasons for this are as follows: when producing biochar, heat is the simplest form of energy to capture and utilize, electrical energy can be generated from heat energy with a wide range of available technologies small and large; rather than immediately combusting the gases released from biomass, there is potential to refine the gases into bio-oil and syngas. However, much larger investments of capital are needed to build facilities for which gaseous fuel production is the primary goal, as compared to those focused on biochar production with heat and electrical energy co-products. While the economic viability of biochar production will be improved by production of high-value co-products (e.g., wood acids for use in pesticides), the simplest production scheme is one in which biochar and heat are the primary products. Here we aim to provide a broader overview of thermochemical processes and technologies most relevant to biochar production in its current state of commercialization. All biochar is a result of pyrolysis (the reaction) but not all biochar is made with a dedicated pyrolysis reactor (the technology type). Further, all biochar is the result of a lack of complete combustion (the reaction), even biochar produced in a combustion or gasification reactor (the technology type). This is an important distinction to acknowledge in the following sections in which we discuss both thermochemical conversion reactions and technology types.

biochar↗

Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: - brady_som_output.gri, brady_som_output.grd, brady_som_output.* - desert_som_output.gri, desert_som_output.grd, desert_som_output.* The data corresponds to two sites: Brady Hot Springs and Desert Peak, both located near Fallon, NV. Input layers include: - Geothermal: Labeled data (0: Non-geothermal; 1: Geothermal) - Minerals: Hydrothermal mineral alterations, as a result of spectral analysis using Chalcedony, Kaolinite, Gypsum, Hematite and Epsomite - Temperature: Land surface temperature (% of times a pixel was classified as "Hot" by K-Means) - Faults: Fault density with a 300mradius - Subsidence: PSInSAR results showing subsidence displacement of more than 5mm - Uplift: PSInSAR results showing subsidence displacement of more than 5mm Also, the results of the classification using Brady and Desert Peak to build 2 Convolutional Neural Networks. These were applied to the training site as well as the other site, the results are in GeoTiff format. - brady_classification: Results of classification of the Brady-trained model - desert_classification: Results of classification of the Desert Peak-trained model - b2d_classification: Results of classification of Desert Peak using the Brady-trained model - d2b_classification: Results of classification of Brady using the Desert Peak-trained model

15 GEOTHERMAL ENERGY↗

Utah FORGE: Slide-Hold-Slide Experiments on Westerly Granite at Temperatures up to 250 Degrees C

Laboratory slide-hold-slide tests were conducted in a conventional triaxial deformation configuration on 1-inch diameter cylindrical cores of Westerly granite bisected by a sawcut oriented at 30 degrees from vertical. Tests were conducted at a constant confining pressure of 30 MPa with a 10 MPa pore fluid pressure. The pore fluid was deionized water. Experiments were conducted at temperatures of 22, 100, 200, and 250 C. This data was collected to examine fault strength recovery in hydrothermal conditions.

15 GEOTHERMAL ENERGY↗

Renewable Energy Potential Model: Hawaii Geothermal Supply Curves

This dataset extends the development of the Renewable Energy Potential (reV) model to include geothermal energy, with a specific focus on Hawaii. Provided here are the results of two scenarios that were modeled for geothermal energy in Hawaii: binary enhanced geothermal systems (EGS) at a depth of 2.5 km and hydrothermal binary systems at a depth of 1.5 km. The resource data for both scenarios were derived from Lautze and Haskins (2024) using an exponential method. The PFA probability of heat map was used as a look up table for which temperature gradient to use (Lautze and Haskins, 2024). The dataset provides geospatial and techno-economic details for evaluating geothermal energy potential. It includes spatial coordinates, estimated capacity factors, developable area, resource potential, and annual energy production metrics. Economic details such as levelized cost of electricity (LCOE), site development costs, transmission costs, and fixed-charge rates are also included. The reV model, originally developed for wind and solar energy, incorporates these variables to evaluate deployment constraints related to land use, environmental and cultural factors, and grid integration.

15 GEOTHERMAL ENERGY↗

What Is the Smallest Zeolite That Could Be Synthesized?**

Zeolites with a few unit cells are promising as catalyst and adsorbents. The quest to synthesize the smallest zeolites has recently resulted in 4 to 8 nm nanozeolites, about 2 to 4 unit cells. These findings pose the question of what is the smallest zeolite that could be obtained by hydrothermal synthesis. We address this question using molecular simulations and thermodynamic analysis. The simulations predict that amorphous precursors as small as 4 nm can crystallize zeolites, in agreement with the experiments. We find that interfacial forces dominate the structure of smaller particles, resulting in size-dependent compact isomers that have ring and pore distributions different from open framework zeolites. The instability of zeolites smaller than 3±0.5 nm precludes a classical mechanism of nucleation from solution or through assembly of small nanoslabs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solution-Based, Anion-Doping of Li 4 Ti 5 O 12 Nanoflowers for Lithium-Ion Battery Applications

Solution–based, anionic doping represents a convenient strategy with which to improve upon the conductivity of candidate anode materials such as Li 4 Ti 5 O 12 (LTO). As such, novel synthetic hydrothermally–inspired protocols have primarily been devised herein, aimed at the large–scale production of unique halogen–doped, micron–scale, three–dimensional, hierarchical LTO flower–like motifs. Although fluorine (F) doping has been explored, the use of chlorine (Cl) dopants is the primary focus here. Several experimental variables, such as dopant amount, lithium hydroxide concentration, and titanium butoxide purity, were probed and perfected. Furthermore, the Cl doping process did not damage the intrinsic LTO morphology. The analysis, based on interpreting a compilation of SEM, XRD, XPS, and TEM–EDS results, was used to determine an optimized dopant concentration of Cl. Electrochemical tests demonstrated an increased capacity via cycling of 12 % for a Cl–doped sample as compared with pristine LTO. Moreover, the Cl–doped LTO sample described in this study exhibited the highest discharge capacity yet reported at an observed rate of 2C for this material at 143mAh g –1 . Overall, these data suggest that the Cl dopant likely enhances not only the ion transport capabilities, but also the overall electrical conductivity of our as–prepared structures. Furthermore, to help explain these favorable findings, theoretical DFT calculations were used to postulate that the electronic conductivity and Li diffusion were likely improved by the presence of increased Ti 3+ ion concentration coupled with widening of the Li migration channel.

25 ENERGY STORAGE↗

Thermochemical Conversion of Plastic Waste into Fuels, Chemicals, and Value-Added Materials: A Critical Review and Outlooks

Plastic waste is an emerging environmental issue for our society. Critical action to tackle this problem is to upcycle plastic waste as valuable feedstock. Thermochemical conversion of plastic waste has received growing attention. Although thermochemical conversion is promising for handling mixed plastic waste, it typically occurs at high temperatures (300–800 °C). Catalysts can play a critical role in improving the energy efficiency of thermochemical conversion, promoting targeted reactions, and improving product selectivity. Here this Review aims to summarize the state-of-the-art of catalytic thermochemical conversions of various types of plastic waste. First, general trends and recent development of catalytic thermochemical conversions including pyrolysis, gasification, hydrothermal processes, and chemolysis of plastic waste into fuels, chemicals, and value-added materials were reviewed. Second, the status quo for the commercial implementation of thermochemical conversion of plastic waste was summarized. Finally, the current challenges and future perspectives of catalytic thermochemical conversion of plastic waste including the design of sustainable and robust catalysts were discussed.

chemolysis↗