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At least 361 records · Page 20

AI-assisted rapid crystal structure generation towards a target local environment

In material design, traditional crystal structure prediction approaches are expensive as they require extensive structural sampling through expensive energy minimization methods. Emerging artificial intelligence (AI) generative models have shown great promise in rapidly generating realistic crystals, but they typically handle only a few tens of atoms per unit cell. To overcome this limitation, we introduce a symmetry-informed approach, the Local Environment Geometry-Oriented Crystal Generator (LEGO-xtal). Our method generates initial structures using AI models trained on an augmented dataset, and then optimizes them using structure descriptors rather than energy-based optimization. We demonstrate its effectiveness by expanding from 25 known low-energy sp2 carbon allotropes to over 1700, all within 0.5 eV/atom of the ground-state energy of graphite. This framework offers a generalizable strategy for the targeted design of materials with modular building blocks, such as metal-organic frameworks and battery materials.

Ridwan, Osman Goni [University of North Carolina a↗

Competitive formation of intercalated versus supported metal nanoclusters during deposition on layered materials with surface point defects

Intercalated metal nanoclusters (NCs) can be formed under the surface of graphite after sputtering to generate surface “portal” defects that allow deposited atoms to reach the subsurface gallery. Although, there is a competition between formation of supported NCs on top of the surface and intercalated NCs under the surface, the latter only dominating at sufficiently high temperature. A stochastic model incorporating appropriate system thermodynamics and kinetics is developed to capture this complex and competitive nucleation and growth process. Kinetic Monte Carlo simulation shows that the model captures experimental trends observed for Cu and other metals and reveals that higher temperatures are needed to facilitate detachment of atoms from supported NCs enabling them to reach the gallery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Determination of Average Burnup in AGR-3/4 Compacts 1-4 and 7-4

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program third and fourth irradiation experiments (AGR-3/4), originally planned as separate tests, were combined in one test train for irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The irradiation test began on December 14, 2011, and ended on April 12, 2014 (Collin 2016). The originally planned AGR-3 and AGR-4 irradiation experiments were both focused on obtaining data on fission product transport to support the improvement of modeling. The AGR-3 experimental plan was focused on gaseous and metallic fission product release from the kernels and diffusion in the coatings during irradiation and post-irradiation safety testing. The AGR-4 experimental plan was focused on diffusivities and sorptivities in the compact matrix and reactor graphite. These two goals were combined in the AGR-3/4 irradiation, which consisted of 12 independently monitored capsules that each contained four AGR-3/4 compacts in a single stack surrounded by an inner ring of matrix or graphite and an outer ring of graphite. Two capsule types were used: a standard capsule and a so-called fuel body, in which the outer graphite ring included a floor and cap that fully enclosed the fuel. The fuel body design supported post-irradiation safety testing of the intact fuel and ring assembly to provide data on fission product transport and release from the matrix and graphite at accident temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Revealing the roles of the solid–electrolyte interphase in designing stable, fast-charging, low-temperature Li-ion batteries

Designing the solid–electrolyte interphase (SEI) is critical for stable, fast-charging, low-temperature Li-ion batteries. Fostering a “fluorinated interphase,” SEI enriched with LiF, has become a popular design strategy. Although LiF possesses low Li-ion conductivity, many studies have reported favorable battery performance with fluorinated SEIs. Such a contradiction suggests that optimizing SEI must extend beyond chemical composition design to consider spatial distributions of different chemical species. In this work, we demonstrate that the impact of a fluorinated SEI on battery performance should be evaluated on a case-by-case basis. Sufficiently passivating the anode surface without impeding Li-ion transport is key. We reveal that a fluorinated SEI containing excessive and dense LiF severely impedes Li-ion transport. In contrast, a fluorinated SEI with well-dispersed LiF (i.e., small LiF aggregates well mixed with other SEI components) is advantageous, presumably due to the enhanced Li-ion transport across heterointerfaces between LiF and other SEI components. An electrolyte, 1 M LiPF 6 in 2-methyl tetrahydrofuran (2MeTHF), yields a fluorinated SEI with dispersed LiF. This electrolyte allows anodes of graphite, μSi/graphite composite, and pure Si to all deliver a stable Coulombic efficiency of 99.9% and excellent rate capability at low temperatures. Pouch cells containing layered cathodes also demonstrate impressive cycling stability over 1,000 cycles and exceptional rate capability down to −20 °C. Through experiments and theoretical modeling, we have identified a balanced SEI-based approach that achieves stable, fast-charging, low-temperature Li-ion batteries.

25 ENERGY STORAGE↗

Radial Deconsolidation and Leach-Burn-Leach of AGR-3/4 Compacts 1-3, 4-3, 10-1, and 10-2

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program’s third and fourth irradiation experiments (AGR-3/4), originally planned as separate tests, were combined into one test train for irradiation in the Advanced Test Reactor at Idaho National Laboratory (INL). The irradiation test began on December 14, 2011 and ended on April 12, 2014 (Collin 2016). The originally planned AGR-3 and AGR-4 irradiation experiments were both focused on obtaining data on fission product transport to support modeling improvement. The AGR-3 experimental plan was focused on gaseous and metallic fission product release from the kernels and diffusion in the coatings during irradiation and post-irradiation safety testing. The AGR-4 experimental plan was focused on diffusivities and sorptivities in the compact matrix and reactor graphite (Petti et al. 2005). These two goals were combined in the AGR-3/4 irradiation, which consisted of twelve independently monitored capsules that each contained four AGR-3/4 compacts in a single stack surrounded by an inner ring of matrix or graphite and an outer ring of graphite. There were two capsule types: a standard capsule and a fuel body in which the outer graphite ring included a floor and cap that fully enclosed the fuel (Stempien et al. 2018a). The fuel body design supported post-irradiation safety testing of the intact fuel and ring assembly to provide data on fission product transport and release from matrix and graphite at accident temperatures (Demkowicz 2017)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Testing and Characterization to Develop a Mechanistic Explanation for Unsaturated Drift of Fiber Optic Sensors during High-Dose Irradiation

The primary limitation for any optical fiber-based sensor for nuclear reactor applications is radiation-induced attenuation (RIA) of the transmitted and/or reflected signals. Based on several recent studies, RIA is tolerable for some fused silica optical fibers with the proper choice of sensing wavelength and fiber dopants. For extreme temperature applications (> 1000°C), sapphire optical fibers have been proposed; however, recent optical transmission measurements performed on bulk sapphire samples showed prohibitively large RIA. For some sensors, radiation-induced dimensional changes in the fiber materials can also cause significant drift. Moreover, the drift that was observed in numerous experiments performed in the High Flux Isotope Reactor (HFIR), the Advanced Test Reactor, the Massachusetts Institute of Technology Reactor, and other international facilities far exceeded what would be expected based on compaction of fused silica glass. Clearly, additional work is needed to better understand the origins of both RIA and radiation-induced drift in both silica and sapphire optical fiber-based sensors before these sensors can be reliably deployed for nuclear applications. This work evaluated the underlying mechanisms that may be responsible for RIA and drift in silica and sapphire materials. First, detailed characterization was performed on bulk fused silica glass samples that were previously irradiated to different neutron fluences at different temperatures to better understand the structural changes that drive radiation-induced drift in the absence of coating effects that are discussed later. Results show that the non-monotonic compaction that occurs with increasing neutron fluence continues up to fast neutron fluences approaching 10 22 n/cm 2 , which has important implications for physics-based models that may be used to compensate for the sensor drift. Initial Raman spectroscopy and synchrotron x-ray diffraction provide insights into the nature of the structural changes. Next, detailed characterizations were performed on silica fibers with various coatings that were subjected to several different thermal treatments. The hypothesis is that the coatings convert to carbon-rich materials that compact under irradiation, putting a large compressive strain on the fiber. Out-of-pile testing confirms that both polyimide and acrylate fiber coatings convert to glassy carbon (GC) materials when heated under inert conditions, and the degree of order (i.e., graphitization) increases with increasing temperature. The results provide increasingly strong evidence that the combination of polymeric coatings and inert (or vacuum) conditions render fiber optic sensors susceptible to significant radiation-induced drift that would not otherwise exist in uncoated fibers. Finally, transmission electron microscopy was performed on bulk sapphire samples that were irradiated to two neutron fluences at different temperatures to gain insights into the potential mechanisms driving the prohibitive RIA at higher neutron fluences and temperatures. Contrary to previous hypotheses, results show that scattering from radiation-induced voids cannot explain the observed RIA. Similarly, models for scattering losses from dislocation loops also do not agree with the experimental results. Instead, fitting to the experimental data shows that increased absorption from aluminum vacancy centers is the most likely explanation for the the prohibitively large RIA that was observed at high irradiation temperature and dose. In addition, the voids that formed in these single-crystal samples were found to align along the basal plane (a-axis) as opposed to that seen in previous observations of c-axis alignment in polycrystalline samples, which could have important implications for anisotropic swelling and other phenomena that could affect sensor performance at high neutron fluence.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Testing and Characterization to Develop a Mechanistic Explanation for Unsaturated Drift of Fiber Optic Sensors during High-Dose Irradiation

The primary limitation for any optical fiber-based sensor for nuclear reactor applications is radiation-induced attenuation (RIA) of the transmitted and/or reflected signals. Based on several recent studies, RIA is tolerable for some fused silica optical fibers with the proper choice of sensing wavelength and fiber dopants. For extreme temperature applications (> 1000°C), sapphire optical fibers have been proposed; however, recent optical transmission measurements performed on bulk sapphire samples showed prohibitively large RIA. For some sensors, radiation-induced dimensional changes in the fiber materials can also cause significant drift. Moreover, the drift that was observed in numerous experiments performed in the High Flux Isotope Reactor (HFIR), the Advanced Test Reactor, the Massachusetts Institute of Technology Reactor, and other international facilities far exceeded what would be expected based on compaction of fused silica glass. Clearly, additional work is needed to better understand the origins of both RIA and radiation-induced drift in both silica and sapphire optical fiber-based sensors before these sensors can be reliably deployed for nuclear applications. This work evaluated the underlying mechanisms that may be responsible for RIA and drift in silica and sapphire materials. First, detailed characterization was performed on bulk fused silica glass samples that were previously irradiated to different neutron fluences at different temperatures to better understand the structural changes that drive radiation-induced drift in the absence of coating effects that are discussed later. Results show that the non-monotonic compaction that occurs with increasing neutron fluence continues up to fast neutron fluences approaching 10 22 n/cm 2 , which has important implications for physics-based models that may be used to compensate for the sensor drift. Initial Raman spectroscopy and synchrotron x-ray diffraction provide insights into the nature of the structural changes. Next, detailed characterizations were performed on silica fibers with various coatings that were subjected to several different thermal treatments. The hypothesis is that the coatings convert to carbon-rich materials that compact under irradiation, putting a large compressive strain on the fiber. Out-of-pile testing confirms that both polyimide and acrylate fiber coatings convert to glassy carbon (GC) materials when heated under inert conditions, and the degree of order (i.e., graphitization) increases with increasing temperature. The results provide increasingly strong evidence that the combination of polymeric coatings and inert (or vacuum) conditions render fiber optic sensors susceptible to significant radiation-induced drift that would not otherwise exist in uncoated fibers. Finally, transmission electron microscopy was performed on bulk sapphire samples that were irradiated to two neutron fluences at different temperatures to gain insights into the potential mechanisms driving the prohibitive RIA at higher neutron fluences and temperatures. Contrary to previous hypotheses, results show that scattering from radiation-induced voids cannot explain the observed RIA. Similarly, models for scattering losses from dislocation loops also do not agree with the experimental results. Instead, fitting to the experimental data shows that increased absorption from aluminum vacancy centers is the most likely explanation for the the prohibitively large RIA that was observed at high irradiation temperature and dose. In addition, the voids that formed in these single-crystal samples were found to align along the basal plane (a-axis) as opposed to that seen in previous observations of c-axis alignment in polycrystalline samples, which could have important implications for anisotropic swelling and other phenomena that could affect sensor performance at high neutron fluence.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High-temperature Pumping of Silicon for Thermal Energy Grid Storage

As the cost of renewable energy falls below fossil fuels, the key barrier to widespread sustainable electricity has become availability on demand. Energy storage can enable dispatchable renewables, but only with drastic cost reductions compared to current batteries. One electricity storage concept that could enable these cost reductions stores electricity as sensible heat in an extremely hot liquid (>2000 °C) and uses multi-junction photovoltaics (MPV) as a heat engine to convert it back to electricity on demand, hours or days later. This paper follows previously reported technoeconomics and liquid containment, examining equipment that would be needed to exchange heat between resistive heaters, a molten silicon storage tank above 2000 °C, and a heat engine. Herein, we report on a pump that was designed and tested to circulate the liquid silicon between these three regions and the effect of spatial thermal cycling was simulated in models and experiments. While the pump successfully circulated silicon between 1800-2080 °C for ten hours, circulation with a temperature gradient caused it and other non-isothermal experiments to dissolve significantly due to the temperature dependent solubility of not only carbon, but also silicon carbide which otherwise protected the graphite infrastructure. Furthermore, methods to reduce dissolution and an alternative embodiment are presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Preliminary Thermal-hydraulics and Selected Safety Analysis for Holos-Quad Reactor Design

This report presents thermal hydraulics and safety analyses of the 10 MWe Holos-Quad micro-reactor design developed by HolosGen LLC. These analyses were executed under steady-state and station black-out (SBO) transient conditions using the System Analysis Module (SAM), with a focus on ensuring peak fuel temperatures do not exceed the safety thresholds of 1,250°C for steady state normal operating conditions and 1,600°C for transient conditions. For steady-state temperature predictions, a coupled 1D fluid-to-3D solid heat conduction methodology was used. The steady-state simulations included a model of the central core region where power peaking occurs to predict the maximum steady-state fuel temperature, and a coarse-mesh full-core model to provide the initial condition for the consequent transient SBO decay heat removal simulation. The maximum fuel temperature predicted from the central core region simulations under the normal operating condition was 1,222°C, which is below the design limit 1,250°C. To simulate a SBO transient, a full core model was necessary because of the non-axial symmetric core design and heat loss from the outer core structures to the environment. To reduce the required computational costs, a novel scaled subassembly approach was used to model the full core domain. With the full core steady-state temperature distribution provided as the initial condition, the passive decay heat removal of the core was simulated with the scaled subassembly full core model under SBO transient conditions. This analysis showed that the peak fuel temperatures of the Holos-Quad core remained below their steady-state values during the transient, therefore much lower than the safety limit 1,600°C. This is mainly due to the large thermal inertia of the graphite matrix, relatively low power density, and the large surface-to-volume-ratio of the core. The preliminary analyses presented in this report confirm the inherent safety of the Holos-Quad micro-reactor thermal-hydraulics design, as the peak fuel temperatures under both normal and off-normal operational conditions remain within design and safety limits.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Thermal energy storage composites with preformed expanded graphite matrix and paraffin wax for long-term cycling stability and tailored thermal properties

Harvesting solar energy, preventing hot spots in electronics, transport of temperature-sensitive materials, and capture and repurposing of thermal energy require a latent heat thermal energy storage (TES) system to store/discharge heat repeatedly. For the practical application of phase change material (PCM) composites within TES systems, reliable thermal performance throughout its operational lifetime is essential. Nevertheless, the reliability of thermal conductivity in multi-phase composites over relevant numbers (>10 3 ) of melt/freeze cycles has barely been studied, particularly for composites containing fillers for thermal conductivity enhancement. Here, we introduce a preform-type expanded graphite (EG)/paraffin wax composite possessing highly robust heat transfer and storage properties even after 10,000 melt/freeze cycles. To achieve such excellent reliability, comparative studies on the combined influence of fabrication process, particle size, EG vol%, binder amount, and compaction on both magnitude and robustness of thermal conductivity were undertaken. Our parametric study has yielded a trade-off between thermal conductivity and latent heat. Based on our modeling, 20 vol% EG approaches the case where all EG particles are well-connected thermally while 10 vol% EG is close to loosely connected fillers in the matrix. Thermal conductivity of our paraffin composites containing 20 vol% EG (25.1 W·m -1 ·K -1 ) is highest among other EG/paraffin composites without aligned EG in the literature. After 10,000 thermal cycling, negligible conductivity fading was observed for the 10 vol% EG composite, while reduction in latent heat remained within 10% for all 10, 14, 17 and 20 vol% EG samples. Here we anticipate this work provides insight on suitable recipe for desirable magnitude and robustness of thermal conductivity of EG/paraffin composites.

25 ENERGY STORAGE↗

Investigation of the Impact of TSL Data Libraries and Geometry Variations on the MSRE Benchmark

The increasing demand for green, low-carbon energy solutions has amplified the focus on advanced nuclear reactor technologies. Among these, Molten Salt Reactors (MSRs) have been spotlighted because of their special features. Historically, Oak Ridge National Laboratory (ORNL) started the Molten Salt Reactor Experiment (MSRE) in 1956. Later, ORNL and the University of California, Berkeley (UCB) jointly developed the MSRE benchmark. This was then reviewed by the International Reactor Physics Experiment Evaluation Project (IRPhEP) committee and added to their 2019 handbook. In the current study, the benchmark model was recreated via the Serpent code. The calculated effective multiplication factor was 1.02087 ± 0.00019, which gives a deviation of about 2000 pcm compared to the benchmark/experimental result. At North Carolina State University (NCSU), recent evaluations were conducted on thermal scattering cross sections for molten salt FLiBe and 20% porous nuclear graphite, anticipated for incorporation in the ENDF/B-VIII.1 library. The influences of these thermal scattering law (TSL) data and geometry changes on the multiplication factor were examined using the ENDF/B-VII.1 and ENDF/B-VIII.0 libraries. Introducing the TSL data for FLiBe and 20% porous graphite resulted in an effective multiplication factor of +270 pcm compared to the reference value obtained with ENDF/B-VII.1 in this study. The adjustment of the reactor vessel dimensions resulted in decrease of -448 pcm in the calculated effective multiplication factor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Enhanced power density in zero-vacuum-gap thermophotovoltaic devices

Thermophotovoltaic (TPV) devices, which convert infrared thermal radiation from a hot emitter into electricity, hold great promise for applications in energy storage and waste heat recovery. While recent advancements have developed TPV devices with high efficiency, much less attention has been focused on improving the power density. Current TPV methods face challenges in significantly boosting the power density using emitters at very high temperatures (>2000 °C) or using complex, costly architectures such as near-field TPV. Here, we present the first experimental demonstration of a novel far-field TPV concept called “zero-vacuum-gap TPV” that eliminates the vacuum or gas-filled gap in conventional designs. By incorporating a high-index, infrared-transparent, and thermally insulating fused quartz spacer, we achieved a two-fold increase in power density compared to the far-field counterpart under identical conditions. Notably, in our experiment, the zero-vacuum-gap far-field design transforms a less-optimized, low-power-density far-field device into one with one of the highest power densities reported at moderate temperatures (700–1100 °C). Moreover, our measurements using a graphite emitter surpass the blackbody limit for gap-integrated far-field devices and match the performance of near-field TPV devices with an ultrathin 200-nm gap. Our findings suggest that zero-vacuum-gap TPV offers potential for cost-effective, scalable manufacturing using current technologies. Additionally, our modelling predicts that further power enhancements over one order of magnitude are possible with other spacer materials.

14 SOLAR ENERGY↗

World Record Demonstration of > 30% Thermophotovoltaic Conversion Efficiency

Thermophotovoltaic (TPV) devices are solid-state heat engines that convert thermal radiation into electricity using semiconductor diodes, and have applications in energy storage, primary power conversion, and waste heat recovery. Higher temperature emitters and wider band gap photovoltaics (PVs) generally afford higher TPV efficiencies. High temperature emitters are accessible in thermal energy storage applications. We have demonstrated a world record 31% +/- 2% TPV conversion efficiency with a 0.9 cm2 GaAs-based PV device under a 2430 °C thermal emitter, producing an electrical output power of 2.23 W. Critical to the result was the cell’s high reflectance of photon energies below the device band gap. Unlike solar PV, for which sub-band gap (SBG) light is lost, a TPV cell can reflect and recycle SBG light to the thermal emitter. The demonstration was made on a custom-built measurement platform in which a ~100 cm2 graphite thermal emitter was heated under vacuum up to 2430 °C. The TPV efficiency was evaluated by comparing the measured electrical output power of the TPV with the calorimetrically measured total net power incident on the cell. The measured TPV efficiency as a function of thermal emitter temperature was corroborated by our full system modeling predictions. As far as the authors are aware, this is the highest TPV conversion efficiency ever measured, and device improvements should yield > 40% efficiency in the near future.

27 ARPA - Advanced Research Projects Agency-Energy↗

Solar-thermal membrane for dewatering aqueous organic-acid solutions

A thermally conductive porous membrane has been developed to directly absorb solar energy and conduct heat that can effectively evaporate liquid water at the interface between the membrane and the bulk feed solution. Here, black, porous, thermally conductive graphite foam support is employed as an effective photothermal-energy absorber and heat conductor that heats up an aqueous feed solution to produce vapor. Graphite nanoparticle-slurry coating is applied onto the foam surface to reduce the pore size and generate a microporous membrane. Then, application of a dense graphene oxide membrane coating as an active separation layer on the microporous nanoparticle surface of internal foam channels allows vapor permeation of volatile molecules. Acetic acid/water solution was studied as a model feed system to experimentally demonstrate effective separation. This model vapor permeation system demonstrates excellent acetic acid separation, with a separation factor of 8.3, under simulated 0.7 sun irradiation. The membrane hydrophobicity and nanostructure, including pore size and surface chemistry, played a significant role in enabling high permselectivity of water vapor over acetic acid molecules, as well as liquid solution. Pore size reduction from open pores to a nonporous dense layer in the membrane enables effective separation of water vapor from the organic vapor, while it reduces the permeation flux. Also, the hydrophilicity of the membrane surface shows ~3 times higher permeation flux with higher permselectivity, compared with the hydrophobic membrane surface. This work introduces a process of directly using renewable energy instead of conventional heating to drive selective separation of water from organic acids.

14 SOLAR ENERGY↗

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗

Search by the SENSEI Experiment for Millicharged Particles Produced in the NuMI Beam

Millicharged particles appear in several extensions of the standard model, but have not yet been detected. These hypothetical particles could be produced by an intense proton beam striking a fixed target. We use data collected in 2020 by the SENSEI experiment in the MINOS cavern at the Fermi National Accelerator Laboratory to search for ultrarelativistic millicharged particles produced in collisions of protons in the NuMI beam with a fixed graphite target. The absence of any ionization events with 3 to 6 electrons in the SENSEI data allow us to place world-leading constraints on millicharged particles for masses between 30 to 380 MeV. This work also demonstrates the potential of utilizing low-threshold detectors to investigate new particles in beam-dump experiments, and motivates a future experiment designed specifically for this purpose. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Experimental demonstration of a data-driven control system for subcritical nuclear facility

Here this paper presents an experimental demonstration of a data-driven control system (DCS) designed for the MIT Graphite Exponential Pile (MGEP). The DCS aims to regulate the neutron flux profile such that symmetry is preserved. Neutron flux perturbations are introduced into the MGEP to test the DCS's capabilities by the movement of an initiating control rod (ICR). To realize this functionality, a control system that relies on an artificial neural network (ANN) was developed, and then demonstrated on the MGEP. A Helium-3 ( 3 He) neutron detector and dual control rods, including their moving mechanisms, were fabricated. The perturbed flux profile was monitored by the moving neutron detector. The prediction accuracy of the neural network (NN) was examined and the DCS response was presented. Our results show that neural network regression model trained by experimental data can achieve a prediction error of less than 2.5 cm with a 95% confidence interval. The demonstration experiment also shows that a perturbation of the ICR can be captured by the control system and flux symmetry can be maintained within 1% after the response of the responding control rod (RCR).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗