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82 records · Page 5

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Protonation Dynamics of Confined Ethanol–Water Mixtures in H-ZSM-5 from Machine Learning-Driven Metadynamics

Zeolites are indispensable heterogeneous catalysts in industrial chemical processes, valued for their strong Brønsted acidity, well-defined microporous frameworks, and tunable pore structures. Their catalytic activity arises primarily from Brønsted acid sites (BAS), typically present as bridging hydroxyl groups (Si–OH–Al). Under aqueous reaction conditions, these protons interact dynamically with water and alcohol molecules, leading to complex solvation and protonation behavior within confined pores. In this study, we investigate the protonation equilibrium occurring between ethanol and water at the BAS of acidic zeolites under varying hydration levels, i.e., C2H5OH–(H2O)n, n=1–4. Local structure was analyzed through an adaptive-learning global optimization algorithm, while enhanced sampling molecular dynamics simulations with Well-Tempered Metadynamics (WMetaD) and machine learning interatomic potentials (MLPs) provide free-energy surfaces (FES) at variable hydration levels. The results reveal a strong dependence of proton localization on the degree of hydration. At low hydration (1 water molecule), the proton resides predominantly on ethanol; with 2 water molecules, it shifts toward water, and at higher hydration (3 or more water molecules), it becomes extensively delocalized over the water cluster. These findings underscore the critical role of solvation in modulating acid site behavior and suggest that a minimum of three water molecules is necessary to fully stabilize the proton on water within the zeolite framework. This solvation threshold has significant implications for catalytic processes, particularly in biomass conversion reactions where alcohol protonation is a key step in dehydration mechanisms.

machine learning↗

Corrosion Engineering of Part‐Per‐Million Single Atom Pt 1 /Ni(OH) 2 Electrocatalyst for PET Upcycling at Ampere‐Level Current Density

The plastic waste issue has posed a series of formidable challenges for the ecological environment and human health. While conventional recycling strategies often lead to plastic down-cycling, the electrochemical strategy of recovering valuable monomers enables an ideal, circular plastic economy. Here a corrosion synthesized single atom Pt 1 /Ni(OH) 2 electrocatalyst with part-per-million noble Pt loading for highly efficient and selective upcycling of polyethylene terephthalate (PET) into valuable chemicals (potassium diformate and terephthalic acid) and green hydrogen is reported. Electro-oxidation of PET hydrolysate, ethylene glycol (EG), to formate is processed with high Faraday efficiency (FE) and selectivity (>90%) at the current density close to 1000 mA cm −2 (1.444 V vs RHE). The in situ spectroscopy and density functional theory calculations provide insights into the mechanism and the understanding of the high efficiency. Remarkably, the electro-oxidation of EG at the ampere-level current density is also successfully illustrated by using a membrane-electrode assembly with high FEs to formate integrated with hydrogen production for 500 h of continuous operation. In conclusion, this process allows valuable chemical production at high space-time yield and is highly profitable (588–700 $\$$ ton −1 PET), showing an industrial perspective on single-atom catalysis of electrochemical plastic upcycling.

36 MATERIALS SCIENCE↗

Simulation Center for Runaway Electron Avoidance and Mitigation (SCREAM SciDAC) (Technical Final Report)

Runaway electrons can severely damage the plasma facing components on ITER during a major disruption and pose a major risk for tokamak fusion. It has been recognized that an adequate disruption mitigation system (DMS) is essential for the safe operation of ITER. The United States is responsible for the design and implementation of the disruption mitigation system on ITER, and in July 2016 the Simulation Center for Runaway Electron Avoidance and Mitigation (SCREAM) was launched by DOE, in a joint Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) collaboration. SCREAM was a comprehensive theory and simulation SciDAC center that provided physics guidance in the avoidance and mitigation of runaway electrons, and in tandem with domestic and international experiments, helped establish the qualitative and quantitative bases for safe operational scenarios and viable mitigation techniques. The SCREAM center assembled a national team of experts in runaway electron physics, tokamak disruptions, magnetohydrodynamic (MHD) simulation, and advanced algorithms and computing. The team combined advanced simulation and analysis capability facilitated by direct participation of ASCR SciDAC institutes with theoretical models and code development by FES scientists to focus on the runaway risk for ITER and tokamaks in general. The research scope was focussed on integrated simulations of kinetic runaway electrons, including MHD and fluid models of impurity transport, within a research plan guided by theory. The specific research tasks were (1) establish the fundamental physics of runaway generation, saturation, and dynamical evolution in a tokamak; (2) examine the critical path toward runaway avoidance; and (3) investigate the viability and effectiveness of the leading candidate schemes for runaway mitigation. In all three areas, members of the team carried out scoping studies that established the readiness for rapid and critical advances, especially in the deployment and further development of large-to extreme-scale simulation tools. Our multi-pronged computational approach included (1) relativistic Fokker-Planck solvers with discretization in phase space, (2) self-consistent particle-in-cell techniques, (3) particle-based Monte-Carlo, and (4) MHD-particle hybrid simulations. Cross-check between these different methods provided an additional means for verification and further bolstered the fidelity of our physics prediction. Validation against experimental results brings confidence to the predictive capability for ITER and frequently leads to new ideas for understanding and mitigating the thermal quench driven runaway electron phenomenon.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Financial Analysis of the High Flow Experiment conducted at the Glen Canyon Dam during Water Year 2023

The Glen Canyon Dam (GCD) is a Colorado River Storage Project (CRSP) power resource that is a component of the Salt Lake City Area Integrated Projects (SLCA/IP). The 2016 record of decision (ROD) for the GCD long-term experimental and management plan (LTEMP) final Environmental Impact Statement (EIS) specified criteria for GCD monthly water releases, daily and hourly operating limits, and experimental releases. This report examines the financial implications of the high flow experiment (HFE) conducted at GCD during the spring of Water Year (WY) 2023 as required by the LTEMP HFE Protocol. This report is part of a series of reports that describe the financial costs of LTEMP experimental releases since the 2016 ROD was adopted in January 2017. Previous reports analyzed the impact of several past HFEs and Bug Flow Experiments. This report focuses on the HFE conducted in April 2023. For this experimental release, financial costs of approximately $1.33 million were incurred because the HFE required sustained water releases exceeding the power plant’s maximum turbine flow rate. In addition, during the experiment, operators were not allowed to shape GCD power production, either to follow Firm Electric Service (FES) customer day-ahead energy deliveries or to respond to market prices. This study identifies the main factors contributing to the HFE costs and examines the interdependencies among these factors. It applies an integrated set of tools to estimate Western Area Power Administration (WAPA) financial impacts by simulating GCD under two types of cases; namely, (1) a “With Experiment” case that mimics the operations that actually occurred and (2) a “Without Experiment” case that simulates operations under the assumption that the HFE did not occur. The “With Experiment” case mimics operations during the HFE and the entire month the HFE occurred. It complies with LTEMP hourly and daily operating criteria. The “Without Experiment” case assumes that the HFE did not occur. The monthly water release volume is assumed to be identical under both cases. The Colorado River Storage Project Python-based model (CRiSPPy) model was the main modeling tool used to simulate the dispatch of the GCD hydropower plant and associated water releases from Lake Powell. In the modeling process, the research team used extensive data sets and historical information on SLCA/IP power plant characteristics, hydrologic conditions, and WAPA’s power purchases and sales prices. In addition to estimating the financial impact of the HFE, the team used the CRiSPPy model to gain insights into the interplay among ROD operating criteria, exceptions made to criteria to accommodate the HFE, and WAPA operating practices.

13 HYDRO ENERGY↗

Antiferromagnetic Ordering in Quasi-One-Dimensional FeBi 4 S 7

Here, we report a detailed study of the synthesis, composition, magnetic structure, and transport properties of a quasi-one-dimensional antiferromagnet FeBi 4 S 7 that contains chains of edge-sharing FeS 6 octahedra. High-resolution powder X-ray diffraction (PXRD) analysis, aided by variation of synthetic conditions, suggests that the true formula of the material is Fe 1.2 Bi 3.8 S 7 , due to the minor substitution of Fe into Bi sites. This finding is in agreement with crystal structure refinement from neutron powder diffraction data as well as with the small band gap of 0.23 eV determined from electrical transport measurements. Analysis of the neutron diffraction pattern collected below the antiferromagnetic ordering temperature of 64 K revealed ferromagnetic coupling between the Fe moments in the chains of FeS 6 octahedra. The overall ordering, however, is antiferromagnetic due to the antiparallel arrangement of moments on neighboring chains. The collinear spin arrangement is described by a k-vector (1, 0, 1/2), which indicates doubling of the unit cell in the c direction and the loss of the C-centering translation as compared to the nuclear cell. The ferromagnetic nature of the sulfide-bridged chains of Fe 2+ ions in FeBi 4 S 7 , in contrast to the antiferromagnetic coupling between Fe moments in compounds with similar structural fragments, can be justified by the analysis of metric parameters that characterize the Fe–S bonding in these materials.

36 MATERIALS SCIENCE↗

Testing of a 15 kA Superconducting Transformer

Here, the manufacturing of superconducting magnets for High Energy Physics (HEP) and Fusion Energy Sciences (FES) applications requires high-current conductors to generate stronger magnetic fields without increasing the inductance of the magnet. Increased inductance is undesirable due to the associated AC losses, which reduce the temperature margin; and the quench protection also becomes complicated. Testing high-current conductors with a direct current (DC) room temperature power supply is unfeasible for two primary reasons: 1) the limited capacity to supply large currents, and 2) the significant heat load losses at the current leads. A superconducting transformer offers a solution to both challenges. A 50-kA superconducting transformer is planned for manufacturing and commissioning at Brookhaven National Laboratory as part of its user facility upgrade. This transformer will facilitate the testing of superconducting cables, conductors, joints, and insert coils under high magnetic field conditions (10 T) and with currents up to 50-kA. To evaluate the manufacturing process and validate the theoretical models, the magnet division has developed and tested a 15-kA prototype transformer. A control loop has been implemented to ensure precise current delivery to the sample. This paper presents the coil design, manufacturing, and experimental results from the cold tests.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Support for the 2019 IEEE Symposium on Fusion Engineering

This award provided financial support to help cover program-related expenses for the 2019 IEEE Symposium on Fusion Engineering (SOFE-2019), which was held 2-6 June 2019 near Jacksonville, FL. The SOFE is a biennial conference that enables fusion engineers from around the world to report on their work and stay current with the latest developments in fusion R&D, both physics and engineering. The symposium was sponsored by the Nuclear and Plasma Sciences Society (NPSS) of the Institute of Electrical and Electronics Engineers (IEEE), an international professional society whose members today span a wide range of disciplines. The IEEE Fusion Technology Standing Committee (FTC), most of whose members are involved in DOE Fusion Energy Sciences (FES) sponsored work, were responsible for organizing the SOFE. The SOFE has been the leading conference of choice for U.S. fusion engineers since its founding in 1965. In recent years, attendance has been growing as the conference has attracted greater participation of fusion researchers from other countries, especially from Asia but also from Europe and from the international ITER project, both central team and domestic agencies. This trend benefits U.S. participants by providing a forum to learn about the world’s most advanced fusion engineering activities and to strengthen collaborative ties with colleagues.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Iron-molybdenum cofactor synthesis by a thermophilic nitrogenase devoid of the scaffold NifEN

The maturation and installation of the active site metal cluster (FeMo-co, Fe 7 S 9 CMo- R -homocitrate) in Mo-dependent nitrogenase requires the protein product of the nifB gene for production of the FeS cluster precursor (NifB-co, [Fe 8 S 9 C]) and the action of the maturase complex composed of the protein products from the nifE and nifN genes. However, some putative diazotrophic bacteria, like Roseiflexus sp. RS-1, lack the nifEN genes, suggesting an alternative pathway for maturation of FeMo-co that does not require NifEN. In this study, the Roseiflexus NifH, NifB, and apo-NifDK proteins produced in Escherichia coli are shown to be sufficient for FeMo-co maturation and insertion into the NifDK protein to achieve active nitrogenase. The E. coli expressed NifDK RS contained P-clusters but was devoid of FeMo-co (referred to as apo-NifDK RS ). Apo-NifDK RS could be activated for N 2 reduction by addition of preformed FeMo-co. Further, it was found that apo-NifDK RS plus E. coli produced NifB RS and NifH RS were sufficient to yield active NifDK RS when incubated with the necessary substrates (homocitrate, molybdate, and S -adenosylmethionine [SAM]), demonstrating that these proteins can replace the need for NifEN in maturation of Mo-nitrogenase. The E. coli produced NifH RS and NifB RS proteins were independently shown to be functional. The reconstituted NifDK RS demonstrated reduction of N 2 , protons, and acetylene in ratios observed for Azotobacter vinelandii NifDK. These findings reveal a distinct NifEN-independent pathway for nitrogenase activation involving NifH RS , NifB RS , and apo-NifDK RS .

Payá-Tormo, Lucía↗

Non-Fouling, Low Cost Electrolytic Coagulation & Disinfection for Treating Flowback and Produced Water for Reuse

Executive Summary This Final Report is composed of two major sections. The first section presents experimental results obtained in the laboratory during Budget Period 1. The second section presents results from the field test conducted during Budget Period 2. Laboratory Results This research investigated a novel electrochemical process for producing a ferric iron coagulant for use in treating flowback and produced water from hydraulic fracturing and oil production operations. The treatment system improves the effectiveness and lowers the cost of coagulation processes using Fe3+ as the coagulant. The electrolytic coagulant generation (ECG) system uses an electrochemical cell to produce acid and base from oilfield brine solutions. The acid is used to dissolve scrap iron to provide a Fe3+ coagulating agent. The base is used to neutralize the treated water. Compared to conventional electrocoagulation (EC), the main advantage of the ECG system is an order of magnitude lower cost for the source of iron. The second advantage over conventional EC is that it can deliver Fe3+ doses greater than 1 mM, since it is not limited by the amount of dissolved oxygen in the water required to oxidize ferrous to ferric iron. The capital costs for conventional EC and the ECG system are similar, but the operational costs for the ECG system are an order of magnitude lower than conventional EC. The combined costs for iron and electrical energy for treating 1 m3 of FPW with 1 mM Fe3+ is estimated to be $0.87 for conventional EC, and $0.087 for the ECG system. The estimated all-in cost for treating FPW with a 2 mM Fe3+ dose is $0.73/m3 ($0.12/bbl). Field Test Results The field test was conducted at the Paul Foster Central Tank Battery (CTB) in Lea County, New Mexico from November 10, 2022 through December 15, 2022. The feed water to the system was produced water from the Tatanka 1H formation. After approximately two weeks of testing, the initial batch of produced water had been treated and no untreated produced water was available. Thus, after this time, the feed water to the system consisted of previously treated water (i.e., recycled water). The recycled water had nearly all colloidal particles removed, and had a much lower alkalinity due to precipitation of carbonate minerals during the first pass through the system. Although the recycled water was not an ideal test solution due to its low particulate concentrations, its lower alkalinity did allow us to identify the main problem with the treatment system. The main problem with the treatment system was caused by the high alkalinity of the initial feed water (5.4 meq/L) that consumed a significant fraction of the electrochemically generated acid. This resulted in pH values exiting the iron contact tank that were too high to dissolve enough iron to effectively treat the produced water. Tests performed with recycled water with lower alkalinity did not have this issue, and dissolved iron concentrations greater than 20 mM could be achieved. One consistent observation was that effluent water from the iron contact tank was always free of particulates, even when fed with circumneutral solutions. This suggests that there is no need to dissolve high concentrations of iron if all the water to be treated is passed through the scrap iron canister. In this case, dissolved O2 and hypochlorous acid can promote sufficient iron corrosion to provide an effective coagulating agent – even in neutral pH water. This solves the problem resulting from highly alkaline produced water. Modifications to the design of the treatment system were made based on the field test results. These modifications will add minimal additional cost, and were tested in bench-scale laboratory experiments. In short-term testing, the modified treatment process was able to remove colloidal FeS particulates to levels below detection. Long-term, steady state testing will be required to determine whether the modified process is suitable for commercial treatment systems.

54 ENVIRONMENTAL SCIENCES↗