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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Precision measurement of lifetime and branching ratios of the 4⁢𝑓 13⁡ 5⁢𝑑⁢6⁢𝑠 1 ⁢[5/2] 5/2 state in Yb + ions

We report spectroscopic and time-resolved experimental observations to characterize the [Xe]⁢4⁢𝑓 13 ⁡( 2 𝐹$^𝑜_{5/2}$)⁢5⁢𝑑⁢6⁢𝑠⁡( 1 𝐷)⁢ 1 ⁢[5/2]$^𝑜_{5/2}$ state in 172 Yb + ions. We access this state from the metastable 4⁢𝑓 14 ⁡5⁢𝑑⁡( 2 𝐷 3/2,5/2 ) manifold and observe an unexpectedly long lifetime of 𝜏 = 37.9⁢(9) ⁢µ⁢s that allows visible Rabi oscillations and resolved-sideband spectroscopy. Using a combination of coherent population dynamics, high-fidelity detection and heralded state preparation, and optical pumping methods, we measure the branching ratios to the 2 𝐷 3/2 , 2 𝐷 5/2 , and 2 𝑆 1/2 states to be 0.359⁢(2), 0.639(2), and 0.0023⁢(16), respectively. The branching ratio to the 4⁢𝑓 13⁡ 6⁢𝑠 2 ⁡( 2 𝐹 7/2 ) is compatible with zero within our experimental resolution. We also report measurements of Landé 𝑔-factor of the 1 ⁢[5/2]$^𝑜_{5/2}$ state. Further, the branching ratio of the 2 𝐷 5/2 to 2 𝑆 1/2 decay in 172 Yb + was measured to be 0.188(3), improving its relative uncertainty by an order of magnitude. Our measurements provide experimental benchmarks for better understanding the atomic structure of Yb + ions, which still lacks accurate numerical descriptions, and the use of high-lying excited states for partial detection and qubit manipulation in the omg architecture.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Simulations of Laser Experiments to Study the Origin of Cosmic Magnetic Fields

Magnetic fields are ubiquitous in the universe; however, their origin is not fully understood. Cosmologists and astrophysicists have proposed a variety of ways in which small seed magnetic fields could be created. It is widely thought that the much larger values of the cosmic magnetic fields that we observe are a result of the amplification of these seed fields by the nonlinear turbulent dynamo mechanism. Such a mechanism had not yet been demonstrated in a controlled laboratory environment. We conceived experiments designed to demonstrate and study the nonlinear turbulent dynamo mechanism in the laboratory. These experiments characterize the distribution of turbulent energy among the velocity, magnetic field, and density fluctuations, providing a comprehensive picture of the energy cascade in a magnetized, turbulent plasma. The experiments build on the pathfinder experiments we have conducted on the Vulcan laser at the Rutherford-Appleton Laboratory in the UK and the OMEGA laser at Laboratory for Laser Energetics at Rochester. They utilize the high-intensity lasers at the Omega Laser Facility, the National Ignition Facility (NIF) at LLNL and the Laser Megajoule (LMJ) Facility in France – the largest laser facilities in the world. The goal of this project was to design and model the highly demanding experiments through simulation campaigns using FLASH, a highly capable radiation-MHD code we have developed, and large-scale 3D simulations on the Mira supercomputer at ANL. The simulations were vital to ensuring the experiments achieve the strong turbulence and large magnetic Reynolds numbers required for the nonlinear turbulent dynamo mechanism to operate. The simulations were also critical to determining when to fire the diagnostics, since the experiments last tens of nanoseconds but the signals of the strongly amplified magnetic fields last only a few nanoseconds. Finally, high-fidelity, validated FLASH simulations were crucial to interpreting the results of the experiments. By combining theory, experiments, and simulations, we were able to succeed in demonstrating and characterizing the nonlinear turbulent dynamo mechanism. The effort leveraged (1) the emergence of the Flash Center for Computational Science as a leader in numerical modeling of academic High Energy Density Physics (HEDP) experiments; (2) the FLASH code, which has been developed by the Flash Center and is a leadership-class, multi- physics, publicly available community code that has been applied successfully in many laser-driven experiments; (3) the expertise acquired through pathfinder experiments we performed on the Vulcan laser at the Rutherford-Appleton Laboratory in the UK and on the Omega laser facility; (4) the experience we have gained in designing and interpreting these experiments using validated simulations done with FLASH; and (5) the close collaborations we have established with outstanding experimental groups in the US and abroad. The broader impacts of the project are two-fold: (1) the work furthered the transformation of the academic community’s ability to design and analyze HEDP experiments at large laser facilities that is happening through the availability of FLASH and its widespread adoption by the academic community – a community that previously had had limited access to open and validated hydro/MHD simulation tools for HEDP experiments; and (2) the work trained young scientists to design and interpret HEDP experiments using validated simulations – a critical national need.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Single-ion magnetism in the extended solid-state: insights from X-ray absorption and emission spectroscopy

Large single-ion magnetic anisotropy is observed in lithium nitride doped with iron. The iron sites are two-coordinate, putting iron doped lithium nitride amongst a growing number of two coordinate transition metal single-ion magnets (SIMs). Uniquely, the relaxation times to magnetisation reversal are over two orders of magnitude longer in iron doped lithium nitride than other 3d-metal SIMs, and comparable with high-performance lanthanide-based SIMs. To understand the origin of these enhanced magnetic properties a detailed characterisation of electronic structure is presented. Access to dopant electronic structure calls for atomic specific techniques, hence a combination of detailed single-crystal X-ray absorption and emission spectroscopies are applied. Together K-edge, L 2,3 -edge and Kβ X-ray spectroscopies probe local geometry and electronic structure, identifying iron doped lithium nitride to be a prototype, solid-state SIM, clean of stoichiometric vacancies where Fe lattice sites are geometrically equivalent. Extended X-ray absorption fine structure and angular dependent single-crystal X-ray absorption near edge spectroscopy measurements determine Fe I dopant ions to be linearly coordinated, occupying a D 6h symmetry pocket. The dopant engages in strong 3dπ-bonding, resulting in an exceptionally short Fe–N bond length (1.873(7) Å) and rigorous linearity. It is proposed that this structure protects dopant sites from Renner–Teller vibronic coupling and pseudo Jahn–Teller distortions, enhancing magnetic properties with respect to molecular-based linear complexes. The Fe ligand field is quantified by L 2,3 -edge XAS from which the energy reduction of 3d z 2 due to strong 4s mixing is deduced. Quantification of magnetic anisotropy barriers in low concentration dopant sites is inhibited by many established methods, including far-infrared and neutron scattering. We deduce variable temperature L 3 -edge XAS can be applied to quantify the J = 7/2 magnetic anisotropy barrier, 34.80 meV (~280 cm –1 ), that corresponds with Orbach relaxation via the first excited, M J = ±5/2 doublet. The results demonstrate that dopant sites within solid-state host lattices could offer a viable alternative to rare-earth bulk magnets and high-performance SIMs, where the host matrix can be tailored to impose high symmetry and control lattice induced relaxation effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Foundations of machine learning for low-temperature plasmas: methods and case studies

Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable tool in tackling a vast array of scientific, engineering, and societal problems. The main drivers behind the recent proliferation of ML in practically all aspects of science and technology can be attributed to: (a) improved data acquisition and inexpensive data storage; (b) exponential growth in computing power; and (c) availability of open-source software and resources that have made the use of state-of-the-art ML algorithms widely accessible. The impact of ML on the field of low-temperature plasmas (LTPs) could be particularly significant in the emerging applications that involve plasma treatment of complex interfaces in areas ranging from the manufacture of microelectronics and processing of quantum materials, to the LTP-driven electrification of the chemical industry, and to medicine and biotechnology. This is primarily due to the complex and poorly-understood nature of the plasma-surface interactions in these applications that pose unique challenges to the modeling, diagnostics, and predictive control of LTPs. As the use of ML is becoming more prevalent, it is increasingly paramount for the LTP community to be able to critically analyze and assess the concepts and techniques behind data-driven approaches. To this end, the goal of this paper is to provide a tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone, for learning multivariable nonlinear data-driven prediction models that are capable of describing the complex behavior of plasma interacting with interfaces, and for guiding the design of experiments to explore the parameter space of plasma-assisted processes in a systematic and resource-efficient manner. We illustrate the utility of various supervised, unsupervised and active learning methods using LTP datasets consisting of commonly-available, information-rich measurements (e.g. optical emission spectra, current–voltage characteristics, scanning electron microscope images, infrared surface temperature measurements, Fourier transform infrared spectra). All the ML demonstrations presented in this paper are carried out using open-source software; the datasets and codes are made publicly available. The FAIR guiding principles for scientific data management and stewardship can accelerate the adoption and development of ML in the LTP community.

Physics↗
DOE OSTI2020

Effects of elastic softening and helium accumulation kinetics on surface morphological evolution of plasma-facing tungsten

Based on a continuous-domain model, capable of accessing the spatiotemporal scales relevant to fuzz formation on the surface of plasma-facing component (PFC) tungsten, we report self-consistent simulation results that elucidate the effects of elastic softening and helium (He) accumulation kinetics on the surface morphological response of PFC tungsten. The model accounts for the softening of the elastic moduli in the near-surface region of PFC tungsten, including both thermal softening at high temperature and softening due to He accumulation upon He implantation. The dependence of the elastic moduli on the He content follows an exponential scaling relation predicted by molecular-dynamics simulations, while the He content in the near-surface region of PFC tungsten evolves according to a first-order saturation kinetics, consistent with experimental and simulation results reported in the literature. We establish that this elastic softening accelerates both nanotendril growth on the PFC surface and the onset of fuzz formation. We also explore the role of the rate of He accumulation to a saturation level in the near-surface region of irradiated tungsten in the onset of fuzz formation. For PFC tungsten surfaces such as W(110) where, under typical irradiation conditions, the characteristic time scale for stress-driven surface diffusion is comparable to the characteristic time scale for He accumulation, we find that accelerating the rate of He accumulation accelerates the growth rate of nanotendrils emanating from the surface. Additionally, we present a systematic parametric study of the PFC surface morphological response to explore its dependence on the He accumulation kinetics that is controlled by the irradiation conditions for low-energy implantation. Finally, we introduce an incubation time for nanotendril growth on the PFC surface, a concept equivalent to that of incubation fluence discussed in the literature, to predict and explain the minimum exposure time required to observe fuzz formation on PFC tungsten surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Puck and Puck/SAW Loop Seals (Final Report)

Tamper-indicating devices (TIDs), also known as seals, play a crucial role in various sectors including international nuclear safeguards, arms control, domestic security, and commercial products, by ensuring that monitored or high-value items are not accessed undetected. These devices do not block access but alert to unauthorized tampering. With adversaries' capabilities evolving, there's a pressing need for seals to advance in terms of effectiveness (e.g., better tamper indication and unique identification), and new technology can improve the efficiency of installation and verification. Passive loop seals, widely used in international nuclear safeguards to ensure that continuity of knowledge is maintained on declared items, face stringent International Atomic Energy Agency (IAEA) requirements that surpass those met by commercial products. The metal cup seal (Figure 1, left), a staple IAEA seal, is robust but requires significant resources for post-use verification – specifically, the seal’s unique identity can only be verified at IAEA headquarters after removal from facilities. Further, the seal has been in use for decades and seal types should periodically be replaced to counter adversarial efforts for defeating seals. In 2020, the IAEA outlined about 40 requirements for a new passive loop seal, aiming for in-situ verification, minimal external tool use, unique identification (UID), and clear tamper indication. In response, research and development efforts focused on creating a new passive loop seal that meets these criteria and in 2022 the IAEA announced the completion of the Field Verifiable Passive Loop Seal (FVPS) (Figure 1, right). Concurrently to the IAEA’s efforts, Sandia National Laboratories (SNL) and Oak Ridge National Laboratory (ORNL) designed, developed, and tested two seal versions – Puck and Puck/SAW, with Puck based on the IAEA’s requirements and including a novel visually-obvious tamper response, and Puck/SAW adding additional beneficial capabilities like the ability to receive a unique identifier from a standoff distance and monitoring the wire integrity. Puck/SAW was specifically designed and developed to address sealing applications in dry spent fuel storage facilities, where the number of sealed spent fuel containers results in heavy verification burden and inspector safety issues related to radiation exposure. These efforts are described in this Executive Summary.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Ligand Control of Oxidation and Crystallographic Disorder in the Isolation of Hexavalent Uranium Mono-Oxo Complexes

Here, the development of high-valent transuranic chemistry requires robust methodologies to access and fully characterize reactive species. We have recently demonstrated that the reducing nature of imidophosphorane ligands supports the two-electron oxidation of U 4+ to U 6+ and established the use of this ligand to evaluate the inverse-trans-influence (ITI) in actinide metal-ligand multiple bond (MLMB) complexes. To extend this methodology and analysis to transuranic complexes, new small-scale synthetic strategies and lower-symmetry ligand derivatives are necessary to improve crys-tallinity and reduce crystallographic disorder. To this end, the synthesis of two new imidophosphorane ligands, [N=P t Bu(pip) 2 ]¯ (NPC 1 ) and [N=P t Bu(pyrr) 2 ]¯ (NPC 2 ) (pip = piperidinyl; pyrr = pyrrolidinyl) is presented, which break pseudo-C 3 axes in the tetravalent complexes, U[NPC 1 ] 4 and U[NPC 2 ] 4 . The reaction of these complexes with two-electron oxygen atom transfer reagents (N 2 O, trimethylamine N-oxide (TMAO) and 2,3:5,6-dibenzo-7-azabicyclo[2.2.1]hepta-2,5-diene (dbabhNO)) yields the U 6+ mono-oxo complexes U(O)[NPC 1 ] 4 and U(O)[NPC 2 ] 4 . This methodology is optimized for direct translation to transuranic elements. Of the two ligands, the NPC 2 framework is most suitable for facilitating detailed bonding analysis and assessment of the ITI. Theoretical evaluation of the U–(NPC) bonding confirms a substantial difference between axially and equatorially-bonded N atoms, revealing mark-edly more covalent U–N ax interactions. The U 6d+5f combined contribution for U–N ax is nearly double that of U–N eq , accounting for ITI shortening and increased bond order of the axial bond. Two distinct N-atom hybridizations in the pyrrolidine/piperidine rings are noted across the complexes, with approximate sp 2 and sp 3 configurations describing the slightly shorter P–N “planar” and slightly longer P–N “pyramidal” bonds, respectively. In all complexes, the NPC 2 ligands feature more planar N atoms than NPC 1 , in accordance with a higher electron-donating capacity of the former.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - Simulated Marine Hydrokinetic Tidal Turbine

The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset is part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with other energy technologies. This dataset contains inputs and outputs from simulations of a floating marine hydrokinetic turbine over approximately half a tidal cycle (~6.6 hours). Inflow conditions were derived from field measurements in Alaska’s Cook Inlet and represent a tidal environment in which the current speed ramps from near 0 m/s to a peak of 3 m/s and back. The original acoustic doppler current profiler dataset is publicly available on the Marine and Hydrokinetic Data Repository. In a full tidal cycle, the flow reverses and the rotor would reorient; this reversal was not modeled. In the Cook Inlet campaign , turbulence intensity was similar in both directions. Two inflow cases are included. In the first case, labeled “raw” in the files, the measured current time series was used directly in the InflowWind module of OpenFAST. Speed and direction were applied as a function of time and elevation, uniformly in the horizontal direction. With full spatial coherence, this approach captures high turbulent variability and results in pronounced power fluctuations, so it is considered a conservative, near-worst-case representation of loading. In the second case, labeled “average” in the files, a 30-minute moving average was applied to extract the slowly varying mean speed. The residual fluctuations about this mean were used to generate spatially varying, full-field turbulence inputs with TurbSim, giving a more physically realistic representation of the inflow across the rotor disk. Two random realizations were used to produce distinct inflow conditions for two OpenFAST simulations representing a two-turbine array. The same turbulence intensity is applied across the full time series, producing larger fluctuations at the start and end, where the mean speed is low. The second case is the more appropriate framework for performance and power assessment but overpredicts turbulence at lower flow speeds and underpredicts it at higher speeds. As the floating platform moves and the rotor changes its x-position, Taylor’s frozen turbulence hypothesis used by InflowWind assumes a constant rather than a time-varying mean velocity, introducing some inaccuracy in the velocity plane sampling. The turbine modeled is the 500-kW Reference Model 1, a horizontal-axis two-bladed hydrokinetic turbine on a four-column floating semisubmersible substructure . Simulations were performed using OpenFAST v4.1 with the Reference Open Source Controller (ROSCO) v2.10. All input files required to reproduce the simulations are included. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel . This unit supports up to 2.5 MW, but NLR has only a single 1.25-MW stack. The datasets report hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. The system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operating current of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The simulated tidal turbine time series data was translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz. Each zip file represents a single tidal electrolysis experiment and is named: {technology}_{inflow method}_{number of 500 kW tidal turbines connected} For instance, “tidal-500kW-RM1_average_2.zip” is a 6-hour experiment using the 500-kW tidal reference model, scaled by 2x (1-MW) to better match the electrolyzer maximum of 1.25MW, fed with the 30-minute moving average current case. Each zip folder contains the following files: A .csv file of raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power. A .csv file combines all tidal profiles as "combined_tidal_experiments.csv." A separate experiment, “characterization_200.zip,” shows the MC250 electrolyzer steady-state response with 30-minute load steps over 5 hours and is accessible with this entry.

08 HYDROGEN↗
DOE OSTI2026

Mechanism-Informed Breakdown: Understanding Degradation by Controlling Voltage-Hold Patterns in Proton Exchange Membrane Water Electrolyzers

Low catalyst loadings pose challenges to performance stability in proton exchange membrane (PEM) water electrolysis over extended operation. To study the impact of degradation mechanisms and voltage loss rates, different stress tests are applied to membrane electrode assemblies. Potential cycling conditions were observed to induce higher degrees of iridium (Ir) oxide crystallization, ionomer degradation, and catalyst layer (CL) thinning, which likely contributed to higher kinetic loss rates. On the other hand, while Ir migrating into the PEM (Ir band) generally impairs performance, the interconnected and more uniform Ir band formed under a constant 2 V hold may allow for Ir at the catalyst/membrane interface to remain electronically connected and kinetically accessible, as well as indicate greater Ir site access during the applied stressor. The 2 V hold also demonstrates improved kinetic durability through a lower Tafel slope, faster polarization kinetics, and reduced charge transfer resistance. In contrast, potential cycling caused the migration of disconnected Ir agglomerates into the membrane bulk and created a steady increase in charge transfer resistance, a more dramatic decrease in capacitance (46.7% loss), and significant damage to the surrounding ionomer, indicating a decline in both the quality and quantity of active sites in the anode CL. This work underscores the distinct degradation pathways associated with load holds versus cycling, highlighting the role of catalyst-ionomer interactions in kinetic performance and long-term stability. These insights can inform operational strategies for PEM electrolyzers powered by intermittent energy sources, aiming to minimize efficiency losses over extended operation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Adsorption Hysteresis Under Control: Tuning Host–Guest Interactions via a Genetic Algorithm

Mesoporous adsorbent materials offer a large volumetric capacity; however, cyclic adsorption/desorption processes in these systems often suffer from hysteresis and may require a significant pressure swing to access this capacity. To mitigate hysteresis, a proposed strategy is to include nucleation sites on the walls of the mesoporous material to facilitate droplet and bubble formation, lowering the free energy barriers to the respective phase transitions. It is unclear, however, what combination of adsorbate− adsorbent interactions and spatial patterning would be beneficial for a given application, considering that improvements to some sorption properties may come at the expense of other attributes. To understand these interconnected observables, we examine two model systems, planar-slit and cylindrical pores with tunable interaction sites, using GPU-accelerated transition matrix Monte Carlo simulations. The simulations provide a free energy map of the pressure−adsorption space in a matter of minutes, which we use to track adsorption isotherm characteristics as a function of adsorbent properties. We then leverage the rapid acquisition of simulation data to construct a genetic algorithm to iteratively modify interaction sites of the slit-pore wall to minimize the hysteresis of this system without sacrificing uptake. We find that the adsorption branch of the isotherm is easily modulated via the average host−guest interaction strength, but desorption is only adjustable if there is a suitable bubble nucleation site. Within the context of a slit-pore system, we identify relative interaction strengths and patch sizes required to gain control over both branches of the hysteresis loop.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Visible-Light Photoinitiation of (Meth)acrylate Polymerization with Autonomous Post-Conversion

Conversion plateaus rapidly in radical photopolymerizations (RPPs) following discontinuation of irradiation due to rapid termination of reactive radicals, which restricts the wider use of RPPs in applications that involve nonuniform light access including those with attenuated light transmission or irregular surfaces. Based on our recent report of a radical dark-curing photoinitiator (DCPI) that continues polymerization beyond the cessation of irradiation by enabling latent redox initiation with photo-released amine in the presence of a suitable oxidant, we developed a new DCPI with an absorption spectrum that extends well into the visible range. Our design process involved a series of computational investigations of candidate molecules, including a systematic study of substituents and their position-dependent effects on absorption characteristics, electronic transitions, and the photochemical mechanism and its associated energetics. Our quantum chemical computations identified the target compound 5,7-dimethoxy-6-bromo-3-aroylcoumarin-DMPT/BPh4 and predicted that it would facilitate the dark-curing mechanism by concurrent photo-radical generation and photo-induced release of an efficient redox reductant under visible irradiation. This reductant-tethered chromophore was then synthesized and optically characterized with UV–vis spectroscopy that revealed its strong visible-light absorption with a molar absorptivity of 5710 M–1 cm–1 at 405 nm and 50 M–1 cm–1 at 455 nm. We then demonstrated extensive dark-curing of >35% additional conversion over 25 min following brief activation of the shelf-stable one-part system by irradiation with a 455 nm LED that was ceased at 20% conversion. In contrast, shuttering irradiation of the control formulation at that same point resulted in immediate cessation of conversion, which plateaued at 20%. We determined a remarkable initiator efficiency of 2.82 that results from the additional redox-generated radicals with a 77% photo-reductant generation quantum yield. The combination of superior photo- and dark-curing efficiencies of this new visible DCPI is expected to open new application opportunities in RPP, especially those involving resins that are highly light attenuating, surfaces that possess irregular features that produce uneven irradiance, and production lines where continued dark-curing downstream of the light activation step enhances line efficiencies.

absorption spectrum↗
DOE OSTI2026

Power and particle exhaust in the ST-E1 fusion power plant

Power exhaust challenges and potential solutions for a 5 m major radius, low-aspect ratio burning tokamak have been explored. 1D edge plasma models have been used to screen for access to detachment using short and long outer divertor legs in double and single null configurations, using Ar as the primary impurity and assuming tungsten plasma-facing components (PFCs). These show that detachment access can be accessed for all but the most conservative assumptions on scrape-off layer (SOL) width and power, but that trade-offs will be required between magnet engineering and the size of the acceptable window of as-yet uncertain plasma parameters. SOLPS-ITER was used to further model selected plasma scenarios, confirming that Ar seeding can be used to achieve dissipative divertor scenarios with peak deposited heat fluxes below 15 MWm -2 . Initial scoping of first wall loads and positioning of limiters has been carried out, showing the feasibility of protecting the breeding blanket wall during steady state without impeding tritium breeding. Initial PFC technology selection is also presented, identifying this as a critical area where further work is needed to find an attractive solution for helium-cooled PFCs that can handle high heat fluxes without excessive power requirements. Key questions and trade-offs for concept development have been identified, including: how to achieve high radiation for reduction of SOL power without core performance degradation; whether power exhaust can be well-controlled in a double null plasma; mechanical design and materials challenges of high-heat flux PFCs; and control of material erosion, redeposition and tritium retention.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Data Curation for Machine Learning Applied to Geothermal Power Plant Operational Data for GOOML: Geothermal Operational Optimization with Machine Learning: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach to physics-guided, data-centric machine learning. This framework has been used to develop digital twins that provide steamfield operators with operational environments to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management in real world applications. To create, test, and apply the GOOML framework, diverse time-series datasets spanning multiple years were sourced from various geothermal power plant components within several complex real-world geothermal operations. These operations are based in the United States and New Zealand and include a variety of technologies, end-uses and configurations, collectively covering nearly all relevant operating conditions for modern geothermal fields. Datasets were acquired from multiple sources to ensure that machine learning experiments generalized properly to various operating conditions. It was found that the data varied in quality, format, and completeness. To ensure consistency between the various datasets, a standardized data curation process was developed to reliably streamline data preparation. This paper will discuss best practices as learned from the GOOML data curation process which takes the following steps: 1) acquisition of large quantities of data from power plant operators, 2) digestion of data to gain an initial understanding of what is included, 3) data transformation, which includes converting the data into a standardized machine-readable format so that they can be visualized, quality checked, and cleaned, 4) quality assurance and quality control, involving identification of significant data gaps and apparent anomalies through mapping of data features to real world componentry via the GOOML historical model, followed by discussion with modelers and power plant operators to identify additional data needs and to resolve issues, 5) use in machine learning algorithms, and 6) repetition of steps one through five until all data needs are met and data are deemed suitable for producing trustworthy modeling results which may be disseminated, ideally along with the curated dataset. This iterative process is focused on improving the quality of the data rather than tuning machine learning model parameters and supports a shift towards data-centric AI as a means to improving real-world applicability of geothermal machine learning projects.

access↗
DOE OSTI2023

Time dependent model for non-inductive ECH X-I current ramp-up for SHPD tokamak facility

Non-inductive (NI) plasma current start-up and ramp-up is an important research topic for spherical tokamak (ST) based reactors and fusion pilot plant (FPP). For a compact FPP, the OH flux availability is highly restricted due to its compact geometry. Efficient fundamental extraordinary mode (X-I) electron cyclotron heating (ECH) current start-up and ramp-up regime was identified for a reactor-like high toroidal magnetic field range which has more than a hundred times higher current drive efficiency compared to more conventional ECH methods for the relevant start-up temperature range. High current drive efficiency is possible due to the strong X-I fundamental ECH interaction only with unidirectional passing electrons constrained by the wave accessibility conditions. Here, we extend the X-I electron cyclotron current drive (ECCD) investigation to a time dependent model to simulate the non-inductive current ramp-up to 10 MA for the Sustained High-Power Density (SHPD) facility. As the X-I ECCD driven current I EC rises, due to the back EMF driven negative current, the net plasma current Ip rises more slowly with the current resistive time scale. For tokamak confinement time (both L-mode and H-Mode) which tends to rise with I p , a positive feedback results and even with constant applied ECH power, T e0 , I EC , and I p can continue to rise to very high values. However, in a realistic situation, the T e0 rise should saturate due to a number of factors such as enhanced core radiation and increased power loss at high temperature. To simulate this effect, we adopt a maximum T e0 model which would limit the temperature rise to certain T e0 . With this model, we investigated the current ramp-up for various ECH power levels and the maximum T e0 of 15, 20, and 25 keV. We find that while the power required is reduced with increasing T e0 limit due to increased current drive efficiency, the time to reach 10 MA tends to go up due to the reduced plasma resistivity for the higher T e0 limit. We also find for a given Te0 limit, the time to reach 10 MA tends to be reduced by increasing the applied ECH power by over driving the current ramp-up where I EC is driven at significantly higher level than 10 MA. While the current ramp-up time may not be an issue for the steady-state reactor systems, if it is desirable to minimize the current ramp-up time, it is prudent to have a sufficient ECH power for current over-drive and have some T e0 limiting tools such as impurity seeding for enhanced radiation. In conclusion, a well-controlled NI ECH start-up also has a potential of improving the tokamak start-up reliability and avoid run-away electrons while the NI off-axis current drive could enhance MHD stability and plasma performance improvements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

Non-von Neumann computing using neuromorphic systems based on analogue synaptic and neuronal elements has emerged as a potential solution to tackle the growing need for more efficient data processing, but progress toward practical systems has been stymied due to a lack of materials and devices with the appropriate attributes. Recently, solid state electrochemical ion-insertion, also known as electrochemical random access memory (ECRAM) has emerged as a promising approach to realize the needed device characteristics. ECRAM is a three terminal device that operates by tuning electronic conductance in functional materials through solid-state electrochemical redox reactions. This mechanism can be considered as a gate-controlled bulk modulation of dopants and/or phases in the channel. Early work demonstrating that ECRAM can achieve nearly ideal analogue synaptic characteristics has sparked tremendous interest in this approach. More recently, the realization that electrochemical ion insertion can be used to tune the electronic properties of many types of materials including transition metal oxides, layered two-dimensional materials, organic and coordination polymers, and that the changes in conductance can span orders of magnitude has further attracted interest in ECRAM as the basis for analogue synaptic elements for inference accelerators as well as for dynamical devices that can emulate a wide range of neuronal characteristics for implementation in analogue spiking neural networks. At its core, ECRAM shares many fundamental aspects with rechargeable batteries, where ion insertion materials are used extensively for their ability to reversibly store charge and energy. Computing applications, however, present drastically different requirements: systems will require many millions of devices, scaled down to tens of nanometers, all while achieving reliable electronic-state tuning at scaled-up rates and endurances, and with minimal energy dissipation and noise. Further, in this review, we discuss the history, basic concepts, recent progress, as well as the challenges and opportunities for different types of ECRAM, broadly grouped by their primary mobile ionic charge carrier, including Li, protons, and oxygen vacancies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Twisted Nonlinear Optics in Monolayer van der Waals Crystals

In addition to a plethora of emergent phenomena, the spatial topology of optical vortices enables an array of applications in optical communications and quantum information science. Multibeam nonlinear optical processes, augmented by optical vortices, are essential in this context, providing robust access to an infinitely large set of quantum states associated with the orbital angular momentum of light. Here, we push the boundaries of vortex nonlinear optics to the ultimate limits of material dimensionality. By exploiting multipulse difference frequency, sum frequency, and four-wave mixing in monolayer quantum materials, we demonstrate their ability to independently control the orbital angular momentum and radial distribution of vortex light-fields in addition to their wavelength. Due to the atomically thin nature of the host crystal, this control spans a broad spectral bandwidth in a highly integrable platform that is unconstrained by the traditional limits of bulk nonlinear optical materials. Our work heralds an innovative path for ultracompact and scalable hybrid nanophotonic technologies empowered by twisted nonlinear light–matter interactions in van der Waals nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Observation of Anisotropic Dispersive Dark-Exciton Dynamics in CrSBr

Many-body excitons in CrSBr are attracting intense interest in view of their highly anisotropic magneto-optical coupling and their potential for novel optical interfaces within spintronic and magnonic devices. Characterizing the orbital character and propagation of these electronic excitations is crucial for understanding and controlling their behavior; however, this information is challenging to access. High resolution resonant inelastic x-ray scattering is a momentum-resolved technique that can address these crucial questions. Here, we present measurements collected at the Cr 𝐿 3 -edge which show a rich spectrum of excitations with a variety of spin-orbital characters. While most of these excitations appear to be localized, the dispersion of the lowest energy dark exciton indicates that it is able to propagate along both the 𝑎 and 𝑏 directions within the planes of the crystal. This two-dimensional character is surprising as it contrasts with electrical conductivity and the behavior of the bright exciton, both of which are strongly one dimensional. The discovery of this propagating dark exciton highlights an unusual coexistence of one- and two-dimensional electronic behaviors in CrSBr.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

A substandard candle: the low-$$\nu $$ method at few-GeV neutrino energies

Abstract As accelerator-based neutrino oscillation experiments improve oscillation parameter constraints with more data, control over systematic uncertainties on the incoming neutrino flux and interaction models is increasingly important. The intense beams offered by modern experiments permit a variety of options to constrain the flux using in situ “standard candle” measurements. These standard candles must use very well understood interaction processes to avoid introducing additional interaction model dependence. One option often discussed in this context is the “low- $$\nu $$ ν ” method, which is designed to isolate neutrino interactions where there is low energy-transfer to the nucleus, such that the interaction cross section is expected to be approximately constant as a function of neutrino energy. The shape of the low-energy transfer event sample can then be used to extract the flux shape. Applications of the method at high neutrino energies (many tens of GeV) are well understood. However, the applicability of the method at the lower energies of current and future few-GeV accelerator neutrino experiments remains unclear due to the presence of nuclear and form-factor effects inherent in the interaction models.In this analysis we examine the prospects for improving constraints on the accelerator neutrino fluxes in situ with the low- $$\nu $$ ν method in an experiment-independent way, using (anti)neutrino interactions on argon and hydrocarbon targets from the GENIE, NEUT, NuWro and GiBUU event generators. We begin by investigating the extent to which deviations from the constant cross-section assumption are dependent on poorly understood aspects of the neutrino interaction model. We then assess whether a low energy-transfer event sample can be confidently identified using experimentally accessible observables. We finally consider how the practicalities of reconstructing the energy spectrum of interacting neutrinos in realistic detectors might further limit the utility of low- $$\nu $$ ν flux constraints. The results show that flux constraints from the low- $$\nu $$ ν method would be severely dependent on the interaction model assumptions used in an analysis of neutrinos with energies below 5 GeV, and anti-neutrinos below at least 15 GeV. The spread of model predictions show that a low- $$\nu $$ ν analysis is unlikely to offer much improvement on typical neutrino flux uncertainties, even with a perfect detector. Notably—running counter to the assumption inherent to the low- $$\nu $$ ν method—the model-dependence increases with decreasing energy transfer for experiments in the few-GeV region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗