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Physics and technology considerations for the deuterium–tritium fuel cycle and conditions for tritium fuel self sufficiency

The tritium aspects of the DT fuel cycle embody some of the most challenging feasibility and attractiveness issues in the development of fusion systems. The review and analyses in this paper provide important information to understand and quantify these challenges and to define the phase space of plasma physics and fusion technology parameters and features that must guide a serious R&D in the world fusion program. We focus in particular on components, issues and R&D necessary to satisfy three 'principal requirements': (1) achieving tritium self-sufficiency within the fusion system, (2) providing a tritium inventory for the initial start-up of a fusion facility, and (3) managing the safety and biological hazards of tritium. A primary conclusion is that the physics and technology state-of-the-art will not enable DEMO and future power plants to satisfy these principal requirements. We quantify goals and define specific areas and ideas for physics and technology R&D to meet these requirements. A powerful fuel cycle dynamics model was developed to calculate time-dependent tritium inventories and flow rates in all parts and components of the fuel cycle for different ranges of parameters and physics and technology conditions. Dynamics modeling analyses show that the key parameters affecting tritium inventories, tritium start-up inventory, and tritium self-sufficiency are the tritium burn fraction in the plasma (f b ), fueling efficiency (η f ), processing time of plasma exhaust in the inner fuel cycle (t p ), reactor availability factor (AF), reserve time (tr) which determines the reserve tritium inventory needed in the storage system in order to keep the plant operational for time t r in case of any malfunction of any part of the tritium processing system, and the doubling time (t d ). Results show that η f f b > 2% and processing time of 1–4 h are required to achieve tritium self-sufficiency with reasonable confidence. For η f f b = 2% and processing time of 4 h, the tritium start-up inventory required for a 3 GW fusion reactor is ~11 kg, while it is <5 kg if η f f b = 5% and the processing time is 1 h. To achieve these stringent requirements, a serious R&D program in physics and technology is necessary. The EU-DEMO direct internal recycling concept that carries fuel directly from the plasma exhaust gas to the fueling systems without going through the isotope separation system reduces the overall processing time and tritium inventories and has positive effects on the required tritium breeding ratio (TBR R ). A significant finding is the strong dependence of tritium self-sufficiency on the reactor availability factor. Simulations show that tritium self-sufficiency is: impossible if AF < 10% for any η f f b , possible if AF > 30% and 1% ≤ η f f b ≤ 2%, and achievable with reasonable confidence if AF > 50% and η f f b > 2%. These results are of particular concern in light of the low availability factor predicted for the near-term plasma-based experimental facilities (e.g. FNSF, VNS, CTF), and can have repercussions on tritium economy in DEMO reactors as well, unless significant advancements in RAMI are made. There is a linear dependency between the tritium start-up inventory and the fusion power. The required tritium start-up inventory for a fusion facility of 100 MW fusion power is as small as 1 kg. Since fusion power plants will have large powers for better economics, it is important to maintain a 'reserve' tritium inventory in the tritium storage system to continue to fuel the plasma and avoid plant shutdown in case of malfunctions of some parts of the tritium processing lines. But our results show that a reserve time as short as 24 h leads to unacceptable reserve and start-up inventory requirements. Therefore, high reliability and fast maintainability of all components in the fuel cycle are necessary in order to avoid the need for storing reserve tritium inventory sufficient for continued fusion facility operation for more than a few hours. The physics aspects of plasma fueling, tritium burn fraction, and particle and power exhaust are highly interrelated and complex, and predictions for DEMO and power reactors are highly uncertain because of lack of experiments with burning plasma. Fueling by pellet injection on the high field side of tokamak has evolved to be the preferred method to fuel a burning plasma. Extrapolation from the DIII-D penetration scaling shows fueling efficiency expected in DEMO to be <25%, but such extrapolations are highly uncertain. The fueling efficiency of gas in a reactor relevant regime is expected to be extremely poor and not very useful for getting tritium into the core plasma efficiently. Gas fueling will nonetheless be useful for feedback control of the divertor operating parameters. Extensive modeling has been carried out to predict burn fraction, fueling requirements, and fueling efficiency for ITER, DEMO, and beyond. The fueling rate required to operate Q = 10 ITER plasmas in order to provide the required core fueling, helium exhaust and radiative divertor plasma conditions for acceptable divertor power loads was calculated. If this fueling is performed with a 50–50 DT mix, the tritium burn fraction in ITER would be ~0.36%, which is too low to satisfy the self-sufficiency conditions derived from the dynamics modeling for fusion reactors. Extrapolation to DEMO using this approach would also yield similarly low burn fraction. Extensive analysis presented shows that specific features of edge neutral dynamics in ITER and fusion reactors, which are different from present experiments, open possibilities for optimization of tritium fueling and thus to improve the burn fraction. Using only tritium in pellet fueling of the plasma core, and only deuterium for edge density, divertor power load and ELM control results in significant increase of the burn fraction to 1.8–3.6%. These estimates are performed with physics models whose results cannot be fully validated for ITER and DEMO plasma conditions since these cannot be achieved in present tokamak experiments. Thus, several uncertainties remain regarding particle transport and scenario requirements in ITER and DEMO. The safety standard requirements for protection of the public and release guidelines for tritium have been reviewed. General safety approaches including minimizing tritium inventories, reducing tritium permeation through materials, and decontaminating material for waste disposal have been suggested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The impact of the charge barrier height on Germanium (Ge) detectors with amorphous-Ge contacts for light dark matter searches

Germanium (Ge) detectors with ability of measuring a single electron–hole (e–h) pair are needed in searching for light dark matter (LDM) down to the MeV scale. We investigate the feasibility of Ge detectors with amorphous-Ge (a-Ge) contacts to achieve the sensitivity of measuring a single e-h pair, which requires extremely low leakage current. Three Ge detectors with a-Ge contacts are used to study the charge barrier height for blocking electrons and holes. Using the measured bulk leakage current and the Döhler–Brodsky model, we obtain the values for charge barrier height and the density of localized energy states near the Fermi energy level for the top and bottom contacts, respectively. We predict that the bulk leakage current is extremely small and can be neglected at helium temperature ( $$\sim $$ ~ 4 K). Thus, Ge detectors with a-Ge contacts possess the potential to measure a single e–h pair for detecting LDM particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗

Fast, High-fidelity Lyα Forests with Convolutional Neural Networks

Full-physics cosmological simulations are powerful tools for studying the formation and evolution of structure in the universe but require extreme computational resources. Here, we train a convolutional neural network to use a cheaper N-body-only simulation to reconstruct the baryon hydrodynamic variables (density, temperature, and velocity) on scales relevant to the Lyα forest, using data from Nyx simulations. We show that our method enables rapid estimation of these fields at a resolution of ~20 kpc, and captures the statistics of the Lyα forest with much greater accuracy than existing approximations. Because our model is fully convolutional, we can train on smaller simulation boxes and deploy on much larger ones, enabling substantial computational savings. Furthermore, as our method produces an approximation for the hydrodynamic fields instead of Lyα flux directly, it is not limited to a particular choice of ionizing background or mean transmitted flux.

79 ASTRONOMY AND ASTROPHYSICS↗

Process-oriented evaluation of quasi-stationary Rossby waves and their impact on surface air temperature extremes in dynamical downscaling over North America

Quasi-stationary Rossby waves are a crucial component of the general circulation and play a significant role in regional water and energy cycles, as well as in extreme events. However, process-oriented evaluation for Rossby waves is rarely performed for dynamical downscaling simulations. To close this gap, we evaluate three classes of dynamical downscaling approaches, with a focus on quasi-stationary Rossby waves and their impact on surface air temperature over North America during Northern Hemisphere summer. The three classes of models differ in the way large-scale forcing is provided: a limited-area model (LAM) constrained only by lateral boundary conditions, represented by RegCM4 from the North American branch of the Coordinated Regional Downscaling Experiment (NA-CORDEX), a LAM with spectral nudging to maintain consistency in large-scale dynamics with the forcing data, represented by the Weather Research and Forecasting (WRF) model simulation in NA-CORDEX, and a global variable-resolution model with smoothly varying grid spacings, represented by the Community Atmosphere Model version 5.4, with the Model for Prediction Across Scales (MPAS) as its dynamical core (CAM-MPAS). With no constraints on the atmospheric dynamics, CAM-MPAS exhibits several mean biases in the upper-level circulations over the Pacific Coast region: a weaker subtropical jet, a northward-shifted mid-latitude jet, and an overestimated southerly flow. With the lateral boundary constraint alone, RegCM4 also exhibits weaker jets and overestimated southerly winds off the West Coast. Rossby ray theory reveals that those wind biases direct incoming Rossby waves northward. The erroneously routed Rossby waves distort the relationship between the accumulation of wave activity over the US West Coast and surface temperature anomalies over the Southern Great Plains, which emerges approximately 4 d after the convergence of wave-activity flux in the ERA-Interim reanalysis. Furthermore, the response of heatwaves to the extreme wave activity flux is not reproduced by the two models, a serious drawback as a dynamical downscaling framework is expected to connect large-scale forcing to local-scale phenomena. The WRF model employing spectral nudging is largely free from the aforementioned problems. A pair of sensitivity simulations suggests that spectral nudging is the key to improving the dynamics of quasi-stationary Rossby waves and their impact on surface air temperature. Our results also demonstrate the effectiveness of Rossby wave diagnostics that allow for realistic background flows for assessing the credibility of dynamical downscaling over North America, where incoming Rossby waves propagate through complex circulation patterns before traveling across the continent.

54 ENVIRONMENTAL SCIENCES↗

A Low-Cost Durable Na-FeCl2 Battery with Ultrahigh Rate Capability

Na-based batteries have long been regarded as an inexpensive, sustainable candidate for large-scale stationary energy storage applications. Unfortunately, the market penetration of conventional Na-NiCl2 batteries is approaching its limit for several reasons, including limited rate capability and high Ni cost. Herein, a Na-FeCl2 battery operating at 190 °C is reported that allows a capacity output of 116 mAh g-1 at an extremely high current density of 33.3 mA cm-2 (˜0.6C). The superior rate performance is rooted in the intrinsically fast kinetics of the Fe/Fe2+ redox reaction. Furthermore, it is demonstrated that a small amount of Ni additive (10 mol%) effectively mitigates capacity fading of the Fe/NaCl cathode caused by Fe particle pulverization during long-term cycling. The modified Fe/Ni cathode exhibits excellent cycling stability, maintaining a discharge energy density of over 295 Wh kg-1 for 200 cycles at 10 mA cm-2 (˜C/5).

Zhan, Xiaowen↗

Dark Energy Survey Year 6 Results: improved mitigation of spatially varying observational systematics with masking

As photometric surveys reach unprecedented statistical precision, systematic uncertainties increasingly dominate large-scale structure probes relying on galaxy number density. Defining the final survey footprint is critical, as it excludes regions affected by artefacts or suboptimal observing conditions. For galaxy clustering, spatially varying observational systematics, such as seeing, are a leading source of bias. Template maps of contaminants are used to derive spatially dependent corrections, but extreme values may fall outside the applicability range of mitigation methods, compromising correction reliability. The complexity and accuracy of systematics modelling depend on footprint conservativeness, with aggressive masking enabling simpler, robust mitigation. We present a unified approach to define the DES Year 6 joint footprint, integrating observational systematics templates and artefact indicators that degrade mitigation performance. This removes extreme values from an initial seed footprint, leading to the final joint footprint. By evaluating the DES Year 6 lens sample MagLim++ plus plus on this footprint, we enhance the Iterative Systematics Decontamination (ISD) method, detecting non-linear systematic contamination and improving correction accuracy. While the mask's impact on clustering is less significant than systematics decontamination, it remains non-negligible, comparable to statistical uncertainties in certain w(theta) scales and redshift bins. Supporting coherent analyses of galaxy clustering and cosmic shear, the final footprint spans 4031.04 deg2, setting the basis for DES Year 6 1x2pt, 2x2pt, and 3x2pt analyses. This work highlights how targeted masking strategies optimise the balance between statistical power and systematic control in Stage-III and -IV surveys.

Rodríguez-Monroy, M. [Madrid, IFT; IJCLab, Orsay]↗

Machine Learning Analysis of Hydrologic Exchange Flows and Transit Time Distributions in a Large Regulated River

Hydrologic exchange between river channels and adjacent subsurface environments is a key process that influences water quality and ecosystem function in river corridors. High-resolution numerical models were often used to resolve the spatial and temporal variations of exchange flows, which are computationally expensive. In this study, we adopt Random Forest (RF) and Extreme Gradient Boosting (XGB) approaches for deriving reduced order models of hydrologic exchange flows and associated transit time distributions, with integrated field observations (e.g., bathymetry) and hydrodynamic simulation data (e.g., river velocity, depth). The setup allows an improved understanding of the influences of various physical, spatial, and temporal factors on the hydrologic exchange flows and transit times. The predictors also contain those derived using hybrid clustering, leveraging our previous work on river corridor system hydromorphic classification. The machine learning-based predictive models are developed and validated along the Columbia River Corridor, and the results show that the top parameters are the thickness of the top geological formation layer, the flow regime, river velocity, and river depth; the RF and XGB models can achieve 70% to 80% accuracy and therefore are effective alternatives to the computational demanding numerical models of exchange flows and transit time distributions. Each machine learning model with its favorable configuration and setup have been evaluated. The transferability of the models to other river reaches and larger scales, which mostly depends on data availability, is also discussed.

97 MATHEMATICS AND COMPUTING↗

Highly ordered graphite (HOPG) to hexagonal diamond (lonsdaleite) phase transition observed on picosecond time scales using ultrafast x-ray diffraction

Here, the response of rapidly compressed highly oriented pyrolytic graphite (HOPG) normal to its basal plane was investigated at a pressure of ~80 GPa. Ultrafast x-ray diffraction using ~100 fs pulses at the Materials Under Extreme Conditions sector of the Linac Coherent Light Source was used to probe the changes in crystal structure resulting from picosecond timescale compression at laser drive energies ranging from 2.5 to 250 mJ. A phase transformation from HOPG to a highly textured hexagonal diamond structure is observed at the highest energy, followed by relaxation to a still highly oriented, but distorted graphite structure following release. We observe the formation of a highly oriented lonsdaleite within 20 ps, subsequent to compression. This suggests that a diffusionless martensitic mechanism may play a fundamental role in phase transition, as speculated in an early work on this system, and more recent static studies of diamonds formed in impact events.

58 GEOSCIENCES↗

Additive Manufacture of Multi-Functional, Large-Scale Components

The poster summarizes the main results for a LDRD focused on developing a arc-based additive manufacturing (AM) system capable of fabricating large components with a composition gradient otherwise known as functionally graded materials (FGMs). FGMs are capable of addressing local extreme conditions in an optimal and cost-effective manner. The AM system (referred to as multi-Wire Arc Additive Manufacturing or m-WAAM) consisted of modifying a standard automated gas tungsten arc welding system to deliver multiple welding wires to the weld pool at controlled rates to deposit desired alloy compositions at critical locations. Numerous shapes and composition gradients were fabricated with the system and the effect of various deposition parameters on the nature of the composition profile were evaluated. Additionally, heat treatment of the FGM was performed to develop graded microstructures which should enhance dynamic impact performance of inexpensive steels. The project highlights the potential of m-WAAM to efficiently fabricate FGMs. However, this project only explored the science behind the technique and additional development work will be required to develop a fully-functional system that can build more complex components.

36 MATERIALS SCIENCE↗

Cation Short-Range Ordering of MgAl 2 O 4 and NiAl 2 O 4 Spinel Oxides at High Temperatures via In Situ Neutron Total Scattering

Complex oxides that adopt the isometric spinel structure (AB 2 O 4 ) are important for numerous technological applications and are relevant for certain geological processes, which involve exposure to extreme environments such as high pressures and temperatures. Recent studies have shown that the changes to the spinel structure caused by these environments are complex and depend on the material length scale under consideration. In this study we have expanded this approach to the behavior of spinels under high temperature. In situ neutron total scattering experiments, coupled with pair distribution function analysis, performed on two spinel compositions with various levels of pre-existing disorder (MgAl 2 O 4 and NiAl 2 O 4 ) revealed that both compositions trend to a state of maximum disorder where the A and B cations are randomly distributed amongst the two available sites. Temperature-induced cation inversion, conventionally understood as exchange of cations on the A and B sites, is locally expressed as an atomic rearrangement to a tetragonal symmetry, a correlation that is retained up to the maximum temperature studied (1000 °C). Furthermore, a complex thermal expansion behavior is revealed wherein the oxide materials expand heterogeneously at the level of coordination polyhedral with an apparent dependence on bond strength.

36 MATERIALS SCIENCE↗

Self-healing Growth of LaNiO 3 on a Mixed-Terminated Perovskite Surface

Developing atomic-scale synthesis control is a prerequisite for understanding and engineering the exotic physics inherent to transition-metal oxide heterostructures. Thus, far, however, the number of materials systems explored has been extremely limited, particularly with regard to the crystalline substrate, which is routinely SrTiO 3 . Here, we investigate the growth of a rare-earth nickelate-LaNiO 3 -on (LaAlO 3 )(Sr 2 AlTaO 6 ) (LSAT) (001) by oxide molecular beam epitaxy (MBE). Whereas the LSAT substrates are smooth, they do not exhibit the single surface termination usually assumed necessary for control over the interface structure. Performing both nonresonant and resonant anomalous in situ synchrotron surface X-ray scattering during MBE growth, we show that reproducible heterostructures can be achieved regardless of both the mixed surface termination and the layer-by-layer deposition sequence. The rearrangement of the layers occurs dynamically during growth, resulting in the fabrication of high-quality LaNiO 3 /LSAT heterostructures with a sharp and consistent interfacial structure. This is due to the thermodynamics of the deposition window as well as the nature of the chemical species at interfaces-here, the flexible charge state of nickel at the oxide surface. This has important implications regarding the use of a wider variety of substrates for fundamental studies on complex oxide synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultrafast multi-cycle terahertz measurements of the electrical conductivity in strongly excited solids

Key insights in materials at extreme temperatures and pressures can be gained by accurate measurements that determine the electrical conductivity. Free-electron laser pulses can ionize and excite matter out of equilibrium on femtosecond time scales, modifying the electronic and ionic structures and enhancing electronic scattering properties. The transient evolution of the conductivity manifests the energy coupling from high temperature electrons to low temperature ions. Here we combine accelerator-based, high-brightness multi-cycle terahertz radiation with a single-shot electro-optic sampling technique to probe the evolution of DC electrical conductivity using terahertz transmission measurements on sub-picosecond time scales with a multi-undulator free electron laser. Our results allow the direct determination of the electron-electron and electron-ion scattering frequencies that are the major contributors of the electrical resistivity.

36 MATERIALS SCIENCE↗

A multi-model assessment of global freshwater temperature and thermoelectric power supply under climate change

Water temperature is a key abiotic factor influencing aquatic ecosystem health and the services provided to both nature and humans. Global water temperature models offer possibilities to improve our understanding of water temperature regimes, which is increasingly important against the backdrop of climate change. Yet, existing studies have predominantly relied on a single model, which can lead to an incomplete representation of uncertainty and potential biases, in addition to limited insight into the range of possible future conditions, which ultimately reduces the robustness of climate impact assessments. Here, we provide a comprehensive assessment of surface freshwater temperature changes from various river and lake models for both past conditions and under future scenarios of climate change. Global models consistently simulate that surface water temperatures are currently 0.5 °C–0.8 °C higher than at the turn of the century (i.e. 1981–2000), and that warming will extend and intensify with future global change throughout the 21st century. While the strength of warming is highly sensitive to the different water temperature models, emissions scenarios and global climate models, our multi-model ensemble shows a global average annual water temperature rise of between +1.3 °C and +4.1 °C by the end of the century. To illustrate a potential societal impact of our results, we evaluate how future changes in discharge and water temperature may affect existing thermoelectric power plants, estimating average annual reductions of 1.5%–6% in global usable capacity by the end of the century. However, with river water temperatures projected to exhibit more pronounced seasonal patterns in the future—especially under the more extreme climate change scenarios and during summer months in the Northern Hemisphere—intra-annual reductions in usable capacity can be much more severe. Given the challenges associated with (large-scale) adaptation to control water temperature regimes, strong climate change mitigation is crucial for minimising water temperature rises and its associated negative impacts on humankind and ecosystems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Probing cold nuclear matter with energy correlators

The future electron-ion collider (EIC) will produce the first-ever high energy collisions between electrons and a wide range of nuclei, opening a new era in the study of cold nuclear matter. Quarks and gluons produced in these collisions will propagate through the dense nuclear matter of nuclei, imprinting its structure into subtle correlations in the energy flux of final state hadrons. In this article, we apply recent developments from the field of jet substructure, namely the energy correlator observables, to decode these correlations and provide a new window into nuclear structure. The energy correlators provide a calibrated probe of the scale dependence of vacuum quantum chromodynamics (QCD), enabling medium modifications to be imaged and interpreted as a function of scale. Using the eHIJING parton shower to simulate electron-nucleus collisions, we demonstrate that the size of the nucleus is imprinted as an angular scale in the correlators, with a magnitude that is visible for realistic EIC kinematics. We can observe the size difference between the proposed EIC nuclear targets 3 He, 4 He, 12 C, 40 Ca, 64 Cu, 197 Au, and 238 U, showing that the energy correlators can image femtometer length scales using asymptotic energy flux. Our approach offers a unified view of jet substructure across collider experiments, and provides numerous new theoretical tools to unravel the complex dynamics of QCD in extreme environments, both hot and cold.

Electron-ion collisions↗

Nonlinear Thomson scattering with ponderomotive control

In nonlinear Thomson scattering, a relativistic electron re-radiates the photons of a laser pulse, converting optical light to x rays or beyond. While this extreme frequency conversion offers a promising source for probing high-energy-density materials and driving uncharted regimes of nonlinear quantum electrodynamics, conventional nonlinear Thomson scattering has inherent tradeoffs in its scaling with laser intensity. Here we discover that the ponderomotive control afforded by spatiotemporal pulse shaping enables novel regimes of nonlinear Thomson scattering that substantially enhance the scaling of the radiated power, emission angle, and frequency with laser intensity. By appropriately setting the velocity of the intensity peak, a spatiotemporally shaped pulse can increase the power radiated by orders of magnitude. Here, the enhanced scaling with laser intensity allows for operation at significantly lower electron energies or intensities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Performing In Situ Closed-Cell Gas Reactions in the Transmission Electron Microscope

Gas reactions studied by in situ electron microscopy can be used to capture the real-time morphological and microchemical transformations of materials at length scales down to the atomic level. In situ closed-cell gas reaction (CCGR) studies performed using (scanning) transmission electron microscopy (STEM) can separate and identify localized dynamic reactions, which are extremely challenging to capture using other characterization techniques. For these experiments, we used a CCGR holder that utilizes microelectromechanical systems (MEMS)-based heating microchips (hereafter referred to as "E-chips"). The experimental protocol described here details the method for performing in situ gas reactions in dry and wet gases in an aberration-corrected STEM. This method finds relevance in many different materials systems, such as catalysis and high-temperature oxidation of structural materials at atmospheric pressure and in the presence of various gases with or without water vapor. Here, several sample preparation methods are described for various material form factors. During the reaction, mass spectra obtained with a residual gas analyzer (RGA) system with and without water vapor further validates gas exposure conditions during reactions. Integrating an RGA with an in situ CCGR-STEM system can, therefore, provide critical insight to correlate gas composition with the dynamic surface evolution of materials during reactions. In situ/operando studies using this approach allow for detailed investigation of the fundamental reaction mechanisms and kinetics that occur at specific environmental conditions (time, temperature, gas, pressure), in real-time, and at high spatial resolution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

νBDX: a Coherent Elastic Neutrino Nucleus Scattering (CEνNS) experiment at Jefferson Lab

Particle physics is an ever-changing field seeking to explain phenomena that lie at the limits of our current knowledge. Among discovered and hypothesized interactions, Coherent Elastic Neutrino-Nucleus Scattering (CE?NS) stands out as a fascinating and elusive phenomenon, offering a unique window into the nature of neutrinos and their interactions with matter. CE?NS, a process predicted by the Standard Model, represents one of the subtle ways in which neutrinos can interact with atomic nuclei. Unlike other neutrinonucleus interactions, CE?NS occurs coherently, meaning that the entire nucleus collectively responds to the neutrino-mediated weak force, resulting in small energy transfers to the nucleus as a whole. The extremely rare nature of CE?NS events presents a formidable challenge to experimenters seeking to detect and study these interactions. Recent advances in detector technologies and the implementation of large-scale experiments, such as coherent neutrino scattering experiments at research facilities around the world, have opened up new avenues for exploring this elusive phenomenon. These experiments aim not only to observe CE?NS directly but also to extract valuable information on neutrino properties, nuclear structure, and potential deviations from the Standard Model. This thesis aims to study the feasibility of an experiment to study CE?NS at The Thomas Jefferson National Accelerator Facility, Newport News, VA, USA. This would be an experiment that exploits the production of neutrinos by an electron beam dumped on a thick target (the beam dump). The large quantity of neutrinos produced and their energy profile are well suited to the purpose of studying the CE?NS. In my thesis, I will start from previous studies on CE?NS and from theoretical considerations regarding the process, then quantify the expected events for a hypothetical experiment and possible backgrounds through simulations aimed at optimizing the geometry of the future detector. I will also show some tests on selected detector components that will be part of a first prototype.

Grazzi, Stefano↗