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DOE OSTI2024

Collaborative Research: Vlasov-Maxwell Simulations to Resolve Electron Heating and Dissipation, in Quasi-Perpendicular Shocks (Final Report)

Collisionless shocks are a grand challenge problem in plasma physics and have been the subject of study for more than six decades. Shocks are ubiquitous phenomena in the universe and are responsible for transforming high energy and momentum flows into thermal energy and energetic particles. Understanding how shocks operate is of primary importance to understand the sun-earth coupling, protecting manned missions and spacecrafts from high energy particles, inertial confinement fusion, and radiation observed from astrophysical plasmas, such as supernova remnants and astrophysical jets. A major unanswered question on this frontier is, how does a collisionless plasma transform flow energy and momentum into electron thermal energy? Many potential mechanisms have been proposed to perform the conversion between flow and thermal energy in a collisionless plasma, but the answer has been elusive. To solve the mystery, non-relativistic perpendicular and quasi-perpendicular shocks are studied via a coordinated approach employing cutting-edge numerical simulations with the continuum kinetic code Gkeyll and spacecraft observations supplied by NASA's Magnetospheric Multiscale (MMS) mission. In both sets of data, we employ novel techniques to identify how and where energy is exchanged between electromagnetic fields and plasma particles. By combining cutting-edge spacecraft data and numerical simulations with these diagnostics, we have been able to identify some of the primary mechanisms responsible electron heating and dissipation in heliospheric shocks. In addition to electron dynamics, we have complete access to proton simulation and in situ data, enabling us to characterize proton heating and acceleration in quasi-perpendicular shocks. Many astrophysical quasi-perpendicular shocks have similar parameters to those in this study, including supernova remnants and shocks in galaxy clusters. Additionally, the simulation code, Gkeyll, and associated analysis scripts are openly available for community use. This award has supported a collaborative effort between Princeton University, the University of Arizona - Tucson, and the University of Maryland - College Park. The award funded three early career scientists, including the funding and training of one female postdoctoral researcher, who was involved in all aspects of the MMS data analysis and some portions of the simulation analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Room temperature chemical transformation of SnSe to Ag 2 Se nanocrystals via cation exchange

Atomic-scale control of the chemical composition of semiconductor nanocrystals through a cation exchange reaction affords greater tunability in the design of multifunctional semiconductor composite nanocrystals. Here, we report a facile route to SnSe–Ag 2 Se composite nanocrystals using cation exchange at room temperature. Starting from freshly synthesized SnSe nanorods, we leverage the strong distortion of the Sn 2+ octahedral coordination in SnSe and the hard–soft acid–base (HSAB) principle, to promote the exchange of an Sn 2+ ion with two Ag + ions in methanol leading to Ag 2 Se/SnSe nanocomposites. The morphology and chemistry of the nanocrystals evolve from nanorods with SnSe@Ag 2 Se (core@shell) structures for SnSe-rich composites to nanorods with a random distribution of Sn 2+ and Ag + ions for nearly equimolar composites, and finally to irregular fragmented nanocrystals for Ag 2 Se-rich composites. A mechanistic understanding of the observed morphology evolution is discussed using the change in the cation coordination from octahedral (Sn 2+ ) to tetrahedral (Ag + ) geometry and the accompanying expansion of the hcp Se 2– sublattice. Interestingly, the synthesized composite nanocrystals exhibit an optical band gap value tunable within a wide energy range by increasing the Ag 2 Se/SnSe ratio. This work provides a useful and facile strategy to modify the optical behavior of semiconductor nanomaterials, which can be leveraged for the design of better optical and/or photovoltaic devices.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Correlated Anion Disorder in Heteroanionic Cubic TiOF 2

Resolving anion configurations in heteroanionic materials is crucial for understanding and controlling their properties. For anion-disordered oxyfluorides, conventional Bragg diffraction cannot fully resolve the anionic structure, necessitating alternative structure determination methods. We have investigated the anionic structure of anion-disordered cubic (ReO 3 -type) TiOF 2 using X-ray pair distribution function (PDF), 19 F MAS NMR analysis, density functional theory (DFT), cluster expansion modeling, and genetic-algorithm structure prediction. Our computational data predict short-range anion ordering in TiOF 2 , characterized by predominant cis-[O 2 F 4 ] titanium coordination, resulting in correlated anion disorder at longer ranges. To validate our predictions, we generated partially disordered supercells using genetic-algorithm structure prediction and computed simulated X-ray PDF data and 19 F MAS NMR spectra, which we compared directly to experimental data. To construct our simulated 19 F NMR spectra, we derived new transformation functions for mapping calculated magnetic shieldings to predicted magnetic chemical shifts in titanium (oxy)fluorides, obtained by fitting DFT-calculated magnetic shieldings to previously published experimental chemical shift data for TiF 4 . We find good agreement between our simulated and experimental data, which supports our computationally predicted structural model and demonstrates the effectiveness of complementary experimental and computational techniques in resolving anionic structure in anion-disordered oxyfluorides. From additional DFT calculations, we predict that increasing anion disorder makes lithium intercalation more favorable by, on average, up to 2 eV, highlighting the significant effect of variations in short-range order on the intercalation properties of anion-disordered materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Structure–Activity Relationships for Ethanol Dehydrogenation to Acetaldehyde by Silica-Supported Zinc Oxide Catalysts

Silica-supported ZnO efficiently catalyzes the nonoxidative dehydrogenation of ethanol to acetaldehyde, which is relevant for production of 1,3-butadiene from bioethanol. Characterization with in situ spectroscopies under dehydrated conditions (high sensitivity-low energy ion scattering (HS-LEIS), diffuse reflectance (DR) UV–vis, X-ray absorption spectroscopy (XAS), diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS), inelastic neutron scattering (INS), and UV Raman), and ammonia adsorption probed by temperature-programmed desorption followed by DRIFTS and mass spectrometry (DRIFTS-MS NH 3 -TPD), and DFT calculations revealed that the supported ZnO x phase was present as isolated surface ZnO x sites on SiO 2 , with the vast majority coordinated by two siloxane bonds and one silicon atom with two nonbridging oxygens ((≡SiO) 2 Zn 2+ O 2 Si=), anchored at 4-, 5-, and 6-membered siloxane rings. A minor fraction of surface ZnO x sites possessed Lewis acidity, and even fewer sites possessed a Bro̷nsted acidic Zn(OH) + Si moiety. Ethanol temperature-programmed surface reaction-mass spectrometry (TPSR-MS) with various oxidative or ethanol reaction pretreatments indicated that only sites with Lewis and Bro̷nsted acidic character (Zn(OH) + Si) were active for ethanol dehydrogenation, while the majority surface (≡SiO) 2 Zn 2+ O 2 Si= sites were inactive. Greater heterogeneity among all surface ZnO x sites, as assessed by in situ DR UV–vis spectroscopy, was associated with a greater number of ZnO x sites that were active for ethanol dehydrogenation as well as lower enthalpic barriers for acetaldehyde production among the most active surface ZnO x sites. Turnover frequencies and the apparent activation energy for ethanol dehydrogenation were determined from steady-state kinetics. Together, these findings suggested that anchoring inactive surface (≡SiO) 2 Zn 2+ O 2 Si= sites on the silica support caused a greater number of active surface ZnO x sites to adopt a more strained configuration, promoting ethanol dehydrogenation catalysis. Pretreatments and catalysts that promoted desorption of ethanol during TPSR, taken as a marker of surface dehydroxylation, were associated with an increased number of the most active surface (Zn(OH) + Si) sites. Such findings suggested that inactive surface ZnO x sites were activated for ethanol dehydrogenation by dehydroxylation of the support and/or decreased coordination to hemilabile siloxane ligands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Ultrafast x-ray diffraction of high-pressure phases in dynamically compressed TiO 2

Here, we investigate the high-pressure polymorphism of Ti⁢O 2 under laser-shock compression from 54(5) to 137(7) GPa using in situ femtosecond x-ray diffraction. Our results provide experimental evidence of the 𝑃⁢𝑐⁢𝑎⁢2 1 -type distorted fluorite structure formed from polycrystalline Ti⁢O 2 dynamically compressed to 54(5) GPa. Upon higher compression, we observe the direct formation of the ninefold coordinated F⁡e 2 ⁢P-type phase at 68(4) and 78(3) GPa in polycrystalline and [001]-oriented Ti⁢O 2 , respectively. This represents an unprecedented 100 GPa reduction in the shock synthesis pressure of the F⁡e 2⁢ P-type structure relative to quasihydrostatic loading conditions. On pressure release, the F⁡e 2⁢ P-type phase transforms to the α-Pb⁢O 2 structure and, at later times, reverts to rutile. Thus, the rutile →F⁡e 2⁢ P and α-Pb⁢O 2 →rutile transformations are both observed to occur on nanosecond timescales. Our results highlight the unique ability of high-strain-rate uniaxial compression to synthesize novel high-pressure phases and also indicate the importance of in situ atomic-level probes in developing pressure-temperature phase diagrams.

Crystal structures↗

DOE OSTI2024

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

United States Muon Collider Community White Paper for the European Strategy for Particle Physics Update

This document is being submitted to the 2024-2026 European Strategy for Particle Physics Update (ESPPU) process on behalf of the US Muon Collider community, with its preparation coordinated by the interim US Muon Collider Coordination Group. The US Muon Collider Community comprises a few hundred American scientists. The purpose of the document is to inform ESPPU about the US plans for Muon Collider research and development (R&D), explain how these efforts align with the broader international R&D initiatives, and present the US community vision for the future realization of this transformative project.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

DOE OSTI2024

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System: Preprint

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Planning and Operations in Electricity Markets Under System Transformation

United States electricity markets, planning mechanisms, and operational procedures are currently evolving in concert with three key trends. First, a range of new resources—solar, wind, energy storage, hybrid co-located storage, and distributed energy—are coming online and require new solutions to ensure they are efficiently integrated into existing systems. Second, consumers now face more opportunities to participate in markets by providing demand response and engaging in two-way interactions with the grid. Third, there is an increasing need for enhanced coordination between generation and transmission planning as well as across transmission and distribution systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Review of Technical Requirements for Inverter-Based Resources in Chile

This document compares the technical requirements in the grid code of Chile (NTSyCS) against the EirGrid (Ireland transmission system operator) and National Grid Electricity System Operator (NESO) grid codes and the Institute of Electrical and Electronics Engineers (IEEE) 2800-2022 standard for conventional inverter technology at the transmission and subtransmission levels in the process of being adopted by system operators in the U.S. The document is intended to be a guide and reference for future updates of the NTSyCS, considering the local system requirements and present improvements in inverter-based resource (IBR) technology. In light of the findings of the aforementioned comparative review, this document proposes and describes the requirements for conventional IBRs that could be incorporated and updated into the Chilean grid code. The document is structured around the main grid challenges posed by the transition to an IBR-dominated grid and conventional IBRs capabilities to help address them. This document does not provide guidance on how this specification should be implemented (e.g., through a mandate or market solution).

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

A dynamic protein interactome drives energy conservation and electron flux in Thermococcus kodakarensis

ABSTRACT Life is supported by energy gains fueled by catabolism of a wide range of substrates, each reliant on the selective partitioning of electrons through redox ( red uction and ox idation) reactions. Electron flux through tunable and regulated protein interactions provides dynamic routes for energy conservation, but how electron flux is regulated in vivo , particularly for archaeal metabolisms that support rapid growth at the thermodynamic limits of life, is poorly understood. Identification of bona fide in vivo protein assemblies and how such assemblies dictate the totality of electron flux is critical to our understanding of the regulation imposed on metabolism, energy production, and energy conservation. Here, 25 key proteins in central metabolic redox pathways in the model, genetically accessible, hyperthermophilic archaeon Thermococcus kodakarensis , were purified to reveal an extensive, dynamic, and tightly interconnected network of protein interactions that responds to environmental cues (such as the availability of various reductive sinks) to direct electron flux to maximize energetic gains. Interactions connecting disparate functions suggest many catabolic and anabolic activities occur in spatial proximity in vivo , and while protein complexes have been historically defined under optimal conditions, many of these complexes appear to maintain alternative partnerships in changing conditions. The totality of the results obtained redefines our understanding of in vivo assemblies driving ancient metabolic strategies supporting the growth of modern Archaea. IMPORTANCE Given the potential for rational genetic manipulations of biofuel- and biotech-promising archaea to yield transformative results for major markets, it is a priority to define how the metabolisms of such species are controlled, at least in part, by in vivo protein assemblies, and from such, define routes of energy flux that can be most efficiently altered toward biofuel or biotechnological gains. Proteinaceous electron carriers (PECs, such as ferredoxins) offer the potential for specific protein–protein interactions to coordinate selective reductive flow. Employing the model, genetically accessible, hyperthermophilic archaeon, Thermococcus kodakarensis , we establish the metabolic protein interactome of 25 key redox proteins, revealing that each redox active protein has a dynamic partnership profile, suggesting catabolic and anabolic activities may occur in concert and in temporal and spatial proximity in vivo . These results reveal critical importance in evaluating the newly identified partnerships and their role and utility in providing regulated redox flux in T. kodakarensis .

Williams, Sere A. (ORCID:0000000235509590)↗

DOE OSTI2026

MARVEL Reactor Digital Engineering Developments

The MARVEL reactor project has served to introduce a new generation of engineers to the processes required to transform a reactor design from simply an idea on paper into what will be an approved, constructed, and operational nuclear power system. Much as there have been advances in materials, analysis, and evaluation methodologies over the 50 years since the last reactor was built at INL, so too has the technology for managing the engineering process itself advanced. Digital Engineering tools and methods provide improved coordination between previously siloed engineering disciplines, reduced burdens of non-value-added data transcription processes and bring forward insights and improvements that might otherwise fall later in the design stage, where changes are much more costly. While the tools and techniques to support the full digital engineering vision are not yet complete, the MARVEL design processes provide valuable demonstrations and validations of key aspects and illuminate further areas for implementation by subsequent projects.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2025

Unraveling Anion-Specific Inhibition and Structural Modulation of Gibbsite Crystallization: Implications for Aluminum Mobility in Natural and Engineered Systems

Gibbsite (α-Al(OH) 3 , sometimes designated as γ-Al(OH) 3 ) plays a crucial role in the chemistry of aluminum in the environment and industry, yet its crystallization behavior under multianionic conditions is not well understood. Here, in this study, we investigate how six common anions─fluoride (F – ), chloride (Cl – ), bromide (Br – ), nitrate (NO 3 – ), sulfate (SO 4 2– ), and phosphate (PO 4 3– )─influence the mineralization, structure, and morphology of gibbsite at room temperature. The results show that PO 4 3– , SO 4 2– , and F – strongly inhibit gibbsite formation, stabilizing amorphous or alternative crystalline phases such as nordstrandite and cryolite. On the contrary, Cl – , Br – , and NO 3 – allow partial to complete crystallization of gibbsite without significant morphological changes. Solid-state 27 Al magic angle spinning nuclear magnetic resonance provides crucial insight into aluminum coordination environments in both crystalline and amorphous phases, distinguishing between octahedral, pentahedral, and tetrahedral Al species. The density functional theory calculations reveal a direct correlation between the Al–X bond strength and the inhibition of crystallization, following the order: PO 4 3– > SO 4 2– > F – > NO 3 – > Cl – > Br – . These findings offer molecular-scale insights into anion-specific effects on aluminum hydroxide nucleation and transformation, improving the understanding of gibbsite formation and aluminum cycling in soils, phosphate retention, contaminant immobilization, and waste treatment strategies in nuclear and industrial settings. These insights can also guide the controlled synthesis of aluminum hydroxide materials with tailored crystallinity and morphology via liquid-assisted methods.

Anions effect↗

DOE OSTI2026

PPT1-mediated plastidic phospho enol pyruvate import enhances fatty acid biosynthesis in sugar-rich tissues

Metabolic engineering of vegetative tissues for lipid production holds transformative potential for sustainable biofuels, yet achieving sufficient yields remains challenging. Here, we present a strategy to enhance fatty acid synthesis by redirecting cytosolic phospho enol pyruvate (PEP) into plastids through overexpression of the plastidial phospho enol pyruvate/phosphate translocator ( PPT1 ) in vegetative tissues of Arabidopsis thaliana . Integrated metabolomic and transcriptomic analyses revealed that AtPPT1 overexpression alleviated metabolite overaccumulation in high-sugar tissues, consistent with enhanced carbon flux coordination between the cytosol and chloroplast. Notably, phosphofructokinase activity, a key step in glycolysis, was elevated, linking plastidic PEP import to increased glycolytic throughput. In Arabidopsis, overexpression of AtPPT1 increased fatty acid content and lipid droplet accumulation in the sugar-accumulating sweet11;12;13 mutant, but not in wild-type Col-0. Together, these findings establish PEP redirection as an effective strategy to boost fatty acid and lipid production in sugar-rich vegetative tissues and provide a complementary metabolic module for future lipid-engineering efforts.

Arabidopsis thaliana↗

DOE OSTI2026

Modeling Framework for Data Center

This chapter highlights the critical need for advanced modeling of data centers due to their rapidly increasing energy consumption and impact on grid reliability. Driven by the demand for AI applications, data centers are projected to consume a significant portion of US energy by 2028, putting stress on an already challenged power grid. The chapter emphasizes the importance of "fast" time-scale models to understand the dynamic interactions between data centers and the grid, especially given the rapid power fluctuations of AI workloads. It outlines a modeling framework that includes both offline and real-time EMT domain simulations, detailing the necessary representations for various components like utility interfaces, transformers, IT loads, UPS, cooling loads, Battery Energy Storage Systems (BESS), generators, protection systems, and higher-level control systems. While standard simulation tools like PSCAD offer basic models, custom development is often required to accurately capture the unique and fast-changing behaviors of modern data centers. The chapter also discusses key metrics and test cases for validating these models, focusing on transient load responses, protection relay coordination, and demand flexibility. Finally, it addresses the challenges of modeling large-scale data centers, such as computational complexity and the trade-off between model fidelity and practicality, suggesting hybrid modeling approaches as a solution. The overarching goal is to create a robust framework that helps assess data center impacts on grid stability, identify vulnerabilities, and inform the development of standards for reliable integration of these large loads into the bulk power system.

25 ENERGY STORAGE↗

DOE OSTI2025

Advanced Building Construction Collaborative (Final Technical Report)

This report summarizes the outcomes of RMI’s five-year U.S. Department of Energy–funded Advanced Building Construction Collaborative (ABC-C), which accelerated adoption of high-performance construction through industry collaboration, market research, technology commercialization, and demand aggregation. It highlights the Collaborative’s achievements—including engagement of more than 130 organizations, support for over $637 million in funding for ABC companies, and recommendations to scale advanced building construction through coordinated market, policy, and investment strategies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Cross-sectoral impact of emerging technologies on U.S. manufacturing resilience and competitiveness

Introducing new technologies in one energy-intensive industry can affect how other industries operate and stay resilient, yet these cross-sector interactions are often underappreciated in conventional technology roadmaps. In practice, industrial systems do not evolve in isolation. They are linked through shared upstream and downstream dependencies, such as electricity and fuel supply, critical materials, transportation networks, and enabling infrastructure. As a result, large-scale technology deployment in one sector can reshape resource availability, infrastructure demand, and operational risk in others. These interdependencies mean that technology deployment decisions in one sector can create unintended bottlenecks or cascading benefits in others. Here, this article argues that a cross-sector, system-of-systems perspective is essential for evaluating and scaling emerging technologies in energy-intensive industries. By framing industrial transformation as an interconnected systems challenge rather than a set of isolated sectoral decisions, the study highlights how interdependence shapes technology feasibility, adoption pathways, and resilience outcomes. The article illustrates how cross-sector linkages can amplify both risks and benefits, and it emphasizes the importance of integrated planning approaches that account for shared dependencies, cascading impacts, and co-optimization opportunities. Adopting this broader perspective can support more robust technology roadmaps, improve strategic coordination across industries, and strengthen the long-term resilience of the industrial sector as a whole.

Nain, Preeti [Oak Ridge National Laboratory (ORNL)↗