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DOE OSTI2025

An Evaluation of Representation Learning Methods in Particle Physics Foundation Models

We present a systematic evaluation of representation learning objectives for particle physics within a unified framework. Our study employs a shared transformer-based particle-cloud encoder with standardized preprocessing, matched sampling, and a consistent evaluation protocol on a jet classification dataset. We compare contrastive (supervised and self-supervised), masked particle modeling, and generative reconstruction objectives under a common training regimen. In addition, we introduce targeted supervised architectural modifications that achieve state-of-the-art performance on benchmark evaluations. This controlled comparison isolates the contributions of the learning objective, highlights their respective strengths and limitations, and provides reproducible baselines. We position this work as a reference point for the future development of foundation models in particle physics, enabling more transparent and robust progress across the community.

Chen, Michael [Caltech]↗

DOE OSTI2025

AI Benchmark Democratization and Carpentry

Benchmarks are a cornerstone of modern machine learning, enabling reproducibility, comparison, and scientific progress. However, AI benchmarks are increasingly complex, requiring dynamic, AI-focused workflows. Rapid evolution in model architectures, scale, datasets, and deployment contexts makes evaluation a moving target. Large language models often memorize static benchmarks, causing a gap between benchmark results and real-world performance. Beyond traditional static benchmarks, continuous adaptive benchmarking frameworks are needed to align scientific assessment with deployment risks. This calls for skills and education in AI Benchmark Carpentry. From our experience with MLCommons, educational initiatives, and programs like the DOE's Trillion Parameter Consortium, key barriers include high resource demands, limited access to specialized hardware, lack of benchmark design expertise, and uncertainty in relating results to application domains. Current benchmarks often emphasize peak performance on top-tier hardware, offering limited guidance for diverse, real-world scenarios. Benchmarking must become dynamic, incorporating evolving models, updated data, and heterogeneous platforms while maintaining transparency, reproducibility, and interpretability. Democratization requires both technical innovation and systematic education across levels, building sustained expertise in benchmark design and use. Benchmarks should support application-relevant comparisons, enabling informed, context-sensitive decisions. Dynamic, inclusive benchmarking will ensure evaluation keeps pace with AI evolution and supports responsible, reproducible, and accessible AI deployment. Community efforts can provide a foundation for AI Benchmark Carpentry.

von Laszewski, Gregor [Virginia U.]↗

DOE OSTI2025

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency

Many workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to bring this emerging paradigm to HEP pipelines. The framework enables LLMs to interface with domain-specific tools, construct and manage simulation workflows, and assist in common utility and data analysis tasks through schema-validated operations and run-card-driven configuration. To demonstrate these capabilities, we consider a representative Beyond the Standard Model (BSM) Monte Carlo validation pipeline that spans model generation, event simulation, and downstream analysis within a unified, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for transparent, human-in-the-loop systems.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗

DOE OSTI2025

Bubbler Design Updates for Nuclear Safeguards Applications

The accurate monitoring of molten salt compositions is crucial for nuclear safeguards, particularly in the context of mixtures used in molten salt reactors as well as pyroprocessing. However, for nuclear material accountancy in actinide bearing molten salts, the solution volume is also needed to determine the total mass of material in the salt. This study explores the effectiveness of two bubbler configurations, triple and single, for density and level measurements within these molten salts for salt volume determinations. The triple bubbler system utilizes three gas dip-tubes strategically positioned at different heights within the molten salt. With this design, the molten salt level, density, and surface tension can be determined simultaneously. The single bubbler configuration, on the other hand, relies on a dynamic single dip-tube to determine the density and level. Both configurations will be tested in aqueous solutions as well as in LiCl-KCl and NaCl-MgCl2 molten salts between 450°C and 750°C. Dip-tube diameters and bubbler inferences will also be explored. A new bubbler is being designed based on results. The findings of this study will provide valuable insights into the optimal bubbler design and configuration for ensuring representative sampling of molten salt compositions in nuclear safeguards applications. This will contribute to enhanced accountability and transparency in the monitoring of actinide bearing molten salts, promoting nuclear safeguards objectives.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Nontraditional Sensors for Aqueous Separation Research & Workforce Development

Idaho National Laboratory’s (INL) nuclear fuel cycle capabilities enable the deployment of technologies that sustain the current reactor fleet, support demonstration and deployment of new advanced reactors, and facilitate management and disposition of existing and future radiological waste materials. INL focuses on deploying nuclear energy systems with confidence by decreasing proliferation risk through research that demonstrates process transparency and supports safeguards and security by design. An example of these capabilities is the Beartooth test bed, set to begin operations toward the end of fiscal year 2026. Beartooth will include a cascade of centrifugal contactors, glove box lines, and solidification and dissolution equipment to aid in the progression of novel separation techniques and to provide hands-on experience to cultivate and maintain a robust workforce of experts. To support Beartooth’s enhanced instrumentation and monitoring equipment needs, several nontraditional sensors are being considered for future deployment. The non-traditional sensors include accelerometers, acoustic microphones, and infrared cameras. These nontraditional sensors have the potential to not only help monitor the process but also enhance nuclear safeguards.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

DOE OSTI2025

Digitizing and Enhancing Accessibility of the Fusion Safety Archives

This project focuses on the digitization and public accessibility to the Fusion Safety Archives at the Idaho National Laboratory. The first phase involves a thorough review of each document in the physical archives to determine its online availability. For documents that are available online, PDF copies and unique identifiers are collected for database integration. Documents not available online are delivered to Red Inc. for digitization. Additionally, defunct storage devices such as diskettes are sent to INL’s archival department for data retrieval where possible. The second phase of the project involves the creation of a comprehensive database to house the digital copies of the archives. The database will facilitate easy access and management of the digitized documents. Following the database creation, we plan to train a Retrieval-Augmented Generation (RAG) based AI on publicly available documents. The trained AI will be integrated into a front-facing application, allowing the public to easily access information from the Fusion Safety Archives. This project aims to preserve valuable historical data, improve accessibility, and promote transparency in fusion safety research.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

3D Play Fairway Analysis for Examining of Superhot Drilling Production Scenarios: Preprint

The DEEPEN (DE-risking Exploration for geothermal Plays in magmatic ENvironments) project was a multi-laboratory, international effort to reduce uncertainty and improve resource characterization in superhot geothermal systems. Building on this foundation, this work advances open-source tools designed to lower the exploration risk and cost of superhot geothermal projects while promoting transparency, reproducibility, and efficiency in exploration workflows. These tools are being tested at two key sites: (1) the Nesjavellir Geothermal Area in Iceland, where the Icelandic Deep Drilling Project (IDDP) will drill its third well, and (2) Newberry Volcano in Oregon, USA, where Mazama Energy will pilot the first superhot enhanced geothermal system (EGS). A major outcome is the creation of a modular, open-source Python framework for play fairway analysis (PFA) in 2D and 3D, called geoPFA. The PFA workflow has been expanded to produce pseudo conceptual models, and will soon be refined to assess reservoir components through integration with the thermo-hydraulic-mechanical-chemical (THMC) simulator TReactMech, to enable iterative coupling between PFA and THMC models, improving characterization of superhot systems. All three of the Icelandic Deep Drilling Project's production scenarios were analyzed via this framework: (1) a superhot deep injection well paired with conventional production wells at Nesjavellir, (2) a superhot deep production well at Nesjavellir, and (3) superhot enhanced geothermal system at Newberry Volcano. This analysis provides useful insights around conceptual modeling of these production scenarios, helping to inform decisions around which scenario is best suited for which types of environments.

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

Affine Transformations to Enable Machine Learning for Semi-Quantitative EDS Analysis

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Affine Transformations to Correlate Experimental and Simulated EDS Spectra for Multi-Element Systems

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Validation of OpenPronghorn for Periodic Hill Flow Separation

OpenPronghorn is an open-source, MOOSE-based thermal-hydraulics simulation tool used for advanced reactor analysis. As an open-source code, it offers a transparent framework for validating governing equations, assumptions, and numerical methods against established benchmarks. This study evaluates OpenPronghorn's RANS turbulence model against the ERCOFTAC Case 81 periodic hill benchmark, a standard test case for separated turbulent flow featuring curved-wall separation, recirculation, shear-layer development, and reattachment. Streamwise velocity profiles predicted by OpenPronghorn were compared to reference LES data at multiple x/h locations. Results show that OpenPronghorn captures the overall trend of the velocity profiles, but the largest discrepancies occur in the separated-flow region, where turbulence is highly anisotropic and strongly affected by adverse pressure gradients and wall curvature—conditions that are inherently difficult for standard RANS models to resolve. Future work will test alternative k-e model variants and correction terms to improve prediction accuracy in this region.

42 - ENGINEERING↗

DOE OSTI2026

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗

DOE OSTI2021

Device Performance of Emerging Photovoltaic Materials (Version 2)

Following the 1st release of the "Emerging photovoltaic (PV) reports", the best achievements in the performance of emerging photovoltaic devices in diverse emerging photovoltaic research subjects are summarized, as reported in peer-reviewed articles in academic journals since August 2020. Updated graphs, tables, and analyses are provided with several performance parameters, e.g., power conversion efficiency, open-circuit voltage, short-circuit current density, fill factor, light utilization efficiency, and stability test energy yield. These parameters are presented as a function of the photovoltaic bandgap energy and the average visible transmittance for each technology and application and are put into perspective using, e.g., the detailed balance efficiency limit. The 2nd installment of the "Emerging PV reports" extends the scope toward tandem solar cells and presents the current state-of-the-art in tandem solar cell performance for various material combinations.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Device Performance of Emerging Photovoltaic Materials (Version 3)

Abstract Following the 2nd release of the “Emerging PV reports,” the best achievements in the performance of emerging photovoltaic devices in diverse emerging photovoltaic research subjects are summarized, as reported in peer‐reviewed articles in academic journals since August 2021. Updated graphs, tables, and analyses are provided with several performance parameters, e.g., power conversion efficiency, open‐circuit voltage, short‐circuit current density, fill factor, light utilization efficiency, and stability test energy yield. These parameters are presented as a function of the photovoltaic bandgap energy and the average visible transmittance for each technology and application, and are put into perspective using, e.g., the detailed balance efficiency limit. The 3rd installment of the “Emerging PV reports” extends the scope toward triple junction solar cells.

14 SOLAR ENERGY↗

DOE OSTI2020

Intercalation-Induced Reversible Electrochromic Behavior of Two-Dimensional Ti 3 C 2 T x MXene in Organic Electrolytes

MXenes, a large family of two-dimensional materials, have attracted tremendous attention due to their unique physical and chemical properties. Reversible ion intercalation between MXene layers allows modification of the optical, thermal, magnetic, and chemical properties. The electrochemical charge/discharge of MXenes in aqueous electrolytes was reported to lead to reversible electrochromic behavior. In this work, the electrochromic effect of semitransparent Ti 3 C 2 T x MXene film was probed by electrochemical intercalation of Li ions. Correspondingly, a peak shift of 100 nm was observed in the UV-vis spectrum. By combining in-situ Raman spectroscopy, in-situ X-ray diffraction, and density functional theory calculations, we show that the electrochromic shift is primarily due to the formation of robust O-Li bonds and the emerging bands induced changes of inter-band excitations. Finally, understanding the mechanism of electrochromic behavior in Ti 3 C 2 T x lays the foundations of designating 2D materials with durable, controllable, and efficient intercalation-induced electrochromic behaviors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Elucidating the Role of Hydrogen at c‐In 2 O 3 /a‐In 2 O 3− x Interface

Ab initio molecular dynamics simulations and hybrid functional electronic structure calculations are employed to determine the formation, the structural and electronic properties, and the dynamics of covalent (In—OH) and ionic (In—H—In) hydrogen defects at crystalline-In 2 O 3 /amorphous-In 2 O 3−x interface. This comprehensive computational study considers (i) various interstitial and substitutional hydrogen site locations within the crystalline, amorphous, and interfacial regions; (ii) several oxygen-to-hydrogen ratios; and (iii) possible defect charged states. The results reveal hydrogen's inability to fully passivate the undercoordinated under-shared in atoms in amorphous highly substoichiometric oxide, giving rise to the formation of deep electron traps even in net-charge neutral structures. These trap defects are found to be sensitive to photoexcitation, in contrast to In—OH with H's electronic states located below the valence band and to In—H—In, where H is found to maintain its charge state upon illumination. Nevertheless, H plays a critical role in photoinduced conductivity and its relaxation by promoting In—O coordination transformations at the interfacial region, including deterioration of the crystalline layer. Finally, the results help identify mobile H species and metastable H defect complexes (such as In—H—H—In, In—OH–H—In, and In—OH–O—In) that are responsible for long relaxation times of the conductivity decay.

H defects↗

DOE OSTI2022

Low‐Loss Tunable Infrared Plasmons in the High‐Mobility Perovskite (Ba,La)SnO 3

Abstract BaSnO 3 exhibits the highest carrier mobility among perovskite oxides, making it ideal for oxide electronics. Collective charge carrier oscillations known as plasmons are expected to arise in this material, thus providing a tool to control the nanoscale optical field for optoelectronics applications. Here, the existence of relatively long‐lived plasmons supported by high‐mobility charge carriers in La‐doped BaSnO 3 (BLSO) is demonstrated. By exploiting the high spatial and energy resolution of electron energy‐loss spectroscopy with a focused beam in a scanning transmission electron microscope, the dispersion, confinement ratio, and damping of infrared localized surface plasmons (LSPs) in BLSO nanoparticles are systematically investigated. It is found that LSPs in BLSO exhibit a high degree of spatial confinement compared to those sustained by noble metals and have relatively low losses and high quality factors with respect to other doped oxides. Further analysis clarifies the relation between plasmon damping and carrier mobility in BLSO. The results support the use of nanostructured degenerate semiconductors for plasmonic applications in the infrared region and establish a solid alternative to more traditional plasmonic materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Enhancing the dark-state bistability and thermal stability of zinc dynamic windows with nitrile electrolytes

Reversible metal electrodeposition (RME) for dynamic windows is a promising alternative to traditional electrochromics. We explore the reasons behind the bistability of practical RME dynamic windows under a wide temperature range, i.e., how well they maintain their dark state without external power. While Zn dynamic windows with dimethyl sulfoxide electrolytes exhibit adequate bistability at room temperature, their performance degrades at elevated temperatures due to the presence of small amounts of water. Here, to overcome this problem, we developed a set of Zn nitrile electrolytes. The integrated devices can maintain dark-state bistability over at least 1 month at 85°C with 0.1% transmission using a propionitrile (PrCN) electrolyte. Additionally, the PrCN-based Zn dynamic windows possess high optical contrast, color-neutral switching, and promising cyclability, making Zn RME in nitrile electrolytes a promising solution for achieving robust dynamic windows.

RME↗

DOE OSTI2022

Carrier Mobility Modulation in Cu 2 Se Composites Using Coherent Cu 4 TiSe 4 Inclusions Leads to Enhanced Thermoelectric Performance

Carrier transport engineering in bulk semiconductors using inclusion phases often results in the deterioration of carrier mobility (μ) owing to enhanced carrier scattering at phase boundaries. Here, we show by leveraging the temperature-induced structural transition between the α-Cu 2 Se and β-Cu 2 Se polymorphs that the incorporation of Cu 4 TiSe 4 inclusions within the Cu 2 Se matrix results in a gradual large drop in the carrier mobility at temperatures below 400 K (α-Cu 2 Se), whereas the carrier mobility remains unchanged at higher temperatures, where the β-Cu 2 Se polymorph dominates. The sharp discrepancy in the electronic transport within the α-Cu 2 Se and β-Cu 2 Se matrices is associated with the formation of incoherent α-Cu 2 Se/Cu 4 TiSe 4 interfaces, owing to the difference in their atomic structures and lattice parameters, which results in enhanced carrier scattering. In contrast, the similarity of the Se sublattices between β-Cu 2 Se and Cu 4 TiSe 4 gives rise to coherent phase boundaries and good band alignment, which promote carrier transport across the interfaces. Interestingly, the different cation arrangements in Cu 4 TiSe 4 and β-Cu 2 Se contribute to enhanced phonon scattering at the interfaces, which leads to a reduction in the lattice thermal conductivity. The large reduction in the total thermal conductivity while preserving the high power factor of β-Cu 2 Se in the (1–x)Cu 2 Se/(x)Cu 4 TiSe 4 composites results in an improved ZT of 1.2 at 850 K, with an average ZT of 0.84 (500–850 K) for the composite with x = 0.01. Furthermore, this work highlights the importance of structural similarity between the matrix and inclusions when designing thermoelectric materials with improved energy conversion efficiency.

36 MATERIALS SCIENCE↗