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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Defining Electrode-Level Metrics for Enabling Earth-Abundant, Mn-Rich Cathodes: A Technoeconomic Analysis of Experimental Materials

Manganese-rich oxides are attractive options as next-generation, earth-abundant cathodes and significant efforts are being directed toward commercial implementation. We report here an updated techno-economic analysis of the lithium- and manganese-rich (LMR) class of earth-abundant cathodes for electric vehicle applications. BatPaC modeling was used to define the cell-level metrics that must be met for these materials to be cost and energy competitive with the current commercial earth-abundant benchmark, LiFePO 4 , as well as anticipated variations such as LiMn 0.8 Fe 0.2 PO 4 . The model was used to evaluate a high-performance material from the literature and subsequently define R&D targets as the likely limits of practical performance for similar LMR systems. Experimental validation and BatPaC evaluation of an advanced, cobalt-free LMR cell system was also conducted. Results show that the advanced LMR cells come within ∼5% of the defined limits and exceed the energy of LiFe(Mn)PO 4 cells at a similar cost. Excellent cycle-life, low impedance, and low impedance rise were also achieved under the conditions tested and reveal that cobalt is not necessary to achieve high-performance LMR oxides. Although the analysis conducted herein reports on LMR cell systems, the methodology and target values defined for performance metrics easily extend to the evaluation of other systems under consideration as earth-abundant options.

Chen, Jiajun [Argonne National Laboratory (ANL), A↗
DOE OSTI2024

Multivariate Time Series Intermittent Fault Detectionin Controller Area Network CAN

Fault detection in Controller Area Network (CAN) systems is crucial for ensuring the reliability and safety of automotive and industrial applications. This study investigates and compares the effectiveness of time series classification models for supervised fault detection in CAN data. This repository contains the code and data for our benchmarking experiment aimed at detecting intermittent faults in automotive Controller Area Network (CAN) data. The goal of this project is to compare various machine learning (ML) and deep learning (DL) models using different Time Series Cross-Validation (TSCV) techniques to evaluate their effectiveness in a streaming environment for fault detection.

Hespeler, Steven [Oak Ridge National Laboratory (O↗
DOE OSTI2025

Multiphysics Modeling of Microreactors with NEAMS codes, and Validation Based on KRUSTY Reactivity Insertion

The NEAMS Multiphysics Applications team continues to assess code usability and functionality for microreactor design and safety analyses, while demonstrating that NEAMS tools capture both steady-state and transient behavior across distinct microreactor concepts. In FY2025, the team advanced full-core, high-fidelity, multiphysics models that solve more complex problems and strengthen verification/validation for several microreactor systems: heat-pipe microreactor (HPMR), gas-cooled microreactor (GCMR), and the KRUSTY experiment. These models employ the MOOSE MultiApp/Transfers architecture with Griffin for neutronics, BISON for heat conduction/thermomechanics, Sockeye for heat pipes, SAM/THM for coolant channels and loops, and SWIFT for hydride behavior, with meshes generated via the MOOSE Reactor Module. The graphite models available in the Grizzly code were also investigated for future analyses. For the HPMR, a Na-HPMR variant was constructed to align with recently validated heat-pipe experiments and Sockeye’s LCVF capability, enabling mechanistic heat-pipe transients and startup modeling. The Na-HPMR will serve as the primary model for HPMR investigations in upcoming tasks. The load-following and single heat-pipe failure scenarios (Griffin/BISON/Sockeye), which were previously modeled for the K-HPMR, were replicated for the Na-HPMR, showing strong negative temperature feedback and highly localized thermal effects, respectively, while the startup case captured vapor-front progression and heat-removal activation. Solid mechanics was added to the previously built K-HPMR full-core model in BISON, showing minimal impact on steady-state reactivity yet enabling stress-field predictions that prepare the path for full-core TRISO performance analyses. For the GCMR, automated steady-state and four transient scenarios were executed using Griffin/BISON/SAM/SWIFT. Results confirm robust inherent safety: power collapses promptly in loss-of-cooling events, the inlet-temperature drop settles to a new equilibrium, and a single-channel blockage yields only a ~30 K local fuel-temperature rise with <0.4% power decrease. SWIFT-predicted hydrogen redistribution affects reactivity during both steady-state and transient conditions, underscoring its importance. A Brayton-cycle balance of plant (BOP) model in SAM/THM demonstrated stable startup behavior, and xenon-driven reactivity during load following was analyzed. To improve TRISO-compact temperature fidelity, a fast multiscale Heat Source Decomposition (HSD) treatment was implemented. Against heterogeneous benchmarks, HSD reduces underprediction of kernel temperatures and lowers predicted peak powers in reactivity-insertion transients compared to previous homogenized models. KRUSTY warm-critical validation progressed from FY2024 baselines: the 15Ȼ insertion shows excellent agreement in peak power (~2% high) and temperature trends, and the 30Ȼ case was automated via a feedback controller that maintained power near 3 kW for ~150 s with close agreement to data. The successful modeling of the warm critical tests has laid a strong foundation for simulating more complex nuclear system tests in the years ahead. Throughout FY2025, developer feedback was provided (e.g., MOOSE batch mesh generation, distributed pre-split meshes, Griffin sweeper on displaced meshes), several new models were contributed to the Virtual Test Bed, and an OECD-NEA WPRS multiphysics benchmark based on the HPMR was initiated to enable broader cross-comparison and best-practice development with the nuclear community at large.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Modeling of standing wave RF cavities for tracking through multi-pass energy recovery linac

Short bunches, high current and multiple linac pass are all characteristics of Energy Recovery Linacs (ERLs), which may result in collective effects. They in turn, may affect the beam, degrading its quality, or even yield to instabilities causing a beam loss. To study and mitigate these effects one needs a numerical simulation code, that can take into account both the collective effects, as well as, particular ERL features, such as a multi-turn design that does not reach a steady state or the multiple passages of the beam through Radio-Frequency (RF) cavities at different energies. CODAL [1], a code developed by SOLEIL in collaboration with IJCLab, enables such studies. It is a 6 dimensional (6D) tracking code applying 'kicks' based on the integration of the local Hamiltonian for each element of the lattice. It is also capable of simulating space charge, wakefields and coherent synchrotron radiation. However, to correctly take into account the ERL dynamics, an upgrade had to be made to include the effect of a standing wave RF cavity in 6D. In this paper, we will concentrate on the implementation and benchmarking (with DESY’s tracking code ASTRA [2]) of both the longitudinal and the transverse models (by J.B. Rosenzweig and L. Serafini [3]), which we use to carry out tracking of fully analytical 6D RF cavity.

Bogacz, A.↗
DOE OSTI2023

Status of HEU-Pb in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

The Department of Energy invests tens of millions of dollars each year to develop the next generation of nuclear engineering modeling & simulation (M&S) tools. These tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers become more powerful, we are able to enhance resolution in our calculations. This improved resolution is taking us to a point where the limitations of simulation capability are in the quality of data, including our ability to quantify the uncertainty and sensitivity of the data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. Thus, M&S tools need evaluated and quality-assured experimental data for validation purposes. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles and evaluates experiment data in a handbook that can be used by criticality safety engineers and others to validate computer codes and cross-section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. Figure 1 organizes all the benchmark evaluations that have been performed by the isotope of interest, in this case Pb, and the average neutron energy the system. Compared to other isotopes of interest for nuclear applications, there are few benchmark evaluations for Pb systems. The lack of integral measurements to determine errors in Pb cross-section data has caused the latest nuclear cross-section libraries to over/underestimate k eff compared to experimental results. Therefore, this evaluation fills an important knowledge gap in benchmark evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

CACTUS: Chemistry Agent Connecting Tool Usage to Science

Large language models (LLMs) have shown remarkable potential in various domains but often lack the ability to access and reason over domain-specific knowledge and tools. In this article, we introduce Chemistry Agent Connecting Tool-Usage to Science (CACTUS), an LLM-based agent that integrates existing cheminformatics tools to enable accurate and advanced reasoning and problem-solving in chemistry and molecular discovery. We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama3-8b, and Mistral-7b, on a benchmark of thousands of chemistry questions. Our results demonstrate that CACTUS significantly outperforms baseline LLMs, with the Gemma-7b, Mistral-7b, and Llama3-8b models achieving the highest accuracy regardless of the prompting strategy used. Moreover, we explore the impact of domain-specific prompting and hardware configurations on model performance, highlighting the importance of prompt engineering and the potential for deploying smaller models on consumer-grade hardware without a significant loss in accuracy. By combining the cognitive capabilities of open-source LLMs with widely used domain-specific tools provided by RDKit, CACTUS can assist researchers in tasks such as molecular property prediction, similarity searching, and drug-likeness assessment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Ground state wave functions for single-band Hubbard models from the Gutzwiller conjugate gradient minimisation theory

The Gutzwiller conjugate gradient minimisation (GCGM) theory is an ab initio quantum many-body theory for computing the ground-state properties of infinite systems. Previous applications of GCGM provides satisfying accuracy of ground-state energy of Hubbard models. In the current work, we address the problem of whether the obtained wave function is a good approximation for the true ground state by comparing the correlation functions with the benchmark data. Additionally, our results confirms the accuracy of the reproduced ground state of the regular Hubbard model, but with some exception for the frustrated Hubbard model.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Water vapor oxidation behaviors of nuclear graphite IG-110 for a postulated accident scenario in high temperature gas-cooled reactors

Water leakage in accidental conditions of high temperature gas-cooled reactors is one of the most critical problems that can compromise the integrity of different nuclear components. In this study, oxidation behaviors of nuclear graphite IG-110 in water ingress accidental conditions were investigated. Mass loss and oxidation rates were evaluated after oxidation tests at temperatures up to 1400 °C in an Ar-20 vol% H 2 O mixed atmosphere. The activation energy decreased from 318.6 to 148.9 kJ/mol with temperature, indicating two different oxidation regimes. The cross-sections of the oxidized samples were systematically characterized. The corresponding logarithmic porosity profiles showed a temperature dependency. Pore formation moved toward near-surface regions with increasing temperature and preferential binder oxidation, with filler particle degradation. Furthermore, oxidant concentration profiles and oxidation depths were estimated using a theoretical model and compared with the experimental results. This work provides important benchmark data and safety analysis guidance for the accident scenario in high temperature gas-cooled reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A unified finite strain gradient-enhanced micropolar continuum approach for modeling quasi-brittle failure of cohesive-frictional materials

Here, in this work, a novel framework for modeling quasi-brittle crack propagation and shear band dominated failure of cohesive-frictional materials like concrete, mortar, rock, tough ceramics, energetic materials, but also granular materials like sands or powders in terms of a unified continuum approach is proposed. It is based on a combination of the gradient-enhanced continuum with gradients of internal variables for representing quasi-brittle cracking, and the micropolar continuum, accounting for the deformation of the microstructure. For developing the gradient-enhanced micropolar framework, the set of balance equations and the kinematic relations are derived, and the constitutive relations are established in a general manner. The framework is formulated in a geometrically exact setting, based on the thermodynamically sound theory of hyperelasto-plasticity, and the numerical implementation by means of the finite element method is discussed. For assessing the approach, realizations of this new approach in terms of constitutive models for particular materials are developed. They are applied to numerical benchmark examples, investigating various loading conditions, and the obtained results are validated by means of a comparison with experiments from the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Trajectory prediction dimensionality reduction for low-cost connected automated vehicle systems

Here, to facilitate low-cost connected automated vehicle (CAV) system development, this study proposes two interpretable dimensionality reduction techniques in vehicle trajectory prediction, i.e., the piecewise Taylor series approximation (PTA) and the piecewise Fourier series approximation (PFA), to lower computation complexity, reduce device investment, and decrease computation energy consumption. Two benchmarks are developed, the long short-term memory (LSTM)-based model without dimensionality reduction and the LSTM-based model with encoder-decoder (a widely used dimensionality reduction technique). Results show that the four predictions have similar accuracy, and the training time (proportional to computation energy consumption) of models with dimensionality reduction techniques is greatly reduced. The reduction is even more significant when PTA/PFA is used. Sensitivity analysis advises PFA/PTA parameter selections to reduce computation complexity without significant loss of prediction accuracy. Further, the robustness of the LSTM PTA/PFA is proven by the investigation of data noises.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

CHQ- SocioEmo: Identifying Social and Emotional Support Needs in Consumer-Health Questions

General public, often called consumers, are increasingly seeking health information online. To be satisfactory, answers to health-related questions often have to go beyond informational needs. Automated approaches to consumer health question answering should be able to recognize the need for social and emotional support. Recently, large scale datasets have addressed the issue of medical question answering and highlighted the challenges associated with question classification from the standpoint of informational needs. However, there is a lack of annotated datasets for the non-informational needs. We introduce a new dataset for non-informational support needs, called CHQ-SocioEmo. The Dataset of Consumer Health Questions was collected from a community question answering forum and annotated with basic emotions and social support needs. This is the first publicly available resource for understanding non-informational support needs in consumer health-related questions online. We benchmark the corpus against multiple state-of-the-art classification models to demonstrate the dataset’s effectiveness.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Fermionic mean-field dynamics for spin systems beyond free fermions

We introduce the fermionized time-dependent Hartree–Fock (fTDHF), a real-time quantum dynamics method for spin-1/2 Hamiltonians following their mapping to fermions via the Jordan-Wigner transformation. fTDHF is formally equivalent to exact dynamics in the case of free fermions, and can efficiently handle non-local string operators arising from long-range interactions via transition matrix elements between non-orthogonal Slater determinants. We show that the fTDHF method can be implemented on a classical computer with a cost that scales polynomially with system size, and linearly with the time steps. We benchmark fTDHF against exact dynamics on three separate spin-1/2 models, representing adiabatic preparation of states with long-range correlations, disorder-driven observation of many-body localization, and particle production in the Schwinger model. For each of these systems, fTDHF is shown to reproduce the qualitative dynamics generated by the exact evolutions, while maintaining a simple physical picture due to its mean-field nature.

Dutta, Rishab↗
DOE OSTI2025

Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data

The accurate calculation of phonons and vibrational spectra remains a significant challenge, requiring highly precise evaluations of interatomic forces. Traditional methods based on the quantum description of the electronic structure, while widely used, are computationally expensive and demand substantial expertise. Emerging universal machine learning interatomic potentials (uMLIPs) offer a transformative alternative by employing pre-trained neural network surrogates to predict interatomic forces directly from atomic coordinates. This approach dramatically reduces computation time and minimizes the need for technical knowledge. In this paper, we produce a phonon database comprising nearly 5000 inorganic crystals to benchmark the performance of several leading uMLIPs. We further assess these models in real-world applications by using them to analyze experimental inelastic neutron scattering data collected on a variety of materials. Through detailed comparisons, we identify the strengths and limitations of these uMLIPs, providing insights into their accuracy and suitability for fast calculations of phonons and related properties, as well as the potential for real-time interpretation of neutron scattering spectra. Our findings highlight how the rapid advancement of AI in science is revolutionizing experimental research and data analysis.

inelastic neutron scattering↗
DOE OSTI2020

Two-particle correlation functions in cluster perturbation theory: Hubbard spin susceptibilities

Cluster perturbation theory (CPT) is a computationally economic method commonly used to estimate the momentum- and energy-resolved single-particle Green's function. It has been used extensively in direct comparisons with experiments that effectively measure the single-particle Green's function, e.g., angle-resolved photoemission spectroscopy. However, many experimental observables are given by two-particle correlation functions. CPT can be extended to compute two-particle correlation functions by approximately solving the Bethe-Salpeter equation. We implement this method and focus on the transverse spin susceptibility, measurable via inelastic neutron scattering or with optical probes of atomic gases in optical lattices. Finally, we benchmark the method with the one-dimensional Fermi-Hubbard model by comparing with known results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Adaptive variational quantum dynamics simulations with compressed circuits and fewer measurements

The adaptive variational quantum dynamics simulation (AVQDS) method performs real-time evolution of quantum states using automatically generated parametrized quantum circuits that often contain substantially fewer gates than Trotter circuits. Here we report an improved version of the method, which we call AVQDS(T), by porting the tiling efficient trial circuits with rotations implemented simultaneously technique. The algorithm adaptively adds layers of disjoint unitary gates to the ansatz circuit so as to keep the McLachlan distance, a measure of the accuracy of the variational dynamics, below a fixed threshold. Here we perform benchmark noiseless AVQDS(T) simulations of quench dynamics in local spin models and compare with an alternative adaptive variational approach on quantum resource requirement. Quantum dynamical simulations implementing realistic noise channels are also reported. Finally, we propose a way to substantially alleviate the measurement overhead of AVQDS(T) while maintaining high accuracy by synergistically integrating quantum circuit calculations on quantum processing units with classical calculations using, e.g., tensor networks to evaluate the quantum geometric tensor. We showcase that this approach enables AVQDS(T) to deliver more accurate results than simulations using a fixed ansatz of comparable final depth for a significant time duration with fewer quantum resources.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Benchmark neutrinoless double- β decay matrix elements in a light nucleus

We compute nuclear matrix elements of neutrinoless double-β decay mediated by light Majorana-neutrino exchange in the $\textit{A}$ = 6 system. The goal for this work is to benchmark two many-body approaches, the no-core shell model and the multireference in-medium similarity renormalization group (SRG). We use a SRG-evolved next-to-next-to-next-to-leading chiral order two-body potential for the nuclear interaction, and make the approximation that the isospin is conserved. We compare the results of the two approaches as a function of the cutoff on the many-body basis space. Although differences are seen in the predicted nuclear radii, the ground-state energies and neutrinoless double-β decay matrix elements produced by the two approaches show significant agreement. We discuss the implications for calculations in heavier nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Toward a unified description of hadron scattering at all energies

The construction of general amplitudes satisfying symmetries and S -matrix constraints has been the primary tool in studying the spectrum of hadrons for over half a century. In this work, we present a new parametrization, which can fulfill many expectations of S -matrix and Regge theory and connects the essential physics of hadron scattering in the resonance region and in asymptotic limits. In this construction, dynamical information is entirely contained in Regge trajectories that generalize resonance poles in the complex energy plane to moving poles in the angular momentum plane. We highlight the salient features of the model, compare with existing literature on dispersive and dual amplitudes, and benchmark the formalism with an initial numerical application to the ρ and σ / f 0 ( 500 ) mesons in π π scattering. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Salt International Collaborations FY2021 Update

This report summarizes the international collaboration work conducted by Sandia and funded by the US Department of Energy Office (DOE) of Nuclear Energy Spent Fuel and Waste Science & Technology (SFWST) as part of the Sandia National Laboratories Salt R&D and Salt International work packages. This report satisfies the level-three milestone M3SF-20SN010303062. Several stand-alone sections make up this summary report, each completed by the participants. The sections discuss international collaborations on geomechanical benchmarking exercises (WEIMOS), granular salt reconsolidation (KOMPASS), engineered barriers (RANGERS), and model comparison (DECOVALEX). Lastly, the report summarizes a newly developed working group on the development of scenarios as part of the performance assessment development process, and the activities related to the Nuclear Energy Agency (NEA) Salt club and the US/German Workshop on Repository Research, Design and Operations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗