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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer

Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.

Clifford↗
DOE OSTI2025

Bimodal Visualization of Industrial X-Ray and Neutron Computed Tomography Data

Advanced manufacturing creates increasingly complex objects with material compositions that are often difficult to characterize by a single modality. Our collaborating domain scientists are going beyond traditional methods by employing both X-ray and neutron computed tomography to obtain complementary representations expected to better resolve material boundaries. However, the use of two modalities creates its own challenges for visualization, requiring either complex adjustments of bimodal transfer functions or the need for multiple views. Together with experts in nondestructive evaluation, we designed a novel interactive bimodal visualization approach to create a combined view of the co-registered X-ray and neutron acquisitions of industrial objects. Using an automatic topological segmentation of the bivariate histogram of X-ray and neutron values as a starting point, the system provides a simple yet effective interface to easily create, explore, and adjust a bimodal visualization. Here, we propose a widget with simple brushing interactions that enables the user to quickly correct the segmented histogram results. Our semiautomated system enables domain experts to intuitively explore large bimodal datasets without the need for either advanced segmentation algorithms or knowledge of visualization techniques. We demonstrate our approach using synthetic examples, industrial phantom objects created to stress bimodal scanning techniques, and real-world objects, and we discuss expert feedback.

image segmentation↗
DOE OSTI2024

PaRSEC: Scalability, flexibility, and hybrid architecture support for task-based applications in ECP

This paper highlights the most significant enhancements made to PaRSEC, a scalable task-based runtime system designed for hybrid machines, during the Exascale Computing Project (ECP). The enhancements focus on expanding the capabilities of PaRSEC to address the evolving landscape of parallel computing. Notable achievements include the integration of support for three major types of accelerators (NVIDIA, AMD, and Intel GPUs), the refinement and increased flexibility of the communication subsystem, and the introduction of new programming interfaces tailored for irregular applications. Additionally, the project resulted in the development of powerful debugging and performance analysis tools aimed at assisting users in understanding and optimizing their applications. We present a comprehensive demonstration of these advancements through a series of benchmarks and applications within ECP and beyond, thereby showcasing the enhanced capabilities of PaRSEC across the diverse architectures within the ECP, providing valuable insights into the runtime system’s adaptability and performance across varied computing environments.

Bouteiller, Aurelien↗
DOE OSTI2025

Parallel Programming in MCNP6

Monte Carlo N-Particle (MCNP)1 is a general-purpose Monte Carlo particle transport code developed by Los Alamos National Laboratory (LANL). To efficiently handle long simulations, MCNP version 6 (MCNP6) supports parallel execution using two primary programming models: • Shared-memory task-based threading using OpenMP (Open Multi-Processing), and • Distributed-memory calculations using MPI (Message Passing Interface). The OpenMP and MPI programming models enable MCNP6 to scale from desktop systems to high-performance computing (HPC) clusters, allowing users to run MCNP in one of three parallel modes: • OpenMP-only, • MPI-only, and • Hybrid (MPI + OpenMP). The choice of parallelization mode depends on the underlying computer architecture and the characteristics of the simulation problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

ReVise: A Human-AI Interface for Incremental Algorithmic Recourse

The recent adoption of artificial intelligence in socio-technical systems raises concerns about the black-box nature of the resulting decisions in fields such as hiring, finance, admissions, etc. If data subjects—such as job applicants, loan applicants, and students—receive an unfavorable outcome, they may be interested in algorithmic recourse, which involves updating certain features to yield a more favorable result when re-evaluated by algorithmic decision-making. Unfortunately, when individuals do not fully understand the incremental steps needed to change their circumstances, they risk following misguided paths that can lead to significant, long-term adverse consequences. Existing recourse approaches focus exclusively on the final recourse goal but neglect the possible incremental steps to reach the goal with real-life constraints, user preferences, and model artifacts. To address this gap, we formulate a visual analytic workflow for incremental recourse planning in collaboration with AI/ML experts and contribute an interactive visualization interface that helps data subjects efficiently navigate the recourse alternatives and make an informed decision. We also present one of the many usage scenarios, developed during exploratory feedback sessions with twelve graduate students using a real-world dataset, which demonstrates that our approach can be instrumental for data subjects in choosing a suitable recourse path.

algorithmic recourse↗
DOE OSTI2025

eDNAjoint: An R package for interpreting paired or semi‐paired environmental DNA and traditional survey data in a Bayesian framework

Abstract Environmental DNA (eDNA) sampling is increasingly used in surveys of species distribution as a potentially sensitive and efficient monitoring method. Yet access to modelling tools designed specifically for interpreting this new data type lags behind its ubiquity. While occupancy modelling software has dominated the analytical landscape for eDNA data analysis of single species, this type of model may not always be the most appropriate. The rate of eDNA detection often corresponds to species density, rather than just occupancy, and researchers often have access to observations from non‐genetic sampling methods at the same sites. To provide users access to a modelling framework designed to maximize the use of all available data, we developed an R package, eDNAjoint . The package provides an easy‐to‐use interface for fitting a ‘joint’ model that integrates data from paired or semi‐paired eDNA and traditional surveys in a Bayesian framework. The model can be used to estimate parameters like the probability of a false positive eDNA detection and mean catch rate at a site, and the package allows access to multiple model variations and Bayesian prior customization. Additional functionality can be used for model selection, summarising posteriors and comparing the relative sensitivities of the two survey methods. We demonstrate the use of eDNAjoint by fitting a variation of the model with site‐level covariates that scale the sensitivity of eDNA sampling relative to traditional sampling. The example workflow uses binary eDNA and seine count data for the endangered tidewater goby ( Eucyclogobius newberryi ) from a study by Schmelzle and Kinziger (2016). This use case includes a prior sensitivity analysis and an evaluation of the relationship between detection rates and environmental variables. eDNAjoint has the potential to greatly increase the range of users who will be able to rigorously analyse eDNA and traditional survey data in a Bayesian framework, understand if and how eDNA can improve monitoring practices, and gain confidence in the interpretability of eDNA data.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2025

Chemist: A Domain-Specific Language by Chemists for Chemists

Managing the complexity of quantum chemistry (QC) software is key to ensuring it remains accessible, maintainable, and reusable. Noticeably missing from the QC ecosystem are modules targeting bottleneck routines. Here we argue that this is likely due to the difficulty in defining interfaces for such modules. To that end, we introduce the open-source, publicly available Chemist library https://github.com/NWChemEx/Chemist. Chemist is a domain-specific language targeting the QC domain. Chemist has been developed focusing on performance and user-friendliness. Using Chemist, QC tasks are defined using familiar domain concepts such as molecules, wave functions, and operators. The domain objects are hierarchical to ensure a systematic encapsulation of information. Key features of Chemist include: extensibility, the ability to alias existing data, and the ability to succinctly define many common QC tasks. The usefulness of Chemist is demonstrated by discussing the interface of NWChemEx’s Fock build module and by showcasing a proof-of-concept self-consistent field algorithm containing uncertainty propagation.

Algorithms↗
DOE OSTI2024

Deciphering Discrepancies: A Comparative Analysis of Docker Image Security

As the use of microservices continues to grow and become a foundational approach to architecting software solutions, ensuring the security of microservices is paramount. Docker images have emerged as the predominant solution to containerize microservices–and thus, Docker images are becoming a large attack surface. Thus, reducing vulnerabilities in Docker images will reduce microservice cyberattacks. A common way to find vulnerabilities in Docker images employs static analysis tools like Trivy and Grype. However, these tools frequently generate disparate vulnerability reports when analyzing the same Docker image, thus causing uncertainty in tool selection. We collected 927 Docker images, analyzed them with Trivy and Grype, and compared the vulnerabilities reported in each image. Among the 865 images found to have vulnerabilities, Trivy and Grype disagreed on both the number of vulnerabilities and the vulnerability IDs found therein. Since both tools interface with external vulnerability databases, some discrepancies can be attributed to how the tools interface with these external resources. The external vulnerability databases partially overlap and frequently contradict one another, thereby creating challenges for static analysis tool developers and end users alike. This New Ideas and Emerging Results (NIER) study contains new and critical information that practitioners need for selecting and using static analysis tools–given that increases in the use of Docker technologies means increases in the size of the attack surfaces.

Boles, Brittany [Montana State University]↗
DOE OSTI2025

DOE Repository Metadata Profile (DRMP): A Metadata Framework for Advancing Interoperability and AI Readiness Across Scientific Repositories

The Department of Energy (DOE) funds a diverse and distributed ecosystem of repositories that steward scientific data, publications, and software across its research programs, user facilities, and national laboratories. While significant progress has been made in standardizing dataset-level metadata, the metadata describing repositories themselves (their identity, governance, access interfaces, policies, and technical capabilities) remains inconsistent and fragmented across DOE-funded systems. This variability limits discoverability, interoperability, automated validation, and AI-driven analysis, all of which are increasingly essential for modern scientific workflows. To address this gap, the DOE Data Curation Working Group (DCWG) developed the DOE Repository Metadata Profile (DRMP). The DRMP is a practical, community-driven framework that defines how repositories can describe themselves in a consistent, machine-actionable, and scalable manner. The DRMP is not a new metadata schema. Instead, it is a mapping profile and structured element set capturing the essential characteristics of DOE repositories. It harmonizes repository-level metadata across six widely adopted community schemas: RE3Data; DCAT-US v3; Schema.org; Dublin Core; DataCite 4.6; and PREMIS 3.0. This harmonization eliminates reinvention and enables interoperability within DOE and across the broader scientific ecosystem. A core objective of the DRMP is to reduce burden on repositories by allowing them to reuse their existing metadata through a Rosetta-style crosswalk rather than redesigning local implementations. The profile introduces a three-level conformance model that supports incremental adoption: • Level 1 – Minimum Viable Record (MVR): foundational identification elements required for workflows, project registration, and basic repository presence. • Level 2 – Interoperable: structured metadata enabling alignment with national and international discovery systems. • Level 3 – AI-Ready: enhanced provenance, policy transparency, fixity, semantic context, and capabilities that support automated reasoning, model training governance, and machine-assisted curation. To support implementation, the DRMP includes JSON Schema definitions, OpenAPI patterns, and MCP templates that allow repositories to publish machine-readable metadata directly within existing platforms. These resources are modular and lightweight, enabling adoption without major architectural change. Adopting the DRMP enables repositories to: • Enhance discoverability and interoperability by aligning identifiers, classifications, and descriptive elements across widely used schema standards. • Support federated discovery and cross-registration across DOE systems, Data.gov, and international catalogs. • Enable AI agents and workflow orchestration systems to interpret repository-level metadata within the American Science Cloud (AmSC) through Model Context Protocol (MCP)-based context publication. • Demonstrate alignment with DOE’s open science, stewardship, and FAIR data priorities. This guidance represents a community-driven step forward. Through voluntary adoption and continued feedback, the DRMP advances a cohesive, machine-actionable description of DOE repositories that supports FAIR data practices, preparing the infrastructure for AI-enabled research, and strengthening the discoverability and reuse of DOE’s scientific outputs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

What more can be done with XPS? Highly informative but underused approaches to XPS data collection and analysis

Because of the importance of surfaces and interfaces in many scientific and technological areas, the use of x-ray photoelectron spectroscopy (XPS) has been growing exponentially. Although XPS is being used to obtain useful information about the surface composition of samples, much more information about materials and their properties can be extracted from XPS data than commonly obtained. This paper describes some of the areas where alternative analysis methods or experimental design can obtain information about the near-surface region of a sample, often information not available in other ways. Experienced XPS analysts are familiar with many of these methods, but they may not be known to new or casual XPS users, and sometimes, they have not been used because of an inappropriately assumed complexity. The information available includes optical, electronic, and electrical properties; nanostructure; expanded chemical information; and enhanced analysis of biological materials and solid/liquid interfaces. Many of these analyses can be conducted on standard laboratory XPS systems, with either no or relatively minor system alterations. Topics discussed include (1) considerations beyond the “traditional” uniform surface layer composition calculation, (2) using the Auger parameter to determine a sample property, (3) use of the D parameter to identify sp 2 and sp 3 carbon information, (4) information from the XPS valence band, (5) using cryocooling to expand range of samples that can be analyzed and minimize damage, and (6) using electrical potential effects on XPS signals to extract chemically resolved electrical measurements including band alignment and electrical property information.

Baer, Donald R. [Pacific Northwest National Labora↗
DOE OSTI2026

Datashare

Datashare facilitates communication and data sharing within local networks in potentially dangerous situations such as an explosive ordnance disposal. During such events, there is a need to transmit information rapidly around the incident area. It is a distributed database that does not require an internet connection for operation. In addition, Datashare interfaces with XTK and other software applications, allowing for seamless integration and data management. Datashare supports video calls over the network, enabling real-time communication among users. This software serves to organize, package, and share between responders on location and export data to those off location. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Eldridge, Bryce [Sandia National Lab. (SNL-CA), Li↗
DOE OSTI2026

LeWRON: Agentic Analysis of Electroweak Phase Transitions

The electroweak phase transition (EWPT) is a central topic in particle physics and cosmology, connecting collider phenomenology, baryogenesis, and gravitational-wave observatories. Its analysis requires a technically demanding, convention-sensitive, and model-dependent pipeline, from constructing the finite-temperature effective potential to tracking thermal histories, computing bubble nucleation rates, and predicting gravitational-wave spectra. We present LeWRON (Learning ElectroWeak phase tRansitiON), an agentic framework that orchestrates this pipeline starting from an input Lagrangian. LeWRON combines audited toolbox construction with an Explorer module that uses the generated model-specific code for further analysis, including scans and plots. Intermediate analytic outputs are checked by auditor agents and stored as structured artifacts, enabling reproducible human inspection and downstream use through both a command-line interface and a public Python API. The framework supports a reproduction mode, which infers conventions from the literature and reproduces published results, and a discovery mode, which guides users through structured checkpoints for new models. We demonstrate LeWRON across representative beyond-the-Standard-Model scenarios and release the code on GitHub.

Wang, Isaac R. [Fermilab] (ORCID:000000030789218X)↗
DOE OSTI2025

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗
DOE OSTI2026

AQDrop Quantum Service (AQDrop) v1.0

AQDrop is a job management system designed to streamline access to the Advanced Quantum Testbed (AQT) at NERSC (National Energy Research Scientific Computing Center). It serves as a centralized middleware layer between researchers and quantum processing hardware. Key Features: AQDrop provides a FastAPI-based server backed by PostgreSQL for job submission, queue management, and role-based access control (members, operators, and administrators). Users submit Qiskit circuits via JSON payloads, which are queued, dispatched to the QPU through the Qubic API, and returned as measurement counts. A Python client library and web dashboard round out the interface options. Primary Use: Researchers submit quantum circuit jobs from a laptop or login node; an operator client executes those jobs on the AQT's physical QPU and returns results — all coordinated through the central API. Advantages: Compared to ad-hoc or direct hardware access, AQDrop adds structured queue management, auditable job-status tracking and OAuth2 authentication — reducing scheduling conflicts and unauthorized access. Its containerized deployment also improves reproducibility and scalability. Overall, AQDrop functions as a purpose-built quantum job broker tailored to NERSC's specific hardware and institutional access requirements.

Caplinger, Evan [Lawrence Berkeley National Labora↗
DOE OSTI2026

Lightfall v0.0.1

Lightfall is a desktop application for synchrotron beamline instrument control, data acquisition, and live analysis at the Advanced Light Source (ALS). Built on Python and Qt, it provides a native graphical interface for operating beamline hardware, configuring and executing experimental scans, and visualizing results in real time. Key features include direct integration with EPICS control systems, a built-in electronic logbook, remote beamline access over secure tunnels, and an interprocess communication (IPC) architecture that coordinates with external analysis applications via ZMQ and EPICS process variables. This IPC approach allows Lightfall to orchestrate specialized analysis tools—including GPU-accelerated streaming correlators—without embedding them, avoiding the dependency conflicts common in monolithic scientific software platforms. Compared to prior approaches such as Xi-CAM's plugin-based architecture, Lightfall's design cleanly separates instrument control from domain-specific analysis, enabling feedback-driven acquisition where live analysis results can adjust scan parameters during an experiment. Its native Qt interface provides responsive performance for real-time data visualization that web-based alternatives struggle to match. Lightfall is designed for use by beamline scientists and staff operating synchrotron instruments at national user facilities.

Pandolfi, Ronald [Lawrence Berkeley National Labor↗
DOE OSTI2025

Biogeochemical controls on iron speciation and cycling across upland to shoreline gradients in freshwater and estuarine coastal soils (Lake Erie and Chesapeake Bay, United States)

Coastal environments are dynamic interfaces that mediate carbon and nutrient exchanges between terrestrial landscapes and open waters, and understanding the biogeochemical factors controlling these exchanges, particularly iron (Fe) redox transformations, is crucial for predicting coastal ecosystem functions. Here, we investigated the mechanisms controlling Fe speciation changes across upland-to-shoreline gradients in freshwater and estuarine soils using Fe K-edge X-ray absorption spectroscopy, solid and porewater composition analysis, and 16S rRNA sequencing analysis. We show that Fe transformations depend primarily on inundation patterns. In unsaturated uplands, Fe occurs as Fe(III) oxyhydroxides, mainly goethite (9–35 %), Fe(II,III)-phyllosilicates (39–89 %), and Fe(III)-organic species (0–61 %). Soils influenced by estuarine waters exhibit porewater sulfide concentrations reaching up to 221 μM, Fe- and S-cycling bacteria, and up to 81 % pyrite (FeS 2 ), indicating that sulfur-driven redox dynamics control Fe transformations. In lacustrine wetlands, Fe(III) reduction is indicated by porewater Fe(II) concentrations increasing to 1.0–2.1 mM, and ~10–15 % of Fe as Fe(II,III)-(hydr)oxides (green rust), vivianite (Fe 3 (PO 4 ) 2 ·8H 2 O), and/or adsorbed Fe(II) species. EXAFS data also indicate reduction of structural Fe(III) to Fe(II) in phyllosilicates. The presence of Fe- and S-cycling bacteria, as well as sulfide (0–10 μM), suggests that Fe-cycling is microbially driven and potentially coupled with cryptic S-cycling. Fe(II) oxidation was indicated above/near the water table by the presence of Fe(III) oxyhydroxides (ferrihydrite, lepidocrocite). Furthermore, negligible Fe(III) or sulfate reduction was observed at some water-saturated sites located at the upland-wetland transition, likely due to oxic (sub-)surface water inputs. Overall, our results highlight the importance of considering both Fe-speciation and hydro-biogeochemical dynamics when predicting Fe-cycling at coastal interfaces.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Singularity-EOS: Performance Portable Equations of State and Mixed Cell Closures

We present Singularity-EOS, a new performance-portable library for equations of state and related capabilities. Singularity-EOS provides a large set of analytic equations of state, such as the Gruneisen equation of state, and tabulated equation of state data under a unified interface. It also provides support capabilities around these equations of state, such as Python wrappers, solvers for finding pressure-temperature equilibrium between multiple equations of state, and a unique modifier framework, allowing the user to transform a base equation of state, for example by shifting or scaling the specific internal energy. All capabilities are performance portable, meaning they compile and run on both CPU and GPU for a wide variety of architectures.

97 MATHEMATICS AND COMPUTING↗