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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The secondary metabolism collaboratory: a database and web discussion portal for secondary metabolite biosynthetic gene clusters

Secondary metabolites are small molecules produced by all corners of life, often with specialized bioactive functions with clinical and environmental relevance. Secondary metabolite biosynthetic gene clusters (BGCs) can often be identified within DNA sequences by various sequence similarity tools, but determining the exact functions of genes in the pathway and predicting their chemical products can often only be done by careful, manual comparative analysis. To facilitate this, we report the first release of the secondary metabolism collaboratory (SMC), which aims to provide a comprehensive, tool-agnostic repository of BGC sequence data drawn from all publicly available and user-submitted bacterial and archaeal genome and contig sources. On the website, users are provided a searchable catalog of putative BGCs identified from each source, along with visualizations of gene and domain annotations derived from multiple sequence analysis tools. SMC’s data is also available through publicly-accessible application programming interface (API) endpoints to facilitate programmatic access. Users are encouraged to share their findings (and search for others’) through comment posts on BGC and source pages. At the time of writing, SMC is the largest repository of BGC information, holding 13.1M BGC regions from 1.3M source sequences and growing, and can be found at https://smc.jgi.doe.gov.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

VirJenDB: a FAIR (meta)data and bioinformatics platform for all viruses

High-throughput sequencing has generated an unprecedented volume of data. However, researcher-submitted data in repositories requires extensive curation and quality control for reuse. These tasks are hindered by the multiplicity of repositories, the sheer volume of the data, and the complexity of virus (meta)data curation. To address these challenges, VirJenDB offers a user-friendly platform to facilitate versioned, community-driven curation, and ontology development. Virus sequences were ingested from 16 sources, including ~200 fields of metadata or standards, covering taxonomy, sample, and host information. Up to 85 metadata fields have undergone at least one round of curation, and are linked to 15.4 million virus sequences, with 88 % from those infecting eukaryotes and the remaining infecting prokaryotes. Subsets were created, including a novel collection of 0.91 million viral operational taxonomic unit (vOTU) sequences across all viruses, while keeping the original sequences from each vOTU to facilitate downstream analyses, e.g. sequence variation. The VirJenDB web portal (https://www.virjendb.org) provides HTTPS and Application Programming Interface (API) access to the sequence datasets and metadata, offering a search engine, filtering, download, visualizations, and documentation. VirJenDB aims to connect the phage and eukaryotic virus research communities by supporting webtool integration, meta-analyses, and metadata schema extensions.

Saghaei, Shahram↗
DOE OSTI2026

Meta-virus resource (MetaVR): expanding the frontiers of viral diversity with 24 million uncultivated virus genomes

Viruses are ubiquitous in all environments and impact host metabolism, evolution, and ecology, although our knowledge of their biodiversity is still extremely limited. Viral diversity from genomic and metagenomic datasets has led to an explosion of uncultivated virus genomes (UViGs) and the development of specialized databases to catalog this viral diversity, though many lack comprehensive integration. Here, we introduce meta-virus resource (MetaVR), the successor of the IMG/VR database, designed to overcome previous limitations such as large-scale querying and programmatic access. Drawing on the increase of publicly available genomes and metagenomes, MetaVR significantly expands viral diversity, now comprising 24,435,662 UViGs, a 57.6% increase from its predecessor, organized into over 12 million viral operational taxonomic units. Key enhancements include the integration of curated eukaryotic host information, the integration of protein clusters and predicted structures for comparative studies, and an API for programmatic data access. Furthermore, MetaVR features an updated taxonomic framework based on ICTV release 39, assignment to Baltimore classes, and enhanced host assignment through novel computational tools like iPHoP. These advancements position MetaVR as a unique resource for exploring viral diversity, evolution, and host interactions across diverse environments. MetaVR can be freely accessed at https://www.meta-virome.org/.

Fiamenghi, Mateus B↗
DOE OSTI2025

BioPortal: an open community resource for sharing, searching, and utilizing biomedical ontologies

Abstract BioPortal (https://bioportal.bioontology.org) is the world’s most comprehensive repository of biomedical ontologies. It provides infrastructure for finding, sharing, searching, and utilizing biomedical ontologies. Launched in 2005, BioPortal now includes 1549 ontologies (1182 of them public). Its open, freely accessible website enables anyone (i) to browse the ontology library, (ii) to search for terms across ontologies, (iii) to browse mappings between terms, (iv) to see popularity ratings and recommendations on which ontologies are most relevant to their use cases, (v) to annotate text with ontology terms, (vi) to submit an ontology, and (vii) to request ontology changes. The library of ontologies can be accessed programmatically via a REST application programming interface (API). Recent enhancements include a BioPortal knowledge graph that integrates knowledge from multiple ontologies; a unified data model for interoperability with other knowledge sources; ontology popularity ratings and recommendations for relevant ontologies; and the ability to request ontology changes via a simple user interface that automatically converts user change requests to GitHub Pull Requests that specify the edits that will be made to the ontology upon approval.

Vendetti, Jennifer↗
DOE OSTI2025

PvaPy streaming framework for real-time data processing

User facility upgrades, new measurement techniques, advances in data analysis algorithms as well as advances in detector capabilities result in an increasing amount of data collected at X-ray beamlines. Some of these data must be analyzed and reconstructed on demand to help execute experiments dynamically and modify them in real time. In turn, this requires a computing framework for real-time processing capable of moving data quickly from the detector to local or remote computing resources, processing data, and returning results to users. In this paper, we discuss the streaming framework built on top of PvaPy, a Python API for the EPICS pvAccess protocol. We describe the framework architecture and capabilities, and discuss scientific use cases and applications that benefit from streaming workflows implemented on top of this framework. We also illustrate the framework's performance in terms of achievable data-processing rates for various detector image sizes.

EPICS pvAccess↗
DOE OSTI2024

Machine Learning (ML) Classifier to Assist Metadata Creation

The Atmospheric Radiation Measurement (ARM) Data Center is responsible for the timely collection, archival, and curation of science data products. These products are freely available through an online data repository. Metadata creation is paramount for scientific users to find and access over seven petabytes of atmospheric science data. The hierarchical metadata structure allows users to search for information at both broad and narrow levels. This project aims to leverage 30 years’ worth of manually created metadata to enable machine predictions of broad-term classifications from narrow-term descriptions. These classification predictions would assist metadata coordinators with their term selections. This paper discusses the cleaning and preprocessing of the training data, the pipeline developed to determine the best model for this task, and the creation of an API metadata classifier for ARM measurement metadata. Our results show that the Linear Support Vector Classification (LinearSVC) algorithm, along with the Term Frequency – Inverse Document Frequency (TF-IDF) vectorizer, is well-suited for our multi-class classification task. Lengthier input training data led to better results, and artificial balancing was unnecessary for this particular use case. This predictive classifier enhances efficiency in metadata creation, as well as supports greater consistency and accuracy in metadata tagging.

Collier, Hannah [ORNL] (ORCID:0000000341284292)↗
DOE OSTI2024

Disruption of Commercial Solar Inverter System by TLS Proxy Man-in-the-Middle Attack

Transport Layer Security (TLS) is a cryptographic protocol that encrypts communication data, providing end-to-end communication encryption and authentication. Currently, TLS is widely adopted for securing communication between servers and end devices, including solar inverter systems. Therefore, users/operators can securely access the solar inverters through a web user interface (WebUI) application programmable interface (API) on a PC or server over TLS-enabled Wi-Fi or Ethernet. However, the security of the TLS-based network becomes compromised if it is breached by a TLS proxy man-in-the-middle (MITM) exploit. This report explores potential vulnerabilities in a commercial solar inverter system that leverages a TLS proxy MITM and discusses the impacts through assume-breached penetration testing. Furthermore, the paper explores recommended mitigation methods against the TLS proxy MITM exploit in solar inverters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

IRIS: Exploring Performance Scaling of the Intelligent Runtime System and its Dynamic Scheduling Policies

High-Performance Computing is becoming increasingly heterogeneous, relying on a diverse mix of hardware to achieve good performance. Paradoxically, current drivers and frameworks for these devices typically require separate languages and implementations for each vendor. Furthermore, there are few tools and little support to schedule codes between these devices in a truly heterogeneous manner-partly because of this fragmentation between vendors and the languages each supports. To overcome both limitations, the Intelligent Runtime System (IRIS) was developed. It allows a common task abstraction to automatically be shared among contemporary vendors and is run from a single host-side API. At runtime, IRIS queries the host system and registers which frameworks and drivers are available, these determine which kernels can be used by the scheduler-CPUs via OpenMP, Nvidia GPUs (CUDA), AMD GPUs (HIP), and Intel and Xilinx FPGAs with OpenCL. IRIS enables tasks to be scheduled to any heterogeneous device and resolves to the appropriate kernel binary at runtimeit only uses the devices supported by the system on which it is run. IRIS supports single-task and graph-based expressions of dependencies of tasks. Additionally, IRIS features a range of dynamic scheduling policies, allowing complex chains of tasks and interactions to be executed, relieving the programmer/user from considering the system to assign tasks to devices optimally. This paper presents the peak performance attainable by IRIS over a range of systems-each with different numbers and types of accelerator devices, it highlights the flexibility of IRIS since these devices are truly heterogeneous, relying on different backends (drivers, frameworks, and languages) which historically required unique implementations to utilize them. We then use this peak performance as a baseline to compare increasingly complex chains of tasks (with increasingly complex task dependencies) and evaluate how IRIS copes. Finally, we consider the performance of different IRIS scheduling policies on this range of task graphs.

Johnston, Beau↗
DOE OSTI2024

eCC++ : A Compiler Construction Framework for Embedded Domain-Specific Languages

eCC++ is a new compiler construction framework for embedding domain-specific programming languages within C++. That is, the host language is C++, the guest language is the DSL to be embedded in C++, and eCC++ is the tool that enables the embedding. The eCC++ framework is composed of three main components: a front-end, an API for program verification based on a functional and declarative intermediate representation (IR), and a Multi-Level Intermediate Representation (MLIR) code generator. The eCC++ front-end consists of a library of C++ classes and operators that can be used to define the guest language. Guest sources are compiled with any standard C++ compiler, and when run, the resulting executable generates an eCC++ IR representation of the program, which can be verified within the eCC++ framework. Finally, eCC++ allows for high-level and domain-specific optimizations before generating MLIR. In summary, eCC++ aims to act as a generic front-end that enables embedding guest languages into C++, and provides necessary compiler technology for program verification, targeting the existing capabilities in the MLIR infrastructure. The paper evaluates the eCC++ expressiveness and usability describing the process of embedding GraphIt, a high-performance graph language in C++.

Gonzalez Tallada, Marc↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Iterative Reconstruction for Multimodal Neutron Tomography

Here, we describe a unified framework for model-based iterative 3-D reconstruction of multimodal neutron transmission, hydrogen-scatter, and induced-fission images from low resolution data recorded using 14.1-MeV neutrons and the associated-particle imaging (API) technique. The framework, which was developed to facilitate use in challenging field-deployment scenarios, is centered around physics-based system models and a total variation (TV) constrained implementation of the simultaneous iterative reconstruction technique (SIRT). Modified to solve a statistically weighted least squares (WLS) problem, the SIRT algorithm is accelerated using ordered subsets and Nesterov’s momentum for which we derive a near-optimal value of the governing Lipschitz constant. The approach enables the reconstruction of images that are high resolution compared to the acquired data and is robust to both limited statistics and a limited number of projection angles. Moreover, the framework is fast enough to be practical. Example images are provided that demonstrate both the ability to perform fast-neutron imaging of high-atomic-number materials with low radiation dose and the benefit of multimodal neutron imaging to identify key materials.

Hydrogen scatter↗
DOE OSTI2024

Controlling Air Conditioners for Frequency Regulation: A Real-World Example

Even though thermostatically controlled loads like air conditioners present a great potential for providing ancillary services to the electric power grid, the practical challenges associated with their real-time coordination have not received the necessary attention. In this work, we present a nondisruptive load control application, specifically, we demonstrate how real residential air conditioners can provide frequency regulation. Aggregate power adjustment is achieved by modifying the ON/OFF modes of the air conditioners. To account for both single and multi-zone houses, we extend the currently available techniques and develop an approach that can be used for controlling aggregations that include both types of houses. A discussion of the practical challenges encountered in our field experiments is provided, along with the hardware and software approaches we developed to circumvent them. Here, we argue that limitations of current thermostat APIs introduce significant challenges and are an impediment to widespread adoption of fast load control applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Detailed Design and Cost Estimation of a 300 MWe Oxy-Fuel sCO2 Turbine

The detailed design of a 300 MWe, utility scale oxy-fuel turbine has been completed for purposed operation in the sCO2 direct fired Allam-Fetvedt cycle, targeting near-zero emissions and a 50% LHV system efficiency. The turbine and its supporting plant aim to offer a lower levelized cost of energy than a natural gas combined cycle plant employing carbon capture. The oxy-fuel turbine conditions include an inlet temperature of 1150°C and inlet pressure of 305 bar, representing temperatures near that of a gas turbine simultaneously with pressures near an ultra-supercritical steam turbine. The combustor housing and turbine designs were completed according to the ASME BPVC; the turbine case specifically incorporates a multi-body design with inner high-pressure barrel case and low-pressure (30 bar) horizontally split outer case of low-chromium steel material. Lateral rotordynamic evaluation demonstrated acceptable vibration response for a range of imbalance conditions per API standards. The cooling flow required in the six-stage turbine flowpath for 30,000 hr. blade and stator lifetime is predicted through thermal and structural modeling of the first stage. The provided cost estimate of the turbine is formed through a combination of scaled up-costs from procured 10 MWe scale sCO2 turbomachinery hardware, and vendor provided budgetary quotes of larger components including the turbine case requiring casting, welding, and final machining processes. The performance and cost estimation of the oxy-fuel turbine predicted for the completed detailed design provides important information towards future development needs for market penetration of utility scale direct fired sCO2 power cycles.

Marshall, Michael [Southwest Research Institute, S↗
DOE OSTI2025

Performance of an optical TPC Geant4 simulation with opticks GPU-accelerated photon propagation

We investigate the performance of Opticks, a NVIDIA OptiX API 7.5 GPU-accelerated photon propagation tool compared with a single-threaded Geant4 simulation. We compare the simulations using an improved model of the NEXT-CRAB-0 gaseous time projection chamber. Performance results suggest that Opticks improves simulation speeds by between 58.47 ± 0.02 and 181.39 ± 0.28 times relative to a CPU-only Geant4 simulation and these results vary between different types of GPU and CPU. A detailed comparison shows that the number of detected photons, along with their times and wavelengths, are in good agreement between Opticks and Geant4.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Streaming Data in HPC Workflows Using ADIOS

The “IO Wall” problem, in which the gap between computation rate and data access rate grows continuously, poses significant problems to scientific workflows which have traditionally relied upon using the filesystem for intermediate storage between workflow stages. One way to avoid this problem in scientific workflows is to stream data directly from producers to consumers and avoiding storage entirely. However, the manner in which this is accomplished is key to both performance and usability. This paper presents the Sustainable Staging Transport, an approach which allows direct streaming between traditional file writers and readers with few application changes. SST is an ADIOS “engine”, accessible via standard ADIOS APIs, and because ADIOS allows engines to be chosen at run-time, many existing file-oriented ADIOS workflows can utilize SST for direct application-to-application communication without any source code changes. This paper describes the design of SST and presents performance results from various applications that use SST, for feeding model training with simulation data with substantially higher bandwidth than the theoretical limits of Frontier’s file system, for strong coupling of separately developed applications for multiphysics multiscale simulation, or for in situ analysis and visualization of data to complete all data processing shortly after the simulation finishes.

Podhorszki, Norbert [ORNL] (ORCID:000000019647542X↗
DOE OSTI2024

Front-end Only Chatbot Interface

This code is a web-based front-end only (HTML, CSS, JS) chatbot interface for any OpenAI compatible text completion API.

Biggs, BrandonS.↗
DOE OSTI2024

Inventory of Composable Elements (ICE) v6.0.0

The Inventory of Composable Elements (ICE) is an open source registry software platform for managing information about biological parts. It is capable of recording information about plasmids, microbial host strains and seeds, as well as DNA parts. Includes features such as DNA sequence visualization, editing and annotation, auto-aligning sequencing trace files against reference templates, SBOL XML/RDF support, and web-of-registries functionality. The web of registries functionality provides strong support for distributed interconnected use and enables sharing and transfer of biological parts across various independent ICE instances. ICE adopts modern software development principles, leveraging component-base frameworks, offering a REST API for convenient third-party integration and emphasizing scalability, security, and service integrations for dynamic content availability. The source code is hosted at https://github.com/JBEI/ice. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects.

Plahar, Hector↗
DOE OSTI2024

Deeplynx Airflow Provider Package

The DeepLynx Airflow Provider Package is a python package used to interact with the data warehouse DeepLynx when using the workflow orchestration tool Apache Airflow. This python package is packaged together using the airflow package standard so that it can be easily installed and used in any Apache Airflow environment. This package is meant to encapsulate the DeepLynx API for use in Airflow so that any interactions with DeepLynx that a user may want to use in their Airflow workflow can be easily accomplished using this provider package. This allows us to develop, implement, and test our DeepLynx-Airflow interactions in one provider package repository, and then easily install and use this package in any airflow instance. This DeepLynx Airflow Provider Package will be used extensively by the DeepLynx DAG repository.

Cavaluzzi, JackM↗