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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 325 records · Page 18

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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 OSTI2022

jupyterhub-announcement v0.8

This is an announcement service for JupyterHub that JupyterHub admins can manage through a JupyterHub-styled UI. JupyterHub administrators can use it to communicate with their hub's users about status, upcoming outages, or share news. It allows admins to post a current announcement, and show previous announcements in reverse chronological order. It provides a REST API hook that admins can use to post the latest announcement on JupyterHub itself (with custom templates).

Thomas, Rollin↗

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↗

DOE OSTI2024

Biological Parts Search Portal (BioParts) v1.0.0

BioParts is a web based search portal for biological parts available in the public domain. It combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically. While there are several standalone biological part repositories, there doesn't exist an application that indexes these publicly available parts and enables features such as keyword and BLAST searches along with automatic sequence annotation.

Plahar, Hector↗

DOE OSTI2024

AqNWB v0.1

This is a C ++ acquisition API for neurophysiological data in the NeurodataWithoutBorders (NWB) data standard.

Prince, Stephanie↗

DOE OSTI2024

ATCCfinder - Download and Search the ATCC Genome Portal

Much strain-specific sequence data exists in research conducted before the deployment of large sequencing repositories, making it challenging to identify and validate the identity of strains used in these studies through bioinformatics and phenotyping. The American Type Culture Collection (ATCC) is an organization that sells a wide variety of microbes with strain-level taxonomy classification and associated sequenced reference genomes. Currently, ATCC does not provide a method for searching for sequence similarity between a query sequence and their database of reference genomes. Here I propose the software ATCCfinder, which utilizes ATCC application interface software (API) to generate query-able databases from ATCC Genome resources.

Koehler, Samuel↗

DOE OSTI2023

BUTTER-Clarifier [SWR-23-61]

This repository contains a python package of neural network interpretability techniques (interpretability) and a keras callback to easily compute and capture data related to these techniques (values metrics) during training. It was developed to be used with NREL's BUTTER Deep Learning Experimental Framework, but does not depend on this framework and may be useful to projects outside of this framework. The vision for this codebase is to collect algorithms for explainable artificial intelligence (XAI) in a single framework that is easy to use, easy to read, and can be expand upon. Here, we package XAI algorithms into a module called "metrics", which are implemented as python functions. The return type of a metric is typically a dictionary holding data of multiple data types, such as real values and numpy matrices. Callbacks and any other connector code is provided as necessary in a separate module to make these metrics more easily usable. This project depends on Tensorflow's Keras API, although it would be nice to try and support multiple backends one day. Related to: https://github.com/NREL/BUTTER-Empirical-Deep-Learning-Experimental-Framework

Perr-Sauer, Jordan↗

DOE OSTI2024

Database Manager for use with PLEXOS XML files [SWR-24-90]

This software is an API for create and modify XML that are used for Plexos. DISCLAIMER: PLEXOS is a registered trademark of Energy Exemplar Pty Ltd ("Owner"). Owner has no affiliation to or participation in this software. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or Alliance for Sustainable Energy, LLC ("Alliance"). The views and opinions of authors expressed in the available or referenced documents do not necessarily state or reflect those of the United States Government or Alliance.

Sanchez Perez, Pedro Andres↗

DOE OSTI2021

Role-Based Access Control for Distributed Energy Resources v.1.0

The Role-Based Access Control (RBAC) for Distributed Energy Resources (DER) software is an automated and transparent stack for RBAC administrators to interact with RBAC policy. The package includes demonstrations of centralized and decentralized RBAC implementation. Both include simulated DER entities that are stored automatically in a centralized Lightweight Directory Access Protocol (LDAP) server. It also includes a REST-API to serve the HTTP requests of the RBAC administrators. A complete front-end is included to serve the users' needs. This software may be used by industry (DER vendors/utilities) as well as the research community to determine if a centralized or decentralized solution fits better the needs of an RBAC model in a DER environment. Additionally, parts of this software may be useful for developing implementations for specific needs. 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. SAND2021-8292 O

Johnson, Jay↗

DOE OSTI2024

Dispatch Optimization Variable Engine

The Dispatch Optimization Variable Engine (DOVE) is software tool written in python, developed at Idaho National Laboratory (INL) that provides an easily accessible application-programming-interface (API) to performing resource dispatch optimization analysis for integrated energy system (IES) configurations. DOVE is an integral part of the Framework for Optimization of Resources and Economics (FORCE) software suite and is leveraged by codes such as the Holistic Energy Resource Optimization Network (HERON) and the Optimization of Real-Time Capacity Allocation (ORCA). The philosophy behind DOVE is to provide a modular software solution to IES planning and operation by utilizing state-of-the-art algorithms and machine learning. The goal is to accurately capture the dispatching behavior of a complex energy system given varying time-dependent signals for demand and commodity pricing.

McDowell, DylanJ. [Idaho National Laboratory (INL)↗

DOE OSTI2024

certified

The missing certificate infrastructure for web APIs.

Rogers, DavidM [Oak Ridge National Laboratory (ORN↗

DOE OSTI2025

PNNL-Predictive-Phenomics/ProCaliper

ProCaliper is a Python library that curates, organizes, and computes protein structure features in a way that easily interfaces with user-provided experimental data. It extracts or computes protein binding site, active site, charge, pLDDT (order/disorder), acid dissociation, protonation, solvent accessible surface area, disulfide bond distance, and protein secondary structure data using precomputed protein structures and publicly available databases. It provides a unified API for integrating additional residue-level data and for visualizing residue features in 3D.

Rozum, Jordan [Pacific Northwest National Lab]↗

DOE OSTI2025

tether

Tether is a python module for benchmarking and assessing large language model (LLMs) performance at generic scientific tasks. The code generates benchmarks, uses the benchmark to prompt LLMs through automatic programming interfaces (APIs), and then logs the number of prompts an LLM correctly answers and presents the results as a completed benchmark.

Kaiser, Bryan [Los Alamos National Laboratory]↗

DOE OSTI2025

NOVA Galaxy Library

The nova-galaxy library provides an abstract API for accessing Galaxy services

Cage, Gregory [Oak Ridge National Laboratory (ORNL↗

DOE OSTI2025

ifbeam

This is a C++ library for acessing the beams database REST api at Fermilab. Example client code is in the demos directory.

Garren, Lynn [Fermi National Accelerator Laborator↗

DOE OSTI2025

libwda

Low level API for IFBeam and other csv data

Mengel, Marc [Fermi National Accelerator Laborator↗

DOE OSTI2025

ChemEcho v1.0

ChemEcho is a tool that converts tandem mass spectra into embeddings used to build machine learning (ML) models with fully explainable predictions. It provides an API for transforming raw tandem mass spectral data into embeddings, along with functions for training and validating ML models. Additionally, it includes utilities for retrieving and cleaning training data. ChemEcho is broadly applicable in ML pipelines that use tandem mass spectra for a variety of tasks, such as chemical classification or bioactivity mining. While there are existing methods to generate embeddings from fragmentation data, ChemEcho's approach ensures that predictions remain interpretable, enabling experts to evaluate results and generate hypotheses about the underlying data.

Harwood, Thomas [Lawrence Berkeley National Labora↗

DOE OSTI2025

BULKI-Store v0.3.2

BULKI-Store is a distributed object storage system optimized for high-performance computing environments. Built with a Rust core and Python bindings, it efficiently manages scientific and machine learning datasets across HPC clusters. The system employs a client-server architecture with MPI integration, enabling seamless scaling on supercomputers like Perlmutter. BULKI-Store's object-oriented approach provides intuitive data organization with rich metadata support, contrasting with traditional file-based solutions. Key optimizations include selective checkpoint loading, unified checkpoint files, and object chunking for large data transfers. For machine learning workloads, BULKI-Store offers advantages through fine-grained access patterns, dynamic data sharing between training instances, and reduced memory pressure. Memory management features include strategic Python GC calls, minimized data copies, and batch processing capabilities. The system leverages Rayon's thread pool for asynchronous data prefetching and supports multiple CPU architectures (ARM64, x86, AMD, RISC-V). By combining performance optimizations with developer-friendly APIs, BULKI-Store addresses the complex data management challenges of modern HPC applications while maintaining compatibility across heterogeneous computing environments.

Zhang, Wei [Lawrence Berkeley National Laboratory ↗