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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 1,153 records · Page 64

pbd-industrial-limit-of-performance (PBD limit of performance) v1.0.0

Software repository that contains models used for a paper about Platform-Based Design with limit of performance analysis for an industrial pilot study. This repository contains process and control models in Modelica and IDAES and scripts to develop an ML based controller that computes the control function that maximizes the techno-economic performance of cost and energy computed by the model. This software is meant to be released to reproduce the work described in a Journal publication that is now drafted with the working title "Energy System Limit of Performance Analysis using an Online Machine Learning Multi-Resolution Optimization Framework".

Amusat, Oluwamayowa [Lawrence Berkeley National La↗

Flutter

The following repositories are a set of libraries that are needed for applications that are being developed for users of the Accelerator control system. The programming language used is Dart and for the user interface use the Flutter framework. URL for code repositories: - https://github.com/fermi-ad/flutter-controls-core - https://github.com/fermi-ad/flutter-controls-plotting - https://github.com/fermi-ad/flutter-controls-auth - https://github.com/fermi-ad/flutter-gql-acsys - https://github.com/fermi-ad/flutter-gql-faas - https://github.com/fermi-ad/dart-gql-acsys - https://github.com/fermi-ad/dart-explicit-imports - https://github.com/fermi-ad/dart-gql-faas - https://github.com/fermi-ad/design-system

Neswold, Rich [Fermi National Accelerator Laborato↗

HydraGNN_GFM_FineTuning4Materials v1.0

This repository enables fine-tuning of the HydraGNN Predictive GFM 2026 — an open-source ensemble of pre-trained graph foundation models for atomistic materials modeling, developed at Oak Ridge National Laboratory. The GFM 2026 is freely available and downloadable via Globus from the OLCF Data Constellation (DOI: 10.13139/OLCF/2562660). Starting from these pre-trained weights, this repository provides a complete transfer learning pipeline for adapting the GFM ensemble to domain-specific molecular and materials property prediction tasks. It includes: 1) Utilities for ensemble fine-tuning with task-specific output heads 2) Example pipelines for eight widely-used materials and molecular datasets 3) Tools for model adaptation and head configuration 4) Data preprocessing utilities for each supported dataset 5) Benchmarking and evaluation scripts

Ungerboeck, Linda↗

LLNL Microbenchmarks

The LLNL Microbenchmarks repository will contain open-source microbenchmarks for HPC system benchmarking activities. The repository will contain the code for various microbenchmarks developed for Request For Proposal (RFP) response evaluation and system acceptance.

Brink, Stephanie [Lawrence Livermore National Labo↗

mphys-surrogate-model

This repository contains python scripts for building and studying reduced-order-modeling representations of droplet coalescence for eventual use in atmospheric models. The included data are generated from high-fidelity superdroplet methods and are utilized by machine learning pipelines to build data-driven models of droplet size distributions that evolve under coalescence. This repository further includes scripts to determine prediction (uncertainty) intervals on the data-driven model products based on conformal prediction.

Katona, JonasE [Lawrence Livermore National Labora↗

Powertrain Autoresearch (TETA Autoresearch: RouteE Powertrain Experiments) [SWR-26-090]

Powertrain Autoresearch is an experiment repository based on the template set in teta-autoresearch containing branch history of LLM workers investigating powertrain ML model improvements. This repository contains an instance of teta-autoresearch applied to ML model exploration for RouteE Powertrain. An AI agent and human-in-the-loop iteratively explored feature space, ML model type, and hyperparameter spaces in an attempt to improve over existing models. The repo catalogs the result for review at USRSE 2026 Conference. Related: https://github.com/NatLabRockies/teta-autoresearch.

Reinicke, Nicholas [National Laboratory of the Roc↗

fermi-ad/flutter-template

This code is a collection of repositories for code that will help modernize the AD controls system. This is a collection of backend services for applications, libraries with common code, and templates to help initialize applications. The individual repositories are: 1. https://github.com/fermi-ad/flutter-template 2. https://github.com/fermi-ad/grpc-alarms-db 3. https://github.com/fermi-ad/alarms-actions-synchronizer 4. https://github.com/fermi-ad/aeolisten-async 5. https://github.com/fermi-ad/aeolisten 6. https://github.com/fermi-ad/acorn-alarms-service 7. https://github.com/fermi-ad/ap-python-template 8. https://github.com/fermi-ad/rust-template 9. https://github.com/fermi-ad/acsys-python-container-example 10. https://github.com/fermi-ad/dev-containers 11. https://github.com/fermi-ad/grpc-reflection-catalog 12. https://github.com/fermi-ad/rust-db-lib 13. https://github.com/fermi-ad/ap-python-launcher

Neswold, Rich [Fermi National Accelerator Laborato↗

lanl/bacterial-classification

bacterial-classification is a sub repository of the Intelligent Immunity project specific to training and testing machine learning models for bacterial classification (Gram-positive, Gram-negative, and non-bacterial samples). Specifically, this repository aims to compare ML classification performance across different dataset curation strategies.

Mancuso, Marina [Los Alamos National Laboratory]↗

Documenting Climate Models and Their Simulations

The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now nonspecialists such as government officials, policy makers, and the general public all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. We describe a pilot community initiative to collect and make available documentation of climate models and their simulations. In an initial application, a metadata repository is being established to provide information of this kind for a major internationally coordinated modeling activity known as CMIP5 (Coupled Model Intercomparison Project, Phase 5). We expected that for a wide range of stakeholders, this and similar community-managed metadata repositories will spur development of analysis tools that facilitate discovery and exploitation of Earth system simulations.

54 ENVIRONMENTAL SCIENCES↗

Newborn Screening Quality Assurance Program for CFTR Mutation Detection and Gene Sequencing to Identify Cystic Fibrosis

All newborn screening laboratories in the United States and many worldwide screen for cystic fibrosis. Most laboratories use a second-tier genotyping assay to identify a panel of mutations in the CF transmembrane regulator (CFTR) gene. Centers for Disease Control and Prevention’s Newborn Screening Quality Assurance Program houses a dried blood spot repository of samples containing CFTR mutations to assist newborn screening laboratories and ensure high-quality mutation detection in a high-throughput environment. Recently, CFTR mutation detection has increased in complexity with expanded genotyping panels and gene sequencing. To accommodate the growing quality assurance needs, the repository samples were characterized with several multiplex genotyping methods, Sanger sequencing, and 3 next-generation sequencing assays using a high-throughput, low-concentration DNA extraction method. The samples performed well in all of the assays, providing newborn screening laboratories with a resource for complex CFTR mutation detection and next-generation sequencing as they transition to new methods.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic Transmission Line Switching Amid Wildfire-Prone Weather Under Decision-Dependent Uncertainty

During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multistage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for decision-dependent uncertainty, where line survival probabilities depend on usage, we employ distributionally robust optimization to model uncertainty in line survival distributions. We adapt the stochastic nested decomposition algorithm and derive a deterministic upper bound for its finite convergence. To enhance computational efficiency, we exploit the Lagrangian dual problem structure for a faster generation of Lagrangian cuts. Using realistic data from the California transmission grid, we demonstrate the superior performance of dynamic response policies against two-stage alternatives through a comprehensive case study. In addition, after solving the multistage formulation, we construct easy-to-implement policies that significantly reduce computational burden while maintaining good performance in real-time deployment. History: Accepted by Russell Bent, Area Editor for Network Optimization: Algorithms and Applications. Funding: This work was supported by the U.S. Department of Energy, Office of Electricity [Grant DE-AC02-05CH11231]. The work of R. Jiang was supported in part by the U.S. National Science Foundation, Division of Electrical, Communications and Cyber Systems [Grant ECCS-1845980] and the U.S. Air Force Office of Scientific Research [Grant FA9550-23-1-0323]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2025.1210 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2025.1210 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Estrada-Garcia, Juan-Alberto↗

Data for "Quantifying the Propagation of Parametric Uncertainty on Flux Balance Analysis"

In the repository are example scripts that perform uncertainty injection and propagation to flux balance analysis with outputs for a small sample size (for demonstration purpose only). For proper analysis, user should download the scripts and run for a large sample size (e.g., 10,000 samples). If you use the scripts, please cite the following Metabolic Engineering article: “Quantifying the propagation of parametric uncertainty on flux balance analysis” (https://doi.org/10.1016/j.ymben.2021.10.012) There are two subdirectories: /uncFBA/uncBiom: injection of normally distributed noise to biomass precursor coeffcients and ATP maintenance (growth-associated ATP maintenance (GAM) and non-growth associated ATP maintenance (NGAM)) /uncFBA/uncRHS: departure from steady-state by adding noise drawn from normal distribution to the RHS terms of mass balance constraints

Metabolomics↗

Data for "Plasmon-driven exciton formation in a non-equilibrium Fermi liquid"

This repository contains source data for key plots presented in the manuscript "Plasmon-driven exciton formation in a non-equilibrium Fermi liquid." Experimental data that was analyzed in Igor Pro 8 are presented as the .pxp files used to generate individual sub-plots. Electronic spectral function calculations are provided as .txt files, in which consecutive rows refer to the meshgrid x coordinate, y coordinate, spectral function (and, where relevant, axis-projected local angular momentum). We additionally include the Wannier model and DFT-obtained bulk band structure on which the Wannier model was based. Files are named as the number of the figure in the manuscript to which they correspond, with additional details included where necessary. Details of file names: 2a_DOS_Lxz_Ek_KGM_40layer_xnum_800kpt_tot.txt: Density of states, xz-axis projected local orbital angular momentum, for 800 points along the K-Gamma-M path, for a 40-layer model. 2c_composite_y.pxp: ARPES (angle-resolved photoemission spectroscopy) spectra along the ky axis, including both a scan near the Fermi level and a scan at high kinetic energies. 2d_LCP_RCP_diff_Sect_20K.pxp: difference between ARPES constant energy cuts at T=20 K at E0 + 0.23 eV taken with left- and right-circularly polarized photons. The polarization-integrated intensity at the constant energy cut is also included. 2e_DOS_L45_E11pt79_m0pt25to0pt25_xnum_800kpt_tot.txt: Density of states, xz-projected local orbital angular momentum, and corresponding k-points in two dimensions from ab-initio electronic structure calculations for a constant-energy cut. 3a_[x]_[y]ps: ARPES cut under excitation at a fluence of x uJ/cm2, measured y ps after photoexcitation. Measurements were performed at 9 K. 3b_[x]: Energy distribution curves under excitation at a fluence x uJ/cm2 at selected delay times after photoexcitation. 4a_ImSigma_vs_temperature.pxp: Imaginary self energy (extracted from ARPES linewidths) at different energies above E0 for selected lattice temperatures. 4b_EELS_lowE.pxp: Electron energy loss spectrum over a low energy range 5b_diff_55m15.pxp: Difference between momentum-integrated Tr-ARPES traces at 55 uJ/cm2 and 15 uJ/cm2 photoexcitation. Time-dependent intensity at each energy level has been normalized to a maximum of 1 for each individual fluence prior to subtraction. 5d_invtau_at_EX_vs_fluence.pxp: decay rate at a specified energy EX for different excitation fluences, from single exponential fits. NOTE: Analyses based on the Wannier model presented here should cite both the associated Article and this dataset. For all other files in the repository, citing the dataset alone is sufficient.

Acharya, Rishi [University of Illinois] (ORCID:000↗

COVID-19 Knowledge Graph -- Dataset for SMCDC 2021 Challenge 2

This repository contains the data for the 2021 Smoky Mountains Computational Sciences Data Challenge (SMCDC21) Challenge 2 -- Finding Novel Links in COVID-19 Knowledge Graph. The total size of all files in this repository is 285MB. Challenge website: https://smc-datachallenge.ornl.gov/2021-challenge-2/ More information about the challenge and the data: https://github.com/ORNL/smcdc-2021-covid-kg

60 APPLIED LIFE SCIENCES↗

Dust Survival in Galactic Winds

This repository contains three-dimensional volumetric data from an Eulerian hydrodynamical simulation (conducted on a uniform Cartesian grid) generated by the Cholla hydrodynamics code. The datasets contain snapshots (full-grid, projections, and slices) in the HDF5 format of a multi-phase medium in which a hot, diffuse, dust-free background wind accelerates a cool, dense cloud of gas and dust. This scenario is intended to represent a supernova-driven galactic outflow, in which hot supernova winds are thought to accelerate cool interstellar medium material out of the galactic disk into the surrounding circumgalactic medium. There are three separate datasets for simulations corresponding to three cloud evolutionary scenarios: long-term cloud survival (surv), marginal cloud survival (disr), and cloud destruction (dest). Projection and slice images of the simulations are also included in this repository.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine Learning assisted optimization and parameter space exploration dataset of spin ice Hamiltonian

This repository contains both simulated and experimental structure factor data for the data challenge involving the inverse scattering problem. The simulated data were generated during a machine-learning-assisted optimization routine described in ref[1]. The experimental structure factor was measured on a rare-earth oxide, Dy2Ti2O7 using diffuse neutron scattering from time-of-flight techniques on the CORELLI instrument at the Spallation Neutron Source, Oak Ridge National Laboratory. A Metropolis Monte Carlo code implemented to run in a High-performance computing setting was used to calculated simulated structure factors for the spin-ice Hamiltonian at 680 mK, which is the same temperature as for the experimental data. The total size of all the files in this repository is 5.12 GB. A detailed description of the files is given below. ExperimentalData_630mK.dat – A linearized version of 3-dimensional experimental data of size 61×81×21. This data was processed to remove an estimation of non-magnetic background, including nuclear scattering signal and instrumentation background. Parameters.dat – 6700 samples were evaluated over the 4-dimensional parameter space (J_1, J_2, J_3 and J_(3^' )). There is an additional parameter, D in the spin Hamiltonian to mimic the dipolar interaction between magnetic ions. However, this parameter, D was fixed to a value determined by prior work. This file contains five columns for the parameters J_1, J_2, J_3, J_(3^' ) and D respectively. 3D_Simulation_Data.dat – The simulated structure factor, S(Q) data are included in this file. Each raw contains a linearized array of 3D volumes of S(Q) calculated for the parameter set given in the corresponding row of the file Parameters.dat. The size of the volume data was matched to the experimental data. Qx(h,-h,0).dat, Qy(k,k,-2k).dat, Qz(l,l,l).dat – These files contain the h, k, and l values along with the reciprocal vectors [h,-h,0], [k,k,-2k] and [l,l,l] respectively.

36 MATERIALS SCIENCE↗

Dataset for Leveraging CryoEM and AI-Driven Morphological Feature Analysis for Insights on Bacterial Structures

This repository hosts an AI-assisted image segmentation and analysis pipeline for Pantoea sp. YR343 cryo-electron microscopy (cryoEM) datasets. The workflow automates membrane thickness measurements, flagella detection, and field-of-view (FOV) screening from low-dose, high-resolution cryoEM micrographs eliminating the need for slow manual annotation. By integrating deep-learning based segmentation (YOLOv11) with quantitative post-processing, this toolkit provides a scalable and reproducible way to study bacterial morphology under hydrated, near-native conditions. The GitHub repository for AI-based tools for cryoEM bacteria ultrastructures can be found here: https://github.com/Sireesiru/Cryo-EM-Ultrastructures/tree/main

60 APPLIED LIFE SCIENCES↗

Continuous removal of fission products from molten-salt-fueled reactors

A method based on separation of volatilized molten salt (MS) components, including by mass, is being developed to extract fission products (FPs) from operating molten-salt reactors. The initial application of this method is for accelerator-driven subcritical reactors fueled by (fluorinated molten salt) spent nuclear fuel (UNF) from any past, present, or future reactor. The actinides remain in the subcritical reactor to produce profitable energy and be transmuted while the extracted FPs can be buried without long-lived actinides such that a geologic repository is not necessarily needed to close the nuclear fuel cycle. By removing neutron-absorbing FPs and operating sub-critically, where the restrictive link between operation and criticality is broken, it is possible to envision complete burnup of the UNF fuel. The game-changing feature of continuously processing the molten salt inside the reactor while the reactor operates eliminates the need for a separate reprocessing plant. This feature also simultaneously improves the neutronics of the reactor, increasing the burnup of the fuel and extending its useful life for generating energy. Nuclear nonproliferation and need for geologic repositories are addressed by keeping actinides inside the reactor containment until they are consumed. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗