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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

In–context promoter bashing of the Sorghum bicolor gene models functionally annotated as bundle sheath cell preferred expressing phosphoenolpyruvate carboxykinase and alanine aminotransferase

In-context promoter bashing via genome editing is a route to identify and characterize critical regulatory regions that govern expression of genes of interest. The outcomes of in-context promoter bashing can be used to inform editing strategies to modulate the expression of selected gene models in a desired fashion. Here, we employed in-context promoter bashing to characterize the proximal upstream regulatory regions of sorghum genes encoding phosphoenolpyruvate carboxykinase bundle sheath (SbPEPCK.BS, SbiTx430.01G455400) and alanine aminotransferase bundle sheath (SbAlaAT.BS, SbiTx430.02G006600), two proteins involved in the PCK C 4 pathway. Characterized germinal edits within the targeted regions upstream of these two genes ranged in size from 138 up to 1790 bp. A 138 bp within the SbPEPCK.BS upstream region and a 1643 bp element within the SbAlaAT.BS upstream region were determined to be important for maintenance of transcription levels. No change in development or various physiological parameters was observed in characterized lineages carrying promoter edits. However, significant changes in seed reserves and a reduction in 100-seed weight were consistently observed, under both greenhouse and field environments, in plants carrying an edit in the promoter of SbPEPCK.BS gene, which were significantly reduced in transcript accumulation for this gene.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Supplementary table, figures and DNA sequences of sorghum gene models SbiRTx430.01G455400 and SbiRTx.02G006600 that feature primers, gRNAs and indels created

In-context promoter bashing via genome editing is a route to identify and characterize critical regulatory regions that govern expression of genes of interest. The outcomes of in-context promoter bashing can be used to inform editing strategies to modulate the expression of selected gene models in a desired fashion. Here we employed in-context promoter bashing to characterize the proximal upstream regulatory regions of sorghum genes encoding phosphoenolpyruvate carboxykinase (Sb.PEPCK.BS, SbiTx430.01G455400) and alanine aminotransferase (SbiTx430.02G006600, SbAlaAT.BS), two proteins involved in the PCK C4 pathway. Characterized germinal edits within the targeted regions upstream of these two genes ranged in size from 138 bp up to 1790 bp. A 138 bp within the Sb.PEPCK.BS upstream region and a 1643 bp element within the Sb.AlaAT.BS upstream region were determined to be important for maintenance of transcription levels. No change in development or various physiological parameters was observed in characterized lineages carrying promoter edits. However, significant changes in seed reserves and a reduction in 100 seed weight were consistently observed, under both greenhouse and field environments, in plants carrying an edit in the promoter of Sb.PEPCK.BS gene were significantly reduced in transcript accumulation for this gene.

Quach, Truyen [Center for Plant Science Innovation↗
DOE OSTI2024

Automating Log Synthesis and Visualization with Python and Splunk

The goal of this project is to automate log analysis by utilizing Splunk, Bash, and Python together. Simplifying the monitoring and analysis of network traffic was the main goal. In order to accomplish this, a Bash script was created to use 'tcpdump' to automate network sniffing. It also included a 24-hour file rotation mechanism to effectively manage the pcap files that were generated. After that, a Python script was written to read these pcap files and retrieve pertinent data about network traffic. After processing the collected data, Splunk is used to summarize the important metrics and visualize said information with relevant graphs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

HTESP (High-throughput electronic structure package): A package for high-throughput ab initio calculations

High-throughput ab initio calculations are the indispensable parts of data-driven discovery of new materials with desirable properties, as reflected in the establishment of several online material databases. The accumulation of extensive theoretical data through computations enables data-driven discovery by constructing machine learning and artificial intelligence models to predict novel compounds and forecast their properties. Efficient usage and extraction of data from these existing online material databases can accelerate the next stage materials discovery that targets different and more advanced properties, such as electron–phonon coupling for phonon-mediated superconductivity. However, extracting data from these databases, generating tailored input files for different ab initio calculations, performing such calculations, and analyzing new results can be demanding tasks. Here, in this work, we introduce a software package named “HTESP” (High-Throughput Electronic Structure Package) written in Python and Bash languages, which automates the entire workflow including data extraction, input file generation, calculation submission, result collection and plotting. Our HTESP will help speed up future computational materials discovery processes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High-throughput electronic structure package

We introduce HTESP (High-Throughput Electronic Structure Package), an automated tool designed for high-throughput ab initio calculations. HTESP simplifies the entire workflow, including data extraction, input files generation, calculation submission, result collection, and plotting. The package is implemented in Python and Bash languages. In this paper, we provide detailed information about the package, its installation process and some illustrative examples to demonstrate its usage. Additionally, the package includes comprehensive online documentation on input parameters and tutorials to assist users.

Nepal, NirajK↗
DOE OSTI2024

Nodeman: A Node Management Tool For Hpc Clusters

NodeMan is a command line tool to manage nodes in an HPC cluster. At it's core, it is an extensible framework composed of bash scripting and GNU parallel. HPC System Administrator will find it useful in that it encapsulates desired functions and allows them to be assembled in a way familiar to administrators - through pipes. In fact, NodeMan functions can work with common command line tools as long as they use stdin/stdout. System Administrators can construct moderately complex logic and filtering on a compact command line that would normally require a substantial shell script. In the spirit of clush and pdsh, it is able to run commands remotely on nodes. Additionally, NodeMan is more flexible. For example, it can interact with IPMI and naturally processes node lists for orchestrating different tools. The library of useful pre-built functions is growing. System administrators can easily create new functions and make it their own.

Serr, ScottM↗
DOE OSTI2025

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗
DOE OSTI2026

wastewater_virus

This repo contains software used to clean and assemble high-throughput sequencing data containing viruses. The input is raw illumina sequencing reads and the output is a database of high-quality viral genomes. The specific application is to wastewater viral concentrates but it is not restricted to that sample type. The software is composed of Nextflow workflows and a set of custom Python and bash scripts that call publicly available bioinformatics tools to accomplish obvious tasks in data analysis in a high performance computing environment. For detailed information, please see the repo's README file.

Kantor, Rose [Lawrence Livermore National Laborato↗
DOE OSTI2026

CodeScribe Agent

SF-26-086 CodeScribe introduces a structured, multi-stage pipeline that combines deterministic program analysis with LLM-powered translation to enable incremental, testable Fortran-to-C++ migration. First, `code-scribe index` traverses the project directory tree and produces `scribe.yaml` metadata files recording all modules, subroutines, and functions at each level, giving the LLM accurate structural context instead of a hallucinated codebase model. Second, `code-scribe draft` performs the deterministic portion of translation — converting Fortran types to C++ equivalents, replacing `use` statements with `#include` and `using namespace` directives, and detecting constructs requiring special handling — while embedding`scribe-prompt` annotations that guide the LLM through non-trivial cases such as statement-function-to-lambda conversions and `extern "C"` wrapper generation. Third, `code-scribe translate` applies project-specific TOML-based few-shot prompt templates and submits the composed prompt to a pluggable LLM backend (OpenAI, Anthropic, Argonne ARGO, any OpenAI-compatible endpoint, or local Hugging Face checkpoints), producing a C++ source file, a header, and a Fortran-C++ interface file for each translated routine so the codebase compiles and runs correctly throughout the migration. Beyond translation, CodeScribe includes a tool-using coding agent (`code-scribe agent`) with read, bash, edit, and write capabilities, and a bounded loop mode (`code-scribe loop`) that runs repeated stateless agent sessions over a task file with restricted tool access — enabling sustained, auditable software development workflows for broader scientific computing tasks.

Dhruv, Akash [Argonne National Laboratory (ANL), A↗
DOE OSTI2026

Data From: "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater"

This repository contains the data and code associated with the paper titled "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater," published in Nature Geoscience, 2026. This study seeks to answer how various ages of groundwater interact with mountainous streamflow in mountainous headwaters such as the East River. It includes various model-data processing scripts, primarily for ParFlow-CLM analysis of simulated water years 2015-2021, and two numerical warming experiments (+2.5 and +4.0 degrees C), including run scripts, forcing scripts, and post-processing, as well as comparison to observation datasets, detailed below. This data requires the use of R (.r, .rmd), Python (.py), Jupyter Notebook or Jupyter Lab (.ipynb), ParFLOW-CLM, EcoSLIM. Further information on the use of all file formats mentioned below (e.g. .tff. .nc) are provided within the associated scripts and directory where the files are located. Contents & Usage ASO/: ​​Contains the bash and python scripts used to convert airborne snow observatory (ASO) data (ASO, 2023) in various data formats (georeferenced tiff file, NetCDF, UTM, and to latitude/longitude) then regrided to the ParFlow equivalent grid. Output data are in regrid_regll_data.zip and subsequently visualized and analyzed in plot_and_compare.py for Supplementary Figures A14 and A15. The wksht_ASO_comparison.xlsx spreadsheet is used to calculate the data for Supplementary Figure A16. EcoSLIM/: Contains the scripts and input files to run the EcoSLIM particle tracking simulations (/run_scripts) and the post-processing python script (/plot_scripts/eco_agedist_plots.ipynb). Jasechko et al./: Contains the jupyter notebook (Extract_Elevation.ipynb) to determine the outlet elevations of the 260 watersheds used in Jasechko et al. (2016), and the corresponding table, Table_S1_Watersheds_alt.csv. Used to create Supplementary Information Figure A2. PLM_Wells/: Contains the QA/QC-ed groundwater level time series of the PLM-1 and PLM-6 Monitoring Wells from Faybishenko et al. (2023), reformatted to water years used for Supplementary Figures A19 and and A20. ParFlow/: Contains the input files and run scripts to run ParFlow-CLM (/run_scripts), the python and tool command language (Tcl) scripts to create and distribute the ParFlow forcing simulation files (/forcing), and various scripts and intermediary files to analyze the model outputs (/post_process). SQUIRE/: Contains the processing scripts and intermediary files for the Surface QUantitatIve pRecipitation Estimation (SQUIRE) data (Grover, 2023) used to generate Supplementary Figure A18. USGS_Streamflow/: Contains the raw and gap-filled United States Geological Survey streamflow data (U.S. Geological Survey, 2026) used at the Almont station (site number 09112500). Gap-filling is performed in the R script with data from the Taylor station (site number 09110000). (/USGS_09112500_EAST_RIVER_AT_ALMONT_GAP_FILLED/code_almont_streamflow_gap_fill.Rmd). discharge/: Contains the gap-filled discharge data at the Watershed Function SFA East River pumphouse site (Newcomer et al., 2022) used to generate Supplementary Figure A13 and to compute hourly Nash-Sutcliffe model efficiency coefficients (NSE) in Table A4. snotel_and_flux_tower/: Contains the snow telemetry data (U.S. Department of Agriculture, 2024) from the Butte (site ID 380) and Schofield (site ID 737) stations, reformatted by water year, accessed with the snotelr R package. Used to create Supplementary Figure A17. Also contains the flux tower observational data (FluxTower_Pumphouse_ESS-DIVE.ET_only.h.txt) from Ryken et al. (2022) and sap flux transpiration data (MaxB_Transpiration_5Sites.daily_sums.h.txt) from Ryken (2021), used to create Supplementary Figures A22 and A23, respectively. Raw EcoSLIM model outputs are in excess of 24TB, and are stored on National Energy Research Scientific Computing Center (NERSC) and publicly available via the external link provided in the paper.

atmospheric warming↗
DOE OSTI2024

The design and construction of the Chips water Cherenkov neutrino detector

Chips (CHerenkov detectors In mine PitS) was a prototype large-scale water Cherenkov detector located in northern Minnesota. The main aim of the R&D project was to demonstrate that construction costs of neutrino oscillation detectors could be reduced by at least an order of magnitude compared to other equivalent experiments. This article presents design features of the Chips detector along with details of the implementation and deployment of the prototype. While issues during and after the deployment of the detector prevented data taking, a number of key concepts and designs were successfully demonstrated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Exploration of mass splitting and muon/tau mixing parameters for an eV-scale sterile neutrino with IceCube

We present the first three-parameter fit to a 3+1 sterile neutrino model using 7.634 years of data from the IceCube Neutrino Observatory on $ν$ μ + $\overline{ν}$ μ charged-current interactions in the energy range 500–9976 GeV. Our analysis is sensitive to the mass-squared splitting between the heaviest and lightest mass state (Δm$^{2}_{41}$), the mixing matrix element connecting muon flavor to the fourth mass state (|U μ4 | 2 ), and the element connecting tau flavor to the fourth mass state (|U $\tau$4 | 2 ). Predicted propagation effects in matter enhance the signature through a resonance as atmospheric neutrinos from the Northern Hemisphere traverse the Earth to the IceCube detector at the South Pole. The remaining sterile neutrino matrix elements are left fixed, with |U e4 | 2 = 0 and δ 14 = 0, as they have a negligible effect, and δ 24 = π is set to give the most conservative limits. The result is consistent with the no-sterile neutrino hypothesis with a probability of 4.3%. Profiling the likelihood of each parameter yields the 90% confidence levels: 2.4eV 2 < Δm$^{2}_{41}$) < 9.6eV 2 , 0.0081< |U μ4 | 2 < 0.10, and |U $\tau$4 | 2 < 0.035, which narrows the allowed parameter-space for |U $\tau$4 | 2 . However, the primary result of this analysis is the first map of the 3+1 parameter space exploring the interdependence of Δm$^{2}_{41}$, |U μ4 | 2 , and |U $\tau$4 | 2 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Improved modeling of in-ice particle showers for IceCube event reconstruction

The IceCube Neutrino Observatory relies on an array of photomultiplier tubes to detect Cherenkov light produced by charged particles in the South Pole ice. IceCube data analyses depend on an in-depth characterization of the glacial ice, and on novel approaches in event reconstruction that utilize fast approximations of photoelectron yields. Here, a more accurate model is derived for event reconstruction that better captures our current knowledge of ice optical properties. When evaluated on a Monte Carlo simulation set, the median angular resolution for in-ice particle showers improves by over a factor of three compared to a reconstruction based on a simplified model of the ice. The most substantial improvement is obtained when including effects of birefringence due to the polycrystalline structure of the ice. When evaluated on data classified as particle showers in the high-energy starting events sample, a significantly improved description of the events is observed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Prototype acoustic positioning system for the Pacific Ocean Neutrino Experiment

We present the design and initial performance characterization of the prototype acoustic positioning system intended for the Pacific Ocean Neutrino Experiment. It comprises novel piezo-acoustic receivers with dedicated filtering- and amplification electronics installed in P-ONE instruments and is complemented by a commercial system comprised of cabled and autonomous acoustic pingers for sub-sea installation manufactured by Sonardyne Ltd. We performed an in-depth characterization of the acoustic receiver electronics and their acoustic sensitivity when integrated into P-ONE pressure housings. These show absolute sensitivities of up to -125 dB re V2/μPa2 in a frequency range of 10–40 kHz. We furthermore conducted a positioning measurement campaign in the ocean by deploying three autonomous acoustic pingers on the seafloor, as well as a cabled acoustic interrogator and a P-ONE prototype module deployed from a ship. Using a simple peak-finding detection algorithm, we observe high accuracy in the tracking of relative ranging times at approximately 230–280 μs at distances of up to 1600 m, which is sufficient for positioning detectors in a cubic-kilometer detector and which can be further improved with more involved detection algorithms. The tracking accuracy is further confirmed by independent ranging of the Sonardyne system and closely follows the ship's drift in the wind measured by GPS. The absolute positioning shows the same tracking accuracy with its absolute precision only limited by the large uncertainties of the deployed pinger positions on the seafloor.

Data analysis↗
DOE OSTI2025

The LED calibration systems for the mDOM and D-Egg sensor modules of the IceCube Upgrade: Design, production, testing and use in module calibration

The IceCube Neutrino Observatory, instrumenting about 1 km 3 of deep, glacial ice at the geographic South Pole, is due to be enhanced with the IceCube Upgrade. The IceCube Upgrade, to be deployed during the 2025/26 Antarctic summer season, will consist of seven new strings of photosensors, densely embedded near the bottom center of the existing array. Aside from a world-leading sensitivity to neutrino oscillations, a primary goal is the improvement of the calibration of the optical properties of the instrumented ice. This calibration will be applied to the entire archive of IceCube data, improving the angular and energy resolution of the detected neutrino events. For this purpose, the Upgrade strings include a host of new calibration devices. Aside from dedicated calibration modules, several thousand LED flashers have been incorporated into the photosensor modules. We describe the design, production, and testing of these LED flashers before their integration into the sensor modules as well as the use of the LED flashers during lab testing of assembled sensor modules.

Analogue electronic circuits↗
DOE OSTI2026

Evidence for a Spectral Break or Curvature in the Spectrum of Astrophysical Neutrinos from 5 TeV to 10 PeV

Here, we report improved measurements of the all flavor astrophysical neutrino spectrum with IceCube by combining complementary neutrino samples in two independent analyses. Both analyses show evidence of a harder spectrum at energies below ∼ 30 TeV compared to higher energies where the spectrum is well characterized by a power law. The spectrum is better described by a log parabola or a broken power law, the latter being the preferred model. Both, however, reject a single power law over an energy range 5 TeV–10 PeV with a significance > 4⁢𝜎, providing new constraints on properties of cosmic neutrino sources.

Abbasi, R. [Loyola University Chicago] (ORCID:0000↗
DOE OSTI2025

Probing the PeV region in the astrophysical neutrino spectrum using 𝜈 𝜇 from the Southern sky

IceCube has observed a diffuse astrophysical neutrino flux over the energy region from a few TeV to a few PeV. At PeV energies, the spectral shape is not yet well measured due to the low statistics of the data. This analysis probes the gap between 1 and 10 PeV by using high-energy downgoing muon neutrinos. Here, to reject the large atmospheric muon background, two complementary techniques are combined. The first technique selects events with high stochasticity to reject atmospheric muon bundles whose stochastic energy losses are smoothed due to high muon multiplicity. The second technique vetoes atmospheric muons with the IceTop surface array. Using 9 yrs of data, we found two neutrino candidate events in the signal region, consistent with expectation from background, each with relatively high signal probabilities. A joint maximum likelihood estimation is performed using this sample and an independent 9.5-yr sample of tracks to measure the neutrino spectrum. A likelihood ratio test is done to compare the single power-law (SPL) vs SPL+cutoff hypothesis; the SPL+cutoff model is not significantly better than the SPL. High-energy astrophysical objects from four source catalogs are also checked around the direction of the two events. No significant coincidence was found.

Abbasi, R. [Loyola University Chicago] (ORCID:0000↗
DOE OSTI2026

Improved measurements of the TeV-PeV extragalactic neutrino spectrum from joint analyses of IceCube tracks and cascades

The IceCube South Pole Neutrino Observatory has discovered the presence of a diffuse astrophysical neutrino flux at energies of TeV and beyond using neutrino induced muon tracks and cascade events from neutrino interactions. Here, we present two analyses sensitive to neutrino events in the energy range 1 TeV to 10 PeV, using more than 10 years of IceCube data. Both analyses consistently reject a neutrino spectrum following a single power-law with a significance of > 4⁢𝜎 in favor of a broken power law. We describe the methods implemented in the two analyses, the spectral constraints obtained, and the validation of the robustness of the results. Additionally, we report the detection of a muon neutrino in the medium energy starting events sample, or MESE, with an energy of 11.4$^{+2.46}_{−2.53}$ PeV, the highest energy neutrino observed by IceCube to date. The results presented here show insights into the spectral shape of astrophysical neutrinos, which has important implications for inferring their production processes in a multimessenger picture.

astroparticles↗