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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

Phase Composition and Phase Transformation of Additively Manufactured Nickel Alloy 718 AM Bench Artifacts

Additive manufacturing (AM) technologies offer unprecedented design flexibility but are limited by a lack of understanding of the material microstructure formed under their extreme and transient processing conditions and its subsequent transformation during post-build processing. As part of the 2022 AM Bench Challenge, sponsored by the National Institute of Standards and Technology, this study focuses on the phase composition and phase evolution of AM nickel alloy 718, a nickel-based superalloy, to provide benchmark data essential for the validation of computational models for microstructural predictions. Here, we employed high-energy synchrotron X-ray diffraction, in situ synchrotron X-ray scattering, as well as high-resolution transmission electron microscopy for our analyses. The study uncovers critical aspects of the microstructure in its as-built state, its transformation during homogenization, and its phase evolution during subsequent aging heat treatment. Specifically, we identified secondary phases, monitored the dissolution and coarsening of microstructural elements, and observed the formation and stability of γ ’ and γ ” phases. The results provide the rigorous benchmark data required to understand the atomic and microstructural transformations of AM nickel alloy 718, thereby enhancing the reliability and applicability of AM models for predicting phase evolution and mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermal conductance of interfaces between titanium nitride and group IV semiconductors at high temperatures

Measuring the temperature dependence of material properties is a standard method for better understanding the microscopic origins for that property. Surprisingly, only a few experimental studies of thermal boundary conductance at high temperatures exist. This lack of high temperature data makes it difficult to evaluate competing theories for how inelastic processes contribute to thermal conductance. To address this, we report time domain thermoreflectance measurements of the thermal boundary conductance for TiN on diamond, silicon-carbide, silicon, and germanium between 120 and 1000 K. In all systems, the interface conductance increases monotonically without stagnating at higher temperatures. For TiN/SiC interfaces, G ranges from 330 to 1000 MW/m2-K, with a room temperature conductance of 750 MW/m2-K. The interface conductance for TiN/diamond ranges from 140 to 950 MW/m2-K. Notably, for all four interfacial systems, the conductance continues to increase with temperature even after all phonon modes in the vibrationally soft material are thermally excited. This observation suggests that inelastic processes are significant contributors to the thermal conductance in all four interfacial systems, regardless of whether the materials forming the interface are vibrationally similar or dissimilar. Our study fills a notable gap in the literature for how interfacial conductance evolves at high temperatures and tests burgeoning theories for the role of inelastic processes in interfacial thermal transport.

Physics↗
DOE OSTI2021

Unified model of short- and long-term HIV viral rebound for clinical trial planning

Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads. Typically suspension of therapy is rapidly followed by rebound of viral loads to high, pre-therapy levels. Indeed, a recent study showed that approximately 90% of treatment interruption study participants show viral rebound within at most a few months of therapy suspension, but the remaining 10%, showed viral rebound some months, or years, after ART suspension. Some may even never rebound. We investigate and compare branching process models aimed at gaining insight into these viral dynamics. Specifically, we provide a theory that explains both short- and long-term viral rebounds, and post-treatment control, via a multitype branching process with time-inhomogeneous rates, validated with data from Li et al. We discuss the associated biological interpretation and implications of our best-fit model. To test the effectiveness of an experimental intervention in delaying or preventing rebound, the standard practice is to suspend therapy and monitor the study participants for rebound. We close with a discussion of an important application of our modelling in the design of such clinical trials.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Operating Dynamic Reserve Dimensioning Using Probabilistic Forecasts

The rapid integration of variable energy sources (VRES) into power grids increases variability and uncertainty of the net demand, making the power system operation challenging. Operating reserve is used by system operators to manage and hedge against such variability and uncertainty. Traditionally, reserve requirements are determined by rules-of-thumb (static reserve requirements, e.g., NERC Reliability Standards), and more recently, dynamic reserve requirements from tools and methods which are in the adoption process (e.g., DynADOR, DRD, and RESERVE, among others). While these methods/tools significantly improve the static rule-of-thumb approaches, they rely exclusively on deterministic data (i.e., best guess only). Consequently, these methods disregard the probabilistic uncertainty thresholds associated with specific days and their weather conditions (i.e., best guess plus probabilistic uncertainty). This work presents practical approaches to determine the operating reserve requirements leveraging the wealth information from probabilistic forecasts. Proposed approaches are validated and tested using actual data from the CAISO system. Furthermore, results show the benefits in terms of risk reduction of considering the probabilistic forecast information into the dimensioning process of operating reserve requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Recent Cryogenic Carbon Capture™ Field Test Results

Sustainable Energy Solutions (SES) has been developing Cryogenic Carbon Capture™ (CCC) since 2008. In that time, two processes have been developed, the External Cooling Loop and Compressed Flue Gas CCC processes (CCC-ECL and CCC-CFG, respectively). The CCC-ECL process cools the flue gas with an external refrigerant loop. This process currently captures up to 1 tonne of CO2 per day (TPD). SES has tested CCC-ECL on real flue gas slip streams from subbituminous coal, bituminous coal, biomass, natural gas, shredded tires, and municipal waste fuels at field sites that include utility power stations, heating plants, cement kilns, and pilot-scale research reactors. The CO2 concentrations from these tests ranged from 5 to 22% on a dry basis. CO2 capture ranged from 95-99+% during these tests. Several other condensable species were also captured including NO2, SO2 and PMxx at 95+%. NO was also captured at a modest rate. The CCC-CFG process has been scaled up to a 0.25 ton per day system. This system has been tested on real flue gas streams including subbituminous coal, bituminous coal, and natural gas at field sites that include utility power stations, heating plants, and pilot-scale research reactors. CO2 concentrations for these tests ranged from 5 to 15% on a dry basis. CO2 capture ranged from 95-99+% during these tests. Several other condensable species were also captured including NO2, SO2, and PMxx at 95+%. NO was also captured at 90+%. Hg capture was also verified and the resulting effluent from CCC-CFG was below a 1ppt concentration. This paper will focus on discussion of the capabilities of CCC generally, the results of CCC-ECL field testing, and future steps surrounding the development of this technology. Test results that will be presented have been collected during 9 months of testing at a commercial power plant under funding from the US Department of Energy (DOE) and the host utility. Testing of one of the systems at a commercial cement plant in the United States will also be discussed. During this testing, the system captured CO2 from the cement plant and stored the CO2 in pressurized tanks. These tanks were provided to a partner company that later used the CO2 in a CO2 utilization demonstration. The CO2 was utilized to cure concrete manufactured using cement from the same plant where the CO2 was captured. This integrated capture and utilization demonstration was the first time that the cement industry has shown in the field that it can sequester its CO2 emissions in its main product stream. This represents a potential game changing solution for industrial CO2 emissions. Operational data and host-site feedback indicate that the CCC process is ideally suited for deployment into a variety of commercial environments. A few areas of de-risking remain to make sure the technology can meet very strict industrial reliability standards. These areas of de-risking are identified and discussed. The product CO2 is shown to meet specification for many uses including industrial and merchant applications. The technology is nearing readiness for deployment at commercial scale and several initial target markets have been identified.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Enabling Efficient Surveillance, Control, and Automation of Geothermal Operations with Advanced Predictive Analytics

Automation and control of geothermal energy production and operations require reliable and efficient predictive tools. While physics-based simulation offers a comprehensive tool for predicting energy production performance in geothermal systems, predicting the behavior of geothermal reservoirs involves complex multi-physics processes with coupling effects, highly uncertain input parameters and subsurface descriptions. Moreover, building, running, and integrating simulation models into standard model calibration and optimization workflows entail significant technical and computational efforts. An emerging alternative to physics-based simulation is data-driven predictive analytics models that have gained popularity in energy industry. In this report, we develop novel predictive models for integration into real-time fault diagnosis and model predictive control algorithms to improve the efficiency of energy production operations in geothermal reservoirs. The report includes two major research Thrust Areas, that is, the surface power plant and the subsurface reservoir.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

SALT3-NIR: Taking the Open-source Type Ia Supernova Model to Longer Wavelengths for Next-generation Cosmological Measurements

Abstract A large fraction of Type Ia supernova (SN Ia) observations over the next decade will be in the near-infrared (NIR), at wavelengths beyond the reach of the current standard light-curve model for SN Ia cosmology, SALT3 (∼2800–8700 Å central filter wavelength). To harness this new SN Ia sample and reduce future light-curve standardization systematic uncertainties, we train SALT3 at NIR wavelengths (SALT3-NIR) up to 2 μ m with the open-source model-training software SALTshaker , which can easily accommodate future observations. Using simulated data, we show that the training process constrains the NIR model to ∼2%–3% across the phase range (−20 to 50 days). We find that Hubble residual (HR) scatter is smaller using the NIR alone or optical+NIR compared to optical alone, by up to ∼30% depending on filter choice (95% confidence). There is significant correlation between NIR light-curve stretch measurements and luminosity, with stretch and color corrections often improving HR scatter by up to ∼20%. For SN Ia observations expected from the Roman Space Telescope, SALT3-NIR increases the amount of usable data in the SALT framework by ∼20% at redshift z ≲ 0.4 and by ∼50% at z ≲ 0.15. The SALT3-NIR model is part of the open-source SNCosmo and SNANA SN Ia cosmology packages.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Measurement of the Higgs boson production via vector boson fusion and its decay into bottom quarks in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A measurement of the Higgs boson (H) production via vector boson fusion (VBF) and its decay into a bottom quark-antiquark pair ($\mathrm{b\bar{b}}$) is presented using proton-proton collision data recorded by the CMS experiment at $\sqrt{s}$ = 13 TeV and corresponding to an integrated luminosity of 90.8 fb$^{-1}$. Treating the gluon-gluon fusion process as a background and constraining its rate to the value expected in the standard model (SM) within uncertainties, the signal strength of the VBF process, defined as the ratio of the observed signal rate to that predicted by the SM, is measured to be $\mu^\text{qqH}_\mathrm{Hb\bar{b}}$ = 1.01$^{+0.55}_{-0.46}$. The VBF signal is observed with a significance of 2.4 standard deviations relative to the background prediction, while the expected significance is 2.7 standard deviations. Considering inclusive Higgs boson production and decay into bottom quarks, the signal strength is measured to be $\mu^\text{incl.}_\mathrm{Hb\bar{b}}$ = 0.99$^{+0.48}_{-0.41}$, corresponding to an observed (expected) significance of 2.6 (2.9) standard deviations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

First observation of the production of three massive vector bosons and search for long-lived particles using delayed photons in pp collisions at $\sqrt{s}=13\text{ TeV}$

This thesis presents the first observation of the production of three massive vector bosons (VVV with V = W, Z) in proton-proton collisions at the LHC at $\sqrt{s}=13\text{ TeV}$. The search was performed in final states with two same-sign charged leptons (electrons or muons) plus one or two jets, and three, four, five, or six leptons from WWW, WWZ, WZZ and ZZZ decays, with a data sample corresponding to an integrated luminosity of 137 fb -1 collected by the CMS experiment during 2016-2018. The observed (expected) significance of the combined VVV production is 5.7 (5.9) standard deviations, and the production cross section is measured to be 1010$^{+210}_{-200}$(stat) $^{+150}_{-120}$(syst) fb, corresponding to a signal strength of 1.02$^{+0.26}_{-0.23}$. We also found evidence for WWW and for WWZ production, with observed significances of 3.3 and 3.4 standard deviations, respectively. The measured production cross sections for individual VVV processes are also reported. The establishment of VVV production opens a new program of many standard model studies (such as gauge-gauge and Higgs-gauge couplings), and provides a new tool for many new physics searches (such as anomalous gauge coupling searches, new resonance searches). This thesis also reports a search for long-lived supersymmetry particles decaying to photons in proton-proton collisions at the LHC at $\sqrt{s} = 13 TeV$, with a data sample corresponding to an integrated luminosity of 77.4 fb -1 collected by CMS during 2016-2017. Results are interpreted with a gauge-mediated supersymmetry breaking model, where the long-lived particle is a neutralino and the lightest supersymmetry particle is a gravitino. For neutralino proper decay lengths of 0.1, 1, 10, and 100 m, masses up to 320, 525, 360, and 215 GeV are excluded at 95% confidence level, respectively. This result extends the limits from previous searches by one order of magnitude for the neutralino proper decay length and up to 100 GeV more for the neutralino mass. Motivated by the need for precision timing measurements for long-lived particle searches, as well as for improvements in general object reconstruction performance, the timing performance of two types of sensors are studied in this thesis: one with a Cerium doped Lutetium Yttrium Orthosilicate (LYSO:Ce) crystal as the scintillator and a silicon photomultiplier (SiPM) as the photodetector, another with a Cadmium-Telluride sensor as the active material for a sampling calorimeter. Both setups have been demonstrated with test beams to be able to provide timing measurements of particles with a resolution below 30 ps.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Soft costs and EVSE – Knowledge gaps as a barrier to successful projects

There has been a recent push to increase access to electric vehicle (EV) charging infrastructure. The National Electric Vehicle Infrastructure (NEVI) program, part of the Bipartisan Infrastructure Law (BIL) has made significant funding available for major charging infrastructure projects along state thruways, and many state and local incentives exist for EV owners to install chargers in their homes. However, deployment of these chargers has not kept up with demand, primarily due to issues in project planning, permitting processes, and unforeseen delays. This paper serves as a review of the current understanding of these and other non-hardware costs in EV charging infrastructure projects (collectively known as “soft costs”). We found that soft costs in EV charging infrastructure projects are not well understood. Specifically, there is little agreement on how soft costs should be categorized and tracked, and less agreement still on best practices for controlling these costs and lowering barriers to infrastructure deployment. A broader review of EV charging infrastructure cost analyses shows that these costs can have significant impacts on project outcomes. EV charging infrastructure projects may be able to examine the success of the solar industry in lowering soft costs, and a similar effort may lower project costs significantly. Further work on standardizing and collecting data on EV charging infrastructure costs is required to begin addressing and controlling these costs.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2020

Introduction to Metadata and Ontologies: Everything You Always Wanted to Know About Metadata and Ontologies (But Were Afraid to Ask)

Metadata are contextual data about your experimental data. Metadata are the who, what, when, where, and why of these data. Metadata puts these data into context. In microbiome research, metadata includes information about the sample: when it was collected, where it was collected from, what kind of sample it is, and what were the properties of the environment or experimental condition from which the sample was taken. Information about sample processing is also metadata: methods used to extract and purify molecules (e.g., DNA) from the sample, type of DNA sequencing or other ’omics analyses done, and where the raw experimental data are located. This documentation includes information on the following topics: What are metadata? What kinds of metadata are there? Why are metadata important? Why should metadata be standardized? Why should metadata be machine readable? What is an ontology? Why are ontologies important? What are some examples of ontologies? The documentation also includes further resources on metadata guides and tools and tips for formatting metadata for maximum utility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Cleaned 5-Minute Resolution Air Quality and Meteorological Data from Nine TCEQ CAMS Sites in Houston, Texas (Nov 2021 – Oct 2022)

These data encompass 5-minute air monitoring and meteorological observations collected in the greater Houston, Texas metropolitan region, at nine (9) Continuous Ambient Monitoring Stations (CAMS) operated by the Texas Commission on Environmental Quality (TCEQ) between November 1, 2021 and October 31, 2022. The CAMS sites (CAMS 1, 8, 35, 45, 148, 403, 405, 410, and 1052) were chosen because their instrumentation includes measurements of PM2.5. These sites also provide continuous multi-parameter air-quality and meteorological measurements. Particulate matter (PM2.5, PM10) was sampled along with several trace gases, including ozone (O3), nitrogen oxides (NO, NO2, NOx), sulfur dioxide (SO2), and carbon monoxide (CO). The data set also contains standard surface meteorological parameters (temperature, humidity, pressure, wind speed, and wind direction). Several sites also include AutoGC-based measurements of volatile organic compounds (VOCs). Air monitoring instruments deployed at the selected sites comprise the following systems: BAM-1020 or TEOM (PM2.5), Thermo Scientific TEI 49i (O3), TEI 42i (NOx), and AutoGCs (VOCs). This data set is similar to the data included within the houairq5mX1.00 datastream, except for a few additional quality control steps. A systematic data cleaning and verification process was performed on the data set to ensure its quality and preparation for analysis. Removal of non-numeric status flags (e.g., [LIM], [QAS], [SPZ], [CAL], [PMA], [AQI], [SPN], [MAL]) was accomplished by employing rule-based string parsing to extract valid numerical values. Missing entries were set to -9999; however, invalid or anomalous values (e.g., 99999) were retained as originally reported by the TCEQ to preserve data provenance. The time sequence was verified for completeness, removal of duplicates, and uniformity at 5-minute intervals. Column labeling was standardized, and corresponding values were assessed for physical plausibility. All timestamps in the data set were reported in Coordinated Universal Time (UTC) as provided by the TCEQ. Further, the latitude and longitude coordinates were added for each CAMS site. A subset of the data (June 1–September 30, 2022) has been used in the following publication: Subba et al. 2025. “Implications of sea breeze circulations on boundary layer aerosols in the southern coastal Texas region.” EGUsphere 2025: 1–49, https://doi.org/10.5194/egusphere-2025-2659.

latitude↗
DOE OSTI2020

End-to-End Physics Event Classification with CMS Open Data: Applying Image-Based Deep Learning to Detector Data for the Direct Classification of Collision Events at the LHC

This paper describes the construction of novel end-to-end image-based classifiers that directly leverage low-level simulated detector data to discriminate signal and background processes in pp collision events at the Large Hadron Collider at CERN. To better understand what end-to-end classifiers are capable of learning from the data and to address a number of associated challenges, we distinguish the decay of the standard model Higgs boson into two photons from its leading background sources using high-fidelity simulated CMS Open Data. We demonstrate the ability of end-to-end classifiers to learn from the angular distribution of the photons recorded as electromagnetic showers, their intrinsic shapes, and the energy of their constituent hits, even when the underlying particles are not fully resolved, delivering a clear advantage in such cases over purely kinematics-based classifiers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Search for Rare Processes: Mu2e and KOTO

The Standard Model (SM) of particle physics has been very successful in describing the fundamental forces, the properties of elementary particles, and predicting particles prior to their discovery, for example the top quark and the Higgs boson. Yet the SM does not explain all phenomena, and discoveries of physics processes beyond the SM will allow progress in our understanding of the fundamental nature of matter and forces. The search for rare processes is one of the paths to look for new physics. Two of these searches are for muon to electron conversion and the decay $\text{K}_\text{L}\rightarrow \pi^0 \nu \bar{\nu}$. Our main effort was in the Mu2e experiment under construction at Fermilab, which has the goal of searching for the neutrinoless conversion of a muon into an electron at a single event sensitivity of 2.87 x 10-17 and, in the process, provide evidence of physics processes beyond the Standard Model. We developed the firmware to be used in the Mu2e tracker readout, assisted in the construction and operation of the Mu2e Vertical Slice Test, and provided input to studies of cosmic event reconstructions in Mu2e using simulated data. Under this reward we also concluded our effort in two KOTO experiment in J-PARC, Japan and set a limit on the rate of the rare decay, $\text{K}_\text{L}\rightarrow \pi^0 \nu \bar{\nu}$ using the data collected in the 2016-2018 period. We also maintained and operated the DAQ system used for data collection thru 2021.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Search for physics beyond the standard model in multilepton final states in proton-proton collisions at $\sqrt{s} =$ 13 TeV

A search for physics beyond the standard model in events with at least three charged leptons (electrons or muons) is presented. The data sample corresponds to an integrated luminosity of 137 fb$^{−1}$ of proton-proton collisions at $ \sqrt{s} $ = 13 TeV, collected with the CMS detector at the LHC in 2016–2018. The two targeted signal processes are pair production of type-III seesaw heavy fermions and production of a light scalar or pseudoscalar boson in association with a pair of top quarks. The heavy fermions may be manifested as an excess of events with large values of leptonic transverse momenta or missing transverse momentum. The light scalars or pseudoscalars may create a localized excess in the dilepton mass spectra. The results exclude heavy fermions of the type-III seesaw model for masses below 880 GeV at 95% confidence level in the scenario of equal branching fractions to each lepton flavor. This is the most restrictive limit on the flavor-democratic scenario of the type-III seesaw model to date. Assuming a Yukawa coupling of unit strength to top quarks, branching fractions of new scalar (pseudoscalar) bosons to dielectrons or dimuons above 0.004 (0.03) and 0.04 (0.03) are excluded at 95% confidence level for masses in the range 15–75 and 108–340 GeV, respectively. These are the first limits in these channels on an extension of the standard model with scalar or pseudoscalar particles.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Reactome and the Gene Ontology: digital convergence of data resources

Abstract Motivation Gene Ontology Causal Activity Models (GO-CAMs) assemble individual associations of gene products with cellular components, molecular functions and biological processes into causally linked activity flow models. Pathway databases such as the Reactome Knowledgebase create detailed molecular process descriptions of reactions and assemble them, based on sharing of entities between individual reactions into pathway descriptions. Results To convert the rich content of Reactome into GO-CAMs, we have developed a software tool, Pathways2GO, to convert the entire set of normal human Reactome pathways into GO-CAMs. This conversion yields standard GO annotations from Reactome content and supports enhanced quality control for both Reactome and GO, yielding a nearly seamless conversion between these two resources for the bioinformatics community. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Organic matter concentration and composition of experimentally burned open air and muffle furnace vegetation chars across differing burn severity and feedstock types from Pacific Northwest, USA (v4).

This dataset represents results from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and feedstock materials. The dataset provides both solid and dissolved phase bulk concentration and organic matter characterization data from experimentally generated chars. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. This data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), fourteen burn table videos, burn table video metadata and three folders containing (A) data; (B) metadata and protocols; and (C) photos. The folder names and the file name of the data package readme include a version number which will be updated with future iterations of this data package. The data folder includes (1) solid carbon and solid nitrogen; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and total dissolved nitrogen (TN); (3) pH; (4) thermocouple time series temperature; (5) methods codes; (6) installation methods; (7) excitation emissions matrix (EEM) methods information; (8) a folder of excitation emissions matrix (EEM) fluorescence and absorbance spectra in dissolved organic matter and EEMs processing instructions; (9) solid state carbon-13 and solution state phosphorus nuclear magnetic resonance (13-C NMR and 31-P NMR) data and methods; (10) benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (11) FTICR-MS methods; (12) Inductively coupled plasma (ICP) data for total calcium, magnesium, iron, aluminum, potassium, phosphorus, sodium, and sulfur along with sodium hydroxide-ethylenediaminetetraacetic acid (sodium hydroxide-EDTA) extractable calcium, magnesium, iron, aluminum, potassium, phosphorus, and sulfur; (13) a folder of phosphorus, carbon, and nitrogen X-ray absorption near edge structure (P-XANES, N-XANES, C-XANES) data for samples and standards; (14) P-XANES, N-XANES, C-XANES methods; (15) molybdate reactive phosphorus; and (16) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains .txt data files and a subfolder containing instruments for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. The metadata and protocols folder includes (1) international geo-sample number (IGSN) mapping file (2) burn and laboratory metadata; (3) burn protocol; (4) laboratory protocol; (5) vegetation collection metadata; and (6) vegetation collection protocol. The folder contains photos of the solid chars. All files are .csv, .txt, .pdf, .jpg, .jpeg, .R, .ref, or .mp4. The data package was originally published October 2022 (v1). It was updated April 2023 (v2; new data files), September 2023 (v3; new and corrected data files), and September 2024 (v4; new and added/updated files). Metadata files were also updated to reflect these changes. See the change history section in the readme for more details.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

PoolDilutionR : An R package for easy optimization of isotope pool dilution calculations

Abstract Isotopic pool dilution is a powerful approach to quantify gross biogeochemical transformation rates, but remains seldom used despite its potential. To facilitate broader implementation of pool dilution methods, we present a user‐friendly R package that optimizes gross production and consumption rates (and optionally fractionation constants as well) based on standard pool dilution time series data. This package features extensive documentation and example analyses, and is easily integrated into analytical pipelines. With this open‐source tool, the biogeochemistry community will be able to readily apply isotope pool dilution to a wide range of processes.

59 BASIC BIOLOGICAL SCIENCES↗