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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Novel microbial based enzymatic CO2 fixation mechanisms: Conformational control of enzymatic reactivity

The broad, long-term goal of the research is to provide insight into the mechanism of novel carboxylation and electron bifurcation reactions as paradigms to study how enzyme utilized protein conformational change to protect reactive intermediates and/or control the pathway in a catalytic cycle. catalyzed by enzymes involved in bacterial alkene, ketone, and epoxide metabolism. We are examining two paradigms in which conformational change is a key mechanistic feature of 1) protecting reaction intermediates that are sensitive to breakdown in the presence of water and 2) directing electron flow in reactions that split electron pairs along two pathways in reactions that fine tune metabolic efficiency in microbial metabolism. Both paradigms are of key importance in defining the molecular determinants of reactions relevant to CO 2 capture and fuel upcycling. In the first paradigm the compounds acetone and bicarbonate are activated by the addition of phosphate creating reaction intermediates (phosphoenolacetone and carboxyphosphate) that are very sensitive to breakdown in the presence of water. We are studying the mechanism of how the enzyme protects these reactive intermediates from water by encapsulating them upon their formation within a hydrophobic protein channel leading to an enzyme active site approximately 40 Å away. In the second paradigm, we are examining how the direction of electron transfer reactions can be modulated through protein conformational change that alters either the difference driving force or distance or both between electron transfer pathways in enzymes that catalyze electron bifurcation. We are using a combination of enzyme kinetics, mass spectrometry, spectroscopy, and structural analysis through X-ray diffraction and scattering methods to characterize the mechanism of conformational changes along the catalytic path. Within the context of the mission of the Department of Energy and the core activities of the Energy Biosciences, the results obtained in the study will reveal new insights into the fundamentals of novel carboxylation / CO 2 capture chemical transformations and electron transfer reactions that equate to biological fuel upcycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Feature Engineering and Ensemble Methods for Imbalanced ICS Intrusion Detection: Pipeline Audit and Constrained Evaluation

Industries are becoming increasingly connected and are more vulnerable to cyberattacks due to the widened attack surface. Industrial Control Systems (ICS) are among the most critical sectors that malicious actors can target, as such attacks can cause significant operational disruption and physical damage. It is imperative to detect such attacks as early as possible. This paper evaluates constraint-conditioned optimistic performance estimates for traditional ML models in ICS intrusion detection (i.e., estimates obtained under contiguous, non-shuffled temporal evaluation without test-set alteration, but with pre-split feature engineering that may introduce temporal leakage, due to dataset constraints). Our findings are threefold. First, we quantify how iterative feature engineering affects tree-based ensemble performance and examine how pipeline decisions (split strategy, sampling scope, and cleaning policy) can inflate or reduce reported IDS results under constraint-bound evaluation. Second, we compare intrinsic class-imbalance handling across ensemble models. Third, under our current pipeline constraints (including pre-split feature engineering), CatBoost achieves the best performance on Water Storage Tank (accuracy: 0.9831, class-1 F1: 0.9682), while Light- GBM achieves the best performance on Gas Pipeline (accuracy: 0.9618, class-1 F1: 0.9086).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Extracted Water Induces Concentration Fluctuations in Model Ternary Liquid–Liquid Extraction System

Organic phase aggregation and phase splitting are two important (and connected) phenomena in liquid–liquid extraction of metal ions. Previously, we demonstrated how structure in binary mixtures of extractant and diluent originates from concentration fluctuations associated with the so-called “third-phase formation” liquid–liquid phase instability. For more complex systems, we sought to understand how extracted aqueous components affect these concentration fluctuations. Here, in this study, we use small-angle X-ray scattering and molecular dynamics simulations to investigate organic phase structural changes upon contact with water in a model ternary system of water/alkane/extractant. Critical exponents were determined from scattering with temperature variation and were consistent with mean field values. Then, by controlling the water content in the organic phase through direct dissolution of fixed quantities at constant temperature, we relate the observed increase in the fluctuation length scale to changes to the spinodal temperature of the third-phase formation phase boundary. We find a roughly linear relationship between water concentration and the spinodal temperature and a similar slope in that relationship for different linear alkane diluents. This suggests that the mechanism by which water extraction impacts the organic phase structure is to enhance concentration fluctuations through the introduction of additional polar extractant-water complexes, which increases the spinodal temperature and thereby decreases the reduced temperature, i.e., the distance to the instability. This explanation for how solutes induce aggregation in liquid–liquid extraction organic phases may extend to more complex systems, explaining the large increases in correlation lengths reported under high acid and metal loading.

Bonnett, Brittany L. [Argonne National Laboratory ↗
DOE OSTI2026

Mountain Basin Controls on the Snow-to-Streamflow Signal: An AIC-Weighted Multiple Linear Regression Framework

A regression-based analysis quantifies how basin characteristics modulate the snow-to-streamflow signal. First, we use the ERA5-Land reanalysis gridded product (European Centre for Medium Range Weather Forecasts reanalysis 5 -Land component) for 4,655 hydrologic unit code - 10 (HUC10) mountain basins across the western United States (US) for water years 1987–2024. Linear regressions are performed for peak snow water equivalent (SWE) and annual streamflow for each mountain basin. Models use ordinary least squares in Python’s statsmodels package. After which, an Akaike Information Criterion (AIC)–weighted ensemble multiple linear regression (MLR) framework with 47 watershed traits is used to predict the linear regression coefficient of determination (r-squared) defining the ability of peak SWE to predict annual streamflow across all mountain basin. Predictor sets are constrained to avoid multicollinearity by excluding models with variance inflation factors (VIF) greater than 5. Mountain basin traits included in the MLR include seasonal climate, topography, vegetation type and structure, and bedrock geology. Accepted models are considered if their AIC is within 2.0 of the model with the minimum AIC, or best model. To compare predictor influence across acceptable models, we computed standardized regression coefficients. To evaluate structural redundancy among models, we constructed binary inclusion vectors for each acceptable model, denoting whether a predictor was present (1) or absent (0). Core predictor variables are defined as occurring in at least 67% of the acceptable models. For this regional analysis, only one model was found acceptable, with higher snow-to-streamflow translation (higher r-squared) occurring in colder mountain basins with higher relative winter precipitation, more snow accumulation and a lower fraction of annual precipitation that falls in the spring and summer. The second component of the data package uses previously published, high-resolution output from an integrated hydrological model of the East River watershed using the U.S. Geological Survey Groundwater and Surface water Flow model (GSFLOW, doi:10.15485/1998576). East River MLR expands upon the approach described above to explore the response of five streamflow metrics—annual streamflow, runoff efficiency, 7-day minimum flow, low-flow duration, and non-perennial stream fraction to snow system indicators including peak SWE, snow-covered area, snow disappearance date, and the fraction of basin area characterized by low-to-no snow, as well as seasonal precipitation and temperature, and annual hydrologic variables representing soil moisture, evapotranspiration (ET), the partitioning of incoming precipitation to evapotranspiration (ET/P), groundwater storage, and groundwater inflow to streams. MLR was done on all water years (P0: 1987-2024) and for each period as determined in the split analysis using pooled regression techniques (P1: 1987-2011 and P2: 2012-2024) to evaluate shifting predictor variable emphasis on streamflow generation. Results indicate that since 2012, peak SWE has lost statistical strength in its prediction of annual streamflow and runoff efficiency, and the indirect influence of spring temperature has emerged as critically important. Low-flow metrics remain largely influenced by soil moisture, vegetation water use and groundwater inflows with summer precipitation becoming a direct influence on minimum summer flow. Together, these data and Python-based analysis tools provide a framework for identifying the key watershed characteristics that control how streamflow responds to snow from year to year. The package also helps quantify uncertainty in statistical models and assess how snow–streamflow relationships vary across regions and over time. This dataset contains comma-separated values files (.csv), text files (.txt), python code files (.py), figure files (.png), and shapefiles (.cpg, .dbf, .prj, .sbn, .sbx, .shp, .xml). Further details on file contents and MLR execution can be found in the readme file and the FLMD files. Work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

VISSTPX2DRECTG16V4MINNIS (c1)

Satellite-based retrievals of cloud and radiation properties are available in this value-added product provided by Bill Smith’s group at NASA/Langley using the VISST (Visible Infrared Solar-Infrared Split Window Technique) algorithm. This product contains VISST-derived pixel-level products from the GOES-16 satellite, rectilinear projection 2-D array.

broadband LW flux↗
DOE OSTI2025

Conceptual Design of a Water Tank Critical Facility for SPARC

Critical experiments, sometimes referred to zero-power reactors, are crucial tools in developing and validating nuclear physics predictions and thus an indispensable capability to ensure criticality safety during all parts of the nuclear fuel cycle and in reducing uncertainties in reactor physics predictions toward optimizing nuclear energy production. The System Physics Advanced Reactor Facility (SPARC) project was recently initiated to enable large-scale criticality experiments using a horizontal split table machine well suited toward solid core materials systems (fuel, moderator, reflector). The facility selected for this mission was a former pool-type research reactor building and thus also well suited toward a second critical experiment capability able to house full-size light-water reactor (LWR) fuel bundles. A conceptual design study was undertaken to review past water tank critical experiments used for LWR physics experiments and to develop an early engineering design for a new critical assembly tank (CAT). The work described here shows that a relatively simple CAT concept can be constructed and deployed in the SPARC facility to meet the urgent demands for new critical experiments on advanced LWR fuel bundles designs. The SPARC facility layout is conducive to the receipt and upending of LWR fuel bundles using existing containers and equipment from the LWR industry. The facility’s overhead crane can then be used to handle fuel bundles and place them in a vertical storage rack or in the CAT for critical experiments, both of which fit within the building’s “open basement” alongside other equipment planned for SPARC and the horizontal split table. A slightly lower area in the basement can serve as a large drain tank so that fail-safe valves drain the CAT reactor tank for safe shutdown. Neutronic configurations were determined where a 3 × 3 array of fuel bundles can be surrounded by full-length “loose rods” to adjust reactivity so that critical is achieved when the bundles are fully submerged. Viable configurations were determined for both pressurized- and boiling-water-reactor-type fuel bundles. This design concept was used to develop an early planning basis for establishing the CAT capability alongside the otherwise planned SPARC project in order to help streamline the process. Recent presidential executive orders have highlighted the need to achieve power uprates in LWR plants and the CAT capability will be a crucial element of these initiatives. Based on the work described herein, it is recommended that an earnest and timely project begin in order to establish this urgently needed capability.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Tuneable electronic coupling in linked bis(cubane) cobalt-oxo clusters

A family of cobalt-oxo bis(cubane) complexes wherein each subunit is derived from the Co 4 O 4 cubane, a known water oxidation catalyst, was synthesized. Both 4,4′-bipyrdine and pyrazine were demonstrated to serve as viable bridging ligands. Through an analysis of their half-wave splitting potentials, it was determined that pyrazine-bridged bis(cubane)s exhibit inter-cubane electronic coupling, and that this coupling may be tuned through ligand substitution. Electrostatic contributions to the half-wave splitting potentials were evaluated and found to result in “non-conformist” behavior related to the ion-pairing ability of the electrolytes.

Maddi, Vincent J. P. [University of California, Be↗
DOE OSTI2025

Lessons Learned: Summary of Insights From the HERO WEC and Waves to Water Deployments Between 2022 and 2024

In 2020, a team from the National Renewable Energy Laboratory (NREL) partnered with the East Carolina University Coastal Studies Institute to develop a small, modular, wave-powered point absorber desalination prototype. That prototype, known as the hydraulic and electric reverse osmosis wave energy converter (HERO WEC), was intended to de-risk the installation activities planned for the Waves to Water Prize sponsored by the Water Power Technologies Office. The NREL team was given approximately 18 months to design, build, bench test, and deploy the HERO WEC prototype. Since the initial HERO WEC development, it has been used for two in-lab test programs and three ocean deployments. The first in-lab test program focused on ensuring that the overall operation of the device occurred as expected and on validating the operation of safety systems such as pressure relief valves or electrical breakers for load mitigation. The second in-lab test program was the first time the NREL team leveraged NREL’s large-amplitude motion platform to characterize the performance of the HERO WEC. Of the three in-water deployments, the first deployment was effectively an installation and recovery practice with no meaningful wave activity during the time that it was installed. The second deployment was a 2-week effort that enabled both the electric and hydraulic configurations of the device to be in the water for approximately 5 days each. This deployment was also the first time that the team had the opportunity to perform a drivetrain swap on the Coastal Studies Institute research vessel. The third deployment had to be split into two separate installations due to minor damage incurred from the WEC spinning during the initial installation. This report summarizes the deployments, the challenges encountered with each deployment, and the lessons learned for future work.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Melting LHC detectors: a novel search for stopped long-lived particles

Particles at the TeV scale with lifetimes of a year or longer could have been abundantly produced at the LHC yet escaped detection because of backgrounds, and could still be trapped within detector materials. With gluinos in split-supersymmetry as a working example, we show that these trapped particles can be recovered from detector materials once prepared in liquid form, for example, by melting silicon detectors, extracting liquid argon from the electromagnetic calorimeter, or constructing a large water pool near ATLAS or CMS. These liquid samples can then be processed using iterative centrifugation followed by mass spectrometry, enabling single-particle sensitivity in macroscopic samples. This method can potentially discover gluinos up to 3 TeV in mass at the HL-LHC. It can also improve upon existing limits for other long-lived particles. For example, it can discover the stop up to 2 TeV, and will also be sensitive to integer-charged particles in the TeV range.

Gonski, Julia L. [SLAC]↗
DOE OSTI2026

A Centralized AI Lakehouse Framework for Brain Tumor MRI Classification and Segmentation, University KPI Forecasting, and Water Potability Prediction

In many university and healthcare projects, models are built for very different data types such as tables, institutional time series, and medical images, but they are deployed as separate applications. In this work, that separation made testing and maintenance difficult because each module had its own pipeline and runtime requirements. This paper presents an integrated AI lakehouse-style implementation that runs three model pipelines inside one containerized backend. For medical imaging, we used MRI datasets from IEEE DataPort: a four-class classification set with 7012 images (5708 train/1304 test) and a segmentation set with 3063 image–mask pairs. The classification model (ResNet50 transfer learning) is evaluated using a proper train–validation–test protocol across multiple splits (80/10/10, 70/10/20, 60/10/30, and 10/30/60), achieving a test accuracy of 99.00% under the standard 80/10/10 split. Additionally, a patient-level evaluation is conducted using an external glioma dataset to provide a more realistic assessment without data leakage. The segmentation model (DeepLabV3-ResNet50) achieved 83.09% validation mIoU and 88.79% Dice score. For university KPI forecasting, we used annual IPEDS and NSF HERD data from 2010 to 2023 for three universities (BSU, EOU, and UAB). To examine the effect of preprocessing on forecasting performance, two case studies are conducted. In the first case, linear interpolation is applied to generate semester-level data. In the second case, the original annual data is used directly without interpolation. Random Forest regression and ARIMA models are evaluated using MAE, RMSE, MAPE, and R 2 . The results showed that interpolation improved apparent forecasting performance due to smoothing, while evaluation on the original annual data provided a more realistic assessment of model behavior. To further validate the framework on a larger dataset, an additional case study is conducted using a student dropout dataset. For water potability, we trained and compared multiple tabular classifiers on a large dataset (1,048,575 samples). A Random Forest model (100 trees, max depth 10) achieved 85.86% test accuracy and high recall for unsafe samples (0.8447). All modules are served via FastAPI and deployed together using Docker, with workflow automation routing requests to the correct endpoint. System-level benchmarking indicates that the backend maintains stable throughput and latency under concurrent requests.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

STAT7 v2.0 User Guide

The STAT7 software was developed to perform steady-state, single-phase thermal hydraulics analysis of plate-fueled reactors based on statistical propagation of uncertainties. Application of the software includes non-power research and test reactor analysis, and it has been used for the conversion to low- enriched uranium fuel of U.S. High Performance Research Reactors such as the Massachusetts Institute of Technology Research Reactor. Since it can be necessary to repeat reactor safety analysis, such as during fuel reloading, STAT7 accommodates flexibility in analyzing many practical aspects of reactor fuel management. STAT7 uses a Monte Carlo approach to model uncertainty in common fuel fabrication parameters and other key reactor operating parameters required for reactor thermal hydraulics analysis. These safety calculations are ultimately intended to protect against high fuel plate temperatures due to critical heat flux, or onset of flow instability. STAT7 supports water properties based on the IAPWS-IF97 functions (The International Association for the Properties of Water and Steam Industrial Formulation 1997 for the Thermodynamic Properties of Water and Steam) in addition to fitted functions. STAT7 predicts axial profiles of fuel, cladding, and coolant temperature along a lateral stripe that runs the full length of the fuel plate from the bottom to the top. STAT7 can simultaneously analyze every axial node in each lateral stripe of all fuel plates and coolant channels in every fuel element of an entire reactor core. Power splits are calculated for each axial node of each plate to determine how much of the power goes out each face of the plate. In a single execution, STAT7 can be used to perform full core analysis by analyzing the margin to onset of nucleate boiling and onset of flow instability for each axial node of each stripe of each plate of each fuel element in the core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

SCILLA Secondary Aerosol Volume Concentration Airborne Data

This data set contains secondary aerosol volume concentration in cubic micrometers per cubic centimeter (um^3/cm^3). The aerosol was generated in an oxidation flow reactor (OFR) and its volume concentration measured with a scanning mobility particle sizer (SMPS). Both components were designed and built at the University of California Riverside. Ambient particles were removed with a Teflon filter upstream of the OFR and then pure ammonium sulfate particles were added to create a stable aerosol surface area on which low-volatility oxidation products condense. High concentrations of hydroxyl radical (OH) formed inside the OFR accelerate the oxidative chemistry that would typically occur over a period of several days in the atmosphere, resulting in the production of secondary aerosol from precursor gases present in the ambient air. Concentrations of added ozone and water vapor were controlled to produce the desired and approximately constant level of photochemical aging. The reactor temperature was controlled, while the pressure was not, and was always slightly lower than that of the sampled outside air. Sampled air was pulled from above the Naval Postgraduate School’s (NPS) Twin Otter aircraft through a rear-facing, ¼” OD PFA Teflon tube. The sample stream was split between the OFR and several gas analyzers (NOx, CO, O3, and H2O). Though not contained in these files, data from an aerosol mass spectrometer intermittently operated downstream of the OFR are also available.

{"secondary aerosol concentration",aerosol_concent↗
DOE OSTI2024

STAT7 v1.2 User Guide: The STAT7 Code for Statistical Propagation of Uncertainties in Steady-State Thermal Hydraulics Analysis of Plate-Fueled Reactors

The STAT7 software was developed to perform steady-state, single-phase thermal hydraulics analysis of plate-fueled reactors based on statistical propagation of uncertainties. Application of the software is for non-power research and test reactors, including conversion to low-enriched uranium fuel of U.S. High-Performance Research Reactors such as Massachusetts Institute of Technology Research Reactor. Since it can be necessary to repeat analysis during fuel reloading, STAT7 accommodates flexibility in analyzing many realistic aspects of reactor fuel management. STAT7 uses a Monte Carlo approach to model uncertainty in common fuel fabrication parameters and other key reactor operating parameters required for thermal hydraulics analyses of research and test reactors. These safety calculations are ultimately intended to protect against high fuel plate temperatures due to critical heat flux, or onset of flow instability. STAT7 supports water properties based on the IAPWS-IF97 functions (The International Association for the Properties of Water and Steam Industrial Formulation 1997 for the Thermodynamic Properties of Water and Steam) in addition to the fit functions. STAT7 predicts axial profiles of fuel, cladding, and coolant temperature along a lateral stripe that runs the full length of the fuel plate from the bottom to the top. STAT7 can simultaneously analyze all of the axial nodes of all of the fuel plates and all of the coolant channels for one latera stripe of a fuel element. Power splits are calculated for each axial node of each plate to determine how much of the power goes out each face of the plate. By running STAT7 multiple times, full core analysis can be performed by analyzing the margin to onset of nucleate boiling and onset of flow instability for each axial node of each stripe of each plate of each fuel element in the core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Insights into the Complexation of Actinides by Diethylenetriaminepentaacetic Acid from Characterization of the Americium(III) Complex

Diethylenetriaminepentaacetic acid (DTPA) is a frequently used chelator in the nuclear and medical industries, especially for the complexation of trivalent actinides. However, structural data on these complexes in the solid-state have long remained elusive. Herein, a detailed structural analysis of the presented crystal structures of [C(NH 2 ) 3 ] 4 [Nd(DTPA)] 2 · n H 2 O and [C(NH 2 ) 3 ] 4 [Am(DTPA)] 2 · n H 2 O, where [C(NH 2 ) 3 ] + is guanidinium, details the subtle differences in the Lewis acidity between a lanthanide/actinide pair of similar ionic sizes. Contractions in nitrogen–metal bond lengths between neodymium(III) and americium(III) were observed, while the metal–oxygen bonds remained relatively consistent, highlighting the marginal favorability for actinide complexation over the lanthanides with moderately soft N-donors. Spectroscopic analysis shows significant splitting of many transitions and relatively strong electronic interactions with traditionally low-intensity transitions in the americium complex, as is demonstrated in the 7 F 0 → 7 F 5 transitions. Pressure-induced spectroscopic analysis showed surprisingly little effect on the americium complex, with 5 f →5 f transitions either not shifting or marginally shifting from 2 to 3 nm at 11.93 ± 0.06 GPa─atypical of a soft, N-donor americium complex under pressure. Finally, large voids occupied by water molecules in between the complexes within the crystal structure may be responsible for the lack of pressure response in the 5 f →5 f transitions.

absorption spectroscopy↗
DOE OSTI2024

Physics analysis and design of heavy water reflected thermal test reactor

Here, this work investigates the option of modifying the Advanced Test Reactor by replacing the current beryllium reflector with heavy water. Such a change may provide some potential benefits for not only increasing the thermal irradiation capabilities but also resolving other problems such as reflector integrity issues due to fast fluence damage, which is always a limiting factor in the lifetime of the current beryllium reflector. This paper presents the analysis and estimation of the ATR core physics parameters by replacing the current beryllium reflector with heavy water (D 2 O). The paper first describes the details of two selected conceptual designs, which are partially reflected with either beryllium or graphite, and how they are derived from the baseline beryllium reflector concept. Then, reactor physics performance parameters for the two new concepts are assessed by comparing with those of the baseline concept. The performance parameters considered in this paper include in-pile tube neutron and gamma fluxes and heating rates, maximum loop voiding reactivity, core power behavior with different power splits, predicted cycle length with a given fuel loading, and thermal hydraulic analysis with a higher lobe power split. It is important to note that this study focuses on the reactor physics aspects and does not delve into the engineering challenges associated with such a design modification.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

A Conjugated Oligoelectrolyte Exhibiting Room Temperature Spin-Correlated Radical Pair Character for Biological Sensing

We report a water-soluble conjugated oligoelectrolyte (COE) composed of carbazole-benzophenone, COE-CbzBP, that exhibits photogenerated spin-correlated radical pair (SCRP) behavior sensitive to static electric fields from DNA but not from lipid bilayers. The SCRP forms from a thermally activated, spin-polarized state enabled by partial π-conjugation disruption at the donor–acceptor (carbazole-benzophenone) nitrogen–carbon (N–C) junction, which facilitates a twisted intramolecular charge-transfer (TICT) geometry. This state minimizes the singlet–triplet energy gap (ΔE ST = 0.12 eV), radical–pair exchange coupling (J RP ∼ ΔE ST /2), and charge separation free energy (ΔG CS ) in both DNA (−0.19 eV) and lipid bilayers (−0.55 eV). Room-temperature continuous-wave electron paramagnetic resonance (CW-EPR) reveals a photogenerated spin-polarized singlet for COE-CbzBP that splits upon DNA association, consistent with modulation of J RP and hyperfine coupling (A x ), presumably via electric field-spin coupling. No spin-polarized signal was observed under dark, cryogenic conditions, or in liposomes, but was quenched by the spin trap 4-POBN. Transient absorption and spectroelectrochemistry confirmed magnetic-field sensitive long-lived excited-state absorption features attributed to charge-separated states 3 [Cbz •+ -BP •– ]*, which were lengthened by DNA, and quenched in lipid bilayers and 4-POBN. Quantum chemical simulations show that planar geometries (lipid-like) increase ΔE ST by 0.31 eV compared to TICT-optimized structures. This geometry-dependent modulation explains the absence of SCRP signatures in rigid environments, underscoring the importance of TICT states, minimized ΔE ST , and favorable ΔG CS for achieving room-temperature SCRP generation. These findings establish design principles for TICT-enabled molecules exhibiting qubit-like behavior that operate under ambient and biologically relevant conditions, with direct implications for quantum information science (QIS).

Aromatic compounds↗
DOE OSTI2025

Metagenome-assembled genomes from topsoils collected during NEON campaign in East River, CO (06/14/2018-06/28/2018)

The Watershed Function Science Focus Area (WF SFA) at Lawrence Berkeley National Lab is working to build a mechanistic understanding of the distribution and dynamics of biogeochemical processes in mountainous watersheds and their response to perturbation. In June 2018, the NEON (National Ecological Observatory Network) Airborne Observatory Platform (AOP) performed a taskable airborne imaging campaign to collect visible to shortwave infrared (VSWIR) imaging spectroscopy and LiDAR data across 330 km2 in the Upper East River at Crested Butte, CO. We conducted a parallel ground sampling campaign to sample vegetation traits, as well as soil physical, chemical, and microbiological characteristics. We collected these samples from 438 sites across 12 locations spanning much of the elevation, topographic, and geologic variability across the study area. A subset of 250 samples were used for soil metagenomics which is presented here. In addition, at each site, vegetation samples were collected to measure species-specific leaf water content and leaf mass area, foliar elemental composition and foliar CN stable isotope ratios. Soil samples were collected to measure soil physical properties which include bulk density and soil texture analysis. A suite of soil chemical properties was measured from the samples collected at each site, including pH, organic matter, concentrations exchangeable cations, total elemental composition, and the concentrations of extractable N pools (e.g. total free amino acids, ammonium, nitrate, dissolved organic N, and total dissolved N). Additionally, we have measured soil microbial biomass CN stoichiometry. Here, we present 1982 metagenome-assembled genomes (MAGs) for the bacterial and archaeal community from topsoil collected from during NEON 2018 campaign. All metagenomes were sequenced at JGI (Joint Genome Institute) (GOLD Study ID: Gs0149986). Metagenomes were assembled using JGI Metagenome Workflow (10.1128/mSystems.00804-20). The dataset includes (1) zip files for 1982 MAG fasta files (neon_genomes1-5.tar.gz, split into 5 tarballs to keep tarballs under 0.5 GB), (2) neon_Gs0149986_samples_soilproperties_metagenomes.csv: the sample information together with the accession numbers for the underlying metagenomes and the associated soil physical and chemical measurements in NMDC (National Microbiome Data Collaborative) compliant format, (3) neon_Gs0149986.kml: location bounding box file for the sampled locations, (4) samples.csv: sample metadata file used to register Internationall Generic Sample Numbers (IGSNs), (5) flmd.csv: file level metadata file, and (6) dd.csv: data dictionary file. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2024

International fuel performance study of fresh fuel experiments for PCMI effects during RIA experiments

This paper presents the results of High-burnup Experiments for Reactivity-initiated Accident (HERA) Modeling & Simulation (M&S) exercise. The HERA project under the Nuclear Energy Agency (NEA) Second Framework for Irradiation Experiments (FIDES-II) program is focused on studying Light Water Reactor (LWR) fuel behavior during Reactivity-Initiated Accident (RIA) conditions. The Part I M&S cases are based on a series of tests in the Transient Reactor Test (TREAT) facility in the United States and the Nuclear Safety Research Reactor (NSRR) in Japan. The purpose of this work is to evaluate the test design to accomplish its goals in establishing clearer understanding of the effects of power pulse width during RIA conditions. Further, the blind predictions using various computational tools have been performed and compared amongst to interpret the behaviors of high burnup fuels during RIA. While many international participants evaluate the thermal–mechanical behavior of fuel rod under different conditions, a considerable scatter of outputs comes out for the cases due to the disparity between codes in predicting mechanical behaviors. In general, however, the results of thermal–mechanical analysis elaborate that nominal design conditions the shorter pulse width tests in NSRR should cause cladding failures while the TREAT tests appear to have more split prediction of failure or not. Furthermore, the sensitivity analysis varying key testing parameters reveals the considerable effect of power pulse width and total energy deposition on prediction of fuel rod failure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗