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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An Experimental Investigation of Students’ Learning Effects When Using a Simplified Nuclear Simulator

Securing enough data has been a main challenge in human reliability analysis (HRA). Many researchers and institutes have made a lot of efforts for collecting HRA data to produce reasonable human error probabilities (HEPs) as well as reduce the uncertainty of HRA quantification. Representatively, U.S. Nuclear Regulatory Commission (U.S. NRC), Korea Atomic Energy Research Institute (KAERI) and Idaho National Laboratory (INL) have led lots of empirical research regarding the HRA data collection. The U.S. NRC and KAERI have mainly carried out full-scope simulator research collecting HRA data through experiments using full-scope simulators with actual operators. In contrast, INL has experimentally collected the data using simplified simulators and student operators. INL has proposed the Simplified Human Error Experimental Program (SHEEP) framework to complement full-scope data collection efforts by suggesting a way to infer full-scope data based on experimental data collected from students operating simplified simulators, specifically the Rancor Microworld Simulator (Rancor) and the Compact Nuclear Simulator (CNS). The aim of the SHEEP framework is to lower the entry point for collecting useful HRA data by securing large sample sizes at a reasonable amount of cost and labor while also guaranteeing a high degree of freedom when designing experiments. The authors’ previous research investigated whether data collected from the SHEEP framework could support a representative full-scope study. Besides, human performance differences between professional and student operators when using Rancor and CNS have been analyzed to understand the lack of fidelity of the simplified simulators and student operators within the SHEEP study. As a follow up research, this study experimentally investigates students’ learning effects and the performance trends over a certain period when using Rancor. This study aims to find out 1) how much training or education is required to collect HRA data from non-experts (i.e., students) when using Rancor and 2) how much differences there are in human performance measures between students and professional operators. In this study, a longitudinal experiment is developed. The four experiment trials with two weeks interval are carried out for sixteen undergraduate students majoring nuclear engineering at Chosun University. Totally four scenarios randomly selected from ten Rancor scenarios are used in each experiment trial. Four human performance measurements (i.e., workload, situation awareness, time and error) are considered in the experiment. Lastly, the trend of students’ performance is compared with operator data having been collected from the previous experiment.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

VTS Dynamic Model and Experimental Validation for Vibration Suppression

High Q-factor superconducting radio-frequency (SRF) cavities are extremely sensitive to mechanical vibrations, which can cause an uncontrolled shift of the electromagnetic resonance frequency, with detrimental effects on the cavity performance. To avoid this phenomenon (i.e. microphonics) the dynamic behavior of the assembly must be studied, to design vibration suppression systems. In this paper, the numerical model of the Vertical Test Stand (VTS) insert adopted at the Fermi National Accelerator Laboratory for cold tests was studied, in the framework of the experimental characterization of Dark SRF cavities conducted by the SQMS (Superconducting Quantum Materials and Systems) center. Due to the complexity of the assembly, experimental activity is of utmost importance to validate the model. Thus, vibration testing was performed on the actual system, and a good correlation between numerical and experimental results was found. Additionally, two different setups were compared, with and without implementing a preliminary passive vibration suppression system, to assess its effectiveness in reducing the microphonics phenomenon. The obtained results allowed for the design of an improved isolation system, which will be the subject of future experimental testing.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Assessment of buffer-IPyC thermomechanical debonding behavior using new experimental strength data in BISON

TRIstructural ISOtropic (TRISO) fuel is a nuclear fuel commonly used in High Temperature Gas-cooled Reactors (HTGRs). A single sub-millimeter-diameter TRISO fuel particle consists of a spherical fuel kernel surrounded by four coating layers: a low-density pyrocarbon buffer layer, an inner pyrolytic carbon (IPyC) layer, a silicon carbide (SiC) layer, and an outer pyrolytic carbon (OPyC) layer. The kernel is commonly made of UO2 or a mixture of uranium carbide and uranium oxide (UCO). During reactor operation, the TRISO coating layers are subjected to irradiation-induced dimensional changes and the associated thermomechanical behavior of each layer. One of the observed behaviors is gap formation between the buffer and IPyC layer due to the porous buffer’s irradiation-induced shrinkage exceeding that of the IPyC layer. Not all irradiated particles will experience buffer-IPyC gap formation. The debonding may be partial, or it may be nearly total. However, from post-irradiation examination of UCO TRISO fuels irradiated as part of the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program, it was concluded that partial buffer-IPyC debonding was the most common type of buffer-IPyC interaction. To predict TRISO thermomechanical performance, multi-physics models have been built that are being continually updated and refined. The BISON code is a finite element-based nuclear fuel performance code that may be used for 1D, 2D, and 3D TRISO particle simulations. This code is used to calculate fuel temperature, kernel swelling, buffer densification, thermal and irradiation creep, fracture, and fission gas production and release. One of the recent additions to the BISON code is the ability to model the process of layer debonding. This paper will focus on the simulation results of the improved BISON debonding model that will utilize updated strengths measured from irradiated AGR TRISO fuel particles. The new experimental strength data from micromechanical tests of irradiated TRISO fuel samples were exercised in the BISON simulations and compared to baseline strength data to assess their applicability in the models. This also includes updated buffer-IPyC bond strengths to simulate layer delamination. Based on current experimental observations it is noted that the buffer-IPyC separation occurs not exactly at the junction of these two layers, but more on the side of the buffer layer. That observation is also implemented in the TRISO interface debonding model. This improved modeling approach using experimental strength data to characterize buffer-IPyC debonding and its potential subsequent cracking will be presented in the paper along with comparisons to available experimental observations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Experimental and Computational Heat Transfer Study of sCO2 Single Jet Impingement

The present study experimentally investigates the heat transfer capability of supercritical carbon dioxide (sCO2) single-jet impingement. The evaluated jet Reynolds number range is between 80,000 and 1,000,000, with a non-dimensional jet-to-target surface spacing of 2.8. CO2- impinging jet stagnation conditions were maintained at approximately 20 MPa and a temperature of 673 K for most experiments. The goal is to understand how changes in the aforementioned parameters influence heat transfer between the working fluid and the heated surface. Additionally, due to the elevated Reynolds numbers and difference in thermodynamic properties between air and CO2, air-derived impingement correlations may not be appropriate for CO2 impingement; these correlations will be evaluated against experimental sCO2 impingement data. At the time of this study, no sCO2 impingement data was available relevant to sCO2 power cycles. The target surface is a 1.5-inch diameter copper block centered on the 3mm jet orifice. A mica heating element bolted to the bottom of the copper block provides a uniform heat flux. Thermocouples embedded in the copper block are used to determine the surface temperature. Nusselt numbers obtained from experimental sCO2 data are compared to area-averaged Nusselt numbers from air-derived correlations. The comparisons showed that air correlations drastically underpredict the heat transfer when sCO2 is used as the working fluid. A modified sCO2 correlation using experimental data at discussed conditions is derived based on an existing air correlation.

Richardson, John↗
DOE OSTI2023

A review of experimental methods to determine bioaerosol transfer in energy recovery ventilators

Increasing ventilation is an effective method to reduce indoor airborne disease transmission. An Energy recovery ventilator (ERV) is a passive energy recovery device used to reduce the energy consumption of heating, ventilation and air-conditioning (HVAC) systems for conditioning the ventilation air. It preconditions the ventilation air by transferring energy from building exhaust air. Therefore, the ventilation and exhaust air streams interact directly/indirectly in the ERV for energy transfer. It is surmised that the ERV may transfer bioaerosols (with pathogens) from the exhaust air to ventilation air, resulting in the spread of infectious diseases. Consequently, many pandemic HVAC guidelines recommend that the use of ERVs be limited. This is a highly unsustainable direction given the increased energy requirements associated with the high ventilation provision advocated for pandemic operation. It must be noted that no validated experimental evidence exists in literature for bioaerosol transfer in ERVs. Hence, it is necessary to conduct extensive bioaerosol transfer research before adopting the unsustainable practice of limiting the utilization of ERVs. The main objective of this review study is to summarize the experimental methods and instrumentation for bioaerosol transfer research in ERVs. This comprehensive article provides a detailed overview of the generation, sampling, and analysis of bioaerosols for conducting the experiments. Further, it explains the possible mechanisms for bioaerosol transfer in various types of ERVs based on which the ERVs that need immediate attention are identified. The main contribution of this research paper is that it provides a novel experimental method which encompasses the biosafety aspects, instrumentation, performance parameters and uncertainties in conducting virus contained bioaerosol transfer study in ERVs. The findings from this review will be helpful in designing bioaerosol transfer experiments and developing future ERV test standards for such experiments.

42 ENGINEERING↗
DOE OSTI2023

Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor

Electrochemical reduction of CO 2 gas is a novel CO 2 utilization technique that has the potential to mitigate the global climate crisis caused by anthropogenic CO 2 emissions, and enable the large-scale storage of energy generated from renewable sources in the form of carbon-based chemicals and fuels. However, due to the complexity of the electrochemical reactions, the explicit first-principles models for CO2 reduction are not available yet, and there has been a limited effort to develop process modeling, optimization and control of CO 2 electrochemical reactors. To this end, a rotating cylinder electrode (RCE) reactor has been constructed at UCLA to understand the mass transfer and reaction kinetics effects separately on the productivity. In the RCE reactor, the applied potential strongly influences the reaction energetics and the electrode rotation speed affects the hydrodynamic boundary layer and modifies the film mass transfer coefficient, which involves convective and diffusive transport. Further, the present work aims to develop a multi-input multi-output (MIMO) control scheme for the RCE reactor that integrates techniques from artificial and recurrent neural network modeling, nonlinear optimization, and process controller design. Specifically, production rates of two products from the experimental reactor, ethylene and carbon monoxide, are controlled by manipulating two inputs, applied potential and catalyst rotation speed. Process dynamics and controllability are analyzed, a feedback control strategy is designed and the controllers are tuned accordingly. The experimental electrochemical cell is employed to gather data for process modeling and implement the multivariable control system. Finally, the experimental results are presented which demonstrate excellent closed-loop performance by the control system and regulation of the outputs at three different set-points including an economically-optimal set-point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

NdPO 4 solubility and aqueous Neodymium speciation in supercritical fluids: An experimental study at 500–700 °C and 1.7 kbar

A key aspect in the formation of rare earth elements (REE) deposits is the role of REE transport as aqueous REE complexes in supercritical hydrothermal solutions, where the nature of the aqueous complex is controlled by solution composition, temperature and pressure. Despite chloride being considered as one of the most abundant transporting ligands in magmatic-hydrothermal fluids, experimental investigations on the stability of aqueous REE chloride complexes are scarce above 300 °C. In this study, synthetic NdPO 4 crystals were reacted with non-saline and saline (0, 0.05 and 0.5 mNaCl), acidic (0.01 mHCl) aqueous solutions in a series of solubility experiments conducted at 500–700 °C and 1.7 kbar, where the solubilities were determined using a stable Nd isotope ( 145 Nd isotope spike) dilution technique. NdPO 4 solubility ranges between 28 ppm and 10,858 ppm, where solubility increases with both temperature and salinity. At 500 °C, log mNdPO 4 increases from –3.93 to –1.60 and there is a strong correlation between NdPO 4 solubility and NaCl concentrations (slope of 1.2 ± 0.3), indicating stabilization of the Nd chloride aqueous complexes with a stoichiometry corresponding to NdCl 2+ . At 600 °C, this correlation is weaker (slope of 0.4, log mNdPO 4 increases from –2.63 to –1.88) indicating the stabilization of both Nd chloride and hydroxyl species controlling solubility. At 700 °C, NdPO 4 solubility is largely independent of NaCl concentration indicating that solubility is controlled by Nd hydroxyl complexes, where stoichiometry suggests the neutral Nd(OH) 3 0 species is dominant. The solubility product (Ksp) of NdPO4 is derived from experimental data with the relation: log K sp = -41.81 – 0.057T – 20987/T, with T temperature in Kelvin. Comparison of the measured Nd phosphate solubility to thermodynamic predictions using the available Helgeson-Kirkham-Flowers equation of state parameters for aqueous Nd complexes indicate that predictions are up to three orders of magnitude lower compared to experimental observations. This discrepancy is most pronounced in saline solutions, suggesting that thermodynamic properties of the REE chloride species in supercritical fluids require revision. Numerical simulations of fluid-rock interaction between acidic, saline fluids and a Strange Lake felsic mineral assemblage demonstrates that NdPO 4 solubility predictions from models are four to six orders of magnitude lower than those calculated based on empirical fits from experiments, which suggests that acidic, saline fluids may play an important role in mobilizing large amounts of light REE from 450 to 700 °C.

58 GEOSCIENCES↗
DOE OSTI2022

Experimental validation of a high fidelity Monte Carlo neutron transport model of the MIT graphite exponential pile

High-fidelity modeling and simulation were performed for the MIT graphite exponential pile (MGEP) using Monte Carlo neutron transport codes OpenMC and MCNP, and the results were validated by experimental data. The MGEP is being used as the test bed for the design of an autonomous control system for the pile's neutron flux distribution. The main contribution of this work is to generate the training data sets of neutron flux distributions with different locations of control rods that perturb the neutron flux profiles. First, code -to-code cross verification between OpenMC and MCNP was performed to ensure consistency of the numerical modeling within statistical uncertainties. To validate the accuracy of this high-fidelity model, a series of neutron flux measurements were conducted using a Helium-3 (He-3) neutron detector on a mobile platform that is placed inside the pile. Second, the neutron flux profiles were measured in four vertical layers of interest, and compared to the corresponding simulation results. The comparison results shows that the root mean square error is less than 2.5% in the two upper layers, and less than 4.5% in all four measured layers. Here the results validated the accuracy of the modeling and simulation. Finally, the relative change of the neutron flux profiles from moving control rods was analyzed, which identified the layer that has the best sensitivity regarding the control rods movements. Thus, this work identified and provided training data sets of both simulated and experimental neutron flux profiles in the most sensitive layer, paving the path forward to the real-time experimental demonstration of the autonomous control system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Bayesian experimental design and parameter estimation for ultrafast spin dynamics

Abstract Advanced experimental measurements are crucial for driving theoretical developments and unveiling novel phenomena in condensed matter and materials physics, which often suffer from the scarcity of large-scale facility resources, such as x-ray or neutron scattering centers. To address these limitations, we introduce a methodology that leverages the Bayesian optimal experimental design paradigm to efficiently uncover key quantum spin fluctuation parameters from x-ray photon fluctuation spectroscopy (XPFS) data. Our method is compatible with existing theoretical simulation pipelines and can also be used in combination with fast machine learning surrogate models in the event that real-time simulations are unfeasible. Our numerical benchmarks demonstrate the superior performance in predicting model parameters and in delivering more informative measurements within limited experimental time. Our method can be adapted to many different types of experiments beyond XPFS and spin fluctuation studies, facilitating more efficient data collection and accelerating scientific discoveries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis

Implementing remote, real-time spectroscopic monitoring of radiochemical processing streams in hot cell environments requires efficiency and simplicity. The success of optical spectroscopy for the quantification of species in chemical systems highly depends on representative training sets and suitable validation sets. Selecting a training set (i.e., calibration standards) to build multivariate regression models is both time- and resource-consuming using standard one-factor-at-a-time approaches. This study describes the use of experimental design to generate spectral training sets and a validation set for the quantification of sodium nitrate (0–1 M) and nitric acid (0.1–10 M) using the near-infrared water band centered at 1440 nm. Partial least squares regression models were built from training sets generated by both D- and I-optimal experimental designs and a one-factor-at-a-time approach. The prediction performance of each model was evaluated by comparing the bias and standard error of prediction for statistical significance. D- and I-optimal designs reduced the number of samples required to build regression models compared with one-factor-at-a-time while also improving performance. Models must be confirmed against a validation sample set when minimizing the number of samples in the training set. The D-optimal design performed the best when considering both performance and efficiency by improving predictive capability and reducing number of samples in the training set by 64% compared with the one-factor-at-a-time approach. The experimental design approach objectively selects calibration and validation spectral data sets based on statistical criterion to optimize performance and minimize resources.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

DOE Microreactor Program: Summary of Experimental Capabilities Development and Activities

This document provides a summary of the experimental capabilities and activities developed and currently performed under the U.S. Department of Energy’s (DOE’s) Microreactor Program. These capabilities, along with other laboratory capabilities, are available to support developer and other stakeholder needs. Specific experimental capabilities described in this document include the single primary heat extraction and removal emulator (SPHERE), the microreactor agile non-nuclear experimental test bed (MAGNET), microreactor applications research validation and evaluation (MARVEL), yttrium hydride fabrication, the Hypatia critical experiment series, and a brief overview of the National Criticality Experiments Research Center (NCERC), which provides the platform to conduct experiments and training with critical assemblies and fissionable material.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

SPRUCE High-Resolution Minirhizotrons in an Experimentally-Warmed Peatland Provide an Unprecedented Glimpse at Fine Roots and their Fungal Partners: Supporting Data

Images were collected using first of their kind, non-destructive, high-resolution automated minirhizotrons (RhizoSystems, LLC) to assess the response of plant fine-root and fungal mycelium dynamics to elevated temperatures after 4-6 years of whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (e[CO2]) in a peat bog where the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment is located. We focused on two SPRUCE experimental plots: Plot 10 has elevated temperature (+9°C) and plot 19 is a control (+0°C). Both have elevated carbon dioxide (e[CO2]). Changes in root and fungal abundance with warming were estimated from a timeseries of landscape-level mosaiced images for each plot by measuring the proportional abundance of five belowground classes: fine roots of vascular plants, ectomycorrhizas, fungal hyphae, fungal rhizomorphs, and fungal sporocarps. To examine root and fungal phenology responses to warming, the length per individual root or fungal structure (except fungal hyphae that did not grow linearly but rather increased in areal coverage) were measured per image area of a set of timeseries patch-level mosaiced images for each plot. The experimental work was conducted in a Picea mariana [black spruce] – Sphagnum spp. bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). This ecosystem, which is located at the southern margin of the boreal forest, is considered especially vulnerable to climate change and anticipated to be near its tipping point. These data were used in analyses published in Defrenne et al (2021). This dataset contains 5 data files in comma-separate values (*.csv) format and a compressed folder (*.zip) containing 383 JPEG (*.jpg) images. Data files contain landscape-level assessment of belowground class abundance, patch-level growth phenology, and environmental variables (originally published in Hanson et al., 2016 and Hanson et al 2020). Images were collected with automated minirhizotrons and analyzed for phenology. Additional metadata are provided: 5 data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

SPRUCE Redox-Active Subsurface Organic Matter, Marcell Experimental Forest, Minnesota, 2023

This dataset contains measurements that report on the effects of the SPRUCE experimental treatments on redox-active organic matter (RAOM) reduction (Valenzuela and Cervantes, 2021). Measurements occurred at the SPRUCE Experiment site in the Marcell Experimental Forest in northern Minnesota, USA. This work is also a follow-up to Rush et al. (2021a) which investigated effects of temperature on RAOM reduction after two years of experimental warming (Rush et al. 2021b). This follow-up dataset addresses two main questions; (i) How does warming and elevated carbon dioxide (CO2) directly affect in situ RAOM reduction, and subsequent methane (CH4) and CO2 production, across the peat depth profile? and (ii) How has long-term warming and elevated CO2 changed the total RAOM pool, and subsequent CH4 and CO2 production, across the peat depth profile? This dataset reports electron shuttling capacity (a proxy for RAOM reduction; Keller, and Takagi, 2013) and carbon dioxide (CO2) and methane (CH4) concentrations both in one-week in situ incubations (2023-05-31 to 2023-08-01) and 42-day laboratory incubations from peat collected in 2023 (2023-05-31 to 2023-06-26). Laboratory incubations also measured acetate concentrations. The 2023 laboratory incubations were also compared with laboratory incubations conducted on peat collected in 2016 (Rush et al. 2021b). This dataset contains three data files in comma-separate (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

BISON Simulated and Experimental Fission Product Release Comparisons from Reradiated AGR-3/4 Compacts During High Temperature Heating Tests

The fuel performance modeling code BISON was used to predict the release of fission products iodine-131 (131I), xenon-133 (133Xe), and krypton-85 (85Kr) from four re-irradiated AGR-3/4 fuel compacts containing tristructural isotropic (TRISO) coated particles during high-temperature isothermal heating tests. The AGR-3/4 fuel compacts were irradiated in the Advanced Test Reactor (ATR) as part of the third and fourth series of planned experiments to support the Advanced Gas Reactor (AGR) Program. They were subsequently stored and re-irradiated in the Neutron Radiography (NRAD) reactor for approximately five days and then stored for another five to eight days before being subjected to isothermal heating tests in the Fuel Accident Condition Simulation (FACS furnace) for 200 to 300 hours at temperatures between 1000°C and 1600°C to evaluate fission product release at elevated temperatures. New nuclide-specific fission product source term models for the three nuclides of interest were developed using the reactor multiphysics code Griffin and implemented into BISON to support this work. The new source term models were incorporated into coupled compact- and particle-scale BISON simulations, which predict spatially- and temporally-resolved radionuclide generation, radioactive decay, transport, and release throughout the entire irradiation history, including the initial ATR irradiation, NRAD re-irradiations, FACS heating tests, and intermediate periods spent in storage. The experimentally measured fission product release from the heating tests were compared to modeling release predictions calculated by BISON to evaluate how well the code compares to experimental results. Overall, the experimental measured and BISON predicted comparative release results varied but generally agreed to within 5 particle equivalents. Comparative release results identified general observations to take into consideration to help refine future models and reduce uncertainties associated with both the measurement results and predictive results. This includes developing new uranium oxycarbide (UCO) specific kernel diffusivities for the three isotopes examined to more accurately reflect the material properties of the fuel form. Deriving new diffusivities will aid in producing a more informed BISON model

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Surface Segregation Studies in Ternary Noble Metal Alloys: Comparing DFT and Machine Learning with Experimental Data

Abstract Surface segregation, whereby the surface composition of an alloy differs systematically from the bulk, has historically been hard to study, because it requires experimental and modeling methods that span alloy composition space. In this work, we study surface segregation in catalytically relevant noble and platinum‐group metal alloys with a focus on three ternary systems: AgAuCu, AuCuPd, and CuPdPt. We develop a data set of 2478 fcc slabs with those compositions including all three low‐index crystallographic orientations relaxed with Density Functional Theory using the PBEsol functional with D3 dispersion corrections. We fine‐tune a machine learning model on this data and use the model in a series of 1800 Monte Carlo simulations spanning ternary composition space for each surface orientation and ternary chemical system. The results of these simulations are validated against prior experimental surface segregation data collected using composition spread alloy films for AgAuCu and AuCuPd. Our findings reveal that simulations conducted using the (110) orientation most closely match experimentally observed surface segregation trends, and while predicted trends qualitatively match observation, biases in the PBEsol functional limit numeric accuracy. This study advances understanding of surface segregation and the utility of computational studies and highlights the need for further improvements in simulation accuracy.

Chemistry↗
DOE OSTI2020

Tropical understory herbaceous community responds more strongly to hurricane disturbance than to experimental warming

The effects of climate change on tropical forests may have global consequences due to the forests’ high biodiversity and major role in the global carbon cycle. In this study, we document the effects of experimental warming on the abundance and composition of a tropical forest floor herbaceous plant community in the Luquillo Experimental Forest, Puerto Rico. This study was conducted within Tropical Responses to Altered Climate Experiment (TRACE) plots, which use infrared heaters under free-air, open-field conditions, to warm understory vegetation and soils + 4°C above nearby control plots. Hurricanes Irma and María damaged the heating infrastructure in the second year of warming, therefore, the study included one pretreatment year, one year of warming, and one year of hurricane response with no warming. We measured percent leaf cover of individual herbaceous species, fern population dynamics, and species richness and diversity within three warmed and three control plots. Results showed that one year of experimental warming did not significantly affect the cover of individual herbaceous species, fern population dynamics, species richness, or species diversity. In contrast, herbaceous cover increased from 20% to 70%, bare ground decreased from 70% to 6%, and species composition shifted pre to posthurricane. The negligible effects of warming may have been due to the short duration of the warming treatment or an understory that is somewhat resistant to higher temperatures. Our results suggest that climate extremes that are predicted to increase with climate change, such as hurricanes and droughts, may cause more abrupt changes in tropical forest understories than longer-term sustained warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Vibrational Spectra of HNIW and its Isotopologues: A Combined Experimental and Computational Study

Incorporating isotopically labelled materials in degradation experiments could help unravel the mechanism(s) of decomposition through use of the kinetic isotope effect. Characterizing synthesized isotopologues however requires an understanding of what observable signals are affected by the isotopic substitution. As vibrational spectroscopy can distinguish between isotopologues, it is an ideal characterization technique to evaluate isotopic variants. To this end, the vibrational spectra of HNIW and its deuterated ( 2 H), 13 C, 15 N (all), 15 N (nitro), and 18 O isotopologues have been computationally predicted in the gas phase using density functional theory. These results are compared to experimentally measured FTIR/ATR and Raman spectra of both unsubstituted HNIW and 15 N-labeled HNIW in which the six nitro groups were synthetically tagged with 15 N atoms ( 15 N nitro -HNIW). The experimental isotopic frequency shift for the -NO 2 asymmetric stretching frequencies agrees with that theoretically calculated (~35.7 cm-1 vs. 36.5cm-1, respectively). Furthermore, analysis of the theoretically predicted frequency shifts for all isotopologues suggest the -NO 2 bending modes are lower in frequency than previously reported. This assignment is supported by the experimentally measured isotopic shift of ~10.1 cm -1 for these features (consistent with the predicted shift of ~13.1 cm -1 ). This work expands our current understanding of the vibrational modes in HNIW as well as provides a method for future work on similar systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hydroxyl radical‐driven transformations of bisphenol A and 2,4‐dinitroanisole: Experimental and computational analysis

Abstract This study used experimental and computational analysis to investigate the advanced oxidation of bisphenol A (BPA) and 2,4‐dinitroanisole (DNAN). The pseudo first‐order reaction rate constants depended on the molar peroxide ratio and were between 0.13 and 0.28 min −1 for BPA and between 0.018 and 0.032 min −1 for DNAN. The kinetic differences appear to be due in part to the energy requirements for oxidation, which depended on the reaction mechanism but were typically lower for BPA than they were for DNAN. Density functional theory (DFT) was used to develop transformation pathways that included experimentally‐detected byproducts. The most energetically favored pathway for BPA oxidation begins with the formation of hydroxylated derivatives, while for DNAN, the most energetically favorable degradation pathway begins with the substitution of the methoxy group. Overall, these findings demonstrate the power of combining experimental and computational tools to reveal transformation mechanisms during water treatment. Practitioner Points Advanced oxidation transformations for two emerging water pollutants, bisphenol A and dinitroanisole, was investigated. The observed reaction kinetics depended on molar peroxide ratio in a manner that is in keeping with previous findings. Density functional theory‐based analysis revealed reaction energy requirements and degradation pathways.

Engineering↗