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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 OSTI2022

Atomic-scale quantum sensing based on the ultrafast coherence of an H 2 molecule in an STM cavity

A scanning tunneling microscope (STM) combined with a pump-probe femtosecond terahertz (THz) laser can enable coherence measurements of single molecules. We report THz pump-probe measurements that demonstrate quantum sensing based on a hydrogen (H 2 ) molecule in the cavity created with an STM tip near a surface. Atomic-scale spatial and femtosecond temporal resolutions were obtained from this quantum coherence. The H 2 acts as a two-level system, with its coherent superposition exhibiting extreme sensitivity to the applied electric field and the underlying atomic composition of the copper nitride (Cu 2 N) monolayer islands grown on a Cu(100) surface. We acquired time-resolved images of THz rectification of H 2 over Cu 2 N islands for variable pump-probe delay times to visualize the heterogeneity of the chemical environment at sub-angstrom scale.

Science & Technology - Other Topics↗
DOE OSTI2022

Pathways to a Sustainable Aviation Ecosystem: Flight DNA: An Anonymized Aviation Data Tool and Repository

The National Renewable Energy Laboratory (NREL) has deep experience developing secure, national data repositories, which it augments with analysis, technology and market expertise, high-performance computing, and innovative data visualization. By adapting the architecture of existing mobility databases (i.e., Fleet DNA, the Transportation Secure Data Center, the National Fuel Cell Technology Evaluation Center), NREL can build a powerful aviation data clearinghouse - Flight DNA - that helps stakeholders navigate the web of pitfalls and possibilities generated by new aviation technologies.

aviation↗
DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

MultiTaskDeltaNet: change detection-based image segmentation for operando ETEM with application to carbon gasification kinetics

Transforming in situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often face limitations due to the scarcity of labeled data, visually ambiguous features of interest, and scenarios involving small objects. To tackle these challenges, we introduce MultiTaskDeltaNet (MTDN), a novel deep learning architecture that creatively reconceptualizes the segmentation task as a change detection problem. By implementing a unique Siamese network with a U-Net backbone and using paired images to capture feature changes, MTDN effectively leverages minimal data to produce high-quality segmentations. Furthermore, MTDN utilizes a multi-task learning strategy to exploit correlations between physical features of interest. In an evaluation using data from in situ environmental TEM (ETEM) videos of filamentous carbon gasification, MTDN demonstrated a significant advantage over conventional segmentation models, particularly in accurately delineating fine structural features. Notably, MTDN achieved a 10.22% performance improvement over conventional segmentation models in predicting small and visually ambiguous physical features. This work bridges key gaps between deep learning and practical TEM image analysis, advancing automated characterization of nanomaterials in complex experimental settings.

08 HYDROGEN↗
DOE OSTI2024

In-Line Optical Transmission Imaging of Decals for Quality Control - Task 3

Quality monitoring is a critical aspect for manufacturing systems. Ideally the monitoring would be done in-line, be non-contact, non-destructive, and fast. This would enable reduced scrap and higher throughput. This poster presents an optical transmission method for evaluating and mapping coatings. With the method shown in the poster we can visualize optical variations on the macro and micro scales. This allows us to see the overall trend in loading in both the cross web and down web directions. Furthermore, we can visualize defects such dewetting spots, streaks, clumps, and pinholes where there is a lack of coating. The optical transmission signal has been found to be proportional to the IrOx loading signal using XRF measurements. Therefore, an optical transmission setup can be installed in-line and allow for a fast, non-contact method for mapping loading variations and defects.

coating uniformity↗
DOE OSTI2021

Validation of the HyRAM+ physics models for use with propane

The Hydrogen Risk Assessment Model Plus (HyRAM+) toolkit combines quantitative risk assessment with simulations of unignited dispersion, ignited turbulent diffusion flames, and indoor accumulation with delayed ignition of fuels. HyRAM+ is differentiated from HyRAM in that it includes models and leak data for other alternate fuels. The models of the physical phenomena need to be validated for each of the fuels in the toolkit. This report shows the validation for propane which is being used as a surrogate for autogas, which is a mixture of propane and butane and used in internal combustion engines in vehicles. For flame length comparisons, five previously published experiments from peer reviewed journals were used to validate our models. The validation looked at flame lengths and flame widths with respect to different leak diameters, mass flow rates, and source pressures. Most of the sources included more than one set of experimental data, which were collected using different methods (CCD cameras, IR visualization etc.). In general, HyRAM+ overpredicts the flame lengths by around 65%. For heat and radiation models, we compared the heat flux and radiation data reported from two different sources to the values calculated by HyRAM+. For higher mass flow rates, the HyRAM+ calculated flame length results gave a better estimate of what is found in the experiments (65% error), but a higher error (85%) is observed between the HyRAM+ calculated lengths and the experimental flame lengthsfor lower mass flows. Some differences can be attributed to outdoor environmental effects (i.e. wind speed) and uncertainties in jet flame shapes. The propane flame trajectory is predicted for a high Reynolds number case with Re = 12,500 and a low Reynolds number case where Re = 2,000. The Re=12,500 case which is momentum dominated matches well with the experimental flame trajectory, but the agreement for the bouancy driven low Reynolds number case is not as good. Dispersion modeling for unignited propane was also analyzed. We compared the mole fraction, mixture fraction, mean velocity, concentration half width, and inverse mass concentration over an axial distance from different credible journals to the values calculated by HyRAM+. The results display good agreement but generally, HyRAM+ predicts a wider profile for mole fraction and mixture fraction experiments. Overall, HyRAM+’s results are reasonable for predicting the flame length, heat flux, flame trajectory, and dispersion for propane and can be used in risk analyses

08 HYDROGEN↗
DOE OSTI2024

Coupled Transport, Reactivity, and Mechanics in Fractured Shale Caprocks

Abstract Shales are low‐permeability caprocks that confine fluid, such as CO 2 , nuclear waste, and hydrogen, in storage formations. Stress‐induced fractures in shale caprocks provide pathways for fluid to leak and potentially contaminate fresh water aquifers. Fractured shales are also increasingly considered as resources for CO 2 sequestration, enhanced geothermal, and unconventional energy recovery. Injecting reactive fluids into shales introduces chemical disequilibrium, causing an onset of a series of dissolution, precipitation, and fines mobilization mechanisms. The reactions have rapid kinetics and significant impact on porosity and permeability; consequently, flow and storage properties of caprocks. While previous research has explored the separate effects of these reactions, this study aims to uncover their simultaneous occurrence and collective influence. This study unveils these highly coupled transport and reactivity mechanisms by tracking and visualizing the reaction‐induced alterations in the matrix, microcracks, and fractures of shales over time. We conducted brine injection experiments sequentially at pH 4 and 2 in a naturally fractured Wolfcamp shale sample while simultaneously imaging the dynamic processes using X‐ray computed tomography (CT). CT images are validated by finer resolution images obtained using micro‐CT and scanning electron microscopy. We also tracked the sample permeability and fluid chemistry using brine permeability and inductively coupled plasma mass spectrometry, respectively. Findings show that fluid primarily flowed through fractures, dissolving reactive minerals and mobilizing fines on fracture surfaces. Dissolution of fracture asperities under confining stress resulted in the closing of fractures. Clogging in narrow fracture pathways, caused by fines accumulation, diverted fluid flow into matrix pores.

58 GEOSCIENCES↗
DOE OSTI2020

Development of a Testbed for Pipeline Flushing - 20425

Pipelines which carry high-level waste within the DOE complex should be properly flushed in the cases where stationary or moving beds of solid sediment occur, or lines are prone to hydrogen gas buildup. Present guidelines establish a minimum for the amount of water (flush volume) and flush velocity values used for post-transfer flushing operations to achieve satisfactory cleaning of pipelines. However, further studies are needed to find optimal operating velocity modes/values in order to minimizing the flush volume and consequent downstream waste. These efforts are significantly helpful to DOE waste remediation sites by preserving tank storage, preventing additional waste processing, and minimizing dilution and changes in waste chemistry. An experimental test loop was recently developed for study of non-Newtonian slurry flushing at the Florida International University (FIU). This loop was designed to create sediment beds of various materials and bed heights and investigate parameters that effect the efficiency of flushing operations. The objective is to find flush velocity values/modes which lead to satisfactory cleaning of transport lines with a minimum amount of water usage. A 165 ft experimental test loop made of 3-inch carbon steel pipes was constructed and used in initial testing campaigns. This pipe loop was equipped with real-time monitoring instruments to record variation of pressure, density, mass flow rate, and temperature during testing. Post-flush in-situ no-flow evaluations were performed using ultrasonic, endoscopy, and visual inspection. Additional post-flush evaluations were conducted using filtration and density monitoring of residuals within a designated circulations loop. These provisions enable comparison of pipeline cleanness before the start and after termination of flushing operations for efficiency evaluation. This paper presents efforts associated with flushing of kaolin-water mixtures at different concentrations and with various flush volume and flush velocity values/modes. In initial testing, efforts focused on creating repeatable sediment beds inside the pipeline in both fully-flooded (no pre-flush drainage) and gravity-drained (pre-flush drained) systems. Bed characterization (i.e., measurement of sediment height and solids concentration) was conducted to ensure about consistency of initial conditions between tests. Preliminary results for flushing study of 10% vol. kaolin-water mixtures starting from a fully-flooded initial condition showed that flushing with 1-line volume (65 gallons) could remove up to 72 percent of solids from the pipeline. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Skeletides: A Modular, Simplified Physical Model of Protein Secondary Structure

Three-dimensional (3D) models are essential for visualization and conceptual understanding of complex architectures such as protein structure. Although there is a plethora of software platforms that allow digital depictions of protein structure at an atomic level in silico, physical models are needed to convey an intuitive understanding of biomolecular architecture. However, it is a challenge to represent all the relevant features of proteins in a single physical model due to their sheer structural complexity. Here, we describe a modular protein model that focuses only on representation of the secondary structure—the underlying structural skeleton. The simplified model consists of amino acid units, which can be linked together to reproduce the two most fundamental structural features of protein secondary structure: the relative positions of the amino acid alpha carbon atoms, and the intra-main chain hydrogen bonding pattern. We use 3D printing and magnets to create a set of three modular amino acid building blocks, which when linked together into a chain, can faithfully represent alpha helices, beta sheets, and turns. These simple to make models can be used to quickly assemble the alpha carbon trace of an entire protein domain, which conveys a tactile experience of the complexity of protein skeletal architecture. These models highlight the modularity of protein structure: where a single structural unit, the amino acid, can be linked together to form a larger, regular secondary structure. These models also have a propensity to spontaneously organize into alpha helices and beta sheets, as demonstrated by their ability to autonomously assemble when placed in a circulating water tank. These models provide a missing educational tool to expand knowledge of protein structure, foster deeper insight into protein folding, and inspire greater interest in biomacromolecular architecture.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Surface chemistry of neutron irradiated tungsten in a high-temperature multi-material environment

Deuterium retention was measured on neutron irradiated tungsten samples where one side of the samples had a visually clean metallic luster and the opposite side appeared to have a reacted surface film. Deuterium plasma exposure and subsequent thermal desorption from the reacted surface side produced spectra with larger total deuterium desorption at lower temperatures than from the clean surface side. For neutron irradiation, these W disk samples were installed in an irradiation capsule in such a way that one side of W sample was in contact with the surface of another W sample, and the opposite side was in contact with a SiC temperature monitor. The composition of the reacted surface was investigated using X-ray photoelectron spectroscopy and showed that SiC had interdiffused into the W samples. Neutron enhanced diffusion likely contributed to this as SiC and W are stable at temperatures exceeding the irradiation temperature. Results highlight the need to consider the surface chemistry of samples in drawing conclusions on hydrogen isotope retention of W materials and also illustrate the complexity of multi-material nuclear environments expected in fusion devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

2023 Real-time Optimization Workflow Status Update

Nuclear integrated energy systems are composed of a diverse set of energy generation sources and exist in dynamic and competitive electricity markets. With the inclusion of thermal energy storage, nuclear power systems can store heat for future use through various processes, such as water desalination or hydrogen generation. This heat storage can be managed in such a way as to economically optimize its usage. By combining real-time price data from the day-ahead and real-time markets with predictive and intelligent models, the charging and discharging of the thermal energy storage may be determined and optimized. This research details an approach through models and systems for the real-time optimization (RTO) of capacity allocation. Virtual models of the energy system and its physics phenomenon and component interactions provide intelligence to verification and prediction of operations. An optimization framework can use data generated from both a set of physical assets as well as the virtual models to predict future performance and create optimization and control workflows. Data warehouse technologies can be used to combine data across models, optimization workflows, market price data, and sensor data to intuitively store various types of data and provide integrations to physical control systems as well as user visualizations. Put together, these components can create a system for the RTO of nuclear integrated energy systems. Various virtual models and bench-scale physical demonstrations have been successfully performed and verified using this system. Larger scale testbeds that include thermal energy storage systems have been identified as future opportunities. A gap analysis that details the steps necessary to reach a physical demonstration at this scale is provided, along with conclusions on the current effort and future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

2D-to-3D image translation of complex nanoporous volumes using generative networks

Image-based characterization offers a powerful approach to studying geological porous media at the nanoscale and images are critical to understanding reactive transport mechanisms in reservoirs relevant to energy and sustainability technologies such as carbon sequestration, subsurface hydrogen storage, and natural gas recovery. Nanoimaging presents a trade off, however, between higher-contrast sample-destructive and lower-contrast sample-preserving imaging modalities. Furthermore, high-contrast imaging modalities often acquire only 2D images, while 3D volumes are needed to characterize fully a source rock sample. In this work, we present deep learning image translation models to predict high-contrast focused ion beam-scanning electron microscopy (FIB-SEM) image volumes from transmission X-ray microscopy (TXM) images when only 2D paired training data is available. We introduce a regularization method for improving 3D volume generation from 2D-to-2D deep learning image models and apply this approach to translate 3D TXM volumes to FIB-SEM fidelity. We then segment a predicted FIB-SEM volume into a flow simulation domain and calculate the sample apparent permeability using a lattice Boltzmann method (LBM) technique. Results show that our image translation approach produces simulation domains suitable for flow visualization and allows for accurate characterization of petrophysical properties from non-destructive imaging data.

58 GEOSCIENCES↗
DOE OSTI2024

Datasets and U-Net Model for "A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma"

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Artificial Intelligence↗
DOE OSTI2021

Structure and assembly of the diiron cofactor in the heme-oxygenase–like domain of the N-nitrosourea–producing enzyme SznF

In biosynthesis of the pancreatic cancer drug streptozotocin, the tridomain nonheme-iron oxygenase SznF hydroxylates N δ and N ω ' of N ω -methyl- L -arginine before oxidatively rearranging the triply modified guanidine to the N-methyl-N-nitrosourea pharmacophore. A previously published structure visualized the monoiron cofactor in the enzyme’s C-terminal cupin domain, which promotes the final rearrangement, but exhibited disorder and minimal metal occupancy in the site of the proposed diiron cofactor in the N-hydroxylating heme-oxygenase–like (HO-like) central domain. We leveraged our recent observation that the N-oxygenating µ-peroxodiiron(III/III) intermediate can form in the HO-like domain after the apo protein self-assembles its diiron(II/II) cofactor to solve structures of SznF with both of its iron cofactors bound. These structures of a biochemically validated member of the emerging heme-oxygenase–like diiron oxidase and oxygenase (HDO) superfamily with intact diiron cofactor reveal both the large-scale conformational change required to assemble the O 2 -reactive Fe 2 (II/II) complex and the structural basis for cofactor instability—a trait shared by the other validated HDOs. During cofactor (dis)assembly, a ligand-harboring core helix dynamically (un)folds. The diiron cofactor also coordinates an unanticipated Glu ligand contributed by an auxiliary helix implicated in substrate binding by docking and molecular dynamics simulations. The additional carboxylate ligand is conserved in another N-oxygenating HDO but not in two HDOs that cleave carbon–hydrogen and carbon–carbon bonds to install olefins. Among ~9,600 sequences identified bioinformatically as members of the emerging HDO superfamily, ~25% conserve this additional carboxylate residue and are thus tentatively assigned as N-oxygenases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A fresh perspective on the role of band bending, and related contributors, in light-driven production of electricity and chemicals

It is widely known that semiconductor-based solar energy conversion could power our planet. This is in part because high-quality semiconductor structures are unrivalled in their ability to separate photogenerated electrons and holes. One effective approach to achieving this photoinduced charge separation relies on a phenomenon known as “band bending”. But details to justify why band bending results in photoinduced charge separation are more complex than often appreciated. This underappreciation is an impediment to the rational, hypothesis-driven design of next-generation approaches to solar energy conversion. Herein we show, by means of derivations rooted in physical chemistry, that several phenomena – not just band bending – can facilitate photoinduced charge separation, and that each is influenced by nonequilibrium species concentration and a parameter, such as diffusion coefficient or rate coefficient, that introduces dynamics. To help visualize the impact of each phenomenon, we introduce plots that depict their contributions as free energy, force, flux, force constant, and rate. We reveal that spatial dopant distributions that define band bending are predictors of initial photogenerated species transport rates. But charge separation alone does not guarantee high-efficiency operation. A photogenerated change in energy that is freely available to do useful work is also essential, and is strongly dependent on semiconductor optical properties and reaction kinetics. Notably, this information reveals that specificity of interfacial chemical reactions – even when they are not preceded by charge separation elsewhere – can result in efficient solar energy conversion. We expect that this tutorial will guide researchers in their pursuit to uncover new mechanisms for light to perform useful work.

14 SOLAR ENERGY↗
DOE OSTI2020

BWR Spent Nuclear Fuel Acquisition and Testing to Support DOE-NE High Burnup Spent Fuel Data Project

The Office of Spent Fuel and Waste Disposition (SFWD) within the US Department of Energy (DOE) Office of Nuclear Energy (NE) established the Spent Fuel and Waste Science and Technology (SFWST) campaign to conduct research and development (R&D) activities related to the storage, transportation, and disposal of spent nuclear fuel (SNF) and high-level radioactive waste. The SFWST program was created within SFWD to address issues of extended or long-term SNF storage and transportation. Some near-term objectives of SFWST are to use a science-based, engineering-driven approach to: Support the enhancement of the technical bases to support the continued safe and secure dry storage of SNF for extended periods; Support the enhancement of the technical bases for retrieving SNF after extended dry storage; Support the enhancement of the technical bases for transporting high burnup (HBU) fuel and transporting low burnup fuel and HBU fuel after dry storage DOE-NE, in partnership with the Electric Power Research Institute, developed the High Burnup Spent Fuel Data Project to perform a large-scale demonstration and laboratory-scale testing of HBU pressurized water reactor (PWR) fuels (exceeding 45 gigawatt-days per metric ton of uranium [GWd/MTU]). Under this project, 25 sister rods—which are rods that have the same design, power histories, and other characteristics—were removed from assemblies at the North Anna Nuclear Power Station and sent to Oak Ridge National Laboratory (ORNL) in January 2016. ORNL performed detailed nondestructive examination (NDE) on all 25 rods. The NDE consisted of visual examinations, gamma and neutron scanning, profilometry and rod length measurements, and eddy current examinations. After completing the NDE, 10 of the sister rods were delivered to Pacific Northwest National Laboratory (PNNL) in a NAC International, Inc. legal-weight truck cask in September 2018 for destructive examination (DE). To date, SFWD work has focused on the PWR fuel that is part of the Sister Rod Test program. No boiling water reactor (BWR) fuel has been tested in the program, and the data needs that were identified for the PWR fuel have not been collected for BWR fuel. The goal to obtain six to nine BWR rods and test them at ORNL will support closing this important data gap. BWR fuel comprises approximately 56% of the total fuel assemblies currently in storage at nuclear power plants in the United States. BWR nuclear fuel and cladding designs and manufacturing are significantly different from PWRs. Differences include the following: BWR fuel pellets are larger than PWR pellets; Variations of Zircaloy-2 (including liners) are used instead of the Zircaloy-4 cladding materials used in PWRs; Clad manufacturing and stress-relief processes are different between PWRs and BWRs; The fuel rod dimensions are different because larger rod diameters and thicker cladding are used in BWRs; BWR fuel typically has lower internal rod pressures and sees vastly different operating conditions than PWR fuel (i.e., two-phase flow); BWR assemblies are “canned,” meaning each assembly is surrounded by a metal fuel channel; BWR cladding is often composed of an inner pure Zr liner that has widely different mechanical properties than the Zircaloy-2 alloy and exhibits a stronger affinity for hydrogen; The BWR SNF generally has more total hydrogen in the cladding/liner than typical PWR fuel; The construction of the PWR and BWR assemblies is vastly different; BWR rods are solidly attached to the assembly nozzles and experience a much different vibration and shock load than PWR rods, which are “floating” within a grid system attached to guide tubes, and the rods sit loosely on the bottom end plates. These numerous differences will affect the way the BWR SNF responds under dry storage preparation processes (e.g., vacuum drying) and during transportation. The results collected in the PWR experimental program must be compared with a subset of similar data collected on BWR SNF to establish a technical basis for whether the larger PWR database is sufficient to bound the BWR SNF end-of-life conditions as is currently assumed for several fuel/clad properties. Changes that occur in both fuel types at HBU could exacerbate any mechanical property differences. As the fuel burnup increases, several changes occur that might affect the performance of the fuel, cladding, and assembly hardware in storage and transportation. These changes include increased cladding corrosion layer thickness, increased cladding hydrogen content, increased cladding creep strains, increased fission gas release, and the formation of the HBU structure at the surface of the fuel pellets. The Nuclear Regulatory Commission (NRC) limits the current maximum rod-averaged burnup to 62 GWd/MTU due to these changes and the lack of data at higher burnups.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

The Multiplanet System TOI-421: A Warm Neptune and a Super Puffy Mini-Neptune Transiting a G9 V Star in a Visual Binary

We report the discovery of a warm Neptune and a hot sub-Neptune transiting TOI-421 (BD-14 1137, TIC 94986319), a bright (V = 9.9) G9 dwarf star in a visual binary system observed by the Transiting Exoplanet Survey Satellite (TESS) space mission in Sectors 5 and 6. We performed ground-based follow-up observations—comprised of Las Cumbres Observatory Global Telescope transit photometry, NIRC2 adaptive optics imaging, and FIbre-fed Echellé Spectrograph, CORALIE, High Accuracy Radial velocity Planet Searcher, High Resolution Échelle Spectrometer, and Planet Finder Spectrograph high-precision Doppler measurements—and confirmed the planetary nature of the 16 day transiting candidate announced by the TESS team. We discovered an additional radial velocity signal with a period of five days induced by the presence of a second planet in the system, which we also found to transit its host star. We found that the inner mini-Neptune, TOI-421 b, has an orbital period of P{sub b} = 5.19672 ± 0.00049 days, a mass of M{sub b} = 7.17 ± 0.66 M{sub ⊕}, and a radius of R{sub b} = 2.68{sub −0.18}{sup +0.19} R{sub ⊕}, whereas the outer warm Neptune, TOI-421 c, has a period of P{sub c} = 16.06819 ± 0.00035 days, a mass of M{sub c} = 16.42{sub −1.04}{sup +1.06} M{sub ⊕}, a radius of R{sub c} = 5.09{sub −0.15}{sup +0.16} R{sub ⊕}, and a density of ρ{sub c} = 0.685{sub −0.072}{sup +0.080} g cm{sup −3}. With its characteristics, the outer planet (ρ{sub c} = 0.685{sub −0.072}{sup +0.080} g cm{sup −3}) is placed in the intriguing class of the super-puffy mini-Neptunes. TOI-421 b and TOI-421 c are found to be well-suited for atmospheric characterization. Our atmospheric simulations predict significant Lyα transit absorption, due to strong hydrogen escape in both planets, as well as the presence of detectable CH{sub 4} in the atmosphere of TOI-421 c if equilibrium chemistry is assumed.

79 ASTRONOMY AND ASTROPHYSICS↗