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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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DOE OSTI2024

Carbon Management Projects (CONNECT) Database and Explorer

Overview The Carbon Management Projects (CONNECT) Toolkit is an online exploratory visualization tool developed by the U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM) with support from other federal agencies such as the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation (DOT). It provides a single point of access to authoritative information on federal agency investment in a portfolio of research, development, and demonstration (RD&D) projects that have been publicly announced to advance technologies for point source carbon capture, carbon dioxide removal, transport, storage, and conversion, collectively referred to as carbon management. The RD&D programs covered in this tool are authorized by annual congressional appropriations ("Base Program") and the 2021 Infrastructure Investment and Jobs Act (IIJA). The tool also incorporates public information on other federal initiatives, such as the Regional Clean Hydrogen Hubs, and public information released by other government agencies, such as the Environmental Protection Agency's (EPA) and Primacy States’ Underground Injection Control Class VI permits and EPA’s facility level greenhouse gas (GHG) emissions. Developed in a geographic information system, the tool organizes carbon management projects into five groups based on the primary technology that a project aims to advance, each visually represented as a digital layer ("carbon management project layer"). Only federally funded projects are included, which can be awarded projects that are completed or ongoing, or projects that have been selected but are currently under negotiation. Project information can be viewed in the map or in the attribute table below it when turned on. In the map view, each project is displayed at either its host site (for field work), where available, or its performer site (project lead's location, further explained in the table below). Host sites and performer sites are represented in distinct icons. Several reference layers offer additional public information on infrastructural and natural resource environment for carbon management. These reference layers, combined with multiple geographical basemaps, enable users to visualize the carbon management project layers in context. Carbon management project information will be updated monthly based on feedback and information availability. Carbon management project layers Point Source Carbon Capture (PSC) This layer contains DOE-funded projects focused on capturing carbon dioxide (CO2) from power plants or industrial facilities. Carbon Dioxide Removal (CDR) This layer contains DOE-funded projects focused on capturing CO2 from the atmosphere, including direct air capture (DAC) and DAC hubs, direct ocean capture, enhanced mineralization, and biomass carbon removal and storage. For projects with multiple host sites, each of the sites are displayed individually with the project cost and cost sharing information representing the total for the entire project. Carbon Transport This layer contains DOE- and DOT-funded projects focused on CO2 transport. The Transport Research and Development sublayer contains projects that do not involve physical infrastructure; the Proposed Transport Corridor sublayer contains projects for which either a route for the transport infrastructure has been proposed or a general area for the transport infrastructure has been identified. Carbon Storage This layer contains DOE-funded key projects focused on CO2 storage. For projects with multiple field-work sites, each of the sites are displayed individually on the map with the project cost and cost sharing information representing the overall total for the entire project. Carbon Conversion This layer contains DOE-funded projects focused on converting CO2 into economically valuable products. Reference layers The following layers provide additional information in the geographic proximity of carbon management projects. Users should reference the original sources for more details (weblinks provided below and in pop-up windows on the map). Regional Clean Hydrogen Hub and Facility These layers illustrate the approximate areas of the Regional Clean Hydrogen Hubs announced by DOE's Office of Clean Energy Demonstrations (OCED) and the approximate locations of individual facilities that constitute the hubs (see "Where are the H2Hubs located?" on the webpage linked above). EPA Facility Level GHG Emissions (direct emitter) This layer shows direct CO2 emissions from stationary sources in 2022, using data extracted from EPA's Facility Level Information on GreenHouse gases Tool (FLIGHT). Captured and injected CO2 are not deducted from direct emitters’ total emissions. Contact EPA for additional details. Underground Injection Control Class VI permit/permit application This layer shows the locations of CO2 injection wells that are granted or in the process of applying for an Underground Injection Control Class VI permit by EPA or a Primacy State (currently Louisiana, North Dakota, and Wyoming). The URLs for the permits or permit applications are provided in the pop-up windows associated with the well locations. Contact EPA for additional details. Carbon Storage Resource This layer contains information on prospective CO2 storage resources in saline formations and oil and gas reservoirs provided by the National Carbon Sequestration Database and Geographic Information System (NATCARB) spatial database. Contact NETL for additional details. Existing CO2 pipeline This layer shows active CO2 pipelines based on information digitized from the map issued by the Pipeline and Hazardous Materials Safety Administration (PHMSA). Contact PHMSA for additional details.

Carbon Conversion↗
DOE OSTI2026

ML-based Micro-CT SOFC Microstructure Models (from Kent 2026 Microstructural Augmentation paper)

Overview -------------------------- This repository contains datasets from the manuscript **"Enhanced Generalizability to Deep-Learning Quantification of 3D Microstructural Characteristics through Microstructurally Aware Augmentation of Scarce Data"** (*William F. Kent, Rochan Bajpai, Rachel C. Kurchin, William K. Epting, Harry W. Abernathy, Paul A. Salvador. Submitted 2026*). The methods are also described in the dissertation **Data Intensive Analysis of Solid Oxide Cell Microstructures** (*Doctoral dissertation, Carnegie Mellon University, 2025*). The datasets here are trained convolutional neural network (CNN) models for predicting key microstructural properties of solid oxide cell (SOC) electrodes from low-res, 2-channel 3D images, as well as some helpful code. The parameters for input images are provided in the paper. Sample data is provided in the file `Combined_anode_aug_dual_1k_examples` - that particular data was used to train `anode_all_aug.pth` and will work most accurately with that model. Please familiarize yourself with all caveats on accuracy and applicability, as detailed in the associated paper. Usage -------------------------- The basic usage is as follows, assuming `model_fn` is the path to the .pth file, and `X` is 2-channel input image(s) of the proper dimensions (either one image of shape `[2,12,24,24]`, or a batch of N input images of shape `[N,2,12,24,24]`): from CNN_inferencer import load_model_for_inference model = load_model_for_inference(model_fn) y_predicted = model(X) The model object automatically handles input scaling and output de-scaling based on the way the models were trained - in other words, pass in a 2-channel micro-CT image, and it will output microstructural property values in real units. ## Other model object attributes Note that model has useful attributes other than its forward pass model(X). * `model.output_descaler` - returns the output descaler object. Model does the de-scaling when generating inferences, but you may want to re-use this de-scaler on other values to e.g. compare predictions to ground truth from already-scaled training data. * `model.prop_names` - Gives the property names of the predicted y values, in order. Only exists if there's an output scaler as part of the model object, which there will be in the models provided here. ## Usage with sample data Here is a short script to use with the included sample data. from CNN_inferencer import display_predictions, load_model_for_inference, calculate_mape, parity_plot import h5py import numpy as np model_fn = 'anode_all_aug.pth' data_fn = 'Combined_anode_aug_dual_1k_examples.h5' N_samples = 200 figure_outdir = '.' model = load_model_for_inference(model_fn) with h5py.File(data_fn,'r') as f: XX = f['X'] #These are the 2-channel 3D images yy = f['y'] #These are the ground-truth microstructural properties, but they have been scaled for training - need to de-scale below N = XX.shape[0] #How many images total in the input data file #Run inferences on N_samples random samples from XX. #Run in a batch, much more efficient than one at a time. ii = np.random.choice(N,N_samples,replace=False) ii.sort() y_pred = model(XX[ii]) #Get the original/true (but normalized/scaled) values from the training dataset... #Because they were normalized, they are not in real units yet. So let's also de-scale them using model.output_scaler. y_true = model.output_scaler.transform(yy[ii]) #Let's display actual values for just 5 random ones for i in np.random.choice(N_samples,5,replace=False): display_predictions(y_true[i], y_pred[i], model.prop_names) #Make parity plots for each property (ground truth vs predicted values) #Also label each plot with the mean abs. percent error (MAPE) of the predicted values for i,key in enumerate(model.prop_names): mape = calculate_mape(y_true[:,i], y_pred[:,i]) parity_plot(y_true[:,i], y_pred[:,i], figure_outdir, key, extra_title=f' ({mape:.2f}% MAPE)')

3D microstructure↗
DOE OSTI2021

GMS Station SOH Monitoring Configuration Guide (V.1.2)

The GMS Station State-of-Health (SOH) monitoring capability provides the system controller the ability to view current SOH values and calculated statistics for stations and channels, view trend plots of SOH values, be notified when station SOH status changes, and acknowledge or quiet notifications while the station issues are being investigated. The SOH monitoring capability includes components to acquire CD 1.1 protocol station data, extract SOH information from the raw data packets, process the raw SOH information for display, store the SOH information, and display the SOH information in an interactive display. All these components use system and processing configuration to provide the system controller mission-relevant information about station health. This document is a guide to setting the processing configuration for GMS SOH monitoring.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Gray-Box Fault Models and Applications for Low-Carbon Emission CO 2 Refrigeration Systems

CO 2 refrigeration systems have attracted more attentions in recent years because of their zero-carbon emission advantages compared with traditional refrigerants. These systems are widely used in certain commercial buildings such as supermarkets. However, very limited energy studies have been done for such refrigeration systems under faults. This study investigated five common faults for supermarket transcritical CO 2 refrigeration systems with display cases. The following major tasks were implemented for this study. (1) Five fault models (gray-box format) regarding the power consumption and supply air temperature were proposed for low- and high-temperature display cases, respectively. The models cover: ice accumulation on evaporator coil, evaporator fan partial failure, expansion valve failure, display door open, and condenser blockage. (2) These fault models were calibrated with field tests, and the modeling accuracies were in good agreement with measurement datasets. (3) The proposed fault models demonstrated more than 90% of fault detection for Fault Detection and Diagnostics (FDD) purposes for both field measurement and simulated data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Solid Phase Gradient Alloying Method via ShAPE

Alloying has been used to confer desirable properties to various metallic systems since the bronze age. For example, Ni, Mn, and Cr are alloyed into an Fe matrix to make steel, which has improved strength and corrosion resistance (as displayed in Fig. 1). In addition to the type of alloying elements, the amount of alloying elements added into a matrix is also very critical for a material’s mechanical property, physical property, machinability, and cost. Conventionally, new alloys are discovered by combining alloy precursors and elemental constituents into a mixture and melting them together. The solidified product or ingot represents a usually non-homogeneous combination of the chemistry with a microstructure dictated by the physics of solidification. It is time and energy intensive to optimize the alloying amounts via the casting process and hence, economically not conducive to rapid alloy discovery. In addition, the cast microstructure seen in the as-cast ingot is often not the ideal, nor even desired structure for optimized performance. Cast materials often need further processing such as homogenization, annealing, and deformation work put in through rolling, forging, extruding, etc. to have favorable microstructures and properties. A faster method to discover new alloy combinations and evaluate them in their worked or processed form is needed. Recently, Laser Engineered Net Shaping was applied to fabricate gradient compositional material for alloy designing. However, the mechanical properties of this gradient alloy were poor due to the existence of impurities, oxidation and cracks that are inherent in the melt-solidification process. Because of these limitations, we propose to use a solid-phase process (ShAPE) to create bulk materials (extrudates) that vary in composition from one end of the extruded solid to the other. Various manufacturing methods for alloy design including conventional casting method, laser based combinatorial method and current solid phase gradient alloying method are displayed and compared in Fig. 2. ShAPE machine and a schematic of ShAPE process are displayed in Fig. 3. Starting material is processed by a rotating and plunging die to form an extrudate. We are proposing through this methodology to invent a new, bulk-scale combinatorial technique. With this novel technique, alloying element can be dissolved into the matrix with a continued gradient without bulk melting. Formation of inter-metallics and defects originating from melt processing can be avoided. In addition, the ShAPE process creates the mixed alloy chemistry, and meanwhile subjects the material to severe plastic strain, which induces the favorable “worked” microstructure. Products from the ShAPE process can be tested in hardness directly providing a path to rapid evaluation of mechanical properties. The ability to create graded structures using friction stir processing (FSP) has been demonstrated, however using the ShAPE process we believe will lead to much faster and higher fidelity results. When combined with high throughput screening methods of physical, mechanical and microstructural property characterization, efficiency and accuracy of alloy design can be significantly improved.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Porous Organic Cage Membranes for Molecular Gas Separations (Final Technical Report for DE-SC0021357)

This proposal aims at demonstrating the development of a novel family of membranes, composed of porous organic cages (POC) which offer the possibility of displaying high separation performance for challenging molecular gas separations relevant to natural gas purification, and olefin/paraffin separation. The proposed POCs synthesized in membrane form will display the most desirable properties of polymers (facile processability and flexibility) and inorganic materials (hierarchically ordered pores with molecular sieving properties) leading to highly selective and permeable membranes. POCs should display distinctive structural, compositional, adsorption and transport properties than those of conventional porous materials, opening the doors for a new research direction in membrane science, and gas separations. Our preliminary results demonstrate the feasibility of preparing POC crystals with controlled size, and continuous POC membranes with remarkable high permeances, and separation ability for CO 2 /CH 4 , N 2 /CH 4 and C 3 H 6 /C 3 H 8 separations serving as a solid foundation for our proposed work. Fundamentally, this proposal aims at elucidating separation mechanisms of different gas mixtures related to natural gas composition, and olefin/paraffin separation over porous organic cage membranes. The proposed research will result in fundamental understanding of adsorption and transport properties of industrially relevant gas molecules through novel microporous membranes, and may lead to the development of a cost effective membrane technology for natural gas purification, and olefin/paraffin separation surpassing the conventional benchmark technology distillation. Furthermore, we aim at demonstrating selective water transport through POC membranes, which can be positively impactful in numerous industrial applications in which water is present. The ability to fabricate thin, chemically and mechanically stable POC membranes for societal relevant gas separations constitute a new and distinctive direction in membrane science. Our proposed work aims at addressing some of the challenges recognized in the Research Agenda for Transforming Separation Science . Specifically: (a) advancing understanding of complex mixtures on separation performance; (b) exploring thermodynamic and kinetic mechanisms through the elucidation of separation mechanisms, and (c) study potential stability issues of the membranes to be assessed by evaluating the long term membrane stability and performance at various temperatures and pressures. The team is uniquely qualified to execute the proposed work. The PI has solid expertise in the rational molecular engineering design of porous crystalline membranes for molecular gas separations. The PNNL collaborator has extensive experience in the synthesis, characterization, and functional applications of microporous crystals, with particular emphasis on gas adsorption.

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

VARI3D & PERSENT: Perturbation and Sensitivity Analysis

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry based transport code. This manuscript serves as a single manual for two separate codes: VARI3D and PERSENT. The VARI3D code (VARIational 3D) is based upon the classic finite difference diffusion theory solver available in DIF3D. The PERSENT code (PERturbation and SENitivity for Transport) is based upon the variational nodal method employed in DIF3D termed VARIANT. The VARIANT solver was added to DIF3D in 1995 and has seen continued development and use for the last 18 years. Because VARI3D primarily uses deprecated coding practices, rather than incorporating the perturbation and sensitivity treatments for transport within VARI3D, a new coding development was built using modern Fortran coding. The primary purpose of this manual is to describe the theory behind PERSENT (and by convenience, that of VARI3D) and discuss the input and output of PERSENT along with giving potential users an idea of how to use it. While this manuscript does describe the input and output of VARI3D, the PERSENT code is intended to be the replacement capability of VARI3D as PERSENT can generate nearly identical (if not superior) diffusion theory results. In this manuscript, the relevant aspects of generalized perturbation theory and exact perturbation theory that apply to both VARI3D and PERSENT are covered. The input and output of VARI3D is displayed by excerpting several of the example problems. Similarly, the input and output of PERSENT is displayed along with tips on how best to use the code. Note that the input and output of the inhomogeneous solver wrapped around DIF3D (DIF3D_IFS) is also discussed as it is needed to carry out some of the sensitivities in PERSENT such as reaction rate ratios. This manuscript describes several perturbation and sensitivity problems, and the results computed using PERSENT. From these sections, potential users should find that PERSENT provides not only the typical tables of numbers desired in perturbation and sensitivity analysis work, but also can visually plot the result for a more thorough understanding of the space and energy distribution (Section 5). Overall, PERSENT is observed to produce accurate reactivity worths and sensitivities for the displayed set of test problems and clearly demonstrates the need to have a transport-based sensitivity capability as evident from the thousands of percent errors observed in the 21-group hexagonal fast reactor problem (covered in Section 7). The uncertainty calculation capability is described in Section 3 and demonstrated in Section 7.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Verification of the REBUS Software

Ongoing design activities at Argonne National Laboratory are requiring a thorough verification of the Argonne Reactor Computation codes be performed. REBUS is central to this system. The driver for this effort requires the Triangular-Z and hexagonal-Z core geometry options of REBUS to be verified. Previous work identified the REBUS features required to be verified to support current design activities, features of which are generally applicable to hexagonal-Z fast reactor designs. The scope of this verification effort includes verifying REBUS’s ability to correctly intepret the user input model, verifying that the features identified yield the intended results, and verifying the correctness of the REBUS output tables. The REBUS software verification relies heavily upon the accuracy of the embedded DIF3D software, the verification of which was completed and documented elsewhere. Given that DIF3D produces an accurate solution, the primary focus of the verification in the REBUS software is to ensure that it properly uses the DIF3D solution and that the depletion system (Bateman equations) are correctly implemented. This manuscript reiterates the verification tasks and displays results with respect to the features needed for current design activities. Analytic solutions of the Batemen equations are displayed and the results calculated with REBUS are displayed demonstrating the accuracy. Since coupled Bateman and neutron diffusion/transport solutions are extremely difficult to obtain, much of the focus is placed on how REBUS uses a given DIF3D solution assuming the accuracy of the DIF3D solution. The verification effort identified no issues that are debilitating or otherwise impactful to the design usage of REBUS, and thus REBUS version 11.0, release 3012 is considered verified. It is important to note that several outputs of REBUS are identified to be inaccurate, such as burnup in MWD/MT. Most of the relevant ones for VTR are generally accurate with 10-20% errors which is not impactful as all regular REBUS users are aware of this issue and know how to hand calculate the results. The REBUS manual further makes it clear that these values are consistent with the methodology being used by REBUS and thus the “errors” are more of an inconsistent definition with respect to what a user would expect given a definition in literature. Other issues that were identified included unclear documentation and software bugs all of which were inconsequential to the final results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Materials for Energy Management across the Electromagnetic Spectrum (MEMES) (LDRD Report)

Electrification of the United States has been a major driver of economic growth, powering industrialization, modern manufacturing, and the digital economy. Today, further economic and environmental benefits can be realized by improving the energy efficiency of the technologies we have come to rely on. This project focused on enhancing the energy efficiency of two cornerstone technologies of modern society: electronic displays and building climatization. While these two technologies operate in different parts of the electromagnetic spectrum (the visible and infrared, respectively), they share a common potential technological solution: electrically-driven displays that change reflectivity. In this work, we developed the first multipixel multicolor reflective display that achieves multi-colorization with fast-changing structural color. In the course of this demonstration, we quantified the structural changes that occur across different time and length scales and resolved device sealing issues, enabling operation of these devices over months (as opposed to days previously). We furthermore developed two reflectivity changing devices in the infrared and demonstrated how these technologies can be used to reduce climatization demands for both smart window and smart wall technologies. Implementing such a device in a scaled down mock room resulted in 10 degree Celsius change.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Trade-Offs Between Growth Rate and Other Fungal Traits

If we better understand how fungal responses to global change are governed by their traits, we can improve predictions of fungal community composition and ecosystem function. Specifically, we can examine trade-offs among traits, in which the allocation of finite resources toward one trait reduces the investment in others. We hypothesized that trade-offs among fungal traits relating to rapid growth, resource capture, and stress tolerance sort fungal species into discrete life history strategies. We used the Biolog Filamentous Fungi database to calculate maximum growth rates of 37 fungal species and then compared them to their functional traits from the fun fun database. In partial support of our hypothesis, maximum growth rate displayed a negative relationship with traits related to resource capture. Moreover, maximum growth rate displayed a positive relationship with amino acid permease, forming a putative Fast Growth life history strategy. A second putative life history strategy is characterized by a positive relationship between extracellular enzymes, including cellobiohydrolase 6, cellobiohydrolase 7, crystalline cellulase AA9, and lignin peroxidase. These extracellular enzymes were negatively related to chitosanase 8, an enzyme that can break down a derivative of chitin. Chitosanase 8 displayed a positive relationship with many traits that were hypothesized to cluster separately, forming a putative Blended life history strategy characterized by certain resource capture, fast growth, and stress tolerance traits. These trait relationships complement previously explored microbial trait frameworks, such as the Competitor-Stress Tolerator-Ruderal and the Yield-Resource Acquisition-Stress Tolerance schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Iodate Reduction by Shewanella oneidensis Requires Genes Encoding an Extracellular Dimethylsulfoxide Reductase

Microbial iodate (IO 3 – ) reduction is a major component of the iodine biogeochemical reaction network in anaerobic marine basins and radioactive iodine-contaminated subsurface environments. Alternative iodine remediation technologies include microbial reduction of IO 3 – to iodide (I – ) and microbial methylation of I – to volatile gases. The metal reduction pathway is required for anaerobic IO 3 – respiration by the gammaproteobacterium Shewanella oneidensis . However, the terminal IO 3 – reductase and additional enzymes involved in the S. oneidensis IO 3 – electron transport chain have not yet been identified. In this study, gene deletion mutants deficient in four extracellular electron conduits (EECs; Δ mtrA , Δ mtrA -Δ mtrDEF , Δ mtrA -Δ dmsEF , Δ mtr A-ΔSO4360) and DMSO reductase (Δ dmsB ) of S. oneidensis were constructed and examined for anaerobic IO 3 – reduction activity with either 20 mM lactate or formate as an electron donor. IO 3 – reduction rate experiments were conducted under anaerobic conditions in defined minimal medium amended with 250 μM IO 3 – as anaerobic electron acceptor. Only the Δ mtrA mutant displayed a severe deficiency in IO 3 – reduction activity with lactate as the electron donor, which suggested that the EEC-associated decaheme cytochrome was required for lactate-dependent IO 3 – reduction. The Δ mtrA -Δ dmsEF triple mutant displayed a severe deficiency in IO 3 – reduction activity with formate as the electron donor, whereas Δ mtrA -Δ mtrDEF and Δ mtr A-ΔSO4360 retained moderate IO 3 – reduction activity, which suggested that the EEC-associated dimethylsulfoxide (DMSO) reductase membrane-spanning protein DmsE, but not MtrA, was required for formate-dependent IO 3 – reduction. Furthermore, gene deletion mutant Δ dmsB (deficient in the extracellular terminal DMSO reductase protein DmsB) and wild-type cells grown with tungsten replacing molybdenum (a required co-factor for DmsA catalytic activity) in defined growth medium were unable to reduce IO 3 – with either lactate or formate as the electron donor, which indicated that the DmsAB complex functions as an extracellular IO 3 – terminal reductase for both electron donors. Results of this study provide complementary genetic and phenotypic evidence that the extracellular DMSO reductase complex DmsAB of S. oneidensis displays broad substrate specificity and reduces IO 3 – as an alternate terminal electron acceptor.

, Shewanella oneidensis↗
DOE OSTI2020

Secular Resonances in Nonrestricted Hierarchical Triple Systems

In this paper, the averaged Hamiltonian of a nonrestricted hierarchical triple system truncated at the third order is investigated. First, each secular resonant term is studied. For the well-studied secular quadrupole theory, it is analytically reformulated in a different manner in our work. The resonance width is numerically determined and displayed on the √(1−e{sub 1}{sup 2})−√(1−e{sub 2}{sup 2}) plane (also denoted as the e-tilde {sub 1}− e-tilde {sub 2} plane). In terms of the octupole terms, we show that for a near-planar configuration of the system, considerable variations of both the eccentricities of the inner and outer orbits can be generated by a single resonant term. The resonance width for every secular resonant angle from the octupole terms is also numerically determined and displayed on the e-tilde {sub 1}− e-tilde {sub 2} plane. The results show that an orbit flip with a near-perpendicular initial mutual inclination is possible for each secular resonance. By displaying the resonance widths of different resonant terms on the same e-tilde {sub 1}− e-tilde {sub 2} plane, we intuitively show the overlap of different secular resonances. Then, the full averaged Hamiltonian with both quadrupole and octupole terms is investigated using the Poincaré surface of section, with a special focus on the orbit flip. For the cases we exploited, we find that the near-planar flip of the inner orbit can be either regular or chaotic while the outer orbit flip is generally chaotic.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Coronal Line Spectrum of the Iron Nova V3666 Ophiuchi

Optical and infrared spectroscopy are presented for the classical nova V3666 Ophiuchi (Nova Ophiuchi 2018 No.3) from 11 months after its outburst. At that epoch, V3666 Oph displayed an [Fe x] λ0.6375 emission line stronger than Hα and nearly a factor of 3 larger, relative to Hα, than in any nova observed previously. The [Fe x] feature, with an equivalent width exceeding 1300 Å, was enormously strong relative to the continuum emission as well. V3666 Oph also reached a state of high excitation for an Fe ii type nova, displaying coronal lines of [Fe xi], [S ix], and [Ar x], and permitted features that can be identified with the C vi (8–7), (9–8), and (10–9) transitions. In addition to [Fe x] and [Fe xi], V3666 Oph also displayed bright lines of [Fe vii], indicating that the prominent iron features were not confined to a single or narrow range of ionization states. Modeling the emission line spectrum of V3666 Oph with the photoionization code Cloudy indicated that the bulk of the emission line gas was matter-bounded, severely reducing the amount of low ionization gas and resulting in coronal lines that were very strong in comparison to lines such as H i and He i, and the familiar low excitation forbidden lines of nitrogen and oxygen. Such matter-bounded regions are observationally rare in novae since they are both faint and short-lived, offering a plausible explanation for why [Fe x] λ0.6375 had not be seen at this strength previously.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Detailed Abundances in the Ultra-faint Magellanic Satellites Carina II and III

We present the first detailed elemental abundances in the ultra-faint Magellanic satellite galaxies Carina II (Car II) and Carina III (Car III). With high-resolution Magellan/MIKE spectroscopy, we determined the abundances of nine stars in Car II, including the first abundances of an RR Lyrae star in an ultra-faint dwarf galaxy (UFD), and two stars in Car III. The chemical abundances demonstrate that both systems are clearly galaxies and not globular clusters. The stars in these galaxies mostly display abundance trends matching those of other similarly faint dwarf galaxies: enhanced but declining [α/Fe] ratios, iron-peak elements matching the stellar halo, and unusually low neutron-capture element abundances. One star displays a low outlying [Sc/Fe] = −1.0. We detect a large Ba scatter in Car II, likely due to inhomogeneous enrichment by low-mass asymptotic giant branch star winds. The most striking abundance trend is for [Mg/Ca] in Car II, which decreases from +0.4 to −0.4 and indicates clear variation in the initial progenitor masses of enriching core-collapse supernovae. So far, the only UFDs displaying a similar [Mg/Ca] trend are likely satellites of the Large Magellanic Cloud. We find two stars with [Fe/H] ≤ −3.5 whose abundances likely trace the first generation of metal-free Population III stars and are well fit by Population III core-collapse supernova yields. An appendix describes our new abundance uncertainty analysis that propagates line-by-line stellar parameter uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Physical Properties of Hilti HIT-RE 500 V3 After Irradiation: Slant Shear, Tensile, Flexural, and Compressive

There are various applications in which epoxy adhesives may be used within hot-cell environments. These epoxies currently see limited use within hot cells since it is known that organics see degradation after small doses even as low as 50 kilogray (kGy). These losses in physical property strengths limit the use of these epoxies to non-structural applications. In modern construction, however, the use of epoxies to bond structural components such as rebar or threaded anchors is becoming increasingly prevalent. To employ these types of materials the Idaho National Laboratory (INL) has begun investigating the specific degradation properties of epoxies for use in structural applications in environments where radiation is present. Hilti HIT-RE 500 V3 is used extensively in new construction and renovation projects across the world. The INL has conducted various tests on this epoxy for low dose environments. These tests include tensile, flexural, compression, and slant shear tests following the American Society for Testing Material International (ASTM) standards D638, D790, D695, and C882/882M respectively. Two sample sets for each test were created where the baseline specimens were not irradiated, and another set was irradiated to an accumulated dose of approximately 50-60 kGy. All the samples were destructively tested and analyzed focusing on the change in physical properties, examples of these tests are shown in Figures 1-4. Tensile testing results indicate a 0.9% loss in maximum load capacity, a 0.5% loss in tensile stress at maximum load, a 1.4% loss in tensile strain at break, and a 15% decrease in modulus of elasticity. Flexural testing results display an increase in all the following: 12% in strain at maximum load, 10% in maximum load capacity, 5% in stress at maximum load, and 3% in young’s modulus. The compressive physical properties after irradiation display a 1% increase in maximum load, a 3% decrease in stress at yield, and a 5% decrease in modulus of elasticity. The maximum compressive stress saw no measurable change after irradiation. The slant shear specimens after irradiation displayed a 2% increase in maximum load capacity and maximum compressive stress. Though a structural analysis would have to be completed as is normal for building design the increases and decreases in the measured physical properties indicate that this material may be used for structural applications in low dose hot-cell environments without adhesive failure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emerging viral threats requires substantial resources and time, and traditional development platforms for vaccines and antibodies are often too slow to combat continuously evolving immunological escape variants, reducing their efficacy over time. Previously, we designed a next-generation synthetic humanized nanobody (Nb) phage display library and demonstrated that this library could be used to rapidly identify highly specific and potent neutralizing heavy chain-only antibodies (HCAbs) with prophylactic and therapeutic efficacy in vivo against the original SARS-CoV-2. In this study, we used a combination of high throughput screening and machine learning (ML) models to identify HCAbs with potent efficacy against SARS-CoV-2 viral variants of interest (VOIs) and concern (VOCs). To start, we screened our highly diverse Nb phage display library against several pre-Omicron VOI and VOC receptor binding domains (RBDs) to identify panels of cross-reactive HCAbs. Using HCAb affinity for SARS-CoV-2 VOI and VOCs (pre-Omicron variants) and model features from other published data, we were able to develop a ML model that successfully identified HCAbs with efficacy against Omicron variants, independent of our experimental biopanning workflow. This biopanning informed ML approach reduced the experimental screening burden by 78% to 90% for the Omicron BA.5 and Omicron BA.1 variants, respectively. The combined approach can be applied to other emerging viruses with pandemic potential to rapidly identify effective therapeutic antibodies against emerging variants.

Antibodies↗
DOE OSTI2020

Thermally Activated Delayed Fluorescence Sensitization for Highly Efficient Blue Fluorescent Emitters

Hyperfluorescence is emerging as a powerful strategy to develop optoelectronic devices with high-color purity and enhanced stability. It requires appropriate integration of a sensitizer displaying efficient thermally activated delayed fluorescence (TADF) and an emitter displaying strong, narrow-band fluorescence. Here, through a joint computational and experimental approach, we provide an unprecedented, end-to-end systems level description of the electronic and optical processes that take place in a hyperfluorescent emissive layer composed of a TADF sensitizer, bis(2,5-di(9H-carbazol-9-yl)phenyl)-1,3,4-oxadiazole (4CzDPO), and a fluorescent emitter, 2,5,8,11-tetra-tert-butylperylene (TBPe). We combine the photophysical properties measurement of the emissive layer with the computational determination of the electronic properties, film morphology, and excitation transfer phenomena. The Förster resonance energy transfer rates from 4CzDPO to TBPe are on the order of 1011 s–1, considerably higher than the radiative and non-radiative recombination rates for 4CzDPO. These features ensure nearly complete energy transfer to TBPe, leading to a five-fold increase in the photoluminescence quantum yields in the 4CzDPO:TBPe system in comparison to neat films of 4CzDPO. Furthermore, our approach highlights the factors that can provide efficient energy transfer from TADF molecules to fluorescent emitters, suppress energy transfer among TADF molecules, and avoid the need for a host material within the emissive layer.

36 MATERIALS SCIENCE↗