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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High Flux Isotope Reactor Low Enriched Uranium U-10Mo Fuel Design Parameters

Activities to convert the HFIR from HEU to LEU are ongoing as part of the US Department of Energy (DOE) National Nuclear Security Administration (NNSA) nuclear nonproliferation mission. Design activities to study the conversion of HFIR from HEU to LEU fuel explored different fuel design features and shapes with a uranium-molybdenum (U-10Mo) monolithic alloy fuel. This high-density alloy contains 90 wt % uranium and 10 wt % molybdenum and has a uranium density of 15.318gU/cm 3 . The goal of these studies is to generate several candidate HFIR LEU fuel designs of varying fuel fabrication complexity that meet the current HEU performance metrics and safety requirements. Recent advancements in modeling and simulation tools and design methods enabled a thorough analysis of the available design space with U-10Mo fuel. A surrogate model used this analysis as training data to quickly determine the performance of a design given specific design parameters. An optimization module used this surrogate model to quickly search this multidimensional search space given specific desired performance characteristics. This approach was made possible by the large available design space with U-10Mo fuel. Shift, a Monte Carlo tool optimized for high-performance computing (HPC) architectures, was used for faster calculation and better data management for reactor physics simulations. Once most of these design studies were complete, a new suite called the Python HFIR Analysis and Measurement Engine (PHAME) was developed to connect all fuel design analysis steps, making design studies more efficient and reproducible. The post-processing capabilities of these new tools are leveraged for the information provided herein. Leveraging these tools, several candidate fuel designs were selected with varying levels of feature complexity and reactor performance. This report provides design feature details for four selected HFIR LEU U-10Mo fuel designs and their corresponding performance and safety metrics. Nominal best-estimate design parameters and irradiation conditions, including fission rate densities, power densities, heat fluxes, and cumulative fission densities, are provided. Simulations show that the high uranium density of U-10Mo fuel provides a large potential design space that enables various LEU designs to meet HEU core performance metrics and safety requirements with a power increase from 85 MW (HEU) to 95 MW or 100 MW (LEU).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

Efficient photoassociation with a train of asymmetric laser pulses

The photoassociation (PA) dynamics implemented by a train of asymmetric slowly turned-on and rapidly turned-off (STRT) laser pulses is investigated theoretically with Cs{sub 2} as an example. A higher PA efficiency is achieved by optimizing the parameters of the STRT pulse train. The PA reaction goes partly beyond the scope of the PA window. Numerical calculations show that an efficient population accumulation in the PA process can be realized with the STRT laser-pulse train which is available in the current experiment based on laser mode-lock and shaping technology.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

A Modified Vegetation Photosynthesis and Respiration Model (VPRM) for the Eastern USA and Canada, Evaluated With Comparison to Atmospheric Observations and Other Biospheric Models

Atmospheric CO 2 measurements from a dense surface network can help to evaluate terrestrial biosphere model (TBM) simulations of Net Ecosystem Exchange (NEE) with two key benefits. First, gridded CO 2 flux estimates can be evaluated over regional scales, not possible using flux tower observations at discrete locations for model evaluation. Second, TBM ability to explain atmospheric CO 2 fluctuations due to the biosphere can be directly tested, an important objective for anthropogenic emissions monitoring using atmospheric observations. Here, we customize the Vegetation Photosynthesis and Respiration Model (VPRM) for an eastern North American domain with strong biological activity upwind of urban areas. Parameters are optimized using flux tower observations from a historical database with sites in (and near) the domain. In addition, the respiration model (originally a linear function of temperature) is modified to account for impacts of changing foliage, non-linear temperature, and water stress. Flux estimates from VPRM, the Carnegie-Ames-Stanford Approach (CASA) model and the Simple Biosphere Model v4 (SiB4), are convolved with footprints from atmospheric transport models for evaluation with CO 2 observations at 21 towers in the domain, with roughly half of the towers used here for the first time. Results show that the new respiration model in VPRM helps to correct a growing season sink bias in the atmosphere associated with underestimated summertime respiration using the original model with annual parameters. The new VPRM also better explains fine-scale atmospheric CO 2 variability compared to other TBMs, due to higher resolution diagnostic phenology, the new respiration model, domain-specific parameters, and high-quality input data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Structural, electronic and optical properties of monoclinic Na{sub 2}Ti{sub 3}O{sub 7} from density functional theory calculations: A comparison with XRD and optical absorption measurements

Powder samples of bulk monoclinic sodium trititanate Na{sub 2}Ti{sub 3}O{sub 7} were prepared carefully by solid state reaction, and its monoclinic P2{sub 1}/m crystal structure and morphology were characterized by X-ray powder diffraction (XRD) and scanning electron microscopy (SEM), respectively. Moreover, the sodium trititanate main energy band gap was estimated as E{sub g}=3.51±0.01 eV employing UV–Vis spectroscopy, which is smaller than the measured 3.70 eV energy gap published previously by other authors. Aiming to achieve a better understanding of the experimental data, density functional theory (DFT) computations were performed within the local density and generalized gradient approximations (LDA and GGA, respectively) taking into account dispersion effects through the scheme of Tkatchenko and Scheffler (GGA+TS). Optimal lattice parameters, with deviations relative to measurements Δa=−0.06 Å, Δb=0.02 Å, and Δc=−0.09 Å, were obtained at the GGA level, which was then used to simulate the sodium trititanate electronic and optical properties. Indirect band transitions have led to a theoretical gap energy value of about 3.25 eV. Our results, however, differ from pioneer DFT results with respect to the specific Brillouin zone vectors for which the indirect transition with smallest energy value occurs. Effective masses for electrons and holes were also estimated along a set of directions in reciprocal space. Lastly, our calculations revealed a relatively large degree of optical isotropy for the Na{sub 2}Ti{sub 3}O{sub 7} optical absorption and complex dielectric function. - Graphical abstract: Monoclinic sodium trititanate Na2Ti3O7 was characterized by experiment and dispersion-corrected DFT calculations. An indirect gap of 3.5 eV is predicted, with heavy electrons and anisotropic holes ruling its conductivity. - Highlights: • Monoclinic Na2Ti3O7 was characterized by experiment (XRD, SEM, UV–Vis spectroscopy). • DFT GGA+TS optimized geometry and optoelectronic properties were obtained. • An experimental (theoretical) indirect gap of 3.5 (3.25) eV is predicted. • Heavy electrons and anisotropic holes rule the conductivity. • Ti-O bond lengths and charge states probably cause oxygen reactivity variations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Development & Validation of Low-Cost, Highly-Durable, Spinel-Based Materials for SOFC Cathode-Side Contact (Final Report)

A cathode-side contact layer is required to provide and maintain stable electrical conduction paths between the interconnect and cathode in a solid oxide fuel cell (SOFC) stack assembly and thus minimize the ohmic resistance and stack power loss. Current cathode-interconnect contact materials are based on noble metals, electrically-conductive perovskites, their composite materials, etc. These materials are either too expensive or do not possess the overall balanced performance required for the cathode-side contact application. To achieve the DOE SOFC system cost and performance stability goals, a new generation of low-cost, high-performance contact materials needs to be developed. In this project, spinel-based materials thermally converted from the Fe-Ni and Co-Mn based alloy precursors were developed and validated for the cathode-side contact application. The precursor alloy compositions were optimized via a combination of composition screening in the (Ni,Fe) 3 O 4 and (Mn,Co) 3 O 4 spinel system, alloy design using physical metallurgy principles, and cost considerations. The alloy powders with the desired composition and particle size were manufactured via gas atomization. The optimal process parameters for thermal conversion of these alloy precursor layers to a spinel-based layer were identified, i.e., 900°C x 2h in air, which is close to the initial stack firing condition. The area-specific resistances (ASRs) of the interconnect/contact/cathode test assemblies with the developed contact layer were determined for various durations (up to 5000 h) under simulated cathodic operation conditions. Some of the alloy-derived spinel contacts exhibited the lowest ASR and ASR degradation rate. The in-stack performance of the most promising alloy-derived contact layer is currently being evaluated via stack testing. To reduce the stack cost, the Co-Mn based alloy powders were utilized as the precursor for synthesis of dense spinel-based interconnect coating. By optimizing both the initial powder size/distribution and the alloy powder composition, a dense (Mn,Co) 3 O 4 -based spinel coating was achieved. Furthermore, co-sintering of the coating/contact dual-layer structure under the initial stack firing condition was realized by utilizing the tailored Co-Mn alloy precursors. Cost analysis of the developed technology indicated a total stack cost reduction of around 10.6% with the implementation of co-sintering of the interconnect coating and the contact layer during initial stack firing. Since low-cost processes such as screen printing is utilized in the precursor application and no reduction heat treatment is needed for the coating formation, the developed technology can be readily implemented at the industrial partner’s manufacturing facilities with no additional capital investment needed.

08 HYDROGEN↗
DOE OSTI2016

Fast time-resolved electrostatic force microscopy: Achieving sub-cycle time resolution

The ability to measure microsecond- and nanosecond-scale local dynamics below the diffraction limit with widely available atomic force microscopy hardware would enable new scientific studies in fields ranging from biology to semiconductor physics. However, commercially available scanning-probe instruments typically offer the ability to measure dynamics only on time scales of milliseconds to seconds. Here, we describe in detail the implementation of fast time-resolved electrostatic force microscopy using an oscillating cantilever as a means to measure fast local dynamics following a perturbation to a sample. We show how the phase of the oscillating cantilever relative to the perturbation event is critical to achieving reliable sub-cycle time resolution. We explore how noise affects the achievable time resolution and present empirical guidelines for reducing noise and optimizing experimental parameters. Specifically, we show that reducing the noise on the cantilever by using photothermal excitation instead of piezoacoustic excitation further improves time resolution. We demonstrate the discrimination of signal rise times with time constants as fast as 10 ns, and simultaneous data acquisition and analysis for dramatically improved image acquisition times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Higher-order factorization machine for accurate surrogate modeling in material design

Efficient and robust optimization is important in material science for identifying optimal structural parameters and enhancing material performance. Surrogate-based active learning algorithms have recently gained great attention for their ability to efficiently navigate large, high-dimensional design spaces. Among surrogate models, 2 nd -order factorization machine (FM) models are widely employed as the surrogate model in active learning algorithms due to their balance between simplicity and effectiveness. However, their quadratic nature limits their capacity to capture complex, higher-order interactions among variables, often leading to suboptimal solutions. To overcome this limitation, we propose an active learning scheme integrating a 3 rd -order FM model, capable of modeling three-variable interactions and more intricate relationships in material systems. We comprehensively evaluate the surrogate modeling performance of the 3 rd -order FM case using various objective functions. Furthermore, we examine the optimization reliability and efficiency of the 3 rd -order FM-based active learning in a real-world material design task (e.g., nanophotonic structures for transparent radiative cooling). Our study shows that the 3 rd -order FM outperforms the 2 nd -order model in both surrogate accuracy and optimization performance, highlighting higher-order models’ promises for material design and optimization problems.

Factorization machine↗
DOE OSTI2026

On the formation of swelling and related flaws in laser powder bed fusion

Process monitoring in laser powder bed fusion additive manufacturing can provide insights into stochastic anomalies, melt pool and plume dynamics, and part quality. Swelling, a build anomaly where overbuilt material protrudes through the powder layer after recoating, is readily detectable in post-recoat visible light images of the powder bed. Here, this work identifies several of the underlying mechanisms driving swelling formation by analyzing the influence of processing parameters, laser scan paths, and build plate locations on the presence of swelling detected in situ. Swelling near the edge of the part and swelling in the internal region of the part are shown to correlate with different process conditions. Edge and internal swelling may be driven by different phenomena, with edge swelling predominately occurring on the edge of a part facing the laser module and correlated to clusters of near-surface voids (detected with X-ray computed tomography). A larger spot size, higher laser power, and lower scan velocity also increased the presence of edge swelling. Laser spot size and scan path influenced internal swelling, which occurred preferentially with a larger spot size and in regions with large melt pools, caused by localized heat accumulation due to non-optimal processing parameters or scan path strategies. For coupons processed with a slicer-defined maximum scan vector length, swelling seldom occurred at internal vector-stripe boundaries. These results provide a mechanistic understanding of how swelling can be linked to material flaws, insight into how some instances of swelling can be avoided, and evidence supporting the use of swelling as an in situ indicator for quality assurance and part qualification.

Anomaly↗
DOE OSTI2019

Influence of Ba Substitutions on Microstructure and Magnetic Properties of La–Ca–Co System Permanent Ferrite

La{sub 0.6}Ca{sub 0.4−x}Ba{sub x}O⋅n/2(Fe{sub 1−y}Co{sub y}){sub 2}O{sub 3}(x = 0, 0.05, 0.1, 0.15 and 0.2) permanent ferrite materials were prepared by ceramic technique. The topography and the structure were characterized by scanning electron microscopy (SEM) and x-ray diffraction (XRD), respectively. The magnetic properties were measured using vibrating sample magnetometer (VSM) and digital magnetometer. Single M-phase and flake-like grains were obtained for samples without Ba substitution(x = 0), and the magnetic properties of the pre-sintering La–Ca–Co ferrite were as follows: B{sub r} = 440 mT, H{sub cb} = 296 kA/m, H{sub cj} = 426 kA/m, (BH){sub max} = 36.6 kJ/m{sup 3} and H{sub k}/H{sub cj} = 0.83. When Ca was substituted by Ba, pre-sintered powder presents single M-phase structure and close three-dimensional size of grains, resulting in an improved rectangle ratio of sintered magnet. The rectangle ratio of sintered magnet reaches a maximum of 0.93 when x = 0.1. By optimizing process parameters, M-type La–Ca–Ba–Co sintered magnet was prepared with B{sub r} = 445 mT, H{sub cb} = 337 kA/m, H{sub cj} = 420 kA/m, (BH){sub max} = 38.6 kJ/m{sup 3} and H{sub k}/H{sub cj} = 0.95.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2010

Installation and Testing of a Jorin Visual Process Analyzer

The Jorin Visual Process Analyzer (ViPA) is an on-line instrument that uses video microscope imaging to detect and measure the physical characteristics of dispersed objects within a process stream or laboratory sample. Object analysis is performed by capturing an on-going sequence of single frames from the video feed and relaying the images in real time to a nearby control computer where the ViPA software then processes and transfigures the information from the images into meaningful process data. The ViPA captures and analyzes approximately 15 images per second and continuously records 17 material parameters including size, shape and optical density. The ViPA software uses the measured parameters to differentiate between different classes of objects including organic droplets, gas bubbles, and solid particles. Procurement of this instrument provides a unique capability to support predictive modeling and further understanding of mass transfer during solvent extraction processes. Organic droplet data collected using the ViPA can be used to develop dispersion profiles of the liquid-liquid mixing and disengagements sections for each type of process equipment. These profiles will provide insight into mixing dynamics and will guide the prevention of emulsion formation that leads to system losses. Additionally, the measurement capabilities of the ViPA will provide the input needed to create new two-phase Computational Fluid Dynamics (CFD) models that characterize both mixing and separation operations in the various types of equipment. These models can then be used to improve process efficiency by optimizing operation parameters for each proposed extraction cycle.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

SISTec: Mathematical Calibration of Large Clearance Monitors - 18265

One major path for clearance of large amount of waste arising from the decommission of nuclear power plants is based on measurement with large clearance monitors (also known as free release measurement facilities). These devices utilize multi-detector plastic scintillator arrays (large clearance monitors can consist of up to 24 plastic scintillators) to offer both, extremely low minimum detectable activities (MDA) and short measurement times for waste packages weighing up to one metric ton. However, a major problem with these devices is to obtain nuclide specific efficiencies, especially for geometrically complex large waste packages. Normal procedure for estimating the efficiency is to device dummy waste packages and attach point sources with well-known activities to unfavourable positions in these packages. In accordance with this procedure, calibration factors can be derived in a radiological conservative way. Devising such test dummies is not always possible and the procedure is prone to generating large measurement uncertainties. In this publication, we propose a new method to derive calibration factors by means of the Los Alamos National Laboratory (LANL) simulation tool Monte Carlo N-Particle (MCNP) and a statistical-phenomenological model for the detector characterization. In a multi-step approach, first the detector response for a distribution of activity in a waste package is calculated and subsequently the detectors are mathematically characterized. Applying state of the art statistical and optimizing procedures, parameters for the detector response are derived in a self-consistent way. This also allows to rigorously propagate the uncertainties to the final calculated calibration factors according to the Guide to the Expression of Uncertainty in Measurement (GUM supplement 1). To validate the derived parameters for the detector characterization a minimally invasive experimental setup was devised and installed into the large clearance monitor. It consisted of an aluminum swivel arm which could position point sources to the relevant coordinates. The so collected measurement data not only allowed to investigate the precision of the calculated calibration factors, but also to probe the location of concentrated activity sources in the waste package. Furthermore, data on measurements with dummy waste packages were collected to test the reproducibility of well-known calibration factors. We present the software tool SIStec, which will provide an intuitive user-interface to generate and simulate waste package models and execute the above-mentioned method. Using SIStec, different scenarios for the distribution of activity in the waste package can be probed. This will also allow to optimize the clearance process on various levels. For example, measurement time for pre-measurements can be reduced in exchange for unfavourable calibration factors, which would still allow to meet the regulator limits for clearance. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Pulsed Magnetic Welding for Advanced Core and Cladding Steel

To investigate a solid-state joining method, pulsed magnetic welding (PMW), for welding the advanced core and cladding steels to be used in Generation IV systems, with a specific application for fuel pin end-plug welding. As another alternative solid state welding technique, pulsed magnetic welding (PMW) has not been extensively explored on the advanced steels. The resultant weld can be free from microstructure defects (pores, non-metallic inclusions, segregation of alloying elements). More specifically, the following objectives are to be achieved: 1. To design a suitable welding apparatus fixture, and optimize welding parameters for repeatable and acceptable joining of the fuel pin end-plug. The welding will be evaluated using tensile tests for lap joint weldments and helium leak tests for the fuel pin end-plug; 2 Investigate the microstructural and mechanical properties changes in PMW weldments of proposed advanced core and cladding alloys; 3. Simulate the irradiation effects on the PWM weldments using ion irradiation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Lower-Stratospheric Control of the Frequency of Sudden Stratospheric Warming Events

The sensitivity of stratospheric polar vortex variability to the basic-state stratospheric temperature profile is investigated by performing a parameter sweep experiment with a dry dynamical core general circulation model where the equilibrium temperature profiles in the polar lower and upper stratosphere are systematically varied. It is found that stratospheric variability is more sensitive to the temperature distribution in the lower stratosphere than in the upper stratosphere. In particular, a cold lower stratosphere favors a strong time-mean polar vortex with a large daily variability, promoting frequent sudden stratospheric warming events in the model runs forced with both wavenumber-1 and wavenumber-2 topographies. This sensitivity is explained by the control exerted by the lower-stratospheric basic state onto fluxes of planetary-scale wave activity from the troposphere to the stratosphere, confirming that the lower stratosphere can act like a valve for the upward propagation of wave activity. It is further shown that with optimal model parameters, stratospheric polar vortex climatology and variability mimicking Southern and Northern Hemisphere conditions are obtained with both wavenumber-1 and wavenumber-2 topographies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A two-step short-term probabilistic wind forecasting methodology based on predictive distribution optimization

With increasing wind penetrations into electric power systems, probabilistic wind forecasting becomes more critical to power system operations because of its capability of quantifying wind uncertainties. In this paper, a two-step probabilistic wind forecasting approach based on pinball loss optimization is developed. First, a multimodel machine learning-based ensemble deterministic forecasting framework is adopted to generate deterministic forecasts. The deterministic forecast is assumed to be the mean value of the predictive distribution at each forecasting time stamp. Then, the optimal unknown parameter (i.e., standard deviation) of the predictive distribution is estimated by a support vector regression surrogate model based on the deterministic forecasts. Lastly, probabilistic forecasts are generated from the predictive distribution. Numerical results of case studies at eight locations show that the developed two-step probabilistic forecasting methodology has improved the pinball loss metric score by up to 35% compared to a baseline quantile regression forecasting model.

17 WIND ENERGY↗
DOE OSTI2017

Utilization of Supercapacitors in Adaptive Protection Applications for Resiliency against Communication Failures: A Size and Cost Optimization Case Study

Microgrids’ adaptive protection techniques rely on communication signals from the point of common coupling to ad- just the corresponding relays’ settings for either grid-connected or islanded modes of operation. However, during communication out- ages or in the event of a cyberattack, relays settings are not changed. Thus adaptive protection schemes are rendered unsuc- cessful. Due to their fast response, supercapacitors, which are pre- sent in the microgrid to feed pulse loads, could also be utilized to enhance the resiliency of adaptive protection schemes to communi- cation outages. Proper sizing of the supercapacitors is therefore im- portant in order to maintain a stable system operation and also reg- ulate the protection scheme’s cost. This paper presents a two-level optimization scheme for minimizing the supercapacitor size along with optimizing its controllers’ parameters. The latter will lead to a reduction of the supercapacitor fault current contribution and an increase in that of other AC resources in the microgrid in the ex- treme case of having a fault occurring simultaneously with a pulse load. It was also shown that the size of the supercapacitor can be reduced if the pulse load is temporary disconnected during the transient fault period. Simulations showed that the resulting super- capacitor size and the optimized controller parameters from the proposed two-level optimization scheme were feeding enough fault currents for different types of faults and minimizing the cost of the protection scheme.

25 ENERGY STORAGE↗
DOE OSTI2020

Creating multifunctional synthetic lichen platforms for sustainable biosynthesis of biofuel precursors

In this project, we were creating a sustainable platform for biofuel production, utilizing carbon-fixing autotrophs to supply oxygen and organic substrates to heterotrophic partners, which in turn produce carbon dioxide to feed the autotrophs. This symbiotic lichen community could lower the input cost, optimize metabolic exchanges and improve the generation of biofuel precursors through multi-omics driven genetic engineering. The cyanobacteria Synechococcus elongatus (S. elongatus) was used as the primary autotroph to provide oxygen and organic substrates, especially sucrose, to a co-culture system. The strain with overexpression of sucrose transporter cscB demonstrated a significant increase in sucrose production under salt stress as what we expected. We also implemented 13C metabolic flux analysis on the sucrose secreting strain S. elongatus cscB-NaCl. Next, transporters proteins like glutamate exporter mscCG from Corynebacterium glutamicum was overexpressed in S. elongatus to improve metabolite exchange. We provided sucrose and glutamate to filamentous fungi to enable their growth and production of biochemicals using substrates from the cyanobacterium. Two fungi ( Aspergillus nidulans and Aspergillus niger ) and two yeast strains ( Rhodotorula toruloides and Lipomyces starkeyi ) served as heterotrophs in this system. They were co-cultured with S.elongatus under different pH condition, and growth on different carbon source to understand the symbiotic system and optimize the parameters for production. The two fungi strained grew much better at pH 7, 8 and 9 with Yeast Nitrogen Base (YNB ) supplementation. Two yeast strains grew well on pH 7 and 8 with YNB supplementation. All four species achieved the highest biomass level when utilizing sucrose as the main carbon sources, which demonstrates a great pairing with S.elongatus . In addition to investigate the metabolite exchange and growth condition of the co-culture system, we incorporated an Aspergillus strain expressing three genes (PAND, BAPAT and HPDH). Expression of these three genes enabled production of 3-hydroxypropionic acid (3HP) with a titer of 3-6 g/L regardless of pH and other nutrient conditions. Moreover, we developed a computational model with different heterotrophic fungi symbiosing with S.elongatus to evaluate the exchange of hundreds of metabolites. The accuracy and sensitivity had been optimized by high-throughput phenotyping assays. This project demonstrated ways to enhance a synthetic lichen platform’s efficiency and scalability to create a robust system for sustainable bioproduct synthesis. The project has enabled us to explore the technological and commercial potential of sustainable lichen co-culture. The project has also trained the next generation of scientists to address sustainability, carbon fixation, and design solutions to contemporary global challenges. The lichen platform represented a novel approach to sustainably producing bioproducts with a reduced carbon footprint and lower costs.

09 BIOMASS FUELS↗
DOE OSTI2012

Application of Spatial Data Modeling and Geographical Information Systems (GIS) for Identification of Potential Siting Options for Various Electrical Generation Sources

Oak Ridge National Laboratory (ORNL) initiated an internal National Electric Generation Siting Study, which is an ongoing multiphase study addressing several key questions related to our national electrical energy supply. This effort has led to the development of a tool, OR-SAGE (Oak Ridge Siting Analysis for power Generation Expansion), to support siting evaluations. The objective in developing OR-SAGE was to use industry-accepted approaches and/or develop appropriate criteria for screening sites and employ an array of Geographic Information Systems (GIS) data sources at ORNL to identify candidate areas for a power generation technology application. The initial phase of the study examined nuclear power generation. These early nuclear phase results were shared with staff from the Electric Power Research Institute (EPRI), which formed the genesis and support for an expansion of the work to several other power generation forms, including advanced coal with carbon capture and storage (CCS), solar, and compressed air energy storage (CAES). Wind generation was not included in this scope of work for EPRI. The OR-SAGE tool is essentially a dynamic visualization database. The results shown in this report represent a single static set of results using a specific set of input parameters. In this case, the GIS input parameters were optimized to support an economic study conducted by EPRI. A single set of individual results should not be construed as an ultimate energy solution, since US energy policy is very complex. However, the strength of the OR-SAGE tool is that numerous alternative scenarios can be quickly generated to provide additional insight into electrical generation or other GIS-based applications. The screening process divides the contiguous United States into 100 x 100 m (1-hectare) squares (cells), applying successive power generation-appropriate site selection and evaluation criteria (SSEC) to each cell. There are just under 700 million cells representing the contiguous United States. If a cell meets the requirements of each criterion, the cell is deemed a candidate area for siting a specific power generation form relative to a reference plant for that power type. Some SSEC parameters preclude siting a power plant because of an environmental, regulatory, or land-use constraint. Other SSEC assist in identifying less favorable areas, such as proximity to hazardous operations. All of the selected SSEC tend to recommend against sites. The focus of the ORNL electrical generation source siting study is on identifying candidate areas from which potential sites might be selected, stopping short of performing any detailed site evaluations or comparisons. This approach is designed to quickly screen for and characterize candidate areas. Critical assumptions supporting this work include the supply of cooling water to thermoelectric power generation; a methodology to provide an adequate siting footprint for typical power plant applications; a methodology to estimate thermoelectric plant capacity while accounting for available cooling water; and a methodology to account for future ({approx}2035) siting limitations as population increases and demands on freshwater sources change. OR-SAGE algorithms were built to account for these critical assumptions. Stream flow is the primary thermoelectric plant cooling source evaluated in this study. All cooling was assumed to be provided by a closed-cycle cooling (CCC) system requiring makeup water to account for evaporation and blowdown. Limited evaluations of shoreline cooling and the use of municipal processed water (gray) cooling were performed. Using a representative set of SSEC as input to the OR-SAGE tool and employing the accompanying critical assumptions, independent results for the various power generation sources studied were calculated.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Bayesian Learning of Adatom Interactions from Atomically Resolved Imaging Data

Atomic structures and adatom geometries of surfaces encode information about the thermodynamics and kinetics of the processes that lead to their formation, and which can be captured by a generative physical model. In this work, we develop a workflow based on a machine-learning-based analysis of scanning tunneling microscopy images to reconstruct the atomic and adatom positions, and a Bayesian optimization procedure to minimize statistical distance between the chosen physical models and experimental observations. We optimize the parameters of a 2- and 3-parameter Ising model describing surface ordering and use the derived generative model to make predictions across the parameter space. For concentration dependence, we compare the predicted morphologies at different adatom concentrations with the dissimilar regions on the sample surfaces that serendipitously had different adatom concentrations. The proposed workflow can be used to reconstruct the thermodynamic models and associated uncertainties from the experimental observations of materials microstructures. The code used in the manuscript is available at https://github.com/saimani5/Adatom_interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗