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At least 253 records · Page 14

BETO 2021 Peer Review - Advanced Catalyst Synthesis and Characterization (ACSC) Project WBS 2.5.4.304; 303; 305

The Advanced Catalyst Synthesis and Characterization (ACSC) project, in close collaboration with the Chemical Catalysis for Bioenergy (ChemCatBio) Consortium enabling projects, CatCost, and the Engineering of Catalyst Scale-Up project, (1) provides fundamental insight into working catalysts leading to actionable recommendations for all of the ChemCatBio catalysis projects, (2) addresses overarching catalysis challenges central to the ChemCatBio Consortium, and (3) adapts and applies new synthesis methodologies and in situ/operando characterization capabilities to meet the evolving needs of the catalysis projects. The outcome is a transition from empirical catalyst development to rational design through the prediction of materials with targeted properties based on advanced characterization combined with computational modeling, and the synthesis of next generation catalysts with predicted structures that yield demonstrated improvements in catalytic performance. In FY18, the ACSC helped to demonstrate the utility of the complete catalyst and process development cycle for dimethyl ether to high-octane gasoline over metal-modified zeolite catalysts for the Upgrading of C1 Building Blocks project, and in FY21 will leverage capabilities, expertise, and computational models established for this effort to target next-generation catalysts for ethanol to distillates for the Upgrading of C2 Intermediates project with enhanced performance in half the time.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Development of Kinetic and Radiation Hydrodynamics Modeling of Thermonuclear Burn Propagation in Isochoric p - 11 B Through the Support of the INFUSE Program

The report summarizes DOE INFUSE-supported work between HB11 Energy and the University of Rochester’s TriForce Institute to improve computational modeling of advanced fusion fuels, especially proton–boron-11 (p- 11 B). The project extended the TriForce particle-in-cell/Monte Carlo collision code to include physics needed for dense, high-temperature p- 11 B burn studies, including p- 11 B fusion reactions, three-alpha-particle reaction products, relativistic Coulomb collisions, large-angle nuclear scattering, bremsstrahlung radiation, inverse bremsstrahlung absorption, and photon transport. The upgraded models were verified against focused physics tests and against known deuterium–tritium burn behavior. The study then used one-dimensional spherical simulations to estimate the conditions required for thermonuclear burn propagation in isochoric p- 11 B fuel. The calculations found that burn propagation is possible in the model, but only under very extreme hot-spot conditions, such as about 7000 g/cm 3 at 500 keV or 9000 g/cm 3 at 300 keV for a 20-micron hot spot. These conditions are much more demanding than current demonstrated inertial confinement fusion hot spots. The report concludes that the INFUSE collaboration successfully advanced kinetic and radiation modeling capabilities for p- 11 B fusion and provided useful estimates of ignition requirements. However, the simulated fuel gains remain below what would be needed for practical inertial fusion energy, and further work is needed to reconcile differences among kinetic, radiation-hydrodynamic, and analytic models and to identify more achievable target designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Approaching the Practical Conductivity Limits of Aerosol Jet Printed Silver

Previous efforts to directly write conductive metals have been narrowly focused on nanoparticle ink suspensions that require aggressive sintering (>200°C) and result in low-density, small-grained agglomerates with electrical conductivities <25% of bulk metal. Here, we demonstrate aerosol jet printing of a reactive ink solution and characterize high-density (93%) printed silver traces having near-bulk conductivity and grain sizes greater than the electron mean free path, while only requiring low temperature (80°C) treatment. We have developed a predictive electronic transport model which correlates the microstructure to the measured conductivity and identifies a strategy to approach the practical conductivity limit for printed metals. Our analysis of how grain boundaries and tortuosity contribute to electrical resistivity provides insight into the basic materials science that governs how an ink formulator or process developer might approach improving the conductivity. Transmission line measurements validate that electrical properties are preserved up to 20GHz, which demonstrates the utility of this technique for printed RF components. Finally, this work reveals a new method of producing robust printed electronics that retain the advantages of rapid prototyping and three-dimensional fabrication while achieving the performance necessary for success within the aerospace and communications industries.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Crystallization of Ammonium Heptamolybdate for Reduction to Mo Metal

The 100 Mo/ 98 Mo recycle process developed by Argonne National Laboratory in collaboration with Oak Ridge National Laboratory (ORNL) and supported by the U.S. Department of Energy (DOE) National Nuclear Security Agency’s (NNSA’s) Office of Material Management & Minimization (M3) is vital to sustaining the economic production of 99 Mo. The high-yield molybdenum solution extraction (MOEX) process recovers enriched Mo by acidifying spent generator solutions, extracting Mo using tri-n-butyl phosphate (TBP), and stripping Mo into ammonium hydroxide, where it is later converted to solid (NH 4 ) 6 M 07 O 24 (ammonium heptamolybdate or AHM) by crystallization. It is important to produce the AHM product with consistent particle size and morphology before its thermal treatment and reduction to Mo metal in a furnace. AHM particles that are too small (< 50 µm) result in Mo metal powder that is much too fine to properly fabricate into targets with optimum properties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Passive method to measure strength of turbulence

Disclosed is a method to passively measure and calculate the strength of turbulence via the index of refraction structure constant Cn2 from video imagery gathered by an imaging device, such as a video camera. Processing may occur with any type computing device utilizing a processor executing machine executable code stored on memory. This method significantly simplifies instrumentation requirements, reduces cost, and provides rapid data output. This method combines an angle of arrival methodology, which provides scale factors, with a new spatial/temporal frequency domain method. As part of the development process, video imagery from high speed cameras was collected and analyzed. The data was decimated to video rates such that statistics could be computed and used to confirm that this passive method accurately characterizes the atmospheric turbulence. Cn2 accuracy from this method compared well with scintillometer data through two full orders of magnitude and more capability is expected beyond this verification.

O'Neill, Mary Morabito↗

Human Factors for Advanced Reactors

Existing light water reactors in the U.S. are primarily large baseload electricity generating facilities. The concept of operations for these plants remains largely unchanged since the advent of commercial nuclear power—the main control room serves as the hub of plant activities and is staffed with multiple licensed operators who work in tandem under the shift supervisor, and staff such as field workers support the control room remotely. While newer plants have brought the advent of digital human-machine interfaces to replace earlier analog and mechanical instrumentation and controls, much of the control process remains unchanged and manual. It is simply a newer version of legacy concepts. Advanced reactors potentially bring considerable changes to the size, fuel type, automation, and staffing of nuclear power plants, necessitating a fundamental shift not just from analog to digital, but further from human to automation, from onsite to remote, from control to monitoring, and from many to few operators. Despite this multitude of parallel evolutions in reactor designs, many of the vendors developing the next generation of reactors represent smaller research and development enterprises. It is therefore not feasible to address all aspects of plant design at the same time. In particular, the competing design aspects of new reactors present a significant challenge to the development of robust and human factored systems at the plant. As vendors develop new reactor designs, much of the early focus is naturally on the fuel and reactor system technology. Looming behind these early advances is the daunting prospect of first-of-a-kind control concepts that have not yet been developed or validated. A failure to address the human element of reactor design early will lead to missed opportunities. The quickest development process is the replication of existing concepts of operations at legacy plants, even when such systems were long ago surpassed by better human-machine technologies outside the nuclear industry. Conversely, attempting to undertake novel concepts of operations late in the design life cycle of a plant could result in protracted development efforts and delays in licensing and deployment. This does not have to happen, and it is imperative that human factors be considered now, early in the design of new reactors.

99 GENERAL AND MISCELLANEOUS↗

Root Cause Correlation Analysis of Software Failures via Orthogonal Defect Classification and Natural Language Processing

Systems theoretic process analysis (STPA) is becoming an increasingly popular technique to assess how complex digital software systems can fail. Rather than defining failures by their observable failure events, which may be sparse especially for safety rated nuclear digital instrumentation and control systems (DI&C), failures are defined as postulated unsafe actions under specific contextual conditions. This permits a top-down analysis of system hazards and identifies whether imposed constraints and requirements can sufficiently address undesirable hazards. However, STPA is a qualitative approach at identifying inadequacies in the development process and cannot currently be used to quantify unsafe action likelihoods for probabilistic risk assessment. Therefore, in this work, we examine the root causes of software failure and explore whether a consistent correlation can be linked to specific unsafe action classes. We implement Lbl2Vec, an unsupervised document classification and retrieval algorithm, on a database of 4,096 software defect reports acquired from various open-source software systems. By analyzing sentence structure, embedded labels, and word vectors, we show that certain defect types positively correlate to specific unsafe action classes over others. The correlations developed can be used to estimate the failure probability of safety intended DI&C systems which provides a licensing basis for nuclear plant modernization efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

The Influence of Ozone: Superstoichiometric Oxygen in Atomic Layer Deposition of Fe 2 O 3 Using tert -Butylferrocene and O 3

Understanding the chemical mechanisms at play in atomic layer deposition (ALD) is critical for effective process development and expansion of ALD into more complex classes of materials. In this work, a mechanistic study of iron oxide deposited by ALD using tert-butylferrocene and ozone as reactants is performed. Iron oxide ALD using ozone is a useful model system for mechanistic studies due to the prevalence of ozone-based ALD processes and the uses of iron oxide in ternary and quaternary metal oxides. Results show that saturation conditions require significantly greater exposures of both reactants than is typically reported in the literature, and growths per cycle of greater than one monolayer of Fe 2 O 3 per cycle are observed and explained. A growth mechanism is proposed whereby increased ozone exposure results in uptake of superstoichiometric oxygen into the film. X-ray characterizations reveal the presence of excess oxygen stored near the surface of films deposited with larger ozone exposures and show that increased ozone exposures cause crystalline domain rearrangement and conversion of the film from the γ-maghemite phase to the α-hematite phase. The mechanism described here has implications for the wider class of ozone-based ALD processes, and potential applications of this growth phenomenon are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Root Cause Correlation Analysis of Software Failures via Orthogonal Defect Classification and Natural Language Processing

Systems theoretic process analysis (STPA) is becoming an increasingly popular technique to assess how complex digital software systems can fail. Rather than defining failures by their observable failure events, which may be sparse especially for safety rated nuclear digital instrumentation and control systems (DI&C), failures are defined as postulated unsafe actions under specific contextual conditions. This permits a top-down analysis of system hazards and identifies whether imposed constraints and requirements can sufficiently address undesirable hazards. However, STPA is a qualitative approach at identifying inadequacies in the development process and cannot currently be used to quantify unsafe action likelihoods for probabilistic risk assessment. Therefore, in this work, we examine the root causes of software failure and explore whether a consistent correlation can be linked to specific unsafe action classes. We implement Lbl2Vec, an unsupervised document classification and retrieval algorithm, on a database of 4,096 software defect reports acquired from various open-source software systems. By analyzing sentence structure, embedded labels, and word vectors, we show that certain defect types positively correlate to specific unsafe action classes over others. The correlations developed can be used to estimate the failure probability of safety intended DI&C systems which provides a licensing basis for nuclear plant modernization efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

BETO 2021 Peer Review - Electrocatalytic CO2 Utilization

The goal of the ChemCatBio DataHub project is to accelerate the catalyst and process development cycle by developing transformational tools for prediction and collaboration in catalyst R&D. The project is currently focused on the development of the Catalyst Property Database (CPD), a free and public resource released in September 2020. The CPD was designed to advance the state of the art for application of computational data. When computational data, such as computed reaction energetics, is used in catalyst design, it is almost always generated by the researchers seeking to use it, even if similar data has been published previously. One barrier to data reuse that results in this duplication of effort is the difficult process of finding and applying published data, which can be slow, error-prone, and manual. The CPD seeks to overcome these challenges by creating a centralized, searchable database of quality catalyst property data. At present, the CPD contains computed adsorption energies for intermediates along catalytic pathways. During FY21 and FY22, development of the CPD continues with a focus on external users and meeting their requirements. A batch upload capability, training and curation procedures, user interviews, and a demonstration of the CPD's utility in accelerating catalyst research are planned. Overall, the Data Hub project and CPD aim to reduce the time and cost of catalyst research by harnessing the power of data in catalyst discovery.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

AOI [1]: Passive Wireless Sensor Systems Fabricated by Direct-Writing for Temperature and Health Monitoring of Energy Systems in Harsh-Environments (Final Report)

Researchers at West Virginia University (WVU) propose to demonstrate a wireless, high-temperature sensor system for monitoring the temperature and health of energy-system components. The active sensor and electronics for wireless communication will be composed entirely of an electroceramic materials (conductive ceramics) which are capable of withstanding the harsh-environments required for fossil energy-based technologies. This work will focus primarily on the fabrication and testing of temperature (thermocouples and thermistors) and health (strain/stress and crack propagation sensors) that function at extreme temperatures (up to 700-1700ºC). The electronics will accompany the high-temperature sensor, which will include a passive wireless communication circuit that allows the transmission of the data based on the LCR resonance principle to a near-by reader antenna. This passive transmission of data will reduce the need for interconnect wires near the active, and possibly rotating, energy-system component. The research will include process development to permit the 2D/3D direct-writing of the entire sensor and communication circuit onto the energy-system component. The direct-writing will be facilitated by using silicon-based polymer-derived precursors to form the high-temperature, stable electroceramic compositions. In addition, methods for direct-writing the circuit onto a fugitive carrier substrate will be completed, which will permit a “peel-and-stick”-like transfer of the sensor circuit to the energy-system component. This feature will allow the economical and precise placement of the sensor circuit onto components of various shapes and locations, without altering the geometry and active features of the manufactured component, or the removal (or decommissioning) of the component for installation. The proposed work will be directed at the following areas: 1) Investigation of phase formation, sintering/grain growth, and electrical properties of polymer-derived electroceramic composites; 2) Definition of processes to direct-write through ink-jet and robo-casting the polymer-derived electroceramic composites onto oxide and polymer surfaces; 3) Development of methods to form monolithic "peel-and-stick" preforms that will efficiently transfer the sensor circuit to ceramic surfaces after thermal treatment; 4) Design of passive wireless LCR circuits and receiver (reader) antennas for communication and testing at high temperatures; 5) Investigation of the passive wireless sensor system developed (and method of transferring sensor system) for temperature and stress/strain measurements on a SOFC repeat unit and a singular gas turbine blade prototype as example applications.

01 COAL, LIGNITE, AND PEAT↗

Fabrication of field-effect transistors with transfer-free nanostructured carbon as semiconducting channel material

Carbon nanostructures as active channel material in field effect transistors (FETs) are appealing in microelectronics for their improved performance such as high speed and low energy dissipation. However, these devices require the incorporation of nanostructure transfer steps in the fabrication process flow, which makes difficult its application in large scale integration circuits. Here we present a novel method for the fabrication of FETs with nanostructured carbon in the channel with p-type semiconducting properties and intermediate drain-source current (IDS) on/off ratio. The method is based on the use of Ni nanoparticles in the source-drain gap region as seed material for the formation of carbon nanostructures in the FET channel. FETs without Ni nanoparticles in the channel showed no modulation of IDS as a function of gate voltage. The device fabrication process does not require any carbon nanostructure transfer steps since it directly forms carbon nanostructures electrically connected to the device's source and drain electrodes via electron-beam evaporation of carbon and conventional lithographic processes. Since all device fabrication steps are compatible with Si technology processes, they are capable of being further optimized following process development protocols practiced by the semiconductor industry.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A Scoping Study to Determine the Location-Specific WEC Threshold Size for Wave-Powered AUV Recharging

The aim of this study is to determine the threshold wave energy converter (WEC) type and size to charge a fleet of U.S. Navy autonomous underwater vehicles (AUVs) in various geographic locations of interest. The U.S. Navy deploys AUVs in locations around the world that must be charged manually, decreasing their operational endurance and creating operational limitations. Ocean waves are a potential power source that can be converted into electricity using a WEC and stored using a battery. It would be beneficial to develop a WEC that could autonomously charge AUVs offshore. Numerous locations were analyzed to determine the minimum size of a WEC capable of providing sufficient charging power and offering a strategic advantage. By predicting the WEC efficiency (based on empirical equations) and wave resource (based on available data), electrical power generation across numerous WEC types and locations was compared in MATLAB. The generalized process developed here could be used to determine the required size and type of WECs to charge a fleet of AUVs in different locations around the world.

16 TIDAL AND WAVE POWER↗

Fuel Fabrication Capability Assessment in Support of Advanced Reactor Deployments

More than 30 U.S. companies are designing a variety of advanced reactor concepts, and several companies are planning to demonstrate their reactor designs in the mid-2020s to late 2030s time frame. In 2020, the U.S. Department of Energy (DOE) announced a series of awards under the Advanced Reactor Demonstration Program (ARDP) to accelerate the successful deployment of 10 of these reactors under three pathways. TerraPower and X-energy were awarded grants under the Advanced Reactor Demonstration Program to deploy their respective Natrium reactor and Xe-100 reactor designs in the next 7–10 years. These demonstrations are in addition to several parallel programs, including the U.S. Department of Defense’s (DoD’s) interest in the development of microreactors, and interest of the National Aeronautics and Space Administration in space nuclear power and propulsion. The National Reactor Innovation Center’s (NRIC’s) mission is to accelerate the demonstration and deployment of advanced reactors; NRIC is partnering with several reactor developers and harnessing the world-class capabilities of the U.S. National Laboratory system to deliver on its mission. Several of these reactor designs will require advanced fuel forms that are not commercially available today, including metal fuel, molten salt fuel, TRi-structural ISOtropic (TRISO) particle fuel, and uranium nitride fuel. Recognizing that there may be potential gaps in the laboratory-scale process development and pilot-scale first-of-a-kind (FOAK) production of these fuel forms leading to delivery of the FOAK cores, NRIC commissioned this study to look at the challenges that need to be overcome for successful deliveries, including the evaluation of existing facilities and the potential need for a new fuel fabrication facility.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data-driven Quasi-static Surrogate Models for Nuclear-powered Integrated Energy Systems

The integration of nuclear power into energy systems presents a promising avenue to address the growing global energy demands while minimizing greenhouse gas emissions. In this paper, we introduce a data-driven quasi-static surrogate model for nuclear-powered Integrated Energy Systems (IES) that comprises various components, including a small modular reactor (SMR), steam manifold, balance of plant (BOP), high-temperature steam electrolysis (HTSE), and district heating (DH) system. Traditional physics-based models for these components often entail significant computational resource and time consumption, necessitating the development of efficient surrogate models. The development of a complete surrogate model for the IES involves the creation of individual surrogate models for each component, leveraging machine learning techniques and simulated data. These isolated surrogate models are subsequently integrated, enabling a holistic view of the IES and reducing the computational burden associated with detailed physics-based simulations. This paper outlines the development process, validation, and the performance evaluation of the surrogate models. The exceptional performance, with low root-mean-squared errors and R-squared scores of at least 99.8% across all individual surrogate models, underscores their accuracy and practical applicability. These results demonstrate the potential of these models to expedite the analysis of nuclear-powered IES, offering insights that can shape future research and development efforts.

08 HYDROGEN↗

Containerization in ATLAS Software Development and Data Production

The ATLAS experiment's software production and distribution on the grid benefits from a semi-automated infrastructure that provides up-to-date information about software usability and availability through the CVMFS dis-tribution service for all relevant systems. The software development process uses a Continuous Integration pipeline involving testing, validation, packag-ing and installation steps. For opportunistic sites that can not access CVMFS, containerized releases are needed. These standalone containers are currently created manually to support Monte-Carlo data production at such sites. In this paper we will describe an automated procedure for the containerization of AT-LAS software releases in the existing software development infrastructure, its motivation, integration and testing in the distributed computing system.

97 MATHEMATICS AND COMPUTING↗

Microstructure and Mechanical Properties of the AA7075 Tube Fabricated using Shear Assisted Processing and Extrusion (ShAPE)

Shear Assisted Processing and Extrusion (ShAPE) experimental setup and tooling were adopted for extruding thin-walled AA7075 aluminum tube from as-cast non-homogenized billet material in a single run. The mechanical and microstructural characterizations were performed on the extrudate in the as-extruded condition without subsequent heat treating. It was shown that the ShAPE process developed a significantly refined microstructure with uniform and almost equiaxed grain structure on both hoop and axial cross-sections of the extrudate as well as through the thickness of the material. The pole figures and inverse pole figures of the EBSD data showed an strong shear texture development, and it was found out that axial shear is the dominant deformation mechanism in the regions near the inner surface of the tube, while combined axial and torsional shears are the two dominant modes of deformation near the outer surface of the extrudate. As for the mechanical properties, there was an increase of 150% and 73% in the yield and ultimate strengths of the tube produced using ShAPE process, respectively, and a 18% decrease in maximum uniform plastic elongation compared to the conventionally extruded AA7075-O tube.

Shear Assisted Processing and Extrusion, Friction ↗