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DOE OSTI2024

Correlative X-ray micro-nanotomography with scanning electron microscopy at the Advanced Light Source

Geological samples are inherently multi-scale. Understanding their bulk physical and chemical properties requires characterization down to the nano-scale. A powerful technique to study the three-dimensional microstructure is X-ray tomography, but it lacks information about the chemistry of samples. To develop a methodology for measuring the multi-scale 3D microstructure of geological samples, correlative X-ray micro- and nanotomography were performed on two rocks followed by scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS) analysis. The study was performed in five steps: (i) micro X-ray tomography was performed on rock sample cores, (ii) samples for nanotomography were prepared using laser milling, (iii) nanotomography was performed on the milled sub-samples, (iv) samples were mounted and polished for SEM analysis and (v) SEM imaging and compositional mapping was performed on micro and nanotomography samples for complimentary information. Correlative study performed on samples of serpentine and basalt revealed multiscale 3D structures involving both solid mineral phases and pore networks. Significant differences in the volume fraction of pores and mineral phases were also observed dependent on the imaging spatial resolution employed. This highlights the necessity for the application of such a multiscale approach for the characterization of complex aggregates such as rocks. Information acquired from the chemical mapping of different phases was also helpful in segmentation of phases that did not exhibit significant contrast in X-ray imaging. Adoption of the protocol used in this study can be broadly applied to 3D imaging studies being performed at the Advanced Light Source and other user facilities.

58 GEOSCIENCES↗

DOE OSTI2025

Thermal Systems Modeling for Integration of Industrial Processes with Advanced Nuclear

Applying combined heat and power concepts to advanced nuclear reactors can enable increased nuclear utilization in the future clean economy, as well as provide safe and reliable clean energy to industrial systems. Analyses have been performed to evaluate the integration of nuclear energy with industrial processes for both clean electricity production and providing process heat for direct use to reduce emissions in the production of chemical commodities. The key research question that needs to be answered is: "What are the prospective approaches for integrating nuclear-generated heat energy into non-electric applications that can facilitate combined heat and power operations by advanced nuclear reactor systems?" This presentation will highlight several case studies showing conceptual designs for thermal delivery systems to integrate small modular reactor (SMR) process steam and electricity with industrial processes including oil refining, hydrogen production, and methanol production.

hydrogen↗

DOE OSTI2022

Summary of Development for Structural Component Modeling in Fiscal Year 2022

This report summarizes efforts performed during Fiscal Year 2022 to develop capabilities for modeling structural component degradation in support of the U.S. Department of Energy's Nuclear Energy Advanced Modeling and Simulation Program. These efforts were centered around development of capabilities for the Grizzly code. Efforts focused both on foundational engineering-scale analysis capabilities for damage and shell formulations and on material-scale tools for accounting for irradiation effects in Grade 91 steel. A major outcome of this effort was the development of a general-purpose tool for nonlocal averaging of material properties, which enabled nonlocal damage models. In addition, the applicability of the shell elements in MOOSE has been expanded to allow modeling a wider range of component geometries and using a wide variety of material models. For irradiation effects on materials, a previously developed cluster dynamics model for light water reactor pressure vessel steels has been adapted for application to Grade 91 alloy. This work builds on prior efforts to build a flexible, capable code for addressing a variety of aging and component performance issues in nuclear power plant structural components.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Stabilizing dynamic subsea power cables using Bi-stable nonlinear energy sinks

This study investigates vibration mitigation of dynamic subsea cables through passive bi-stable nonlinear energy sinks (B-NESs). These devices suppress vibration energy in a broadband way, and can be regarded as extensions of classical linear tuned mass dampers (TMDs) which are narrowband devices. Through the open-source MoorDyn library, we simulated the vibrations of a vertical subsea cable equipped with a set of B-NESs. Multi-objective optimization was performed to detect the B-NES parameters for optimal mitigation of the cable vibrations. Advanced signal processing verified the efficacy of the optimized B-NESs not only to rapidly absorb and locally dissipate vibration energy, but also to nonlinearly scatter vibration energy from low to high frequencies within the cable itself. This last feature is especially beneficial for vibration mitigation of the undersea cable, as at higher frequencies the cable vibrations exhibit drastically reduced amplitudes and are more effectively dissipated by inherent structural damping and hydrodynamic radiation damping. This contrasts with traditional TMDs which can mitigate vibration only at a single frequency. Furthermore, our robustness study confirms the B-NES's effectiveness under even varying environmental conditions. Overall, the B-NES's capacity for broadband vibration mitigation renders it a promising retrofit solution for improving the performance and operational safety of dynamic power cables in offshore wind farms and other marine applications.

17 WIND ENERGY↗

DOE OSTI2014

Fission Yields and Other Diagnostics for Nuclear Performance

I summarize advances in our understanding of basic nuclear physics cross sections and decay properties that are needed to characterize the magnitude and energy-dependence of a neutron flux, and to determine the amount of fission burnup in plutonium fuel. The number of fissions that have occurred in a neutron environment can be deduced from measurements of the fission products created, providing that the fission product yields are known accurately. I describe how our understanding of plutonium fission product yields has improved in recent years through a meta-analysis of various measured data, and through identification of fission product yield incident-energy dependencies over the 0.2-2 MeV fast energy region. This led to the resolution of a previous discrepancy between the Los Alamos and Lawrence Livermore National Laboratories in their plutonium yield assessments in the fast energy region, although more experimental work is still needed to resolve discrepancies at 14 MeV. Work is also described that has improved our understanding of (n,2n) cross sections that are used as diagnostics of the high-energy neutron spectrum – both on plutonium and americium, and on the radiochemical detectors yttrium, iridium, and thulium. Finally, some observations are made on the importance of continuing to develop our Evaluated Nuclear Data Files (ENDF) database using physics insights from differential cross section and integral laboratory experiments and from nuclear theory advances.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1976

A summary of the ECAS performance and cost results for MHD system

The interagency-funded, NASA-coordinated Energy Conversion Alternatives Study (ECAS) has studied the potential of various advanced power plant concepts using coal and coal-derived fuel. Principle studies were conducted through prime contracts with the General Electric Company and the Westinghouse Electric Corporation. The results indicate that open-cycle coal-fired direct-preheat MHD systems have potentially one of the highest coal-pile-to-bus-bar efficiencies and also one of the lowest costs of electricity (COE) of the systems studied. Closed-cycle MHD systems may have the potential to approach the efficiency and COE of open-cycle MHD. The 1200-1500 F liquid-metal MHD systems studied do not appear to have the potential of exceeding the efficiency or competing with the COE of advanced steam plants.

Seikel, G. R.↗

DOE OSTI2015

Fully Coupled Simulation of Lithium Ion Battery Cell Performance

Lithium-ion battery particle-scale (non-porous electrode) simulations applied to resolved electrode geometries predict localized phenomena and can lead to better informed decisions on electrode design and manufacturing. This work develops and implements a fully-coupled finite volume methodology for the simulation of the electrochemical equations in a lithium-ion battery cell. The model implementation is used to investigate 3D battery electrode architectures that offer potential energy density and power density improvements over traditional layer-by-layer particle bed battery geometries. Advancement of micro-scale additive manufacturing techniques has made it possible to fabricate these 3D electrode microarchitectures. A variety of 3D battery electrode geometries are simulated and compared across various battery discharge rates and length scales in order to quantify performance trends and investigate geometrical factors that improve battery performance. The energy density and power density of the 3D battery microstructures are compared in several ways, including a uniform surface area to volume ratio comparison as well as a comparison requiring a minimum manufacturable feature size. Significant performance improvements over traditional particle bed electrode designs are observed, and electrode microarchitectures derived from minimal surfaces are shown to be superior. A reduced-order volume-averaged porous electrode theory formulation for these unique 3D batteries is also developed, allowing simulations on the full-battery scale. Electrode concentration gradients are modeled using the diffusion length method, and results for plate and cylinder electrode geometries are compared to particle-scale simulation results. Additionally, effective diffusion lengths that minimize error with respect to particle-scale results for gyroid and Schwarz P electrode microstructures are determined.

25 ENERGY STORAGE↗

DOE OSTI2025

Versatile Liquid Crystal Elastomer Formulations Using Amine-Acrylate Chemistry and Processing for Advanced Manufacturing

This study aims to tune rheological properties of liquid crystal elastomers (LCEs) through a strategic approach, leveraging the differing reaction rates of thiols and primary and secondary amines with acrylate monomers or the inclusion of processing additives to enable amenability to advanced manufacturing. We found that varying the time of oligomerization at elevated temperatures of amine-functional monomers with acrylate-functional monomers enabled simple control of rheological properties. Additionally, we could also control rheological properties by introducing reinforcing fillers or organic solvents. By varying the oligomerization conditions, we achieved a broad range of viscosities, from 1.1 Pa s to 560 Pa s as measured at 60 °C. When the rheological properties were varied through the incorporation of various solid and liquid inclusions, viscosities could range from less than 1 Pa s to nearly 1000 Pa s when measured at 60 °C. The shape morphing capabilities that are intrinsic to LCEs and the mechanical properties were also characterized. Here, we find that the oligomerization conditions and the addition of fillers influence shape morphing and energy absorption, as characterized by the stress–strain characteristics, further suggesting their potential to be used in energy dissipation applications where performance can be turned. Last, we demonstrate how the range of accessible rheological properties grants formulations amenable to various advanced manufacturing techniques.

Liquid chromatography↗

DOE OSTI2022

Accelerating the discovery of novel magnetic materials using machine learning–guided adaptive feedback

Magnetic materials are essential for energy generation and information devices, and they play an important role in advanced technologies and green energy economies. Currently, the most widely used magnets contain rare earth (RE) elements. An outstanding challenge of notable scientific interest is the discovery and synthesis of novel magnetic materials without RE elements that meet the performance and cost goals for advanced electromagnetic devices. Here, we report our discovery and synthesis of an RE-free magnetic compound, Fe 3 CoB 2 , through an efficient feedback framework by integrating machine learning (ML), an adaptive genetic algorithm, first-principles calculations, and experimental synthesis. Magnetic measurements show that Fe 3 CoB 2 exhibits a high magnetic anisotropy ( K 1 = 1.2 MJ/m 3 ) and saturation magnetic polarization ( J s = 1.39 T), which is suitable for RE-free permanent-magnet applications. Our ML-guided approach presents a promising paradigm for efficient materials design and discovery and can also be applied to the search for other functional materials.

36 MATERIALS SCIENCE↗

DOE OSTI2017

ATR Spent Fuel Options Study

The Advanced Test Reactor (ATR) is a materials and fuels test nuclear reactor that performs irradiation services for the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Naval Reactors, the National Nuclear Security Administration (NNSA), and other research programs. ATR achieved initial criticality in 1967 and is expected to operate in support of needed missions until the year 2050 or beyond. It is anticipated that ATR will generate approximately 105 spent nuclear fuel (SNF) elements per year through the year 2050. Idaho National Laboratory (INL) currently stores 2,008 ATR SNF elements in dry storage, 976 in wet storage, and expects to have 1,000 elements in wet storage before January 2017. A capability gap exists at INL for long-term (greater than the year 2050) management, in compliance with the Idaho Settlement Agreement (ISA), of ATR SNF until a monitored retrievable geological repository is open. INL has significant wet and dry storage capabilities that are owned by the DOE Office of Environmental Management (EM) and operated and managed by Fluor Idaho, which include the Idaho Nuclear Technology and Engineering Center’s (INTEC’s) CPP-666, CPP-749, and CPP-603. In addition, INL has other capabilities owned by DOE-NE and operated and managed by Battelle Energy Alliance, LLC (BEA), which are located at the Materials and Fuel Complex (MFC). Additional storage capabilities are located on the INL Site at the Naval Reactors Facility (NRF). Current INL SNF management planning, as defined in the Fluor Idaho contract, shows INTEC dry fuel storage, which is currently used for ATR SNF, will be nearly full after transfer of an additional 1,000 ATR SNF from wet storage. DOE-NE tasked BEA with identifying and analyzing options that have the potential to fulfill this capability gap. BEA assembled a team comprised of SNF management experts from Fluor Idaho, Savannah River Site (SRS), INL/BEA, and the MITRE Corp with an objective of developing and analyzing options for fulfilling the capability gap. This management options analysis is not an alternatives analysis as defined by DOE Order 413.3B; rather, it is an evaluation of near-term, mid term and long-term actions needed to fulfill the capability gap. The actions are described in sufficient detail to inform stakeholders and DOE decision makers regarding a potential path forward. The recommended path forward will inform Fiscal Year 2019 budget formulation, support potential National Environmental Policy Act (NEPA) analyses, and may or may not include capital asset projects.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Social energy: mining energy from the society

The inherent nature of energy, i.e., physicality, sociality and informatization, implies the inevitable and intensive interaction between energy systems and social systems. From this perspective, we define 'social energy' as a complex sociotechnical system of energy systems, social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system interactions. The recent advancement in intelligent technology, including artificial intelligence and machine learning technologies, sensing and communication in Internet of Things technologies, and massive high performance computing and extreme-scale data analytics technologies, enables the possibility of substantial advancement in socio-technical system optimization, scheduling, control and management. In this paper, we provide a discussion on the nature of energy, and then propose the concept and intention of social energy systems for electrical power. A general methodology of establishing and investigating social energy is proposed, which is based on the ACP approach, i.e., 'artificial systems' (A), 'computational experiments' (C) and 'parallel execution' (P), and parallel system methodology. A case study on the University of Denver (DU) campus grid is provided and studied to demonstrate the social energy concept. In the concluding remarks, we discuss the technical pathway, in both social and nature sciences, to social energy, and our vision on its future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

In situ embedment of type K sheathed thermocouples with directed energy deposition

Advanced nuclear reactor systems require new technologies for heat transfer and system monitoring. Additive manufacturing (AM) offers the design flexibility to allow in-situ sensor embedment through smart manufacturing for real-time monitoring, and performance of these systems. Here, this study focuses on experiments investigating the feasibility of in-situ sensor embedment using directed energy deposition (DED). Type K thermocouples are embedded into 316L stainless steel (SS) samples using two different configurations (e.g., exposed and embedded tips) and two designs (e.g., flush to substrate) within an AM base. Embedded sensor samples are analyzed via in-situ measurements and high-temperature performance validation tests at 350ºC and 900ºC. Temperature performance results at both temperature tests show good agreement with manufacturer specifications proving that these sensors could still capture accurate temperature readings after in-situ embedment during DED processing. An additional optimization experiment was conducted on the exposed tip configuration using a surrogate thermocouple to improve tolerances and the embedment process. Results improved tolerances, lower porosity, smaller gaps between the sensor and base, and better junction contact for the sensor. Although further optimization of this embedment strategy is necessary to improve the structural stability and tolerances within the component, this research strategy provides a proof-of-feasibility for DED embedment with commercial sheathed thermocouples. This research provides early impact on embedment of sensor for multiple materials and complex geometric components..

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

DEMO-FTES: Development, Monitoring, and Control of Fracture Thermal Energy Storage in Crystalline Rock Formations (CRADA Final Report)

The DEMO-FTES project investigated the feasibility of Fracture Thermal Energy Storage (FTES) as a seasonal energy storage solution in crystalline rock formations. FTES leverages hydraulically induced fractures to exchange heat between circulating fluids and the surrounding rock mass, enabling long-term thermal energy retention due to the high specific heat and low thermal conductivity of rock. This approach has the potential to reduce heating and cooling energy demands and enhance building energy resilience. The project combined dimensional analysis, numerical modeling, laboratory experiments, and meso-scale field tests to evaluate FTES performance and advance its technology readiness level from 3 to 5. Scaling analysis identified key dimensionless parameters governing heat transfer and fluid flow, ensuring laboratory and field tests were representative of larger-scale systems. Numerical simulations using TOUGH and iTOUGH2 frameworks supported experiment design and interpretation, modeling fracture geometry, thermal-hydraulic behavior, and thermo-mechanical coupling. Laboratory tests at EPFL involved creating single and multiple fractures in 25 cm cubic samples of Gabbro and Granite under true triaxial stress.

25 ENERGY STORAGE↗

DOE OSTI2014

Organo-sulfur molecules enable iron-based battery electrodes to meet the challenges of large-scale electrical energy storage

Rechargeable iron-air and nickel-iron batteries are attractive as sustainable and inexpensive solutions for large-scale electrical energy storage because of the global abundance and eco-friendliness of iron, and the robustness of iron-based batteries to extended cycling. Despite these advantages, the commercial use of iron-based batteries has been limited by their low charging efficiency. This limitation arises from the iron electrodes evolving hydrogen extensively during charging. The total suppression of hydrogen evolution has been a significant challenge. We have found that organo-sulfur compounds with various structural motifs (linear and cyclic thiols, dithiols, thioethers and aromatic thiols) when added in milli-molar concentration to the aqueous alkaline electrolyte, reduce the hydrogen evolution rate by 90%. These organo-sulfur compounds form strongly adsorbed layers on the iron electrode and block the electrochemical process of hydrogen evolution. The charge-transfer resistance and double-layer capacitance of the iron/electrolyte interface confirm that the extent of suppression of hydrogen evolution depends on the degree of surface coverage and the molecular structure of the organo-sulfur compound. An unanticipated electrochemical effect of the adsorption of organo-sulfur molecules is "de-passivation" that allows the iron electrode to be discharged at high current values. The strongly adsorbed organo-sulfur compounds were also found to resist electro-oxidation even at the positive electrode potentials at which oxygen evolution can occur. Through testing on practical rechargeable battery electrodes we have verified the substantial improvements to the efficiency during charging and the increased capability to discharge at high rates. We expect these performance advances to enable the design of efficient, inexpensive and eco-friendly iron-based batteries for large-scale electrical energy storage.

Yang, B↗

DOE OSTI2015

Photoluminescence of radiation-induced color centers in lithium fluoride thin films for advanced diagnostics of proton beams

Systematic irradiation of thermally evaporated 0.8 μm thick polycrystalline lithium fluoride films on glass was performed by proton beams of 3 and 7 MeV energies, produced by a linear accelerator, in a fluence range from 10{sup 11} to 10{sup 15} protons/cm{sup 2}. The visible photoluminescence spectra of radiation-induced F{sub 2} and F{sub 3}{sup +} laser active color centers, which possess almost overlapping absorption bands at about 450 nm, were measured under laser pumping at 458 nm. On the basis of simulations of the linear energy transfer with proton penetration depth in LiF, it was possible to obtain the behavior of the measured integrated photoluminescence intensity of proton irradiated LiF films as a function of the deposited dose. The photoluminescence signal is linearly dependent on the deposited dose in the interval from 10{sup 3} to about 10{sup 6 }Gy, independently from the used proton energies. This behavior is very encouraging for the development of advanced solid state radiation detectors based on optically transparent LiF thin films for proton beam diagnostics and two-dimensional dose mapping.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

03.02.02.45: Energy Efficiency Improvement Approaches in Ice Related Processes

The primary objective of this project was to facilitate the dislocation of the interfacial ice layer by employing advanced materials and ultrasonic vibration to reduce ice adhesion strength. This work employed two technical approaches that were thoroughly investigated and previously reported. The effectiveness of these approaches, both individually and in combination, has been quantified, demonstrating notable energy savings. The projected payback period for these enhancements is approximately 2.2 years or less, contingent upon specific energy costs. Furthermore, these advancements hold significant promise for reducing carbon emissions across various equipment scales. This study particularly focused on the ultrasonic deicing technique for diverse structures, utilizing numerical simulations to evaluate performance and potential benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing

The application of data science in cancer research has been boosted by major advances in three primary areas: (1) Data: diversity, amount, and availability of biomedical data; (2) Advances in Artificial Intelligence (AI) and Machine Learning (ML) algorithms that enable learning from complex, large-scale data; and (3) Advances in computer architectures allowing unprecedented acceleration of simulation and machine learning algorithms. These advances help build in silico ML models that can provide transformative insights from data including: molecular dynamics simulations, next-generation sequencing, omics, imaging, and unstructured clinical text documents. Unique challenges persist, however, in building ML models related to cancer, including: (1) access, sharing, labeling, and integration of multimodal and multi-institutional data across different cancer types; (2) developing AI models for cancer research capable of scaling on next generation high performance computers; and (3) assessing robustness and reliability in the AI models. In this paper, we review the National Cancer Institute (NCI) -Department of Energy (DOE) collaboration, Joint Design of Advanced Computing Solutions for Cancer (JDACS4C), a multi-institution collaborative effort focused on advancing computing and data technologies to accelerate cancer research on three levels: molecular, cellular, and population. This collaboration integrates various types of generated data, pre-exascale compute resources, and advances in ML models to increase understanding of basic cancer biology, identify promising new treatment options, predict outcomes, and eventually prescribe specialized treatments for patients with cancer.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Performance Analysis of Li-ion Battery Under Various Thermal and Load Conditions

In the recent years, with the rapid advancements made in the technologies of electric and hybrid electric vehicles, selecting suitable batteries has become a major factor. Among the batteries currently used for these types of vehicles, the lithium-ion battery leads the race. Apart from that, the energy gained from regenerative braking in locomotives and vehicles can be stored in batteries for later use for propulsion thus improving the fuel consumption and efficiency. But batteries can be subjected to a wide range of temperatures depending upon the operating conditions. Thus, a thorough knowledge of the battery performance over a wide range of temperatures and different load conditions is necessary for their successful employment in future technologies. In this context, this study aims to experimentally analyze the performance of Li-ion batteries by monitoring the charge–discharge rates, efficiencies, and energy storage capabilities under different environmental and load conditions. Sensors and thermal imaging camera were used to track the environment and battery temperatures, whereas the charge–discharge characteristics were analyzed using CADEX analyzer. The results show that the battery performance is inversely proportional to charge–discharge rates. This is because, at higher charge–discharge rates, the polarization losses increase thus increasing internal heat generation and battery temperature. Also, based on the efficiency and energy storage ability, the optimum performing conditions of the Li-ion battery are 30–40 °C (temperature) and 0.5 C (C-rate).

25 ENERGY STORAGE↗