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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ultrafast carrier dynamics in terahertz photoconductors and photomixers: beyond short-carrier-lifetime semiconductors

Abstract Efficient terahertz generation and detection are a key prerequisite for high performance terahertz systems. Major advancements in realizing efficient terahertz emitters and detectors were enabled through photonics-driven semiconductor devices, thanks to the extremely wide bandwidth available at optical frequencies. Through the efficient generation and ultrafast transport of charge carriers within a photo-absorbing semiconductor material, terahertz frequency components are created from the mixing products of the optical frequency components that drive the terahertz device – a process usually referred to as photomixing. The created terahertz frequency components, which are in the physical form of oscillating carrier concentrations, can feed a terahertz antenna and get radiated in case of a terahertz emitter, or mix with an incoming terahertz wave to down-convert to DC or to a low frequency photocurrent in case of a terahertz detector. Realizing terahertz photoconductors typically relies on short-carrier-lifetime semiconductors as the photo-absorbing material, where photocarriers are quickly trapped within one picosecond or less after generation, leading to ultrafast carrier dynamics that facilitates high-frequency device operation. However, while enabling broadband operation, a sub-picosecond lifetime of the photocarriers results in a substantial loss of photoconductive gain and optical responsivity. In addition, growth of short-carrier-lifetime semiconductors in many cases relies on the use of rare elements and non-standard processes with limited accessibility. Therefore, there is a strong motivation to explore and develop alternative techniques for realizing terahertz photomixers that do not rely on these defect-introduced short-carrier-lifetime semiconductors. This review will provide an overview of several promising approaches to realize terahertz emitters and detectors without short-carrier-lifetime semiconductors. These novel approaches utilize p-i-n diode junctions, plasmonic nanostructures, ultrafast spintronics, and low-dimensional materials to offer ultrafast carrier response. These innovative directions have great potentials for extending the applicability and accessibility of the terahertz spectrum for a wide range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Recent Trends and Innovation in Additive Manufacturing of Soft Functional Materials

The growing demand for wearable devices, soft robotics, and tissue engineering in recent years has led to an increased effort in the field of soft materials. With the advent of personalized devices, the one-shape-fits-all manufacturing methods may soon no longer be the standard for the rapidly increasing market of soft devices. Recent findings have pushed technology and materials in the area of additive manufacturing (AM) as an alternative fabrication method for soft functional devices, taking geometrical designs and functionality to greater heights. For this reason, this review aims to highlights recent development and advances in AM processable soft materials with self-healing, shape memory, electronic, chromic or any combination of these functional properties. Furthermore, the influence of AM on the mechanical and physical properties on the functionality of these materials is expanded upon. Additionally, advances in soft devices in the fields of soft robotics, biomaterials, sensors, energy harvesters, and optoelectronics are discussed. Lastly, current challenges in AM for soft functional materials and future trends are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Transducerless time domain reflectance measurement of semiconductor thermal properties

The dominant techniques for laser-based thermal measurement, time-domain thermoreflectance (TDTR) and frequency-domain thermoreflectance, generally require that samples be coated with a metal transducer layer. The properties of the transducer and its interface to the sample are then important to the interpretation of results, and heat conduction in the transducer layer can limit measurements of ultra-thin samples or in-plane conductivity. Here, we demonstrate the feasibility of measuring semiconductor samples using standard TDTR instrumentation, without the use of a metal transducer. A mathematical model accounting for non-zero laser penetration depth as well as both thermal and charge carrier effects is presented, and the ability of the model to describe and fit to experimental data for silicon and germanium samples is demonstrated. Though at this stage measurement uncertainties are larger than for traditional TDTR, we anticipate that the use of this technique will expand the range of samples that can be measured with existing TDTR setups.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Numerically exact generalized Green's function cluster expansions for electron-phonon problems

We generalize the family of approximate momentum average methods to formulate a numerically exact, convergent hierarchy of equations whose solution provides an efficient algorithm to compute the Green's function of a particle dressed by bosons suitable in the entire parameter regime. We use this approach to extract ground-state properties and spectral functions. Our approximation-free framework, dubbed the generalized Green's function cluster expansion (GGCE), allows access to exact numerical results in the extreme adiabatic limit, where many standard methods struggle or completely fail. We showcase the performance of the method, specializing three important models of charge-boson coupling in solids and molecular complexes: the molecular Holstein model, which describes coupling between charge density and local distortions, the Peierls model, which describes modulation of charge hopping due to intersite distortions, and a more complex Holstein + Peierls system with couplings to two different phonon modes, paradigmatic of charge-lattice interactions in organic crystals. Furthermore, the GGCE serves as an efficient approach that can be systematically extended to different physical scenarios, thus providing a tool to model the frequency dependence of dressed particles in realistic settings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Meta-Study of Particulate Detection Losses on Radioactive Air Sample Filters

Several mathematical relationships between air sample filter mass loading and the correlated analytical self-absorption factor were developed using data from other published research in this meta-study. Gross-alpha and -beta applications are addressed for this research. As filter media becomes loaded with particulate matter, there is potential for measurement losses due to self-absorption by mass loading. Components contributing to absorption include particulate dust, radioactive particulates, and filter material. Standards indicate a correction factor should be used when the penetration of radioactive material into the collection media or self-absorption of radiation by the material collected would reduce the detection rate by more than 5%. Previously, losses due to self-absorption have been reported up to 100% over a range up to ~10 mg∙cm -2 mass loading. These absorption losses then can be used to determine a correction factor for sample results. For low mass loadings (e.g., ≤0.1 mg∙cm -2 ) corrections factors in the 0.85 - 1 range have been recommended and used, while at higher mass loadings nearer to 10 mg∙cm -2 correction factors closer to 0 (representing near 100% losses) are used. Based on data from published studies, the different methods for relating percent loss due to self-absorption to mass loading include linear, exponential, quadratic, and trinomial derived functions. Where applicable, both forced zero and non-forced zero results were evaluated. From the derived functions evaluated, the trinomial function provided the best fit. Once the sample filter mass loading is known, the trinomial function can be applied to estimate losses and the corresponding self-absorption factor. When applied to routine operating conditions for radiological facility stacks monitored at the Pacific Northwest National Laboratory for an average sample filter mass loading of 0.09 ± 0.12 (2σ) mg∙cm -2 (excluding negative values and outliers) and a range from 0 - 0.24 mg∙cm -2 , the estimated trinomial function nominal self-absorption losses are less than 5% at 0.09 mg∙cm -2 and less than 10% at 0.24 mg∙cm -2 . The trinomial function is one method that may be used to adjust the activity results of an air sample when the sample-specific mass loading is determined. The application of no correction factor when the ANSI/HPS N13.1-2021 guidance of a 5% threshold for loss is not reached with typical stack sample mass loadings may be reasonable in high-efficiency particulate air filtered systems. For simplicity, it would be conservative in assigning the self-absorption correction factor at the 5% threshold (i.e., 0.95) for general uses but in cases of heavy mass loading to calculate the factor.

air sampling↗
DOE OSTI2025

Lines of Bound States in the Continuum in Monodisperse Microsphere Structures

Incorporating epitaxially grown active semiconductor media into self-assembled microsphere crystals has remained a major challenge as the curved geometry of the spheres is incompatible with conventional planar growth and patterning techniques. As a result, active photonic devices based on such self-assembled structures, which have other desirable properties such as enabling the rapid assembly of large area systems, have been elusive. Here, we numerically demonstrate an alternative route to creating high-Q resonances in microsphere-based nanophotonic assemblies compatible with standard optical gain materials. We show that close-packed layers of monodisperse microspheres can exhibit symmetry bandgaps, regardless of their layer stacking order. Thus, this microsphere environment can be used to create lines of bound states in the continuum (BICs) of an embedded slab made of active material. Using a realistic ZnS@SiO 2 (core-shell) architecture and sphere diameters compatible with scalable colloidal assembly, we predict sharp spectral features in angle-resolved transmission that trace these lines of BICs and persist in the presence of some fabrication disorder. Altogether, in enabling the integration of unpatterned epitaxial gain slabs with large-area colloidal microsphere assemblies, this approach opens a practical path toward active, dynamically reconfigurable photonic devices that leverage BIC physics for narrow-linewidth lasing and enhanced light–matter interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Learning crystal field parameters using convolutional neural networks

We present a deep machine learning algorithm to extract crystal field (CF) Stevens parameters from thermodynamic data of rare-earth magnetic materials. The algorithm employs a two-dimensional convolutional neural network (CNN) that is trained on magnetization, magnetic susceptibility and specific heat data that is calculated theoretically within the single-ion approximation and further processed using a standard wavelet transformation. We apply the method to crystal fields of cubic, hexagonal and tetragonal symmetry and for both integer and half-integer total angular momentum values J J of the ground state multiplet. We evaluate its performance on both theoretically generated synthetic and previously published experimental data on CeAgSb _2 2 , PrAgSb _2 2 and PrMg _2 2 Cu _9 9 , and find that it can reliably and accurately extract the CF parameters for all site symmetries and values of J J considered. This demonstrates that CNNs provide an unbiased approach to extracting CF parameters that avoids tedious multi-parameter fitting procedures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Fabric properties and electric efficiency limits of mechanical moisture extraction from fabrics

Residential clothes drying consume about 650 TBtu of primary energy per year in the United States, equivalent to 3% of primary residential energy consumption. There is a strong impetus to reduce the energy consumption of clothes dryers by both improving existing technology and developing alternatives that use fundamentally different drying mechanisms. Clothes drying technologies are broadly classified into either evaporative or mechanical drying. The focus of this paper is on mechanical drying, including vibrational, centrifugal, and press-based methods. In this work, the physical processes involved in these mechanical fabric drying processes were analyzed to develop general theories of mechanical cloth drying energy efficiency. Quantitative evaluation of the theories requires measured fabric properties. To accomplish this, a set of experiments was conducted on samples of a standard test fabric. The fabric was a cotton-polyester blend specified by the US Department of Energy to evaluate the standardized efficiency of all residential clothes dryers in the US. Mercury porosimetry experiments were conducted to determine the fabric pore size distribution, apparent density, and porosity. Elasticity experiments were conducted to determine the fabric’s Young’s modulus. Isostatic press experiments were conducted to establish a relationship between compression force and fabric moisture content. The data resulting from these experiments were combined with mathematical models developed in this work to calculate the theoretical maximum performance limits for mechanical drying of the standard fabric. The results of the analysis are used to make recommendations for the most promising technologies that offer the greatest potential energy savings for residential clothes drying.

36 MATERIALS SCIENCE↗
DOE OSTI2020

GCAM-Demeter-LU

This GCAM-Demeter-LU is made available under the Open Data Commons Attribution License:http://opendatacommons.org/licenses/by/1.0/. The dataset includes the projected global gridded land cover (excluding the Antarctic) for the period of 2015-2100 at 0.05-degree resolution and 5-year time step under fifteen SSP-RCP scenarios driven by five GCMs (i.e., gfdl, hadgem, ipsl, miroc, and noresm), using the Global Change Analysis Model (GCAM) and a geospatial downscaling model (Demeter). The data has been stored in self-describing NetCDF format. The dataset also includes the mean and standard deviation of the results driven by the five GCMs. More specifically, the data in each year includes grid-explicit fraction (in percent) of each of the 32 plant functional types that are widely used in current Earth system models. The NetCDF files are named as “GCAM_Demeter_LU_SSP_RCP_Model_Year.nc”, where “SSP” and “RCP” denote the SSP and RCP scenarios, including 'ssp1_rcp26', 'ssp1_rcp45', 'ssp1_rcp60', 'ssp2_rcp26', 'ssp2_rcp45', 'ssp2_rcp60', 'ssp3_rcp45', 'ssp3_rcp60', 'ssp4_rcp26', 'ssp4_rcp45', 'ssp4_rcp60', 'ssp5_rcp26', 'ssp5_rcp45', 'ssp5_rcp60', and 'ssp5_rcp85'. “Year” denotes the year of the land use data, and “GCM” denotes the source driving forcing data from five global climate models (gfdl, hadgem, ipsl, miroc, and noresm), or the mean (“modelmean”) and the standard deviation (“modelstd”) of the results from the five GCMs.See https://github.com/JGCRI/chen_et_al_2020a for details on how to reproduce this data. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Intermediate-Term Thermal Aging Effect Evaluation for Grade 92 and 316L at The LWR Relevant Temperature

Life extension of the existing nuclear reactors imposes accumulated damages, such as higher fluences and longer period of corrosion, to structural materials, which would result in significant challenges to the traditional reactor materials such as type 304 and 316 stainless steels. Advanced alloys with superior radiation resistance will increase safety margins, design flexibility, and economics for not only the life extension of the existing fleet but also new builds with advanced reactor designs. The Electric Power Research Institute (EPRI) teamed up with Department of Energy (DOE) on the Advanced Radiation Resistant Materials (ARRM) program, aiming to develop and test degradation resistant alloys from current commercial alloy specifications by 2021 to a new advanced alloy with superior degradation resistance in light water reactor (LWR)-relevant environments by 2024. Based on a comprehensive microstructure and property screening performed in Phase-1 of the ARRM program, a total of five alloys, together with 316L and X-750 as references, were down-selected for Phase-2 neutron irradiation studies. Because thermal aging could exert a synergistic effect on neutron irradiation due to the low neutron damage rate on the order of 10 –7 displacements per atom per second (dpa/s), Grade 92 (one of the five down-selected alloys) and two heats of 316L were selected in this task to study the effect of aging at 350°C for 12.5–12.7 kh on microstructure and mechanical properties. The aging time is approximately corresponding to 5 dpa neutron irradiation, which can be served as a reference for the 5-dpa-irradiated samples of the alloys to help understand the independent neutron damage influence on microstructure and mechanical properties. Optical microscopy and scanning electron microscopy were used for microstructural characterization. Hardness, tensile, Charpy impact toughness, and fracture toughness in the ductile regime of the aged samples were examined. The aging of Grade 92 led to the formation of many Laves phase in sizes of ~100–200 nm and resulted in some reduction in hardness and yield/ultimate tensile strength with some increases in uniform and total plastic elongations, which may have helped the enhancement of Charpy impact toughness, e.g., ~4 J increase in upper-shelf energy and 20.5°C reduction in ductile-brittle transition temperature compared with the unaged condition. The fracture toughness of the aged Grade 92 showed decent toughness of ~303 MPa√m (K Jq ) with ~87 tearing modulus at 22°C, which reduced to ~241 MPa√m (~20% reduction) with ~75 tearing modulus at 300°C. The two heats of 316L are differentiated by their amounts of δ-ferrite, i.e., ~1 vol% in heat T1103 and ~4 vol% in heat N5B8. The two heats of 316L were subjected to 15% cold work (CW) as this condition is often used in nuclear reactors to help trapping radiation-induced defects and thus postpone the steady state swelling stage. The aging did not result in any noticeable microstructure changes, except for possible segregations at grain boundaries that need to be further investigated. The aging resulted in slight reduction in hardness of 316L-T1103 and slight increase in hardness of 316L-N5B8, which is consistent with their tensile testing results. The 15%CW might have introduced some inhomogeneity, resulting in large standard deviations in hardness, which were reduced after the aging. The aged 316L followed the same trend as the unaged condition for the strength and elongation results from the tensile testing. Minimum elongations appeared within ~300–600°C, above which the elongations seem to increase. Unlike the negligible or minor changes in microstructure, hardness and tensile results of the two heats of 316L, their fracture toughness showed noticeable difference. The aged 316L-T1103 showed good toughness of ~350 MPa√m with ~80 tearing modulus at 22°C, which reduced to ~271 MPa√m (~23% reduction) with ~83 tearing modulus at 300°C. In contrast, the aged 316L-N5B8 showed lower toughness of ~244 MPa√m with ~53 tearing modulus at 22°C, which reduced to ~180 MPa√m (~26% reduction) with ~31 tearing modulus at 300°C. The preliminary results indicate that the presence of high volume of δ-ferrite would noticeable impair fracture toughness although it may not influence hardness and tensile properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Defining Probe Closure Offset and Scan Stitching Methodology for Element Contact Profilometry in the Hot Fuel Examination Facility

The Element Contact Profilometer (ECP) is a non-destructive post-irradiation examination (PIE) method established in the Materials and Fuels Complex (MFC) Hot Fuel Examination Facility (HFEF). The ECP suspends a fuel rod with a standard end-fitting in a vertical orientation and draws it between two opposed Sony probes with sapphire rod tips, which measure the diameter directly as a function of vertical stage position through contact profilometry. The ECP is equipped with concave rollers, which pinch the rod to maintain a consist position between these sapphire probe tips. A schematic of the analysis head is shown in Figure 1. The gripper that suspends the rod end-fitting is able to rotate to allow measuring of any azimuthal angle around the rod. This system is used to characterize the diameter of full-length light water reactor (LWR) irradiated fuel rods at multiple azimuthal angles in support of the Advanced Fuels Campaign (AFC).

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Regulatory Treatment of Non-Core Sources of Radioactivity for Advanced Reactor Designs

The recent resurgence in advance (non-light water) reactor development has been paralleled by the development of risk-informed performance-based (RIPB) licensing pathways. Specifically, the creation of the RIPB Licensing Modernization Project (LMP) approach and subsequent endorsement by the U.S. Nuclear Regulatory Commission (NRC) now provides advanced reactor vendors with a defined RIPB method to develop an affirmative safety case for licensing. In addition, the Technology Inclusive Content of Applications Project (TICAP) has published guidance on developing a license application based on the LMP approach. To support the utilization of risk information as part of advanced reactor design and licensing efforts, the American Society of Mechanical Engineers (ASME)/American Nuclear Society (ANS) Joint Committee on Nuclear Risk Management (JCNRM) has developed a probabilistic risk assessment (PRA) standard for advanced reactors. The standard, which was formerly approved by the American National Standards Institute (ANSI) in 2021 and recently endorsed by the NRC in trial use Regulatory Guide (RG) 1.247, is an integral standard, covering from initiating events to offsite consequence. A major feature of the standard is that it permits the inclusion of any source of radioactivity material at the site within the plant PRA. Therefore, non-core sources of radioactivity, such as fuel storage, fuel processing, and purification systems, can be included within a single comprehensive plant PRA. For those advanced reactor vendors utilizing a RIPB licensing approach, there is an opportunity to include the non-core sources of radioactivity within the RIPB framework for licensing decision-making, such as the categorization of events, classification of structures, systems, and components (SSCs), and evaluation of the adequacy of defense-in-depth (DID). For advanced reactor designs that contain multiple non-core sources of radioactivity, or for monolithic plant sites that include associated fuel facilities, this approach could potentially simplify licensing applications through the use of a single, uniform, and consistent decision-making framework across all radioactive sources at the site. In addition, a RIPB approach could provide additional insights regarding plant behavior, flexibility regarding licensing decision-making, and potentially allow the use of risk information as part of the plant oversight process. Risk-informing these aspects of advanced reactor licensing would also be consistent with the NRC’s risk policy statement. However, there is diverse regulation and guidance regarding the licensing of non-core sources of radioactivity and generally limited experience using RIPB approaches for the evaluation as part of licensing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

SANS quantification of bound water in water-soluble polymers across multiple concentration regimes

Contrast-variation small-angle neutron scattering (CV-SANS) is a widely used technique for quantifying hydration water in soft matter systems, but it is predominantly applied in the dilute regime or for systems with a well-defined structure factor. Here, CV-SANS was used to quantify the number of hydration water molecules associating with three water-soluble polymers with different critical solution temperatures and types of water–solute interactions in dilute, semidilute, and concentrated solution through the exploration of novel methods of data fitting and analysis. Multiple SANS fitting workflows with varying levels of model assumptions were evaluated and compared to give insight into SANS model selection. These fitting pathways ranged from general, model-free algorithms to more standard form and structure factor fitting. In addition, Monte Carlo bootstrapping was evaluated as a method to estimate parameter uncertainty through simulation of technical replicates. The most robust fitting workflow for dilute solutions was found to be form factor fitting without CV-SANS ( i.e. polymer in 100% D 2 O). For semidilute and concentrated solutions, while the model-free approach can be mathematically defined for CV-SANS data, the addition of a structure factor imposes physical constraints on the optimization problem, suggesting that the optimal fitting pathway should include appropriate form and structure factor models. The measured hydration numbers were consistent with the number of tightly bound water molecules associated with each monomer unit, and the concentration dependence of the hydration number was largely governed by the chemistry-specific interactions between water and polymer. Polymers with weaker water–polymer interactions ( i.e. those with fewer hydration water molecules) were found to have more bound water at higher concentrations than those with stronger water–polymer interactions due to the increase in the number of forced water–polymer contacts in the concentrated system. This SANS-based method to count hydration water molecules can be applied to polymers in any concentration regime, which will lead to improved understanding of water–polymer interactions and their impact on materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Active learning for robust, high-complexity reactive atomistic simulations

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. In this paper, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory in terms of structure, dynamics, and speciation.

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

Evaluation of the Reconstruction Accuracy of the Ultrasound Model–Based Image Reconstruction (U-MBIR) Method for Concrete to Optimize Damage Detection

Reinforced concrete is a critical structural material used to construct nuclear power plants (NPPs). As such, its safety and performance must be thoroughly examined throughout the life cycle of the NPP infrastructure system. Ultrasonic measurements have been an industry standard for both surface and subsurface inspections. To support the development of these techniques, Oak Ridge National Laboratory (ORNL) has researched and developed advanced image reconstruction algorithms to capture internal damage. The results and discussion presented herein summarize the current state of the ultrasonic model–based iterative reconstruction (U-MBIR) algorithm developed at ORNL. In the work documented in this report, the U-MBIR methodology was applied to four sets of ultrasonic data collected from concrete specimens. The results demonstrate that the U-MBIR algorithm can successfully detect defects within the four concrete samples. The reconstruction images help identify the specimen thickness, regions of delamination, and location of rebar embedded within the concrete. The reconstruction images allow engineers and technicians to characterize the internal defects within concrete specimens and structural members. Ultimately, this knowledge can guide engineers in making informed decisions regarding the performance, safety, and reliability of structural materials (i.e., reinforced concrete) throughout the life cycle of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Manifold projection image segmentation for nano-XANES imaging

As spectral imaging techniques are becoming more prominent in science, advanced image segmentation algorithms are required to identify appropriate domains in these images. We present a version of image segmentation called manifold projection image segmentation (MPIS) that is generally applicable to a broad range of systems without the need for training because MPIS uses unsupervised machine learning with a few physically motivated hyperparameters. We apply MPIS to nanoscale x-ray absorption near edge structure (XANES) imaging, where XANES spectra are collected with nanometer spatial resolution. We show the superiority of manifold projection over linear transformations, such as the commonly used principal component analysis (PCA). Moreover, MPIS maintains accuracy while reducing computation time and sensitivity to noise compared to the standard nano-XANES imaging analysis procedure. Finally, we demonstrate how multimodal information, such as x-ray fluorescence data and spatial location of pixels, can be incorporated into the MPIS framework. We propose that MPIS is adaptable for any spectral imaging technique, including scanning transmission x-ray microscopy, where the length scale of domains is larger than the resolution of the experiment.

36 MATERIALS SCIENCE↗