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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Test Plan: Enhanced HLW Glass Property-Composition Models - Phase I, VSL-13T3080-1 (May 2013) (Rev. 0)

In the present work, previously compiled glass property-composition databases for WTP HLW glasses will be updated with any new data that have become available. The previous evaluation of the baseline WTP models against the larger data sets in terms of range of validity and prediction performance will be used together with a review of the HLW glass property-composition data to identify gaps in the composition space that will need to be filled to support the development of expanded models. The results will be used to identify the composition spaces where gaps exist that need to be filled by new compositions to be tested. Composition matrices will be developed for this purpose. Crucible melts of the glass compositions identified in these matrices will be prepared and tested for the properties of interest. Finally, the entire composition space and glass property data available will be used in the development of improved and extended models. Review of the WTP HLW glass property-composition models against the extended datasets and initial identification of the data gaps will also be used to judge whether to develop one set of models for the entire HLW glass composition space or to develop separate models for discrete composition spaces. The longer-term objective of this multi-year task is to develop new glass property-composition models for PCT release, spinel crystallization (T1%), nepheline formation on CCC, TCLP Cd response, viscosity and electrical conductivity to control glass compositions for HLW vitrification at Hanford.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Design and assembling status of the Mu2e electromagnetic calorimeter mechanical structures

The muon-to-electron conversion (Mu2e) experiment at Fermilab will search for the Charged Lepton Flavour Violating neutrino-less coherent conversion of a muon into an electron in the field of an aluminum nucleus. The observation of this process would be the unambiguous evidence of physics beyond the Standard Model. The detector has been designed as a state-of-the-art crystal calorimeter and employs 1348 pure Cesium Iodide (CsI) crystals readout by UV-extended silicon photosensors and fast front-end and digitization electronics. A design consisting of two identical annular matrices (named disks ) positioned at the relative distance of 70 cm, downstream the aluminum target along the muon beamline, satisfies the Mu2e physics requirements. The hostile Mu2e operational conditions, in terms of radiation levels (total ionizing dose of 12 krad and a neutron fluence of 5 10^{10} n/cm2 @ 1 MeVeq (Si)/y), magnetic field intensity (1 T) and vacuum level (10−4 Torr) have posed tight constraints on the design of the detector mechanical structures and materials choice. The support structure of the two 674 crystal matrices employs two aluminum hollow rings and parts made of open- cell vacuum-compatible carbon fiber. The photosensors and service front-end electronics for each crystal are assembled in a unique mechanical unit inserted in a machined copper holder. The 674 units are supported by a machined plate made of vacuum-compatible plastic material. The plate also integrates the cooling system made of a network of copper lines flowing a low temperature radiation-hard fluid and placed in thermal con- tact with the copper holders. The data acquisition electronics is hosted in aluminum custom crates positioned on the external lateral surface of the two disks. The crates also integrate the electronics cooling system. In this poster we will review the constraints on the calorimeter mechanical structures, the technological choices, and the status of assembling at Fermilab.

Pasciuto, D.↗
DOE OSTI2024

Ion Exchange Processing of AN-107 Hanford Tank Waste through Crystalline Silicotitanate in a Staged 2- then 3-Column System

The Hanford Site stores an estimated 56 million gallons of mixed radioactive and chemically hazardous waste in large underground tanks. In support of the Direct Feed Low-Activity Waste (DFLAW) Program for expediting Hanford tank waste supernate treatment, laboratory-scale ion exchange processing using prototypic unit operations was conducted on AN-107 tank waste at the Pacific Northwest National Laboratory Radiochemical Processing Laboratory. This report describes the small-scale ion exchange testing with 13.7 L of diluted and filtered supernate from Tank 241-AN-107 (hereafter referred to as AN-107) at 16 °C (62 °F). One of the waste acceptance criteria (WAC) for the Waste Treatment Plant (WTP) Low-Activity Waste Facility is that the waste must contain less than 3.18×10 -5 Ci 137 Cs per mole of Na. For the AN-107 tank waste to meet this criterion, only 0.147% of the influent 137 Cs concentration may be delivered to the WTP; this requires a Cs decontamination factor of 678. Testing with AN-107 matched current Tank Side Cesium Removal (TSCR) facility prototypic operations where a lead-lag configuration was used until the lag column reached the WAC limit, then a polish column was brought online for continued processing in a lead-lag-polish column configuration. Feed was processed at 1.9 bed volumes (BVs) per hour; the flowrate, in terms of contact time with the crystalline silicotitanate (CST) bed, matched the expected flowrate at TSCR. The Cs-decontaminated product was retained for vitrification testing (to be reported separately). The lead column reached 40% Cs breakthrough after processing ~1700 BVs of feed; the 50% Cs breakthrough was extrapolated from the breakthrough data to occur at 1873 BVs. Testing compared to previous AP-101 and AP-107 testing at 16 °C showed ~300 BV increases in volume processed to reach the WAC limit for both lead and lag columns. The increase in capacity was determined to be due to the significantly lower K concentration in the AN-107 compared to the other tank waste matrices. A comparison in breakthrough curves for the three tests indicated slightly slower kinetic behavior in the AN-107, with variations in feed matrices (high organic complexants) likely responsible for the deviation. The Cs effluent from the lag column reached the WAC limit after processing 1097 BVs. Anticipating this breakthrough point, the polish column was preemptively installed around 900 BVs. Cs breakthrough from the lag column began at 500 BVs, reaching 3.06×10 0 µCi/mL, or 2.6 % Cs breakthrough, after processing all 1700 BVs of feed. Table S.1 and Figure S.1 summarize the observed column performance and relevant Cs loading characteristics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Physics-informed Estimation of the Covariance Matrix for Various Neutron Spectra

A method for estimating covariance matrices which capture the uncertainties in calculated reactor spectra has been developed. This method is based on perturbing the parameters of a physics-based analytic model fitted to a calculated spectrum. The covariance of the perturbed analytic spectra imposes energy-dependent correlations due to the physics of the neutron processes in the reactor, i.e., a fission component, a 1/E down-scatting component, and a thermal Maxwellian component. An analytic model is developed which is shown to produce good fits to several reactor environments. The covariance matrices produced via this method are then used as the prior spectrum in STAYSL least squares spectrum adjustment where it is combined with integral metrics, such as activation measurements, to produce a high-fidelity neutron spectrum characterization. It was concluded that the methodology showed agreeable results for the ACRR free-field spectrum adjustment in STAYSL resulting in a 𝜒 2 value of 2.21 (per degree of freedom), but further work is needed to describe scattering and interface regions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

FY24 Task 5: Leachate Disposition

Directly feeding sludge solids to the high-level waste (HLW) Waste Treatment Plant represents an alternative flowsheet seeking to initiate sludge processing as soon as possible. Key processing functions previously captured during baseline pretreatment operations include leaching and washing prior to solids concentration. These operations should be considered in the potential direct feed flowsheets to maximize waste feed loading, minimize HLW volume, and mitigate corrosion challenges associated with vitrification of high phosphate and fluoride concentrations. Additionally, single-shell tank (SST) retrievals and waste transfers to double-shell tanks (DSTs) in a direct feed flowsheet would likely also benefit from some level of leaching, washing, and solids concentration in order to reduce DST space and mission duration. These operations could occur in a new facility or potentially in available DSTs. If washing and leaching are utilized, an effective disposition pathway for the wash water and leachate solutions are needed. Three target species that benefit significantly from leaching and washing are phosphate, fluoride and aluminum. Phosphate (PO 4 3- ) and fluoride (F - ) can contribute substantially to the amount of carrier fluid needed for dissolution, and the resulting volume of liquid generated. Disposition of this retrieval solution should be evaluated in order to prevent crystallization of these anions throughout system processing. Since there is a high probability that any retrieval solutions will be at or near their PO 4 3- and F - solubility limits, evaporation or blending with a high Na supernate (>3.5 M) is not recommended for the wash water streams without a method to remove precipitants prior to solution disposal. Additionally, aluminum present in the southeast quadrant of the Hanford site represents roughly 60% of the waste solids in the initial processing tanks. These aluminum solids are in the form of gibbsite (Al(OH) 3 ) and can pose significant challenges for processing due to the fast-settling times and high solids loading associated with these materials. Easily remediated by caustic addition to the solids, these wash solutions could be processed through crystalline silicotitanate (CST) ion exchange columns to prepare the supernate solutions for disposition. The current target for feed conditions to the Low Activity Waste (LAW) melter are waste streams that contain nominally 5-6 M Na. Fractions within the tanks contain upwards of 0.2 M phosphate and fluoride in solution at 3.5 M Na. Concentrating these solutions above 5 M Na would result in an exceedance of the solubility limits, and potential for uncontrolled precipitation of the phosphate and fluoride crystal material. The resulting crystalline salt material is typically sodium fluoride phosphate, also referred to as natrophosphate (Na 7 FPO 4 ·19H 2 O). Salt phases are of importance in tank waste due to their chemical reactivity, which can result in precipitation, dissolution, or transformation, impacting any downstream processes (Bolling et al. 2020, Russell, Snow, and Peterson 2010). Salt generation and precipitation could pose challenges by causing system plugging and melter corrosion if left in the supernate stream, or limit sodium molarity of the supernate that would be accepted without incident in waste operations. To understand the impact of this salt generation, the crystallization of natrophosphate in multiple simulant feed matrices was studied to understand the implications of various tank waste supernate chemistries. Three matrices were examined: high PO 4 3- /low F - , low PO 4 3- /high F - , and an average matrix. Subsequent testing was performed with the average matrix with the inclusion of CsNO 3 , and a final run with the average matrix including CsNO 3 and a 137 Cs spike for tracer purposes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

L3:RTM.MCH.P19.06: Neutronics UQ

This report summarizes some of the work performed in the last year on the nuclear data uncertainty tasks using the multipole representation. This approach was proposed to provide a simple and integrated way of evaluating the nuclear data uncertainty in a Monte Carlo simulation and evaluating their impact on multigroup cross sections. As previously described, the windowed multipole format allows for a resonance based representation of the cross sections with direct Doppler broadening. This representation also lends itself nicely to the evaluation of sensitivities of resonance parameters and the direct perturbation of resonance parameters in the simulation environment. Both of these approaches rely on the need of conversion of the covariance data (File 32 of the ENDF library) into a pole and residues form: i.e. into a multipole covariance. Section 5 details the current pathways that have been used so far to achieve this. In order to verify the conversion process of the covariance data, the sensitivies to the resonance parameters and the sampling from these parameters, an analytical benchmark of the slowing process was developed. The benchmark provides a closed-form solution for the flux in the presence of Hydrogen and multiple resonant nuclides. Section 2 details the analytical benchmark and provides the closed-form solutions for the flux and its sensitivity to resonance parameters. A verification of the proposed methodology is performed and compared with the analytic solution to demonstrate the accuracy of the benchmark and the applicability of our embedded resonance perturbation approach in a small Monte Carlo code. Papers are currently being drafted documenting the benchmark and the generation of sensitivities. As paths to best generate multipole covariance matrices are being compared, we also explored new methods to propagate nuclear data uncertainty across the Monte Carlo neutron transport calculation. Section 4 studies the use of multipole covariance matrices to perform sensitivity analysis. Section 3.2 documents the results of our investigations into a new way of propagating nuclear data uncertainty across Monte Carlo transport simulations by sampling new epistemic cross sections for each new neutron.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Baltimore Turfgrass Field Experiment Campaign Report

The Baltimore Turfgrass Field Experiment (BTFE) consisted of an observation eddy covariance flux station, measuring CO 2 , H 2 O, and turbulent energy fluxes between the turfgrass field and the atmosphere. The tower was sited before the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s arrival, but for the purposes of this report, we can say that the campaign lasted as long as the Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) campaign, 12 months, 12/2024 through 11/2025. As stated, the flux tower was part of the COURAGE campaign on the M1 site. We set out to measure turfgrass because it is a ubiquitous part of the urban environment—in fact, it is the dominant vegetation land cover type in Baltimore and most cities. It contributes small but significantly to greenhouse gas balances as well as the energy balance in the urban environment. We also installed a soil temperature and matric potential profiling system as part of this experiment. Additionally, AmeriFlux asked us to participate in their soil matric potential soil moisture mapping experiment. We collected 12 soil samples to be analyzed by a team in Bloomington, Indiana: results are pending.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Performance Improvements of the Griffin Solvers in FY24

The Griffin code is a MOOSE-based reactor physics application jointly developed by Idaho National Laboratory and Argonne National Laboratory under the Department of Energy Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation Program. This fiscal year, we have made significant efforts to improve the performance of transport solver options and cross-section generation for the efficient use of Griffin in advanced reactor applications. For the HFEM-PN solver, the residual evaluations of HFEM kernels were optimized by utilizing the pre- computed averaged cross sections for individual elements. Numerical integration involving the evaluation of basis functions at quadrature points was bypassed by facilitating precomputed element mass matrices for response matrices. Red-black iterations were improved by introducing a new generalized minimum residual based solver. The memory usage of response matrix storage was significantly reduced by applying basis function rotations on interfaces and calculating volumetric odd-parity moments on the fly. Additionally, the adjoint flux and transient calculation capabilities of the HFEM-PN solver were successfully implemented and verified using the TWIGL benchmark problem. For the DFEM-SN solver, memory footprint and computation time were significantly reduced by not treating angular flux vectors as the MOOSE nonlinear system vectors. Specifically for IQS, scalar adjoint weighting was introduced to further eliminate angular adjoint flux storage in the MOOSE auxiliary system. It was demonstrated through the three-dimensional Advanced Burner Test Reactor core problem that the memory usage for transient calculations with the IQS method was reduced by over 7.5× compared to before the optimizations. For the self-shielding application programming interface, a new double-heterogeneity treatment method, named the Bell Function-Based Analytic Two-Region Slowing Down Method, was developed to efficiently flux-volume homogenize TRISO particles with the matrix. Additionally, optimizations were made to hyper- fine group (HFG) slowing down calculations by pretabulating collision probability coefficients and grouping isotopes, significantly reducing the computational time for calculating scattering sources per HFG. Lastly, the pin power reconstruction module was extended to account for temporal behavior in a microreactor analysis problem, specifically for a control drum transient. Verification tests for each of these improvements demonstrated significant performance enhancements and memory reduction.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Development, construction and qualification tests of the mechanical structures of the electromagnetic calorimeter of the Mu2e experiment at Fermilab

The “muon-to-electron conversion” (Mu2e) experiment at Fermilab will search for the Charged Lepton Flavour Violating neutrino-less coherent conversion of a muon into an electron in the field of an aluminum nucleus. The observation of this process would be the unambiguous evidence of physics beyond the Standard Model. Mu2e detectors comprise a straw-tracker, an electromagnetic calorimeter and an external veto for cosmic rays. The calorimeter provides excellent electron identification, complementary information to aid pattern recognition and track reconstruction, and a fast calorimetric online trigger. The detector has been designed as a state-of-the-art crystal calorimeter and employs 1340 pure Cesium Iodide (CsI) crystals readout by UV-extended silicon photosensors and fast front-end and digitization electronics. A design consisting of two identical annular matrices (named “disks”) positioned at the relative distance of 70 cm downstream the aluminum target along the muon beamline satisfies the Mu2e physics requirements.The hostile Mu2e operational conditions, in terms of radiation levels (total ionizing dose of 12 krad and a neutron fluence of 5x1010 n/cm2 @ 1 MeVeq (Si)/y), magnetic field intensity (1 T) and vacuum level (10$^{-4}$ Torr) have posed tight constraints on the design of the detector mechanical structures and materials choice. The support structure of the two 670 crystal matrices employs two aluminum hollow rings and parts made of open-cell vacuum-compatible carbon fiber. The photosensors and service front-end electronics for each crystal are assembled in a unique mechanical unit inserted in a machined copper holder. The 670 units are supported by a machined plate made of vacuum-compatible plastic material. The plate also integrates the cooling system made of a network of copper lines flowing a low temperature radiation-hard fluid and placed in thermal contact with the copper holders to constitute a low resistance thermal bridge. The data acquisition electronics is hosted in aluminum custom crates positioned on the external lateral surface of the two disks. The crates also integrate the electronics cooling system as lines running in parallel to the front-end system.The constraints on the calorimeter mechanical structures design, the development from the conceptual design to the specifications of all the structural components, the status of components production and the components quality assurance tests are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Algebraic Bethe Circuits

The Algebraic Bethe Ansatz (ABA) is a highly successful analytical method used to exactly solve several physical models in both statistical mechanics and condensed-matter physics. Here we bring the ABA into unitary form, for its direct implementation on a quantum computer. This is achieved by distilling the non-unitary R matrices that make up the ABA into unitaries using the QR decomposition. Our algorithm is deterministic and works for both real and complex roots of the Bethe equations. We illustrate our method on the spin-$\frac{1}{2}$ XX and XXZ models. We show that using this approach one can efficiently prepare eigenstates of the XX model on a quantum computer with quantum resources that match previous state-of-the-art approaches. We run small-scale error mitigated implementations on the IBM quantum computers, including the preparation of the ground state for the XX and XXZ models on 4 sites. Finally, we derive a new form of the Yang-Baxter equation using unitary matrices, and also verify it on a quantum computer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Reduction of the scattering matrix array

The scattering matrix approach is widely applied in wave engineering and quantum physics. Usually, a combination of multiple scattering matrices is used. In this article, we consider arbitrary arrays of interconnected scattering matrices and present a formal result for the reduced scattering matrix. We demonstrate this approach in two well-known scattering problems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Dimension Reduction and Redundancy Removal through Successive Schmidt Decompositions

Quantum computers are believed to have the ability to process huge data sizes, which can be seen in machine learning applications. In these applications, the data, in general, are classical. Therefore, to process them on a quantum computer, there is a need for efficient methods that can be used to map classical data on quantum states in a concise manner. On the other hand, to verify the results of quantum computers and study quantum algorithms, we need to be able to approximate quantum operations into forms that are easier to simulate on classical computers with some errors. Motivated by these needs, in this paper, we study the approximation of matrices and vectors by using their tensor products obtained through successive Schmidt decompositions. We show that data with distributions such as uniform, Poisson, exponential, or similar to these distributions can be approximated by using only a few terms, which can be easily mapped onto quantum circuits. The examples include random data with different distributions, the Gram matrices of iris flower, handwritten digits, 20newsgroup, and labeled faces in the wild. Similarly, some quantum operations, such as quantum Fourier transform and variational quantum circuits with a small depth, may also be approximated with a few terms that are easier to simulate on classical computers. Furthermore, we show how the method can be used to simplify quantum Hamiltonians: In particular, we show the application to randomly generated transverse field Ising model Hamiltonians. The reduced Hamiltonians can be mapped into quantum circuits easily and, therefore, can be simulated more efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Transformative Impacts of Laser-Induced Breakdown Spectroscopy on Environmental and Biological Research at Oak Ridge National Laboratory

This manuscript will present an advancement of transformative research that has been conducted at Oak Ridge National Laboratory (ORNL) over a 25-year period (2000–2025) on a variety of environmental and biological matrices. These investigations derived a fundamental understanding of how elemental detection and analysis of these matrices led to the knowledge and discovery of natural processes in plants and the environment. Each project led to the initiation of a new research area which unearthed awesome and novel breakthroughs. Highlights are listed below: 1. The preliminary research at ORNL centered on the detection of aerosols utilizing Laser-induced Breakdown Spectroscopy (LIBS) technology. The Clean Air Act Amendment (CAAA) of 1990 highlighted the importance of identifying hazardous air pollutants (HAPs) due to their impact on environmental and human health, thereby underscoring the need to detect various toxic elements. Research in aerosol chemistry aimed to identify these harmful elements released by factories during periods of increased emissions in their manufacturing processes. LIBS emerged as the most effective method for real-time, in situ measurements of metal species in both gaseous and aerosol phases. 2. An understanding of the presence of total carbon in soils gives perspective on how to develop carbon sequestration strategies. The recognition that carbon sinks can evolve back to carbon sources to emit back to the atmosphere was an important consideration. Also, the concentration of carbon in soil indicates the health of land areas for growing crops successfully. 3. The direct detection of most of the elements in a wood sample in a single emission spectrum, without sample preparation, encouraged the research to use the LIBS technique for preservative treated wood coupled with use of multivariate statistical methodology. Additionally, it encouraged the researchers to try to differentiate natural woods from different parts of the country, and it was successfully demonstrated that LIBS coupled with MVA analysis could differentiate wood of different species from each other and of similar species grown in different environments based on their elemental spectra. This was a breakthrough since it revealed a systematic approach to connect elemental scarcity and abundance to either drought or typical rainfall conditions for the hardwood trees grown in specific areas. 4. Furthermore, the research progressed to reveal physiological and developmental processes contributing to biomass production such that the variation in leaf elemental composition increases our understanding of terrestrial nutrient cycles, as well as tracking the transfer of toxic elements from soils to living organisms. 5. Recently another breakthrough viz., ionomics initiated the correlation of elements to specific genes, uncovering the function that the element performed in the plant. More recently, this has been extended from plants to fungi as well as fungi growing in symbiotic relations with plants.

09 BIOMASS FUELS↗
DOE OSTI2024

Generalized Quasi-Static Mooring System Modeling with Analytic Jacobians

This paper presents a generalized and efficient method for quasi-static analysis of mooring systems, including complex scenarios such as when shared mooring lines interconnect multiple floating wind or wave energy devices. While quasi-static mooring models are well established, most published formulations are focused on specific applications, and no publicly available implementations provide efficient handling of large mooring system networks. The present formulation addresses these gaps by: (1) formulating solutions for edge cases not typically supported by quasi-static models; (2) creating a fully generalized model structure such that any combination of mooring lines, point masses, and floating bodies can be assembled; and (3) deriving analytic expressions for the system Jacobians (stiffness matrices) so that systems with many degrees of freedom can be solved efficiently. These techniques form the theory basis of MoorPy, an open-source mooring analysis library. The model is demonstrated on nine scenarios of increasing complexity with features of interest for offshore renewable energy applications. When compared with steady-state results from a lumped-mass dynamic model, the results show that the quasi-static formulation accurately calculates profiles and tensions and that its analytic approach provides more efficient and reliable computation of system stiffness matrices than finite-differencing methods. These results verify the accuracy of the MoorPy model.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Implications of Microstructure in Helium-Implanted Nanocrystalline Metals

Helium bubbles are known to form in nuclear reactor structural components when displacement damage occurs in conjunction with helium exposure and/or transmutation. If left unchecked, bubble production can cause swelling, blistering, and embrittlement, all of which substantially degrade materials and—moreover—diminish mechanical properties. On the mission to produce more robust materials, nanocrystalline (NC) metals show great potential and are postulated to exhibit superior radiation resistance due to their high defect and particle sink densities; however, much is still unknown about the mechanisms of defect evolution in these systems under extreme conditions. Here, the performances of NC nickel (Ni) and iron (Fe) are investigated under helium bombardment via transmission electron microscopy (TEM). Bubble density statistics are measured as a function of grain size in specimens implanted under similar conditions. While the overall trends revealed an increase in bubble density up to saturation in both samples, bubble density in Fe was over 300% greater than in Ni. To interrogate the kinetics of helium diffusion and trapping, a rate theory model is developed that substantiates that helium is more readily captured within grains in helium-vacancy complexes in NC Fe, whereas helium is more prone to traversing the grain matrices and migrating to GBs in NC Ni. Our results suggest that (1) grain boundaries can affect bubble swelling in grain matrices significantly and can have a dominant effect over crystal structure, and (2) an NC-Ni-based material can yield superior resistance to irradiation-induced bubble growth compared to an NC-Fe-based material and exhibits high potential for use in extreme environments where swelling due to He bubble formation is of significant concern.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Developing Enzyme Immobilization with Fibrous Membranes: Longevity and Characterization Considerations

Fibrous membranes offer broad opportunities to deploy immobilized enzymes in new reactor and application designs, including multiphase continuous flow-through reactions. Enzyme immobilization is a technology strategy that simplifies the separation of otherwise soluble catalytic proteins from liquid reaction media and imparts stabilization and performance enhancement. Flexible immobilization matrices made from fibers have versatile physical attributes, such as high surface area, light weight, and controllable porosity, which give them membrane-like characteristics, while simultaneously providing good mechanical properties for creating functional filters, sensors, scaffolds, and other interface-active biocatalytic materials. This review examines immobilization strategies for enzymes on fibrous membrane-like polymeric supports involving all three fundamental mechanisms of post-immobilization, incorporation, and coating. Post-immobilization offers an infinite selection of matrix materials, but may encounter loading and durability issues, while incorporation offers longevity but has more limited material options and may present mass transfer obstacles. Coating techniques on fibrous materials at different geometric scales are a growing trend in making membranes that integrate biocatalytic functionality with versatile physical supports. Biocatalytic performance parameters and characterization techniques for immobilized enzymes are described, including several emerging techniques of special relevance for fibrous immobilized enzymes. Diverse application examples from the literature, focusing on fibrous matrices, are summarized, and biocatalyst longevity is emphasized as a critical performance parameter that needs increased attention to advance concepts from lab scale to broader utilization. This consolidation of fabrication, performance measurement, and characterization techniques, with guiding examples highlighted, is intended to inspire future innovations in enzyme immobilization with fibrous membranes and expand their uses in novel reactors and processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Heterogeneous Morphologies and Hardness of Co-Sputtered Thin Films of Concentrated Cu-Mo-W Alloys

Heterogeneous microstructures in Cu-Mo-W alloy thin films formed by magnetron co-sputtering immiscible elements with concentrated compositions are characterized using scanning transmission electron microscopy (STEM) and nanoindentation. In this work, we modified the phase separated structure of a Cu-Mo immiscible system by adding W, which impedes surface diffusion during film growth. The heterogeneous microstructures in the Cu-Mo-W ternary system exhibited bicontinuous matrices and agglomerates composed of Mo(W)-rich phase. This is unique, as these are the slower-diffusing species, contrasting past reports of binary Cu-Mo thin films that exhibited Cu-rich agglomerates. The bicontinuous matrices comprised of Cu-rich and Mo(W)-rich phases exhibited bilayer thicknesses of less than 5 nm. The hardness of these thin films measured using nanoindentation is reported and compared to similar multilayers and nanocomposites in binary systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Filled Elastomers: Mechanistic and Physics-Driven Modeling and Applications as Smart Materials

Elastomers are made of chain-like molecules to form networks that can sustain large deformation. Rubbers are thermosetting elastomers that are obtained from irreversible curing reactions. Curing reactions create permanent bonds between the molecular chains. On the other hand, thermoplastic elastomers do not need curing reactions. Incorporation of appropriated filler particles, as has been practiced for decades, can significantly enhance mechanical properties of elastomers. However, there are fundamental questions about polymer matrix composites (PMCs) that still elude complete understanding. This is because the macroscopic properties of PMCs depend not only on the overall volume fraction (ϕ) of the filler particles, but also on their spatial distribution (i.e., primary, secondary, and tertiary structure). This work aims at reviewing how the mechanical properties of PMCs are related to the microstructure of filler particles and to the interaction between filler particles and polymer matrices. Overall, soft rubbery matrices dictate the elasticity/hyperelasticity of the PMCs while the reinforcement involves polymer–particle interactions that can significantly influence the mechanical properties of the polymer matrix interface. For ϕ values higher than a threshold, percolation of the filler particles can lead to significant reinforcement. While viscoelastic behavior may be attributed to the soft rubbery component, inelastic behaviors like the Mullins and Payne effects are highly correlated to the microstructures of the polymer matrix and the filler particles, as well as that of the polymer–particle interface. Additionally, the incorporation of specific filler particles within intelligently designed polymer systems has been shown to yield a variety of functional and responsive materials, commonly termed smart materials. We review three types of smart PMCs, i.e., magnetoelastic (M-), shape-memory (SM-), and self-healing (SH-) PMCs, and discuss the constitutive models for these smart materials.

36 MATERIALS SCIENCE↗