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At least 181 records · Page 10

Nuclear forensics: How science helps stop the trafficking of nuclear materials

Nuclear forensics is an essential activity in support of national counter-nuclear smuggling operations, as it can be used to provide unique and useful data to law enforcement for the prosecution of criminal nuclear smugglers and traffickers. Nuclear forensics can also be used to determine the origin of nuclear materials that have fallen out of regulatory control, allowing for the identification of weaknesses and vulnerabilities in the safeguarding of nuclear materials, while also generating a deterrent effect through attribution to the legal and responsible owners of nuclear materials out of regulatory control. This article describes the benefits of a nuclear forensics capability to any country in possession of nuclear materials, and describes how nuclear forensics can support an investigation into the origin of interdicted nuclear materials, using a case study of a nuclear materials interdiction in Australia to describe how nuclear forensics works in practice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Author Correction: An autonomous laboratory for the accelerated synthesis of inorganic materials

Following publication of this article, concerns were raised about the unambiguous identification of the compound structures using diffraction as well as the original claims of material novelty. We acknowledge that the original claims of material novelty were subject to misinterpretation—their intention was to indicate that the materials were new to the prediction platform, not necessarily new to science. The article text has been updated to reflect this in the HTML and PDF versions of the article.

Szymanski, Nathan J. [University of California, Be↗

Covert MOF-Based Photoluminescent Tags via Tunable Linker Energetics

We report that the optical anticounterfeiting tags utilize the photoluminescent properties of materials to encode unique patterns, enabling identification and validation of important items and assets. These tags must combine optical complexity with ease of production and authentication to both prevent counterfeiting and to remain practical for widespread use. Metal–organic frameworks (MOFs) based on polynuclear, rare earth clusters are ideal materials platforms for this purpose, combining fine control over structure and composition, with tunable, complex energy transfer mechanisms via both linker and metal components. Here we report the design and synthesis of a set of heterometallic MOFs based on combinations of Eu, Nd, and Yb with the tetratopic linker 1,3,6,8-tetrakis(4-carboxyphenyl)pyrene. The energetics of this linker facilitate the intentional concealment of the visible emissions from Eu while retaining the infrared emissions of Nd and Yb, creating an optical tag with multiple covert elements. Unique to the materials system reported herein, we document the occurrence of a previously not observed 11-metal cluster correlated with the presence of Yb in the MOFs, coexisting with a commonly encountered 9-metal cluster. We demonstrate the utility of these materials as intricate optical tags with both rapid and in-depth screening techniques, utilizing orthogonal identifiers across composition, emission spectra, and emission decay dynamics. This work highlights the important effect of linker selection in controlling the resulting photoluminescent properties in MOFs and opens an avenue for the targeted design of highly complex, multifunctional optical tags.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of composition and canister centerline cooling on microstructure, phase distribution, and chemical durability of dehalogenated iron phosphate waste forms

This paper discusses the effects of composition and canister centerline cooling (CCC) on the microstructures, phase distribution, and chemical durability of dehalogenated iron phosphate waste forms starting from chloride-based salt simulants including KCl (Simple-1), NdCl3 (Simple-2), SrCl2 (Simple-3), LaCl3 (Simple-4), LiCl (Simple-5), CsCl (Simple-6), as well as a complex simulant containing LiCl, KCl, NaCl, CsI, SrCl2, CeCl3, and NdCl3 called ERV2. The simulants represent salt constituents present in salt wastes from electrorefiners used for electrochemical reprocessing. These salts are reacted with ammonium dihydrogen phosphate (ADP) resulting in a NH4Cl (dechlorination) byproduct that is captured and phosphate product containing oxides of the salt cations. This product is further stabilized using Fe2O3 through vitrification at higher temperatures. The results presented herein describe the properties of CCC-treated materials following dechlorination and vitrification including phase identification and quantification, elemental distributions, and chemical durabilities. The chemical durability in the CCC-cooled samples are lower durability than quenched materials for the ERV2 samples. The phases formed upon CCC cooling are very complex compositionally and microstructurally.

iron phosphate glass, iron phosphate waste forms, ↗

Aging of Concrete for the Evaluation of Repair Materials to Protect the Walls of the HCAEX Tunnel at Savannah River - 20301

H-Canyon, located in the Savannah River site, is a unique facility for chemical reprocessing of plutonium, highly-enriched uranium, and other radioactive materials. The exhaust gases of the H-Canyon are sent through the H-Canyon Exhaust (HCAEX) tunnel for contamination removal. Robotic inspections of the tunnel revealed significant degradation of the reinforced concrete structure that was associated with acid attack, and could compromise the structural stability of the tunnel. Thus, the identification and evaluation of potential repair materials that could be applied on the degraded walls to mitigate and prevent further degradation is of significant interest to the Department of Energy and the Savannah River representatives. This research effort has been divided into two phases: 1) Development and evaluation of aged concrete under accelerated aging conditions (which is the focus of this paper) and 2) Evaluation of potential repair materials applied on aged and non-aged concrete under simulated aggressive conditions. In order to develop and evaluate concrete samples exposed to accelerated aging conditions in simulated aggressive environments, a literature review of the HCAEX tunnel was conducted that included 1) characterization and extent of the concrete damage, 2) environmental conditions inside the tunnel and 3) primary deterioration mechanisms. In addition, potential coatings and/or repair materials for degraded concrete surfaces exposed to aggressive environments (primarily acidic) were selected from the literature review and the most common testing and measurements for evaluating acid attack phenomena, erosion, etc. were reviewed. From the literature review findings, a preliminary bench-scale test plan for the concrete aging was developed, including accelerated aging tests with aggressive conditions (acid fumes, humidity, etc.). Concrete samples were exposed to the aging accelerated conditions (e.g. immersion in acid solutions) and visual inspection, mass loss and pH change (acid solution) were recorded over time. Correlations between the visual inspection, mass loss and pH changes results and the aging time or the aging conditions were developed. Specimens submitted to the highest acid concentration showed the fastest and most intense degradation. The type of coarse aggregate (limestone) used for the concrete seemed to be the cause of the fastest aging observed, compared to the cement paste. The research findings created the foundation for the ongoing investigation, in which new concrete samples with a mix design similar to the HCAEX tunnel will be tested and will serve as the substrate for testing the selected coatings and /or repair materials. In this paper, the literature review and preliminary results from the aging tests are provided. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Exploratory Efforts to Constrain Geologic Material Properties from Remote Sensing Data: Joint Study (FY2020 Final Report)

Identification and characterization of underground events from surface or remote data requires a thorough understanding of the rock material properties. However, material properties usually come from borehole data, which is expensive and not always available. A potential alternative is to use topographic characteristics to approximate the strength, but this has never been done before quantitatively. Here we present the results from the first steps towards this goal. We have found that there are strong correlations between compressive and tensile strengths and slopes, but these correlations vary depending on data analysis details. Rugosity may be better correlated to strength than slope values. More comprehensive analyses are needed to fully understand the best method of predicting strength from topography for this area. We also found that misalignment of multiple GIS datasets can have a large influence on the ability to make interpretations. Lastly, these results will require further study in a variety of climatic conditions before being applicable to other sites.

58 GEOSCIENCES↗

Rietveld Refinement for Macromolecular Powder Diffraction

Powder X-ray diffraction (PXRD) has been employed extensively for the structural characterization of materials, quantitative analysis of multicomponent mixtures, phase identification, texture, and microstructural analysis. At the heart of all those lies the Rietveld method, which has revolutionized the use of powder diffraction for materials studies. Initially applied to minerals and inorganics, the Rietveld method has progressively been used for more complex materials, for instance, zeolites and pharmaceuticals. A major advance of the method came some 20 years ago, when the first protein structure was successfully refined. Because of the sheer complexity of macromolecules, several new approaches and algorithms had to be pioneered or adapted from macromolecular single-crystal diffraction experiments, thus constituting macromolecular PXRD a quite unique field of study. This review aims to provide necessary elements of theory and application of structure solution and refinement via the Rietveld method for macromolecular PXRD data. Here, practical explanations and highlighted case studies are also presented.

36 MATERIALS SCIENCE↗

pyvisco [SWR-22-30]

pyvisco is a Python library that supports the identification of Prony series parameters for linear viscoelastic materials described by a Generalized Maxwell model. The necessary material model parameters are identified by fitting a Prony series to the experimental measurement data. pyvisco allows for the identification of Prony series parameters from experimental data measured in either the frequency-domain (via Dynamic Mechanical Thermal Analysis) or time-domain (via relaxation measurements). The experimental data can be provided as raw measurement sets at different temperatures or as pre-processed master curves. An optional minimization routine is included to reduce the number of Prony elements. This routine is helpful in Finite Element simulations where reducing the computational complexity of the linear viscoelastic material models can shorten the simulation time. See also, https://pypi.org/project/pyvisco/

Springer, Martin↗

Identification of durable and non-durable FeN x sites in Fe–N–C materials for proton exchange membrane fuel cells

We report that while Fe–N–C materials are a promising alternative to platinum for catalysing the oxygen reduction reaction in acidic polymer fuel cells, limited understanding of their operando degradation restricts rational approaches towards improved durability. Here we show that Fe–N–C catalysts initially comprising two distinct FeN x sites (S1 and S2) degrade via the transformation of S1 into iron oxides while the structure and number of S2 were unmodified. Structure–activity correlations drawn from end-of-test 57 Fe Mössbauer spectroscopy reveal that both sites initially contribute to the oxygen reduction reaction activity but only S2 substantially contributes after 50 h of operation. From in situ 57 Fe Mössbauer spectroscopy in inert gas coupled to calculations of the Mössbauer signature of FeN x moieties in different electronic states, we identify S1 to be a high-spin FeN 4 C 12 moiety and S2 a low- or intermediate-spin FeN 4 C 10 moiety. These insights lay the groundwork for rational approaches towards Fe–N–C cathodes with improved durability in acidic fuel cells.

36 MATERIALS SCIENCE↗

Prioritizing Nuclear Materials for SAM-3 Neutron Irradiation Campaign: Structural and Cladding Materials Candidates

This report outlines a framework for selecting structural and cladding materials for the Nuclear Science User Facilities (NSUF) SAM-3 neutron irradiation campaign to support the advancement of nuclear energy technologies. The document begins with an introduction that provides background context, highlights the motivations for launching a new irradiation campaign, and defines the overall objectives. The core of the report describes the design considerations for the irradiation campaign, including capsule configurations, irradiation temperature ranges, and target dose levels (defined by displacements per atom, or dpa). The material recommendation was guided by the Specimen Identification and Prioritization (SIP) Working Group, a multidisciplinary team of experts representing national laboratories, academia, industry, federal government and agency. This group played a central role in identifying candidate materials, evaluating technical justifications, and ensuring alignment with boarder programmatic goals. A detailed set of criteria for material prioritization is then presented, taking into account reactor relevance, performance gaps, advanced manufacturing methods, and emerging material classes. Based on the input of SIP working group, specific materials were selected and justified for inclusion in the irradiation campaign by the NSUF leadership and its U.S. Department of Energy (DOE)-Office of Nuclear Energy (NE) management. The final section provides recommended capsule designs, summarizing critical parameters such as material type, fabrication method, sample geometry, irradiation conditions, and specimen quantities. This report serves as a foundation for executing a focused and high-impact neutron irradiation campaign aimed at addressing key materials challenges for both existing and advanced nuclear reactors.

36 - MATERIALS SCIENCE↗

Magnetic Interactions of the Centrosymmetric Skyrmion Material Gd 2 PdSi 3

The experimental realization of magnetic skyrmion crystals in centrosymmetric materials has been driven by theoretical understanding of how a delicate balance of anisotropy and frustration can stabilize topological spin structures in applied magnetic fields. Recently, the centrosymmetric material Gd 2 PdSi 3 was shown to host a field-induced skyrmion crystal, but the skyrmion stabilization mechanism remains unclear. Here, we employ neutron-scattering measurements on an isotopically enriched polycrystalline Gd 2 PdSi 3 sample to quantify the interactions that drive skyrmion formation. Our analysis reveals spatially extended interactions in triangular planes, and large ferromagnetic interplanar magnetic interactions that are modulated by the Pd/Si superstructure. The skyrmion crystal emerges from a zero-field helical magnetic order with magnetic moments perpendicular to the magnetic propagation vector, indicating that the magnetic dipolar interaction plays a significant role. To conclude, our experimental results establish an interaction space that can promote skyrmion formation, facilitating identification and design of centrosymmetric skyrmion materials.

36 MATERIALS SCIENCE↗

Mixed Enthalpy–Entropy Descriptor for the Rational Design of Synthesizable High-Entropy Materials Over Vast Chemical Spaces

The practically unlimited high-dimensional composition space of high-entropy materials (HEMs) has emerged as an exciting platform for functional material design and discovery. However, the identification of stable and synthesizable HEMs and robust design rules remains a daunting challenge. Here, we propose a mixed enthalpy–entropy descriptor (MEED) that enables highly efficient, robust, high-throughput prediction of synthesizable HEMs across vast chemical spaces from first-principles. The MEED is based on two parameters: the relative formation enthalpy with respect to the most stable competing compound and the spread of the point-defect formation energy spectrum. The former measures the relative synthesizability of an HEM to its most stable competing phase, going beyond the conventional thermodynamic understanding. Further, the latter gauges the relative entropy forming ability of an HEM, entailing no sampling over numerous alloy configurations. By applying the MEED to two structurally distinct representative material systems (i.e., 3D rocksalt carbides and 2D layered sulfides), we not only successfully identify all experimentally reported HEMs within these systems but also reveal a cutoff criterion for assessing their relative synthesizability within each system. By the MEED, tens of new high-entropy carbides and 2D high-entropy sulfides are also predicted, which have the potential for a wide variety of applications such as coating in aerospace devices, energy conversion and storage, and flexible electronics.

36 MATERIALS SCIENCE↗

Greybox Thermal Parameter Identification of Electric Machine Stators

The parameters of electric machine thermal equivalent circuit networks are difficult to predict due to material and manufacturing uncertainties. In this paper, a Greybox system identification approach is used to identify parameters of electric machine stator lumped parameter thermal networks (LPTNs). LPTNs provide a low order, computationally efficient, dynamic model of temperatures at specific locations. Second and third order LPTN model structures are defined as state space equations with stator thermal parameters to be identified. To test the Greybox electric machine stator thermal system identification, five stator motorette prototypes were constructed with controlled variations in slot fill and slot liner thickness. The variation in the motorette thermal parameters and thermal time constants are detected using the Greybox identification. Special attention is given to the impact of sampling rate and Greybox data record length on parameter estimation accuracy.

33 ADVANCED PROPULSION SYSTEMS↗

Review of multi-faceted morphologic signatures of actinide process materials for nuclear forensic science

Particle morphology is an emerging signature that has the potential to identify the processing history of unknown nuclear materials. Using readily available scanning electron microscopes (SEM), the morphology of nearly any solid material can be measured within hours. Coupled with robust image analysis and classification methods, the morphological features can be quantified and support identification of the processing history of unknown nuclear materials. The viability of this signature depends on developing databases of morphological features, coupled with a rapid data analysis and accurate classification process. With developed reference methods, datasets, and throughputs, morphological analysis can be applied within days to (i) interdicted bulk nuclear materials (gram to kilogram quantities), and (ii) trace amounts of nuclear materials detected on swipes or environmental samples. In conclusion, this review aims to develop validated and verified analytical strategies for morphological analysis relevant to nuclear forensics.

36 MATERIALS SCIENCE↗

Adaptively driven X-ray diffraction guided by machine learning for autonomous phase identification

Machine learning (ML) has become a valuable tool to assist and improve materials characterization, enabling automated interpretation of experimental results with techniques such as X-ray diffraction (XRD) and electron microscopy. Because ML models are fast once trained, there is a key opportunity to bring interpretation in-line with experiments and make on-the-fly decisions to achieve optimal measurement effectiveness, which creates broad opportunities for rapid learning and information extraction from experiments. Here, we demonstrate such a capability with the development of autonomous and adaptive XRD. By coupling an ML algorithm with a physical diffractometer, this method integrates diffraction and analysis such that early experimental information is leveraged to steer measurements toward features that improve the confidence of a model trained to identify crystalline phases. We validate the effectiveness of an adaptive approach by showing that ML-driven XRD can accurately detect trace amounts of materials in multi-phase mixtures with short measurement times. The improved speed of phase detection also enables in situ identification of short-lived intermediate phases formed during solid-state reactions using a standard in-house diffractometer. Our findings showcase the advantages of in-line ML for materials characterization and point to the possibility of more general approaches for adaptive experimentation.

36 MATERIALS SCIENCE↗

Identification of the Electronic and Structural Dynamics of Catalytic Centers in Single-Fe-Atom Material

The lack of model single-atom catalysts (SACs) and atomic-resolution operando spectroscopic techniques greatly limits our comprehension of the nature of catalysis. Herein, based on the designed model single-Fe-atom catalysts with well-controlled microenvironments, we have explored the exact structure of catalytic centers and provided insights into a spin-crossover-involved mechanism for oxygen reduction reaction (ORR) using operando Raman, X-ray absorption spectroscopies, and the developed operando 57 Fe Mössbauer spectroscopy. In combination with theoretical studies, the N-FeN 4 C 10 moiety is evidenced as a more active site for ORR. Moreover, the potential-relevant dynamic cycles of both geometric structure and electronic configuration of reactive single-Fe-atom moieties are evidenced via capturing the peroxido (*O 2 -) and hydroxyl (*OH-) intermediates under in situ ORR conditions. Overall, we anticipate that the integration of operando techniques and SACs in this work shall shed some light on the electronic-level insight into the catalytic centers and underlying reaction mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Delayed onset of discontinuous precipitation-based phase transformation in U10Mo alloys doped with Silicon

A uranium-10 wt% molybdenum (U-10Mo) alloy is one of the primary candidates for metallic fuels that would use low-enriched uranium in place of highly enriched uranium, to support nuclear nonproliferation efforts. Optimal performance of a U-based metallic nuclear fuel can be achieved by retaining the high-temperature, body-centered cubic (bcc) allotrope (γ-U) at room temperature, which can be accomplished in the U-10Mo alloy. However, presence of minor alloying elements can influence the final constitution of room-temperature phases in the U10Mo alloy, specifically, formation of α-U phase which results in anisotropic behavior of the fuel in reactor. Further, through a detailed transmission electron microscopy analysis, the present study reports the constituent phases that are present in a U10Mo alloy containing ~0.1 wt% Si after it is subjected to homogenization heat treatment and thermomechanical processing. For comparison, results from an undoped U10Mo alloy are also included. The experimental results reveal that γ-UMo solid solution is the major phase in a hot-rolled, Si-doped U10Mo alloy metallic fuel foil, along with U 2 MoSi 2 C, UC, and U 2 Mo, after isothermal annealing at 460 °C for 10h. In contrast, after the same heat treatment, the undoped U10Mo alloy metallic fuel had formed a noticeable amount of α-U along prior γ-UMo grain boundaries through discontinuous precipitation (DP, area fraction: ~27.9%) with characteristic lamellar morphology, together with γ-UMo, UC, and U 2 Mo. This result indicates that doping with Si could mitigate the DP reaction in U10Mo alloy and prevent formation of undesirable α-U. This work sheds light on optimizing Si-doping–dominated microstructure in U10Mo fuels and facilitates designing and tuning of microstructures of U10Mo alloys for tailoring the final designed performance of the fuel under irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Ice Phase Classification Made Easy with Score-Based Denoising

Accurate identification of ice phases is essential for understanding various physicochemical phenomena. However, such classification for structures simulated with molecular dynamics is complicated by the complex symmetries of ice polymorphs and thermal fluctuations. For this purpose, both traditional order parameters and data-driven machine learning approaches have been employed, but they often rely on expert intuition, specific geometric information, or large training data sets. In this work, we present an unsupervised phase classification framework that combines a score-based denoiser model with a subsequent model-free classification method to accurately identify ice phases. Further, the denoiser model is trained on perturbed synthetic data of ideal reference structures, eliminating the need for large data sets and labeling efforts. The classification step utilizes the smooth overlap of atomic position (SOAP) descriptors as the atomic fingerprint, ensuring Euclidean symmetries and transferability to various structural systems. Our approach achieves a remarkable 100% accuracy in distinguishing ice phases of test trajectories using only seven ideal reference structures of ice phases as model inputs. This demonstrates the generalizability of the score-based denoiser model in facilitating phase identification for complex molecular systems. The proposed classification strategy can be broadly applied to investigate structural evolution and phase identification for a wide range of materials, offering new insights into the fundamental understanding of water and other complex systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗