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DOE OSTI2026

Affine Transformations to Enable Machine Learning for Semi-Quantitative EDS Analysis

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Affine Transformations to Correlate Experimental and Simulated EDS Spectra for Multi-Element Systems

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Hierarchical Defect Engineering for LiCoO 2 through Low-Solubility Trace Element Doping

Real-world industry-relevant battery composite electrodes are hierarchically structured. Their structural and chemical complexity is featured by ubiquitous multi-scale porosity and cracks, solid-solid and solid-liquid interfaces, compositional and redox heterogeneity, as well as lattice disordering and deformation. In particular for the active cathode particles, which are the fundamental building blocks for the energy reservoir, it is a consensus that these structural and chemical defects could have a profound impact on the battery performance. An in-depth understanding of the underlying mechanisms could critically inform the cathode material engineering, which would have a tremendous potential but remains a daunting challenge at present. In this work, we tackle this question by studying LiCoO 2 (LCO) with trace doping of Ti, which exhibits a low solubility in the LCO layered lattice. Additionally, we observed the spontaneous and heterogeneous segregation of the dopant (Ti) across a wide range of length scales. In addition to the modification of the particle surface and the buried grain boundaries within the particle, we reveal that the Ti doping has induced a significant amount of lattice distortions, which, in turn, promotes the robustness of the LCO lattice at high state of charge (above 4.5V). Our result formulates a multi-scale defect engineering strategy that could be applicable to the synthesis of a broad range of energy materials for applications in batteries and beyond.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Evidence of Cooperative Effects for the Fe(phen) 2 (NCS) 2 Spin Crossover Molecular Complex in Polyaniline Plus Iron Magnetite

The spin crossover complex Fe(phen) 2 (NCS) 2 and its composite, Fe(phen) 2 (NCS) 2 , combined with the conducting polymer polyaniline (PANI) plus varying concentrations of iron magnetite (Fe 3 O 4 ) nanoparticles were studied. A cooperative effect is evident from the hysteresis width in the plot of magnetic susceptibility multiplied by temperature versus temperature (χ m T versus T) for Fe(phen) 2 (NCS) 2 with PANI plus varying concentrations of Fe 3 O 4 nanoparticles. The hysteresis width in the composites vary no more than 2 K with respect to the pristine Fe(phen) 2 (NCS) 2 spin crossover crystallites despite the fact that there exists a high degree of miscibility of the Fe(phen) 2 (NCS) 2 spin crossover complex with the PANI. The Fe 3 O 4 nanoparticles in the Fe(phen) 2 (NCS) 2 plus PANI composite tend to agglomerate at higher concentrations regardless of the spin state of Fe(phen) 2 (NCS) 2 . Of note is that the Fe 3 O 4 nanoparticles are shown to be antiferromagnetically coupled with the Fe(phen) 2 (NCS) 2 when Fe(phen) 2 (NCS) 2 is in the high spin state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Complexation of Light Trivalent Lanthanides with N-(2-Hydroxyethyl)ethylenediamine-N,N',N'-triacetic Acid in Aqueous Solutions: Thermodynamic Analysis and Coordination Modes

N-(2-hydroxyethyl)ethylenediamine-N,N',N'-triacetic acid (HEDTA, denoted as H 3 L) is a strong chelating ligand that is widely used in separation of f-elements as relevant to the nuclear fuel cycle. There is much to be known about the structure and composition of the coordination sphere of the complexes of HEDTA with lanthanides. The complexation of HEDTA with light lanthanides (La 3+ , Nd 3+ and Eu 3+ ) was investigated thermodynamically and structurally in aqueous solutions. Potentiometry and microcalorimetry were performed to acquire the complexation constants (25-70°C) and enthalpies (25°C), respectively, at I = 1.0mol·L -1 NaClO 4 . Coordination modes of the complexes were analyzed by luminescence spectroscopy and nuclear magnetic resonance spectroscopy. The results indicate that there are two successive Ln 3+ /HEDTA complexes, LnL(aq) and Ln 2 (H -1 L) 2 2- (Ln 3+ referred to La 3+ , Nd 3+ and Eu 3+ ; H -1 L 4- referred to the deprotonation of the hydroxyl group) during the titration. The hydroxyl group of HEDTA is coordinated in Ln 3+ /HEDTA complex. The dinuclear Ln 2 (H -1 L) 2 2- complex is present as a carboxyl-bridged centrosymmetric dimer, and two carboxyl groups in bridging positions are coordinated to two adjacent Ln 3+ cations. Complexation of the NdL(aq) is exothermic, while formation of the hydrolytic complex Nd 2 (H -1 L) 2 2- is endothermic. Both NdL aq and Nd 2 (H -1 L) 2 2- complexes are driven by entropic force. These data will help to predict the behavior of lanthanides in the separation process where HEDTA is used as the aqueous complexant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Precipitation-site competition in duplex stainless steels: Cu clusters vs spinodal decomposition interfaces as nucleation sites during thermal aging

Competing microstructural evolution mechanisms can exist simultaneously when duplex stainless steels are operating for several decades in a high temperature service environment. Such competition between different microstructural evolution pathways can be difficult to ascertain using simple model alloy systems necessitating detailed structural and compositional analysis of phase transformation mechanisms in complex alloys Thus, in this study duplex stainless steels with complex but well understood chemistries were used to investigate the relative importance of different heterogeneous nucleation sites – specifically spinodal decomposition and Cu clustering – on precipitation of Ni-Si-Mn particles during long term thermal aging. Precipitation of Ni-Si-Mn particles in duplex stainless steels and ferritic steels during thermal aging and irradiation is known to have profound effect on mechanical properties. Using duplex stainless steels with custom modified compositions along with atom probe tomography characterization and first-passage kinetic Monte Carlo (FPKMC) simulations it is revealed that while the interface between Cr and Fe formed during spinodal decomposition can be a pathway for diffusion of Ni, Si, Mn, and Cu, it is not a site that encourages precipitation of Ni-Si-Mn rich particles. Instead, the presence of a higher concentration of Cu in these steels leads to formation of small Cu clusters with high energy interfaces that act as nucleation sites for Ni-Si-Mn particles because of its strong interaction particularly with Ni increasing the chemical driving force for precipitation. These results will help inform predictive models for the use of duplex stainless steels and other precipitation-hardened alloys for extended operation at high temperatures.

Duplex stainless steel, Thermal aging, Precipitati↗

DOE OSTI2019

Development of nickel-incorporated MCM-41–carbon composites and their application in nitrophenol reduction

MCM-41–carbon composites were obtained by soft-templating strategy by adding resorcinol and formaldehyde as carbon precursors during the synthesis of MCM-41. The synthesis of these composites was optimized until mesoporous MCM-41 domains remained highly ordered and the overall specific surface area and pore volume remained relatively high. The one-pot synthetic procedure was further extended to obtain the Ni-containing MCM-41–carbon composites using nickel nitrate as an additive. A homogeneous distribution of nickel nanoparticles in the composites was achieved by adding histidine to the reaction mixture, which was able to form a complex with nickel ion. Carbonization of organic components in the composites produced carbon that was responsible for in situ reduction of nickel(II) to metallic nickel (Ni0) at elevated temperatures, eliminating the post-synthesis reduction step carried out in the presence of hydrogen gas or other reducing agent. Furthermore, the resulting composites showed enhanced catalytic activity toward nitrophenol reduction obeying the zero-order kinetics. Three unique features of the resulting composites, namely mesoporous channels of MCM-41, carbon-induced in situ reduction of Ni ions to metallic Ni nanoparticles, and abundance of highly active Ni sites due to high dispersion of Ni0, make this strategy applicable for the synthesis of other transition metal-based catalysts. XRD and STEM analyses revealed a homogeneous distribution of nickel nanoparticles in the composites without significant distortion of their ordered mesoporosity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Computationally aided, entropy-driven synthesis of highly efficient and durable multi-elemental alloy catalysts

Multi-elemental alloy nanoparticles (MEA-NPs) hold great promise for catalyst discovery in a virtually unlimited compositional space. However, rational and controllable synthesize of these intrinsically complex structures remains a challenge. Here, we report the computationally aided, entropy-driven design and synthesis of highly efficient and durable catalyst MEA-NPs. The computational strategy includes prescreening of millions of compositions, prediction of alloy formation by density functional theory calculations, and examination of structural stability by a hybrid Monte Carlo and molecular dynamics method. Selected compositions can be efficiently and rapidly synthesized at high temperature (e.g., 1500 K, 0.5 s) with excellent thermal stability. We applied these MEA-NPs for catalytic NH 3 decomposition and observed outstanding performance due to the synergistic effect of multi-elemental mixing, their small size, and the alloy phase. We anticipate that the computationally aided rational design and rapid synthesis of MEA-NPs are broadly applicable for various catalytic reactions and will accelerate material discovery.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Revisiting Multi-Material Composite Structures with Homogenized Composite Properties

Composite structures inherently develop residual stresses during their curing process. Driven predominately by mismatched thermal strains between differing materials or ply orientations, but also affected by curing process phenomena like polymer shrinkage, these residual stresses can lead to failure within composite structures. There are several methods varying in complexity that can be used to model the development of residual stresses, all of which are capable of capturing sufficient detail to understand the residual stress state at the ply level. However, explicitly modeling all plies of a layup in a composite structure can be prohibitively expensive based on the number of plies, structure size, and required element size. The computational cost can be reduced through the homogenization of the composite layup without losing much fidelity of the overall response of the structure. The homogenization process reduces the many plies of a laminate to a single lamina that reduces complexity and increases the mesh size where a single element can span multiple plies. This report focuses on verification and validation efforts for a homogenization process using a suite of finite element simulations rather than an analytic solution derived from classical laminate theory. Initial verification using representative element volumes indicated there was minimal error in the homogenization process; however, this compounded to a small, but acceptable error in strip and split ring experimental composite structures. The error does under predict the residual stress state in the strip and split ring and should be accounted for when simulating composite structures with homogenized properties.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Computational alchemy clarifies origins of alloy strengthening

Solid solution strengthening (SSS) is widely used to enhance mechanical properties of metals. Originally developed for dilute alloys, classical SSS theories are presently challenged by the rise of complex concentrated alloys (CCA) with nearly equiatomic compositions. Here, we propose and develop a method of “computational alchemy” in which interatomic interactions are modified to systematically vary two key physical parameters defining SSS - atomic size misfit and elastic stiffness misfit - over a maximally wide range of two misfits. The resulting alchemical alloys are subjected to massive (~10 8 atoms) molecular dynamics (MD) simulations reproducing full complexity of plastic strength response. At variance with prevailing views, stiffness misfit is observed to contribute to SSS on par if not more than size misfit. Furthermore, depending on exactly how two misfits are combined, they result in synergistic (amplification) or antagonistic (compensation) effect on alloy strengthening. Unlike real CCAs in which each component element comes with its own specific size and stiffness, our alchemical model alloys span the space of two misfits continuously revealing trends in alloy strengthening unrecognized so far. Our study demonstrates unique value of intentionally unrealistic models for gaining deep physical insights into material behaviors that are difficult to reveal otherwise.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Is Radioactive Tank Waste a Bingham Fluid?

Slurries and sludges across the United States Department of Energy (DOE) complex rank among the most rheologically interesting. Their composition is heterogeneous, spanning a very broad range of particle sizes, densities, and interparticle forces. All exhibit shear thinning, some have yield stresses, and many are thixotropic. Despite the variety, these complex fluids are often represented using the historic Bingham fluid model, which fits higher shear rate data to a simple straight line. The intercept provides a yield stress, which has been a key design parameter in construction of large-scale waste processing facilities. However, many radioactive wastes are simply not Bingham fluids, which extrapolate but poorly across low to intermediate shear rates that are characteristic of typical processing conditions. Indeed, processing shear rates as high as 200 1/s, which has been a typical minimum shear rate used in fitting, are seldom encountered in nuclear waste processing. Therefore, more realistic rheological models are necessary to accurately predict waste processing performance. PNNL recently re-evaluated the rheology of reconstituted Hanford REDOX sludge waste against a wide variety of rheological models including the Bingham, Cross, Cross with yield stress, Carreau, biviscous, Herschel-Bulkley (which includes a power law dependence), Casson, and Gay models. They found that all of the models provided a closer fit than the Bingham model and that the biviscous model and Cross with yield stress model were convincing. However, reconstituted Hanford REDOX sludge waste is but one type of DOE waste and a direct contrast and comparison of these three models against undiluted, unmixed tank waste (actual not simulant) has not been performed previously. Therefore, the purpose of this paper is to evaluate the rheology of actual tank waste with these more accurate rheological models. In this paper, we evaluate select rheological data for slurry samples from Hanford’s AZ-101, AZ-102, and SY-101 waste tanks. In each of these cases, we find that Cross’ model with yield stress and the biviscous model significantly outperform the Bingham fluid model. Furthermore, the AZ-101 data also shows that the shear stress peak that startup significantly exceeds the Bingham yield stress, which is commonly observed in the incipient moments of rheological measurements on simulants. In contrast, Cross’ model may empirically accommodate an initial spike in shear stress at modest shear rates. These are important observations because computational and analytical fluid dynamics simulations rely on rheological constitutive models for accurately and conservatively predict waste processing performance. These findings suggest the need for better rheological modeling of and validation against radioactive waste.

Rheology, Radioactive Waste↗

DOE OSTI2019

Fiber motion in highly confined flows of carbon fiber and non-Newtonian polymer [Advanced modeling of non-Newtonian polymer and carbon fibers]

Inks compounded of short carbon fibers suspended in polymer resin can be extruded to produce composite materials during additive manufacturing or 3D printing processes. The flow process induces anisotropic orientation of the fibers which is set into the matrix and significantly affects the mechanical and physical properties of the final product. Therefore, the flow of fiber suspensions needs to be understood in order to predict the orientation distribution of the fibers during such manufacturing processes. There is still a lack of knowledge for extrusion of the complex mixture of a non-Newtonian polymer containing a high-volume fraction of fibers with high fiber aspect ratio, where both inter-particle, fluid-particle and fiber-wall interactions are computationally evaluated. This paper presents predictive numerical simulations and experimental results of such confined flow in a concentrated regime. The code is based on Lagrange multiplier technique and resolves each particle and interaction between the fibers and surrounding fluid and nozzle walls. We investigate numerically how the fiber length impacts the fiber alignment during extrusion. We found that a fiber length above 67% of the nozzle's diameter induces dramatic change in the fiber flow, causing fibers to concentrate at the nozzle boundaries with very low concentration of fibers in the center of the nozzle. It was found that the best fiber alignment is reached for fiber lengths equal to 40–50% of the nozzle diameters. Numerical findings are supported by experimental results. In conclusion, this work improves understanding of fiber orientation during 3D printing and is an important milestone for the prediction of the complex mechanical properties of additively manufactured fiber composites.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Unconventional Complex Coacervation between Neutral Polymer and Inorganic Polyoxometalate in Aqueous Solution via Direct Water Mediation

Water, specifically in a hydration shell, is critical for many biological supramolecular aggregations in nature, where water can directly mediate intermolecular association via hydrogen bonding and is regarded as “structured water”. Conversely, little has been reported on the biomimetic water-mediated supramolecular assembly with adequately high water content to date, because of the competing thermodynamic processes of water hydration and water as a building block to participate in self-assembly. In this work, we explore water-mediated complexation based on entropy-driven biphasic coacervate formation using highly hydrophilic neutral polymer and inorganic mineral-analogous nanoclusters. For the first time (to the best of our knowledge), nonelectrostatic liquid–liquid separating coacervate formation is demonstrated between polyethylene glycol (PEG) and polyoxometalate (POM) nanoclusters in aqueous solutions of varied PEG and POM concentrations, POM types, and aqueous medium conditions. Comprehensive characterization using fluorescence microscopy, small-angle X-ray scattering, calorimetry, and other techniques has confirmed that the compositions, microstructure, and thermodynamics of PEG–POM complex coacervation are highly similar to entropy-driven complex coacervation between oppositely charged polyelectrolytes in aqueous solution. However, the effect of heavy water on critical POM concentration for the onset of coacervate formation suggests that water, instead of the counter ions as commonly debated for polyelectrolyte complex coacervation, is responsible for PEG–POM coacervate formation. Specifically, structured water works as a hydrogen bond donor for both highly hydrated PEG and POM to directly mediate the PEG–water–POM association, resulting in the release of excess hydrated water for entropy-driven PEG–POM complex coacervation. Furthermore, water-mediated complex coacervation could be developed as a general and simple strategy to build biomimetic hybrid nanomaterials with high water content for various applications from energy-related functional nanomaterials to biomedical ramification.

36 MATERIALS SCIENCE↗

DOE OSTI2024

ER-associated VAP27-1 and VAP27-3 proteins functionally link the lipid-binding ORP2A at the ER-chloroplast contact sites

Abstract The plant endoplasmic reticulum (ER) contacts heterotypic membranes at membrane contact sites (MCSs) through largely undefined mechanisms. For instance, despite the well-established and essential role of the plant ER-chloroplast interactions for lipid biosynthesis, and the reported existence of physical contacts between these organelles, almost nothing is known about the ER-chloroplast MCS identity. Here we show that the Arabidopsis ER membrane-associated VAP27 proteins and the lipid-binding protein ORP2A define a functional complex at the ER-chloroplast MCSs. Specifically, through in vivo and in vitro association assays, we found that VAP27 proteins interact with the outer envelope membrane (OEM) of chloroplasts, where they bind to ORP2A. Through lipidomic analyses, we established that VAP27 proteins and ORP2A directly interact with the chloroplast OEM monogalactosyldiacylglycerol (MGDG), and we demonstrated that the loss of the VAP27-ORP2A complex is accompanied by subtle changes in the acyl composition of MGDG and PG. We also found that ORP2A interacts with phytosterols and established that the loss of the VAP27-ORP2A complex alters sterol levels in chloroplasts. We propose that, by interacting directly with OEM lipids, the VAP27-ORP2A complex defines plant-unique MCSs that bridge ER and chloroplasts and are involved in chloroplast lipid homeostasis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Structures of the TMC-1 complex illuminate mechanosensory transduction

The initial step in the sensory transduction pathway underpinning hearing and balance in mammals involves the conversion of force into the gating of a mechanosensory transduction channel1. Despite the profound socioeconomic impacts of hearing disorders and the fundamental biological significance of understanding mechanosensory transduction, the composition, structure and mechanism of the mechanosensory transduction complex have remained poorly characterized. Here we report the single-particle cryo-electron microscopy structure of the native transmembrane channel-like protein 1 (TMC-1) mechanosensory transduction complex isolated from Caenorhabditis elegans. The two-fold symmetric complex is composed of two copies each of the pore-forming TMC-1 subunit, the calcium-binding protein CALM-1 and the transmembrane inner ear protein TMIE. CALM-1 makes extensive contacts with the cytoplasmic face of the TMC-1 subunits, whereas the single-pass TMIE subunits reside on the periphery of the complex, poised like the handles of an accordion. A subset of complexes additionally includes a single arrestin-like protein, arrestin domain protein (ARRD-6), bound to a CALM-1 subunit. Single-particle reconstructions and molecular dynamics simulations show how the mechanosensory transduction complex deforms the membrane bilayer and suggest crucial roles for lipid–protein interactions in the mechanism by which mechanical force is transduced to ion channel gating.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Tailored Fiber Placement for Complex Preforms

Tailored Fiber Placement (TFP) offers a novel approach to optimize fiber architecture for the fabrication of complex, structural parts not traditionally suitable for advanced composites. This technology not only offers new routes for weight reduction via metal substitution, it also offers cost reduction through minimization of material scrap and reduced labor. This reduction in component weight leads to increased fuel efficiency, and reduced production energy consumption, thereby, helping to achieve the stated IACMI technical goals. This technology leverages centuries of manufacturing development in support of the textile and embroidery industry. One major drawback to this technology is the lack of commercial or non- proprietary structural performance data and robust analytical tools used to optimize fiber architecture and predict performance. This project was structured to utilize common sub-element features to validate analytical performance tools, generate performance data, and gather cost and performance data on components of interest. This project was designed to give industry sponsors the confidence and ability to take full advantage of TFP to fabricate primary, highly loaded structure and integrate features such as metallic fasteners. The project focused principally on the use of high strength carbon fiber, such as T700, and the use of aerospace epoxy resin matrix to primarily support development of new composite applications in vehicle, aerospace, and industrial markets. This project applied previously developed analytical tools to predict the performance of TFP produced parts. This work focused on developing the pipeline to characterize material in order to accurately predict component performance when modifying the TFP print paths and stitch density. This focused on experimental characterization via standardized ASTM testing, alongside experimental testing of more representative service components by testing curved beam strength, beam shear performance, a large scale TFP lug, and ultimately designing a fully TFP clip bracket that reduced weight and cost compared to a traditional metallic component. The new knowledge gained from this program included: 1) development and demonstration of novel analytical tools applied to analysis of TFP preforms; 2) development and demonstration of a building block approach using coupons and sub-elements to optimize the design of a more complex component; 3) demonstration that optimized fiber orientation using TFP can exceed performance of conventional textile composite materials and can open new applications currently limited to metallic components; 4) Demonstration of performance and cost benefits of the TFP process as compared to metallic and conventional textile composites. Recommendations for follow-on work include development of design allowables to assess the impact of high temperature/moisture exposure or saturation during loading, tracking the impact of stitching needle wear on the performance of parts and ability to stitch thicker preforms, using TFP preforms as local reinforcement at areas of bearing or complex loading, and topology optimization of components by tow steering. The expertise developed during the course of this project can be leveraged to provide commercial engineering design and fabrication services using TFP. UDRI is in the process of formalizing their partnership with Spintech, who will serve as the commercialization partner for this technology and provide molding services and deliver finished components to the end user. UDRI will continue to produce the preforms until the economics allow Spintech to procure its own TFP equipment or lease UDRI equipment, at which point UDRI will step away from manufacture and serve as the engineering and design lead on product development.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Ultrathin films based on luminescent complexes of 4-n-octyloxybenzoic acid with lanthanides

Europium(III) and terbium(III) complexes with 4-n-octyloxybenzoic acid of the composition LnL{sub 3} were synthesized and their luminescent properties were studied. It was established that the luminescence intensity of the TbL{sub 3} complex in the visible region is much higher than that of EuL{sub 3}. Langmuir monolayers of these compounds on the water subphase and Langmuir–Blodgett films on solid substrates were prepared. The morphological characteristics of the latter were studied. The results obtained indicate good prospects for application of these compounds in the design and fabrication of planar photonic and optoelectronic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

Identifying Sample Provenance From SEM/EDS Automated Particle Analysis via Few-Shot Learning Coupled With Similarity Graph Clustering

Automated particle analysis (APA) provides a vast amount of compositional data via energy-dispersive X-ray spectroscopy along with size and shape data via scanning electron microscopy for individual particles in a sample. In many instances, APA data are leveraged to support identification of the source of a sample based on the detection of particles of a specific composition. Often, the particles that provide context make up a minuscule portion of the sample. Additionally, the interpretation of complex samples can be difficult due to the diversity of compositions both in the mixture and within a particle. In this work, we demonstrate a method to compute and cluster similarity graphs that describe inter-particle relationships within a sample using a multi-modal few-shot learning neural network. Here, as a proof-of-concept, we show that samples known to have been exposed to gunshot residue can be distinguished from samples occasionally mistaken for gunshot residue. Our workflow builds upon standard APA techniques and data processing methods to unveil additional information in a readily interpretable and quantitatively comparable format.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗