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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Intrinsic Properties of Individual Inorganic Silicon–Electrolyte Interphase Constituents

Because of the complexity, high reactivity, and continuous evolution of the silicon-electrolyte interphase (SiEI), 'individual' constituents of the SiEI were investigated to understand their physical, electrochemical, and mechanical properties. For the analysis of these intrinsic properties, known SiEI components (i.e., SiO 2 , Li 2 Si 2 O 5 , Li 2 SiO 3 , Li 3 SiO x , Li 2 O, and LiF) were selected and prepared as amorphous thin films. The chemical composition, purity, morphology, roughness, and thickness of prepared samples were characterized using a variety of analytical techniques. On the basis of subsequent analysis we found, LiF shows the lowest ionic conductivity and relatively weak, brittle mechanical properties, while lithium silicates demonstrate higher ionic conductivities and greater mechanical hardness. This research establishes a framework for identifying components critical for stabilization of the SiEI, thus enabling rational design of new electrolyte additives and functional binders for the development of next-generation advanced Li-ion batteries utilizing Si anodes.

14 SOLAR ENERGY↗
DOE OSTI2019

Local atomic structure of thin and ultrathin films via rapid high-energy X-ray total scattering at grazing incidence

Atomic pair distribution function (PDF) analysis is the most powerful technique to study the structure of condensed matter on the length scale from short- to long-range order. Today, the PDF approach is an integral part of research on amorphous, nanocrystalline and disordered materials from bulk to nanoparticle size. Thin films, however, demand specific experimental strategies for enhanced surface sensitivity and sophisticated data treatment to obtain high-quality PDF data. The approach described here is based on the surface high-energy X-ray diffraction technique applying photon energies above 60 keV at grazing incidence. In this way, reliable PDFs were extracted from films of thicknesses down to a few nanometres. Compared with recently published reports on thin-film PDF analysis from both transmission and grazing-incidence geometries, this work brought the minimum detectable film thickness down by about a factor of ten. Depending on the scattering power of the sample, the data acquisition on such ultrathin films can be completed within fractions of a second. Hence, the rapid-acquisition grazing-incidence PDF method is a major advancement in thin-film technology that opens unprecedented possibilities for in situ and operando PDF studies in complex sample environments. By uncovering how the structure of a layered material on a substrate evolves and transforms in terms of local and average ordering, this technique offers new opportunities for understanding processes such as nucleation, growth, morphology evolution, crystallization and the related kinetics on the atomic level and in real time.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Novel Geometric Operations for Linear Programming

This report summarizes the work performed under the project "Linear Programming in Strongly Polynomial Time." Linear programming (LP) is a classic combinatorial optimization problem heavily used directly and as an enabling subroutine in integer programming (IP). Specifically IP is the same as LP except that some solution variables must take integer values (e.g. to represent yes/no decisions). Together LP and IP have many applications in resource allocation including general logistics, and infrastructure design and vulnerability analysis. The project was motivated by the PI's recent success developing methods to efficiently sample Voronoi vertices (essentially finding nearest neighbors in high-dimensional point sets) in arbitrary dimension. His method seems applicable to exploring the high-dimensional convex feasible space of an LP problem. Although the project did not provably find a strongly-polynomial algorithm, it explored multiple algorithm classes. The new medial simplex algorithms may still lead to solvers with improved provable complexity. We describe medial simplex algorithms and some relevant structural/complexity results. We also designed a novel parallel LP algorithm based on our geometric insights and implemented it in the Spoke-LP code. A major part of the computational step is many independent vector dot products. Our parallel algorithm distributes the problem constraints across processors. Current commercial and high-quality free LP solvers require all problem details to fit onto a single processor or multicore. Our new algorithm might enable the solution of problems too large for any current LP solvers. We describe our new algorithm, give preliminary proof-of-concept experiments, and describe a new generator for arbitrarily large LP instances.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The evolution of analytical techniques for multiplex analysis of protein biomarkers

Introduction: The landscape of biomarker development has evolved with advanced analytical technologies, particularly affinity- and mass spectrometry-based techniques. These advancements have deepened our understanding of disease mechanisms, enabling the development of precise diagnostic tools and personalized medicine. Protein biomarkers, which play pivotal roles in biological processes, have become invaluable in diagnosing and monitoring diseases, aided by their presence in various biological samples and the availability of established detection methods. Areas covered: This review covers the role of protein biomarkers in clinical practice, the development and dimensionality of protein biomarkers, advancements in detection technologies, a comparison of these technologies, and future directions in biomarker discovery and disease mechanism elucidation. Expert opinion: Advances in biomarker technologies have the potential to transform diagnostics and personalized treatment but face challenges such as high costs and technical complexity. Enhancing reproducibility and integrating multi-omics approaches may offer better insights. In conclusion, the field should evolve toward high-throughput, automated methods, continuously adapting research, and clinical practices.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Gas-Phase Composition as a Predictive Metric for Calendar Life Behavior of Next-Generation Silicon Anodes

The expansion of renewable technologies and electrification of the transportation sector is driving increased demand for next-generation battery materials that provide higher power and energy density with superior cycling and calendar life stability. Silicon (Si) has a theoretical capacity nearly 10x that of graphite, and is therefore a promising anode material candidate to meet these rigorous performance demands. While leading Si anode battery demonstrations are approaching target metrics for cycle life, a series of complex and interrelated modes of reactivity lead to reduced calendar life and therefore challenge practical adoption of these materials. Deconvoluting the degradation processes that impact Si calendar life is critical to informing the rational and accelerated design of improved Si materials. In the present work, we employ novel sampling techniques and GC-MS-FID characterization to measure gas-phase composition during initial Si cycling, which we tie to selective mechanisms of Si passivation. We utilize a tiered analysis approach to identify and quantify the gas-phase reaction products associated with three advanced Si material candidates under practical operating conditions. Ex situ analysis of Si powders (pure chemical reactivity) is coupled with nondestructive in situ sampling of Si electrodes in a practical pouch-cell format (coupled chemical and electrochemical reactivity). We link the observed gas-phase species evolution to electrochemical behavior and measured calendar life of the three Si materials. Further, we evaluate the voltage-resolved evolution of gas-phase species for one such Si nanomaterial, where nonmonotonic gas generation implies competition between passivating reaction pathways. The measured gas-phase compositional data serves as a critical input for our advanced electrochemical SEI models to identify favorable vs unfavorable reaction pathways to stabilize Si. In addition to bolstering a fundamental understanding of Si reactivity, the present approach informs specific and quantifiable gas-phase metrics tied to calendar life improvements in Si, which can streamline and accelerate the process of next-generation material development.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗
DOE OSTI2022

Thin film combinatorial sputtering of Al-Ce alloys: Investigating the phase separation of as-deposited solid solutions and determining the coefficient of thermal expansion

Al x Ce 100–x thin films with a composition range of ~75.0 < x < 99.5 at% (36.5 < x < 97.5 wt%) were synthesized via combinatorial co-sputtering from an Al and an Al 50 Ce 50 target. The crystal structure, phase fraction, film morphology, electrical resistivity, and temperature-dependent coefficients of thermal expansion (CTE) are all correlated to the Al x Ce 100–x composition. The as-deposited films form a metastable solid-solution, and annealing leads to the formation of the thermodynamically stable two-phase system of Al and the α-Al 11 Ce 3 intermetallic. Temperature dependent x-ray diffraction (XRD) reveals that the two phases expand independently of one another, and the thin film Al temperature-dependent CTE is similar to bulk Al. The thin film Al 11 Ce 3 intermetallic phase has a nearly constant CTE of ~1.5 × 10 –5 /°C within the temperature range studied (25–550 °C). To confirm the thin film Al 11 Ce 3 results, bulk stoichiometric Al 11 Ce 3 and +/- 1 wt% Ce samples were prepared and the CTE of each was measured with the same conditions. A Rietveld analysis of the bulk data enabled an estimation of the CTE in each of the 3 orthorhombic lattice parameters, which displayed anisotropic behavior. The thin film and bulk CTE measurements were in very good agreement. Estimations of the temperature dependent CTE of the two-phase alloys are made via the Reuss and Voigt models. Finally, by demonstrating the efficacy of the approach, more complex multi-component rapid materials discovery of low CTE Al-alloys can be pursued via the combinatorial thin film synthesis and XRD measurement.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Material coherence from trajectories via Burau eigenanalysis of braids

In this paper, we provide a numerical tool to study a material’s coherence from a set of 2D Lagrangian trajectories sampling a dynamical system, i.e., from the motion of passive tracers. We show that eigenvectors of the Burau representation of a topological braid derived from the trajectories have levelsets corresponding to components of the Nielsen–Thurston decomposition of the dynamical system. One can thus detect and identify clusters of space–time trajectories corresponding to coherent regions of the dynamical system by solving an eigenvalue problem. Unlike previous methods, the scalable computational complexity of our braid-based approach allows the analysis of large amounts of trajectories.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Characterization of Pseudomonas aeruginosa and Acinetobacter calcoaceticus-baumannii complex traumatic wound isolates

Healing of traumatic wounds is complicated by infecting pathogens, with Pseudomonas aeruginosa and members of the Acinetobacter calcoaceticus-baumannii complex among the most common infectious agents. However, a full understanding of genotypic and phenotypic differences between circulating wound isolates is lacking. To address this, traumatic wounds were sampled at Emory University Hospital, and 24 isolates were characterized; we focused on P. aeruginosa and Acinetobacter due to their prevalence and tendency for antibiotic resistance. Even though these species are renowned for antibiotic resistance, only two of the tested isolates could be classified as multidrug resistant. Whole-genome sequencing and analysis revealed that isolates from different patients were genetically distinct; however, longitudinal isolates from the same patient were closely related and appeared to represent chronic colonization by the same strain. Phylogenetic analysis revealed that laboratory strains (PAO1 and AB5075) that were isolated decades previously and from different locations grouped closely to subsets of the recent wound isolates. Given the importance of biofilm formation in infection, the ability of the isolates to form biofilms was assessed; all isolates formed biofilms but showed temporal and magnitude differences. Analysis of a subset of isolates revealed that planktonic P. aeruginosa was resistant to human serum-mediated killing. While the same was true for the majority of Acinetobacter isolates, one showed planktonic sensitivity that was abrogated when grown in a biofilm. Taken together, these data reveal genotypic and phenotypic differences in circulating isolates of P. aeruginosa and A. baumannii.

Acinetobacter↗
DOE OSTI2021

Semi-supervised Bayesian Low-shot Learning

Deep neural networks (NNs) typically outperform traditional machine learning (ML) approaches for complicated, non-linear tasks. It is expected that deep learning (DL) should offer superior performance for the important non-proliferation task of predicting explosive device configuration based upon observed optical signature, a task which human experts struggle with. However, supervised machine learning is difficult to apply in this mission space because most recorded signatures are not associated with the corresponding device description, or “truth labels.” This is challenging for NNs, which traditionally require many samples for strong performance. Semi-supervised learning (SSL), low-shot learning (LSL), and uncertainty quantification (UQ) for NNs are emerging approaches that could bridge the mission gaps of few labels and rare samples of importance. NN explainability techniques are important in gaining insight into the inferential feature importance of such a complex model. In this work, SSL, LSL, and UQ are merged into a single framework, a significant technical hurdle not previously demonstrated. Exponential Average Adversarial Training (EAAT) and Pairwise Neural Networks (PNNs) are chosen as the SSL and LSL methods of choice. Permutation feature importance (PFI) for functional data is used to provide explainability via the Variable importance Explainable Elastic Shape Analysis (VEESA) pipeline. A variety of uncertainty quantification approaches are explored: Bayesian Neural Networks (BNNs), ensemble methods, concrete dropout, and evidential deep learning. Two final approaches, one utilizing ensemble methods and one utilizing evidential learning, are constructed and compared using a well-quantified synthetic 2D dataset along with the DIRSIG Megascene.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Quantum textures of the many-body wavefunctions in magic-angle graphene

Interactions among electrons create novel many-body quantum phases of matter with wavefunctions that often reflect electronic correlation effects, broken symmetries, and novel collective excitations. A wide range of quantum phases has been discovered in MATBG, including correlated insulating, unconventional superconducting, and magnetic topological phases. The lack of microscopic information, including precise knowledge of possible broken symmetries, has thus far hampered our understanding of MATBG's correlated phases. Here we use high-resolution scanning tunneling microscopy to directly probe the wavefunctions of the correlated phases in MATBG. The squares of the wavefunctions of gapped phases, including those of the correlated insulators, pseudogap, and superconducting phases, show distinct patterns of broken symmetry with a √3 x √3 super-periodicity on the graphene atomic lattice that has a complex spatial dependence on the moiré superlattice scale. We introduce a symmetry-based analysis to describe our measurements of the wavefunctions of MATBG's correlated phases with a set of complex-valued local order parameters. For the correlated insulators in MATBG, at fillings of ±2 electrons per moiré unit cell relative to charge neutrality, we compare the observed quantum textures to those expected for proposed theoretical ground states. In typical MATBG devices, the textures of correlated insulators' wavefunctions closely match those of the theoretically proposed IKS order, while in ultra-low-strain samples our data has local symmetries like those of a T-IVC phase. Here, we also study the wavefunction of MATBG's superconducting state, revealing strong signatures of intervalley coherence that can only be distinguished from those of the insulator with our phase-sensitive measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

East Tennessee Technology Park Biological Monitoring and Abatement Program 2024 Calendar Year Report

The East Tennessee Technology Park (ETTP) Biological Monitoring and Abatement Program (BMAP) consists of three tasks that reflect different but complementary approaches to evaluating the ecological integrity of waters near ETTP. These tasks include (1) bioaccumulation monitoring of fish and clams, (2) benthic macroinvertebrate species richness and density monitoring, and (3) fish community monitoring. The sampling and analysis requirements for the ETTP BMAP in calendar year 2024, covering in part both FY 2024 and FY 2025, are outlined in the respective FY sampling and analysis plans (UCOR 2023, 2024). Sampled water bodies and locations for the ETTP BMAP are shown in Figures 1 and 2. This ETTP BMAP report presents the CY 2024 results and provides context with results from previous years. The report also includes Oak Ridge National Laboratory (ORNL)–generated biological monitoring data collected for other US Department of Energy programs, including the UCOR Water Resources Restoration Program (WRRP) off-site fish bioaccumulation data (UCOR 2023) and select Y-12 National Security Complex (Y-12) BMAP fish bioaccumulation data. Historical data collected for the ETTP BMAP and other programs in the nearby Poplar Creek and Clinch River are provided where appropriate. This progress report provides an update on the biological monitoring activities supporting the ETTP UCOR Environmental Compliance organization, which sponsors the ETTP BMAP. In addition to this internal reporting, ETTP BMAP results are provided in the annual remediation effectiveness reports and the annual site environmental reports, both of which are publicly available. BMAP data are also available to the public via the Oak Ridge Environmental Information System (https://ucor.com/oak-ridge-environmental-information-system-oreis/).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Solute Redistribution During Aging in a Laser-Based Powder Bed Fusion-Produced Fe-18Ni-9Co-5Mo-Ti Maraging Steel

Solute distribution during the laser-based powder bed fusion of metals process is highly complex because of solidification. This study builds on a previous investigation of how solute heterogeneities across different scales influence phase distribution and aging physical phenomena in a Fe-18Ni-9Co-5Mo-Ti maraging steel (Santana et al. in Addit Manuf 104494, 2024). Previous work using energy-dispersive X-ray spectroscopy revealed heterogeneous Ni and Mo enrichment at intercellular regions. Using X-ray diffraction, 8 ± 3% retained austenite was quantified in as-built samples. Additionally, electron backscatter diffraction analysis exposed the location of retained austenite along cell boundaries. In this work, scanning transmission electron microscopy results revealed the presence of non-enriched retained austenite in the as-built condition. With increased aging temperature, Ni and Mo enrichment in austenite increased, especially at the austenite/martensite boundary. Solute diffusion was simulated in DICTRA Thermo-Calc® software to assess solute redistribution between the matrix and second phases and to comprehend whether elemental diffusion processes are interconnected. Three different scenarios were considered: (1) solute diffusion in the matrix; (2) diffusion with enriched austenite in the intercellular region; (3) diffusion with non-enriched austenite in the intercellular region. Results showed that Ni partitioning controls austenite growth and that boundary regions exhibit higher element enrichment than the core.

42 ENGINEERING↗
DOE OSTI2019

Advanced FIB-based Preparation of Cryogenically-prepared Specimens for APT Analysis

The utilization of the focused ion beam scanning electron microscope (FIB-SEM) has aided the application of Atom Probe Tomography (APT) to a continually-growing variety of materials, including soft biological materials. However, the regular application of APT to hydrated interfaces such as those found in biological and environmental materials is lacking in large part due to difficulties in specimen preparation under high and ultra-high vacuum conditions. Although a FIB-SEM based cryogenic specimen preparation approach offers a rational route to the preparation of such specimens for APT analysis, many practical aspects such as welding and limitations in the cryo stage manipulation makes it challenging for routine liftout of site-targeted specimens. In this work, we describe our recent efforts in the development of a site-specific liftout and attachment scheme for cryogenically cooled specimens involving a combination of redeposition and overcoating of organic and organometallic molecules, as shown in Fig. 1a-d for a cryogenically-frozen corroded glass sample containing a hydrated porous gel surface layer. Application of an annular milling pattern to the frozen specimens leads to a needle-shaped morphology necessary for APT analysis with the targeted water-ice filled porous corroded silicate glass region of interest near the apex. Using a custom shuttle device and environmental transfer hub at PNNL to facilitate environmentally-protected specimen transfer, APT analysis was applied to directly map, for the first time, a water/solid interface in 3D to reveal the complex nanoscale water-filled porous network of corroded glass. Application of this unique specimen preparation approach to biological specimens will also be discussed, as well as the application of a unique cryo nanomaniupulator with integrated gas injection system to enable controlled FIB-based welding under cryogenic temperatures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Bioactivity Profiling of Chemical Mixtures for Hazard Characterization

Abstract The assessment and regulation of chemical toxicity to protect human health and the environment are done one chemical at a time and seldom at environmentally relevant concentrations. However, chemicals are found in the environment as mixtures, and their toxicity is largely unknown. Understanding the hazard posed by chemicals within the mixture is critical to enforce protective measures. Here, we demonstrate the application of bioactivity profiling of environmental water samples using the sentinel and ecotoxicology model species Daphnia to reveal the biomolecular response induced by exposure to real-world mixtures. We exposed a Daphnia strain to 30 sampled waters of the Chaobai River and measured the gene expression response profiles. Using a multiblock correlation analysis, we establish correlations between chemical mixtures identified in 30 water samples with gene expression patterns induced by these chemical mixtures. We identified 80 metabolic pathways putatively activated by mixtures of inorganic ions, heavy metals, polycyclic aromatic hydrocarbons, industrial chemicals, and a set of biocides, pesticides, and pharmacologically active substances. Our data-driven approach discovered both known bioactivity signatures with previously described modes of action and new pathways linked to undiscovered potential hazards. This study demonstrates the feasibility of reducing the complexity of real-world mixture toxicity to characterize the biomolecular effects of a defined number of chemical components based on gene expression monitoring of the sentinel species Daphnia.

Engineering↗
DOE OSTI2018

Analysis and Distribution of Proppant Recovered from Fracture Faces in the HFTS Slant Core Drilled through a Stimulated Reservoir

Although sand proppant has been used since 1949 to increase efficacy of hydraulically fractured treatments by preventing fractures from closing after well depressurization, many questions remain regarding the behavior and distribution of proppant in the subsurface. To this end, we quantified the amount of recovered proppant in open fractures within a slant core drilled through hydraulically fractured Wolfcamp Shale. To improve understanding of hydraulic-fracture growth and patterns, we then addressed basic questions such as the following regarding proppant behavior in the subsurface: Is there variation along the length of the examined core? Is the proppant mainly found in hydraulic fractures, in reactivated natural fractures, or is it transported into drilling-induced fractures during recovery? Do the majority of proppant grains remain whole or tend to get crushed? To answer these questions, we collected all material from every open fracture (407 samples total) within ~600 ft of core. Samples consisted of drilling mud, aluminum shavings from the core barrel, shale and lithic fragments, calcite, and, potentially, sand proppant (95% plain and 5% colored resin-coated grains) pumped during the hydraulic fracturing of adjacent wells. We then washed, sieved into four size fractions, weighed, and imaged all samples for quantitative image analysis. Retrieved samples were labeled with respect to a master fracture database, where fractures were identified in the core and on CT scans of each 3-ft interval, allowing us to code them as either hydraulic, natural reactivated, or drilling/recovery-induced fractures. From this coding, we quantified the amount of proppant within each fracture, analyzed the distribution of grains among different fracture types, and traced base versus colored grains. Proppant packs 0.5–1 cm thick were found in two locations where there was complex fracture geometry, but fracture faces showed no evidence of proppant embedment. In situ sand patches were found on a few fracture faces, mostly in fractures near the proppant packs. Pumped proppant was 100 and 40/70 mesh (149–420 μm), and even though widespread grain crushing is not observed, the majority of recovered proppant ranges from 63 to 250 μm. The distribution of retrieved proppant, especially the larger retrieved sizes (250– >500 μm), mirrors the proximity of the slant core to the hydraulic fracture treatment wells. Hydraulic fracture samples contained variable amounts of proppant, and natural reactivated fractures sometimes contained more proppant than nearby hydraulic fractures, suggesting transference between fracture types in the subsurface. Regarding colored proppant, some colored sands occurred in discreet fractures, whereas other colors appeared to be mixed and widespread. Ultimately, all fractures contain at least some proppant, especially in the smallest size fractions; however, the extent to which the proppant was introduced during the core-drilling process is still unknown. Our study is one of the first attempts at physically recovering and quantifying injected proppant from parted fracture breaks within a stimulated reservoir, and the results are significant in terms of understanding propped fracture networks and predicting future proppant distribution during hydraulic fracturing.

Elliott, Sara↗
DOE OSTI2018

Aluminum Clad Spent Nuclear Fuel Task 4: Performance of Aluminum SNF in Dry Storage Experiment Test Plan

This document presents the activities to be performed in support of understanding the performance of aluminum spent nuclear fuel (ASNF) in dry storage. These activities will visually examine and acquire baseline samples of as-irradiated ATR fuel assembly components to determine fuel condition and the morphology of the aluminum oxyhydroxides present on the fuel external surfaces. Because the boehmite phase of oxyhydroxide is projected to be a significant contributor to radiolytic hydrogen production and general corrosion, being able to quantify its presence is of major importance to long term storage of aluminum spent nuclear fuel. Baseline samples will be taken from irradiated end adapters, removed from ATR SNF elements, stored in the ATR Canal. These will be transferred to Idaho National Laboratory (INL) Materials and Fuels Complex (MFC) to perform non-destructive and destructive testing to determine the degree of hydration of the wet-stored aluminum components prior to drying and air storage. Examination of the dry stored SNF at Idaho Nuclear Technology and Engineering Center (INTEC) in CPP-603 Irradiated Fuel Storage Facility (IFSF) will allow the opportunity to identify gross degradation and as conditions permit, sample the surface oxide on fueled and un-fueled portions of the stored assemblies. The information resulting from analysis of the ATR Canal samples will be used to support validation of surrogate samples prepared under Task 6, sample surrogate preparation, and used in Task 1, oxyhydroxide layer behavior and chemistry, Task 2, oxide layer radiolytic gas generation, and Task 5, oxide layer response to drying. Surface oxide samples collected from SNF in IFSF dry storage will SNF dry storage prediction modeling from Task 3, sealed and vented system episodic breathing and gas generation prediction.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Comparing Sensor Fusion and Multimodal Chemometric Models for Monitoring U(VI) in Complex Environments Representative of Irradiated Nuclear Fuel

Optical sensors and chemometric models were leveraged for the quantification of uranium(VI) (0–100 μg mL –1 ), europium (0–150 μg mL –1 ), samarium (0–250 μg mL –1 ), praseodymium (0–350 μg mL –1 ), neodymium (0–1000 μg mL –1 ), and HNO 3 (2–4 M) with varying corrosion product (iron, nickel, and chromium) levels using laser fluorescence, Raman scattering, and ultraviolet–visible–near-infrared absorption spectra. In this paper, an efficient approach to developing and evaluating tens of thousands of partial least-squares regression (PLSR) models, built from fused optical spectra or multimodal acquisitions, is discussed. Each PLSR model was optimized with unique preprocessing combinations, and features were selected using genetic algorithm filters. The 7-factor D-optimal design training set contained just 55 samples to minimize the number of samples. The performance of PLSR models was evaluated by using an automated latent variable selection script. PLS1 regression models tailored to each species outperformed a global PLS2 model. PLS1 models built using fused spectra data and a multimodal (i.e., analyzed separately) approach yielded similar information, resulting in percent root-mean-square error of prediction values of 0.9–5.7% for the seven factors. Further, the optical techniques and data processing strategies established in this study allow for the direct analysis of numerous species without measuring luminescence lifetimes or relying on a standard addition approach, making it optimal for near-real-time, in situ measurements. Nuclear reactor modeling helped bound training set conditions and identified elemental ratios of lanthanide fission products to characterize the burnup of irradiated nuclear fuel. Leveraging fluorescence, spectrophotometry, experimental design, and chemometrics can enable the remote quantification and characterization of complex systems with numerous species, monitor system performance, help identify the source of materials, and enable rapid high-throughput experiments in a variety of industrial processes and fundamental studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

A Ricin Forensic Profiling Approach Based on a Complex Set of Biomarkers

A forensic method for the retrospective determination of preparation methods used for illicit ricin toxin production was developed. The method was based on a complex set of biomarkers, including carbohydrates, fatty acids, seed storage proteins, in combination with data on ricin and Ricinus communis agglutinin. The analyses were performed on samples prepared from four castor bean plant ( Ricinus communis ) cultivars by four different sample preparation methods (PM1 – PM4) ranging from simple disintegration of the castor beans to multi-step preparation methods including different protein precipitation methods. Comprehensive analytical data was collected by use of a range of analytical methods and robust orthogonal partial least squares-discriminant analysis- models (OPLS-DA) were constructed based on the calibration set. By the use of a decision tree and two OPLS-DA models, the sample preparation methods of a test set of ricin preparations were determined. The model statistics of the two models were good and a 100% rate of correct predictions of the test set was achieved.

Fredriksson, Sten-Åke (ORCID:0000000237131990)↗