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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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At least 37 records · Page 2

Visualizing the Nanoscale Oxygen and Cation Transport Mechanisms during the Early Stages of Oxidation of Fe–Cr–Ni Alloy Using In Situ Atom Probe Tomography

Abstract Understanding the early stages of interactions between oxygen and material surfaces—especially at very high spatial resolutions—is highly beneficial for fields ranging from materials degradation, corrosion, geological sciences, forensics, and catalysis. The ability of in situ atom probe tomography (APT) is demonstrated to track the diffusion of oxygen and metal ions at nanoscale spatial resolution during the early stages of oxidation of a model Fe–Cr–Ni alloy. Using 18 O isotope tracers in these in situ APT experiments and complementary ex situ multimodal microscopy, spectroscopy, and computational simulations allows to precisely analyze the kinetics of oxidation and determine that outward cation diffusion to oxide/air interface is the primary mechanism for intragranular oxide growth in this alloy at 300 °C. This unique in situ isotopic tracer APT approach and the insights gained can be highly beneficial for studying early stages of gas–surface reactions in a broad array of materials.

36 MATERIALS SCIENCE↗

Evaluation of polyanionic cyclodextrins as high affinity binding scaffolds for fentanyl

Abstract Cyclodextrins (CDs) have been previously shown to display modest equilibrium binding affinities ( K a ~ 100–200 M -1 ) for the synthetic opioid analgesic fentanyl. In this work, we describe the synthesis of new CDs possessing extended thioalkylcarboxyl or thioalkylhydroxyl moieties and assess their binding affinity towards fentanyl hydrochloride. The optimal CD studied displays a remarkable affinity for the opioid of K a = 66,500 M −1 , the largest value reported for such an inclusion complex to date. One dimensional 1 H Nuclear Magnetic Resonance (NMR) as well as Rotational Frame Overhauser Spectroscopy (2D-ROESY) experiments supported by molecular dynamics (MD) simulations suggest an unexpected binding behavior, with fentanyl able to bind the CD interior in one of two distinct orientations. Binding energies derived from the MD simulations work correlate strongly with NMR-derived affinities highlighting its utility as a predictive tool for CD candidate optimization. The performance of these host molecules portends their utility as platforms for medical countermeasures for opioid exposure, as biosensors, and in other forensic science applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Use of carbonyldiimidazole as a derivatization agent for the detection of pinacolyl alcohol, a forensic marker for Soman, by EI-GC–MS and LC-HRMS in official OPCW proficiency test matrices

Pinacolyl alcohol (PA), a key forensic marker for the nerve agent Soman (GD), is a particularly difficult analyte to detect by various analytical methods. In this work, we have explored the reaction between PA and 1,1'-carbonyldiimidazole (CDI) to yield pinacolyl 1H-imidazole-1-carboxylate (PIC), a product that can be conveniently detected by gas chromatography–mass spectrometry (GC–MS) and liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Regarding its GC–MS profile, this new carbamate derivative of PA possesses favorable chromatographic features such as a sharp peak and a longer retention time (RT = 16.62 min) relative to PA (broad peak and short retention time, RT = 4.1 min). Additionally, the derivative can also be detected by LC-HRMS, providing an avenue for the analysis of this chemical using this technique where PA is virtually undetectable unless present in large concentrations. From a forensic science standpoint, detection of this low molecular weight alcohol signals the past or latent presence of the nerve agent Soman (GD) in a given matrix (i.e., environmental or biological). The efficiency of the protocol was tested separately in the analysis and detection of PA by EI-GC–MS and LC-HRMS when present at a 10 μg/mL in a soil matrix featured in the 44th PT and in a glycerol-rich liquid matrix featured in the 48th Official Organization for the Prohibition of Chemical Weapons (OPCW) Proficiency Test when present at a 5 μg/mL concentration. In both scenarios, PA was successfully transformed into PIC, establishing the protocol as an additional tool for the analysis of this unnatural and unique nerve agent marker by GC–MS and LC-HRMS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Durable Module Materials (DuraMAT) Consortium (Final Technical Report)

The DuraMAT Consortium brings together DOE national lab and university research capabilities with the photovoltaic (PV) and supply-chain industries to accelerate a sustainable, just, and equitable transition to zero carbon electricity generation by 2035 through our five core objectives: development of a central data resource for PV modules, multi-scale and multi-physics modeling, disruptive acceleration science, forensic tools for fielded modules, and materials solutions for more durable, reliable, and resilient modules.

14 SOLAR ENERGY↗

Explainable Machine Learning for Functional Data

Black-box machine learning models are recognized as useful tools for prediction applications, but the algorithmic complexity of some models causes interpretation challenges. Explainability methods have been proposed to provide insight into these models, but there is little research focused on supervised modeling with functional data inputs. We argue that, especially in applications of high consequence, it is important to explicitly model the functional dependence in a black-box analysis to not obscure or misrepresent patterns in explanations. As such, we propose the V ariable importance E xplainable E lastic S hape A nalysis (VEESA) pipeline for training supervised machine learning models with functional inputs. The pipeline is an analysis process that includes the data preprocessing, modeling, and post-hoc explanations. The preprocessing is done using elastic functional principal components analysis, which accounts for vertical and horizontal variability in functional data and, ultimately, allows for explanations in the original data space that identify the important functional variability without bias due to correlated variables. Here, we demonstrate the pipeline on two high-consequence applications: explosives classification for national security and inkjet printer identification in forensic science. The applications exhibit the VEESA pipeline’s ability to provide an understanding of the characteristics of the functional data useful for prediction. Code for implementing the pipeline is available in the veesa R package (and supplemental python code).

Elastic Shape Analysis↗

NEAR Gamma Ray Spectrometer Characterization and Repair

This report covers the work completed in the third year of the contract. The principle activities during this period were (1) the characterization of the NEAR 2 Gamma Ray Spectrometer using a neutron generator to generate complex gamma ray spectra and a large Ge Detecter to identify all the major peaks in the spectra; (2) the evaluation and repair of the Engineering Model Unit of the Gamma Ray Spectrometer for the NEAR mission; (3) the investigation of polycapillary x-ray optics for x-ray detection; and (4) technology transfer from NASA to forensic science.

Groves, Joel Lee↗

Versatile Vials

Advanced Fuel Research, Inc. (AFR) developed a new sol-gel material coating for sample vials to be used in surface-enhanced Raman (SER) spectroscopy. In the fields of biomedical and forensic science, the coated vials are used to identify physiological chemicals present in blood and urine. The vials are used in the pharmaceutical industry in the area of drug development and discovery. In the drug enforcement field, using the vials helps with detection of trace amounts of drugs on surfaces. The SER vials will also help to identify contaminants in water sources, such as various inorganics and pesticides. The new vials have advantages over other SER materials. Former products required that samples be pre-mixed or dissolved into specific solvents or reagents. The SER vials do not have these limitations, and measurements can be performed using any solvent. Furthermore, the signal appears in less than one second. The sol-gel material will stay active for at least one year and the vials are compatible with any Raman spectrometer. Most importantly, the SER activity can be duplicated from vial-to-vial, allowing for reproducible results.

Source record↗

Twenty Years of Collaborative Materials Exercises by the Nuclear Forensics International Technical Working Group

The Collaborative Materials Exercise (CMX) series are a critical mechanism used to advance the ITWG's mission of identifying, developing and promoting the best practices of nuclear forensics. These exercises are not designed to test laboratory performance, but as learning experiences that provide opportunities for participants to test and demonstrate state-of-the-practice to the global scientific and law enforcement communities. They are run as mock nuclear forensic investigations under realistic scenarios, with timelines and conditions designed to mimic actual operations. These situations provide the relatively unique opportunity for the appropriate governmental agencies to exercise their collective response to a nuclear security incident. Utilizing well-characterized materials of a known history and origin that are taken from specific process locations within the nuclear fuel cycle, these 'real world' materials are used to fully consider the potential significance of process-derived heterogeneities and characteristics that might be used by investigators to derive useful information such as intended use, point of loss of control, process history or origin. While individual laboratory results are kept confidential, a summary of the major outcomes of each exercise is published in the open literature. The ITWG has carried out six CMXs since 1999. The sixth (CMX-6) and largest (21 participants) was completed in June 2019. Each CMX has contributed demonstrably to advancements in the state of practice and the emergence of novel techniques in nuclear forensic science.

Schwantes, Jon M.↗

RIMS analysis of isotopically tagged uranium particles with application to Intentional Forensics

Traditional nuclear forensics approaches leverage isotopic measurements for characterizing nuclear forensics signatures in fuel cycle materials. To aid in provenance assessment, isotopically perturbed transition metal taggants can be added to fuel cycle materials. We present a case study for examining natural uranium oxide powder that was tagged with isotopically perturbed Mo before and after irradiation using resonance ionization mass spectrometry. In conclusion, this method accurately and precisely measures taggant and uranium compositions, rapidly enabling the ability to clearly discriminate between tagged particles and other material with application for robust assessment of material provenance.

Forensic Anthropology↗

Predicting U 3 O 8 powder processing conditions: An AI/ML approach analyzing deep learning embeddings of SEM micrographs

High-resolution SEM images of uranium-oxide powders encode micro- and nanoscale clues to their synthesis route and calcination temperature. We trained a ResNet-50 model on 11 commercial-scale U₃O₈ classes, ammonium diuranate (ADU) or uranyl peroxide (H₂O₂) precursors calcined at temperatures ranging from 400 to 750 °C and added a 256-D projection head before the classifier to analyze the learned representation. The best of eight seeds reached 92.4 % accuracy on reserved testing data, but our focus is the structure of the embedding space rather than the accuracy and labels. We quantify class relatedness in the original 256-D space using centroid similarity and distributional distances, and we use Uniform Manifold Approximation Projection (UMAP) for visualization. ‘Unknown’ images from different preparation methods, SEM operators, and from the literature localized near the expected classes under a nearest-centroid analysis without retraining, as well as clustered in similar UMAP space. In conclusion, this embedding-centered workflow complements black-box classification by providing quantitative, similarity-based comparisons of U₃O₈ morphologies and reduces storage space by up to 98 % for image data used in millisecond vector search comparisons.

36 MATERIALS SCIENCE↗

Applications in Forensic Proteomics: Protein Identification and Profiling. ACS Symposium Series

Proteomics is a mature research tool in the life sciences, and it can be a powerful addition to the forensic science toolbox. This work presents several areas in which proteomics was used to answer forensic questions. Illustrating current applications of proteomics methods, this work introduces opportunities for proteomics to answer compelling questions in forensic science and biosecurity. These "case studies" will be valuable to both practicing forensic scientists and researchers developing proteomics methods.

proteomics, forensics, mass spectrometry, toxins, ↗

Advancing nuclear forensics competencies at the National Nuclear Center of the Republic of Kazakhstan and conceptual development of a National Nuclear Forensics Library

Since 2021, the National Nuclear Center (NNC) of the Republic of Kazakhstan has been successfully developing a project dedicated to nuclear forensics. The relevance of this project is underscored by Kazakhstan’s leading position in the global uranium mining and export market. The country operates research reactors and is involved in the production of experimental nuclear fuel. The nuclear forensics project is being implemented in several key areas: the project will develop competencies in laboratory research of samples, interpretation of results, and develop a prototype concept for the National Nuclear Forensics Library. In implementing these challenges, the NNC experts draw on the experience of colleagues from world-leading scientific and research centers. Designing a prototype National Nuclear Forensics Library (NNFL) is a challenging project. In conclusion, the solution to this task is based on the IAEA’s approaches, recommendations, and the experience gained from the construction of similar systems in other countries.

and nuclear chemistry↗

NACS 2022 FRIB Investment Strategy

The Facility for Rare Isotope Beams (FRIB) that will begin operations later this year will vastly increase the number of unstable isotopes available for experiments that, together with new theoretical developments will expand our understanding of nuclear structure and nuclear reactions that produce the elements of the periodic table and power the cosmos. The knowledge and understanding gained from FRIB will benefit a variety of applications including stockpile science, nuclear forensics, nonproliferation, nuclear energy, and nuclear medicine. LLNL is actively involved in a variety of basic and applied science activities related to FRIB. These activities are listed below and documented in the following sections: 1. FRIB Decay Station, 2. Isotope Harvesting, 3. Direct Reactions, 4. Surrogate Reactions, 5. Nuclear Structure and Collectivity, 6. Nuclear Fission, and 7. Nuclear Theory.

07 ISOTOPE AND RADIATION SOURCES↗

MARLOWE: An Untargeted Proteomics, Statistical Approach to Taxonomic Classification for Forensics

General proteomics research for fundamental science typically addresses laboratory- or patient-derived samples of known origin and composition. However, in a few research areas, such as environmental proteomics, clinical identification of infectious organisms, archeology, art/cultural history, and forensics, attributing the origin of a protein-containing sample to the organisms that produced it is a central focus. A small number of groups have approached this problem and developed software tools for taxonomic characterization and/or identification using bottom-up proteomics. Most such tools identify peptides via database search, and many rely on organism-specific peptides as markers. Our group recently introduced MARLOWE, a software tool for taxonomic characterization of unknown samples based on de novo peptide identification and signal-erosion-resistant strong peptides, which are shared peptides distributed in a taxonomy-dependent manner. In the current work, we further characterize the utility of MARLOWE using publicly available proteomics data from forensically-relevant samples. MARLOWE characterizes samples based on their protein profile, and returns ranked organism lists of potential contributors and taxonomic scores based on shared strong peptides between organisms. Overall, the correct characterization rate ranges between 44 and 100%, depending on the sample type and data acquisition parameters (with lower numbers associated with lower-quality data sets). MARLOWE demonstrates successful characterization of true contributors and close relatives, and provides sufficient specificity to distinguish certain microbial species. MARLOWE demonstrates its ability to provide insight into potential taxonomic sources for a wide range of sample types without prior assumptions about sample contents. As a result, this approach can find utility in forensic science and also broadly in bioanalytical applications that utilize proteomics approaches for taxonomic characterization.

Bacteria↗

Interlaboratory comparison of secondary ion mass spectrometry analysis results from the 7th international technical nuclear forensics working group collaborative material exercise

A review and interlaboratory comparison of secondary ion mass spectrometry (SIMS) data obtained by laboratories participating in the International Technical Nuclear Forensics Working Group (ITWG) 7th Collaborative Material Exercise (CMX-7) has been conducted. The analyzed materials were two uranium compounds in powder form and two pieces of uranium metal. The instruments used in this comparison were a small-geometry (SG) SIMS, CAMECA IMS 7f from the Research Centre Rez, and a large-geometry (LG) SIMS, CAMECA IMS 1280 from Los Alamos National Laboratory. Despite the differences in instruments and analytical procedures, e.g., sample preparation, SIMS setups, and data post-processing, there was good agreement for the 234 U/ 238 U, 235 U/ 238 U, and 236 U/ 238 U ratios in the analyzed materials. The main difference was in the precision, which was, as expected, higher for the LG-SIMS. In addition, a comparison between the laboratories was also made for the image processing algorithms applied to raw data acquired in automated particle measurement (APM) mode. In conclusion, the result of this comparison has led to identification of best practices for setting up parameters of the APM software.

and nuclear chemistry↗

Bayesian Statistical Analysis for Mass Spectrometric Data Processing

• Thermal ionization mass spectrometry (TIMS) is a “gold standard’ technique for actinide isotope amount ratio and assay measurements. • Ubiquitously used in: • Nuclear Nonproliferation • Nuclear Safeguards • Nuclear Forensics • Basic Science • Savannah River National Laboratory (SRNL) installed a new Thermo Scientific TRITON Plus TIMS in early 2024.

McLarty, Ellis C. [Savannah River National Laborat↗

Bayesian Statistical Analysis for Mass Spectrometric Data Processing

Thermal ionization mass spectrometry (TIMS) is a “gold standard’ technique for actinide isotope amount ratio and assay measurements. • Ubiquitously used in: • Nuclear Nonproliferation • Nuclear Safeguards • Nuclear Forensics • Basic Science • Savannah River National Laboratory (SRNL) installed a new Thermo Scientific TRITON Plus TIMS in early 2024.

McLarty, Ellis C. [Savannah River National Laborat↗