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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

In-situ Synthesis of PuCl 3 and Corresponding Raman and Density Functional Theory Vibrational Modes

The experimental and calculated Raman spectrum of PuCl 3 has been reported for the first time. PuCl 3 is a primary species found in plutonium metal refinement, specifically in pyrochemical salt processes including multicycle direct oxide reduction, metal chlorination, and electrorefining. As such, Raman signatures of PuCl 3 could serve as potential forensic indicators of material process history. A novel technique for synthesizing PuCl 3 from the in-situ chlorination of plutonium metal with HCl was developed to establish these signatures. Cerium metal surrogates were utilized to ensure optimization of the plutonium experiments and to minimize personnel exposure, and all experiments were carried out in a Raman reaction chamber designed for air-tight, high vacuum environments. In-situ Raman spectroscopy was employed in conjunction with Density Functional Theory (DFT) to investigate the vibrational modes of PuCl 3 . Associated mixed oxy and hydroxyl phases are also reported. The combined Raman and DFT results have eliminated inconsistencies in Raman mode assignments for the MX 3 family of metal chlorides having P6 3 /m symmetry, and IR modes derived from the DFT calculations are additionally presented. The data observed in this study is of potential interest to nuclear forensic analyses, nuclear sample aging, nuclear energy, plutonium processing, and stockpile stewardship.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Comparing multiple statistical methods for inverse prediction in nuclear forensics applications

Forensic science seeks to predict source characteristics using measured observables. Statistically, this objective can be thought of as an inverse problem where interest is in the unknown source characteristics or factors ( X ) of some underlying causal model producing the observables or responses (Y = g ( X ) + error ). Here, this paper reviews several statistical methods for use in inverse problems and demonstrates that comparing results from multiple methods can be used to assess predictive capability. Motivation for assessing inverse predictions comes from the desired application to historical and future experiments involving nuclear material production for forensics research in which inverse predictions, along with an assessment of predictive capability, are desired.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

High-Activity Microscopic Nuclear-Sourced Particles to Investigate Nuclear Release Scenarios - 18026

Advances in microscopy and materials analysis have allowed for the study of materials at resolutions not previously attainable a decade ago. Such information extends to not only their existence, but also their composition, the likely source term and if applicable, their short or long-term environmental stability. This work describes the analysis undertaken on the larger 'ejecta' type of particulate collected following the INES Level 7 incident at the Fukushima Daiichi Nuclear Power Plant in March 2011. However, the methods and procedures employed during this work, on material with enormously contrasting characteristics, have far wider applications within nuclear forensics, safeguards, security and material compliance. Resulting from the analysis of micron-scale 'atmospheric' material in previous works have been able to derive information relating to the emission and subsequent transportation characteristics of the release event, as well as determining the local-scale impacts of this radioactive fallout. This analysis of the larger-scale (100's of micron) 'ejecta' material, collected from closer to the plant, has been able to reveal details pertaining to the specific in-reactor conditions at the time of the release as well as the nature of the explosion events. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Nuclear forensics of a non-traditional sample: Neptunium

Recent nuclear forensics cases have focused primarily on plutonium (Pu) and uranium (U) materials. By definition however, nuclear forensics can apply to any diverted nuclear material. This includes neptunium (Np), an internationally safeguarded material like Pu and U, that could offer a nuclear security concern if significant quantities were found outside of regulatory control. This case study couples scanning electron microscopy (SEM) with quantitative analysis using newly developed specialized software, to evaluate a non-traditional nuclear forensic sample of Np. Here, the results of the morphological analyses were compared with another Np sample of known pedigree, as well as other traditional actinide materials in order to determine potential processing and point-of-origin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Nd and Sm isotopic composition of spent nuclear fuels from three material test reactors

Rare earth elements such as neodymium and samarium are ideal for probing the neutron environment that spent nuclear fuels are exposed to in nuclear reactors. The large number of stable isotopes can provide distinct isotopic signatures for differentiating the source material for nuclear forensic investigations. The rare-earth elements were isolated from the high activity fuel matrix via ion exchange chromatography in a shielded cell. The individual elements were then separated using cation exchange chromatography. In conclusion, the neodymium and samarium aliquots were analyzed via MC–ICP–MS, resulting in isotopic compositions with a precision of 0.01–0.3%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Chemometrics and visible diffuse reflectance spectroscopy to classify plutonium dioxide

Diffuse reflectance (DR) spectra in the Vis-NIR (∼380–1050 nm) region were acquired for a series of PuO 2 samples with a spot size of about 10 × 10 μm. Two batches of six PuO 2 samples, synthesized approximately 7.5 months apart, were prepared using both Pu(III) and Pu(IV) oxalate precursors at three distinct calcination temperatures (450, 650, and 950 °C). This yielded a total of 12 PuO 2 samples and 433 DR spectra. The DR spectrum of PuO 2 contained numerous peaks in the visible region, and characteristic features were identified with respect to calcination temperature and chemistry. A distinct peak multiplet near 615 nm was observed for samples prepared at low calcination temperatures, and a peak near 660 nm was observed for higher calcination temperatures. A multivariate classification strategy based on principal component analysis (PCA) was developed to distinguish PuO 2 calcination temperatures of 450, 650, and 950 °C with 100 % accuracy. Classification results also indicate the potential to distinguish chemical processing history (i.e., Pu(III) or Pu(IV)) based on the spectra with 72 % accuracy based on k-nearest neighbors applied to the PCA scores. Partial least squares discriminant analysis was used to identify variation among batches with 88 % accuracy and found that peaks near 669, 681, 811, and 970 nm were the most useful for predicting the batch identity. Here, this work demonstrates how micro-diffuse reflectance spectroscopy and chemometrics can be used to classify PuO 2 processing history based on Vis-NIR spectral features. Combining the chemometric approach with mapping sequences could provide a rapid, nondestructive approach to classify Pu oxide materials for environmental, forensics, and nonproliferation applications.

Actinide↗
DOE OSTI2016

Livermore Accelerator Source for Radionuclide Science (LASRS)

The Livermore Accelerator Source for Radionuclide Science (LASRS) will generate intense photon and neutron beams to address important gaps in the study of radionuclide science that directly impact Stockpile Stewardship, Nuclear Forensics, and Nuclear Material Detection. The co-location of MeV-scale neutral and photon sources with radiochemical analytics provides a unique facility to meet current and future challenges in nuclear security and nuclear science.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Structuring Cooperative Nuclear RIsk Reduction Initiatives with China.

The Stanford Center for International Security and Cooperation engaged several Chinese nuclear organizations in cooperative research that focused on responses to radiological and nuclear terrorism. The objective was to identify joint research initiatives to reduce the global dangers of such threats and to pursue initial technical collaborations in several high priority areas. Initiatives were identified in three primary research areas: 1) detection and interdiction of smuggled nuclear materials; 2) nuclear forensics; and 3) radiological (“dirty bomb”) threats and countermeasures. Initial work emphasized the application of systems and risk analysis tools, which proved effective in structuring the collaborations. The extensive engagements between national security nuclear experts in China and the U.S. during the research strengthened professional relationships between these important communities.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS2016

Electric Potential and Electric Field Imaging with Applications

The technology and techniques for remote quantitative imaging of electrostatic potentials and electrostatic fields in and around objects and in free space is presented. Electric field imaging (EFI) technology may be applied to characterize intrinsic or existing electric potentials and electric fields, or an externally generated electrostatic field may be used for (illuminating) volumes to be inspected with EFI. The baseline sensor technology, electric field sensor (e-sensor), and its construction, optional electric field generation (quasistatic generator), and current e-sensor enhancements (ephemeral e-sensor) are discussed. Demonstrations for structural, electronic, human, and memory applications are shown. This new EFI capability is demonstrated to reveal characterization of electric charge distribution, creating a new field of study that embraces areas of interest including electrostatic discharge mitigation, crime scene forensics, design and materials selection for advanced sensors, dielectric morphology of structures, inspection of containers, inspection for hidden objects, tether integrity, organic molecular memory, and medical diagnostic and treatment efficacy applications such as cardiac polarization wave propagation and electromyography imaging.

Generazio, Ed↗
NASA NTRS2017

Electric Potential and Electric Field Imaging with Dynamic Applications: 2017 Research Award Innovation

The technology and methods for remote quantitative imaging of electrostatic potentials and electrostatic fields in and around objects and in free space is presented. Electric field imaging (EFI) technology may be applied to characterize intrinsic or existing electric potentials and electric fields, or an externally generated electrostatic field may be used for illuminating volumes to be inspected with EFI. The baseline sensor technology (e-Sensor) and its construction, optional electric field generation (quasi-static generator), and current e- Sensor enhancements (ephemeral e-Sensor) are discussed. Critical design elements of current linear and real-time two-dimensional (2D) measurement systems are highlighted, and the development of a three dimensional (3D) EFI system is presented. Demonstrations for structural, electronic, human, and memory applications are shown. Recent work demonstrates that phonons may be used to create and annihilate electric dipoles within structures. Phonon induced dipoles are ephemeral and their polarization, strength, and location may be quantitatively characterized by EFI providing a new subsurface Phonon-EFI imaging technology. Initial results from real-time imaging of combustion and ion flow, and their measurement complications, will be discussed. These new EFI capabilities are demonstrated to characterize electric charge distribution creating a new field of study embracing areas of interest including electrostatic discharge (ESD) mitigation, crime scene forensics, design and materials selection for advanced sensors, combustion science, on-orbit space potential, container inspection, remote characterization of electronic circuits and level of activation, dielectric morphology of structures, tether integrity, organic molecular memory, atmospheric science, and medical diagnostic and treatment efficacy applications such as cardiac polarization wave propagation and electromyography imaging.

Generazio, Ed↗
DOE OSTI2016

Final Report on Small Particle Speciation for Forensics Analysis by Soft X-ray Scanning Transmission X-ray Microscopy

Materials of interest for nuclear forensic science are often highly heterogeneous, containing complex mixtures of actinide compounds in a wide variety of matrices. Scanning transmission X-ray microscopy (STXM) is ideally suited to study such materials, as it can be used to chemically image specimens by acquiring X-ray absorption near-edge spectroscopy (XANES) data with 25 nm spatial resolution. In particular, STXM in the soft X-ray synchrotron radiation regime (approximately 120 – 2000 eV) can collect spectroscopic information from the actinides and light elements in a single experiment. Thus, STXM combines the chemical sensitivity of X-ray absorption spectroscopy with high spatial resolution in a single non-destructive characterization method. This report describes the application of STXM to a broad range of nuclear materials. Where possible, the spectroscopic images obtained by STXM are compared with information derived from other analytical methods, and used to make inferences about the process history of each material. STXM measurements can yield information including the morphology of a sample, “elemental maps” showing the spatial distribution of major chemical constituents, and XANES spectra from localized regions of a sample, which may show spatial variations in chemical composition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Protein-based forensic identification using genetically variant peptides in human bone

Bone tissue contains organic material that is useful for forensic investigations and may contain preserved endogenous protein that can persist in the environment for extended periods of time over a range of conditions. Single amino acid polymorphisms in these proteins reflect genetic information since they result from non-synonymous single nucleotide polymorphisms (SNPs) in DNA. Detection of genetically variant peptides (GVPs) — those peptides that contain amino acid polymorphisms — in digests of bone proteins allows for the corresponding SNP alleles to be inferred. Resulting genetic profiles can be used to calculate statistical measures of association between a bone sample and an individual. In this study proteomic analysis on rib cortical bone samples from 10 recently deceased individuals demonstrates this concept. A straight-forward acidic demineralization protocol yielded proteins that were digested with trypsin. Tryptic digests were analyzed by liquid chromatography mass spectrometry. A total of 1736 different proteins were identified across all resulting datasets. On average, individual samples contained 454 ± 121 ($\bar{x}$ ± σ) proteins. Thirty-five genetically variant peptides were identified from 15 observed proteins. Overall, 134 SNP inferences were made based on proteomically detected GVPs, which were confirmed by sequencing of subject DNA. Inferred individual SNP genetic profiles ranged in random match probability (RMP) from 1/6 to 1/42,472 when calculated with European population frequencies in the 1000 Genomes Project, Phase 3. Similarly, RMPs based on African population frequencies were calculated for each SNP genetic profile and likelihood ratios (LR) were obtained by dividing each European RMP by the corresponding African RMP. In conclusion, resulting LR values ranged from 1.4 to 825 with a median value of 16. GVP markers offer a basis for the identification of compromised skeletal remains independent of the presence of DNA template.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

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↗
DOE OSTI2018

A composite position independent monitor of reactor fuel irradiation using Pu, Cs, and Ba isotope ratios

When post-irradiation materials from the nuclear fuel cycle are released to the environment, certain isotopes of actinides and fission products carry signatures of irradiation history that can potentially aid a nuclear forensic investigation into the material's provenance. In this study, combinations of Pu, Cs, and Ba isotope ratios that produce position (in the reactor core) independent monitors of irradiation history in spent light water reactor fuel are identified and explored. These position independent monitors (PIMs) are modeled for various irradiation scenarios using automated depletion codes as well as ordinary differential equation solutions to approximate nuclear physics models. Experimental validation was performed using irradiated low enriched uranium oxide fuel from a light water reactor, which was sampled at 8 axial positions from a single rod. Plutonium, barium and cesium were chemically separated and isotope ratio measurements of the separated solutions were made by quadrupole and multi-collector inductively coupled mass spectrometry (Cs and Pu, respectively) and thermal ionization mass spectrometry (Ba). The effect of axial variations in neutron fluence and energy spectrum are evident in the measured isotope ratios. Furthermore, two versions of a combined Pu and Cs based PIM are developed. A linear PIM model, which can be used to solve for irradiation time is found to work well for natural U fuel with <10% 240 Pu and known or short cooling times. A non-linear PIM model, which cannot be solved explicitly for irradiation time without additional information, can nonetheless still group samples by irradiation history, including high burnup LEU fuel with unknown cooling time. 137 Ba/ 138 Ba is also observed to act as a position independent monitor; it is nearly single valued across the sampled fuel rod, indicating that samples sharing an irradiation history (same irradiation time and cooling time) in a reactor despite experiencing different neutron fluxes will have a common 137 Ba/ 138 Ba ratio. Modeling of this Ba PIM shows it increases monotonically with irradiation and cooling time, and a confirmatory first order analytical solution is also presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Nuclear Forensics

Nuclear forensics is a key part of the nuclear security strategy for the United States and the international community. The NACS Division is central to the leadership role that LLNL has had in nuclear forensics over the past 25 years. Our current nuclear forensic program includes conducting R&D on provenance and attribution signatures, collaborating with international partners, training the next generation of nuclear forensic experts, developing test materials for verification and validation exercises, and providing expert advice to national and international policy makers. Key to our success in these areas has been the strong and continuing involvement in nuclear forensic casework obtained through law enforcement and intelligence channels as well as our outstanding analytical capabilities. NACS must continue to conduct forward-thinking R&D in nuclear forensics that supports operational programs and addresses intelligence gaps. To maintain leadership in nuclear forensics, we must attract, develop, and retain the best talent. The NNSA has a central leadership role in developing educational initiatives for nuclear forensics. In concert with the Glenn T. Seaborg Institute, the NACS Division will continue to participate in all nuclear forensic educational initiatives (undergraduate, graduate, postdoctoral) and incorporate LLNL’s D&I vision into its student and postdoc recruitment efforts. We will continue to build formal relationships with key academic partners and institutions with active and emerging nuclear forensic research interests. We will also strengthen relationships with NNSA DNN and SSAA funded university consortia (e.g. NSSC, ACE, CNEC, CVT, ETI, MTV), helping them conduct research of interest and relevance to nuclear forensics, while at the same time evaluating and recruiting promising talent from these programs.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

A case study in contrastive learning information combination: Application to technical forensics of additive manufacturing filament source identification

Combination of information from disparate data sources into a single decision is a core challenge in many fields, including the field of technical forensics. Technical forensics (TF) utilizes technical characterization of questioned samples to determine properties of that sample; these properties are then used to infer information of forensic interest, such as provenance, age, or attribution. TF is utilized in traditional forensic applications, such as the attribution of material fragments from an explosive, and in nuclear forensic applications, such as the attribution of actinides which have been interdicted out of regulatory control. The challenge of combining information from disparate sources, described alternately by many terms including “Data Fusion” and “Data Integration”, is exacerbated in the technical forensics domain due to at least two factors: the challenge of interpreting each information source singularly, and the relatively small data set sizes available. Extensive literature exists attempting to combine technical forensics information sources, both in manual and automated processes. These attempts are often bespoke to the specific information sources (such as the bi-, tri-, or quad-isotope chart (Moody, Grant, and Hutcheon 2005)), with some emerging examples of simple early- and late- fusion (, respectively). Simultaneous to the information combination efforts described in the previous paragraph, the field of natural language processing attempted (and largely succeeded) in combining information from multiple non-technical information sources. The ecosystem of “multi-modal” language models, which can take text and images as input, and generate text and images as output, became large and diverse by 2025 (Khan et al. 2025). In a generalized sense, many of these methods are trained by learning neural networks which can convert raw text or images into a vector of numbers describing the text or image, hereafter called “embeddings” and the neural networks performing the conversion are called “embedders”. By using a separate embedder for text and images, finding coincident text and images (such as images with their captions), and optimizing the parameters of the embedders such that the embeddings for the text and the image are similar, the field has found a bridge between text and images (Girdhar et al. 2023). It is the contention of the authors of this report that this insight is not limited to text and images but instead can be extended to any modality which can be found coincidently. The subject of the rest of this report is the application of this method to example multi-modal technical forensic data. Some details about the data used in this report are not appropriate for this report, and are included in a companion report (PNNL-38669).

36 MATERIALS SCIENCE↗