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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Bias Voltage-Dependent Impedance Spectroscopy Analysis of Hydrothermally Synthesized ZnS Nanoparticles

In this report, bias voltage-dependent dielectric and electron transport properties of ZnS nanoparticles were discussed. ZnS nanoparticles were synthesized by introducing a modified hydrothermal process. The powder XRD pattern indicates the phase purity, and field emission scanning electron microscope image demonstrates the morphology of the synthesized sample. The optical band gap energy (E{sub g }= 4.2 eV) from UV measurement explores semiconductor behavior of the synthesized material. The electrical properties were performed at room temperature using complex impedance spectroscopy (CIS) technique as a function of frequency (40 Hz-10 MHz) under different forward dc bias voltages (0-1 V). The CIS analysis demonstrates the contribution of bulk resistance in conduction mechanism and its dependency on forward dc bias voltages. The imaginary part of the impedance versus frequency curve exhibits the existence of relaxation peak which shifts with increasing dc forward bias voltages. The dc bias voltage-dependent ac and dc conductivity of the synthesized ZnS was studied on thin film structure. A possible hopping mechanism for electrical transport processes in the system was investigated. Finally, it is worth to mention that this analysis of bias voltage-dependent dielectric and transport properties of as-synthesized ZnS showed excellent properties for emerging energy applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Quantum algorithm to simulate Lindblad master equations

We present a quantum algorithm for simulating a family of Markovian master equations that can be realized through a probabilistic application of unitary channels and state preparation. Our approach employs a second-order product formula for the Lindblad master equation, achieved by decomposing the dynamics into dissipative and Hamiltonian components and replacing the dissipative segments with randomly compiled, easily implementable elements. The sampling approach eliminates the need for ancillary qubits to simulate the dissipation process and reduces the gate complexity in terms of the number of jump operators. We provide a rigorous performance analysis of the algorithm. We also extend the algorithm to time-dependent Lindblad equations, generalize the family of Markovian master equations it can be applied to, and explore applications beyond the Markovian noise model. A new error bound, in terms of the diamond norm, for second-order product formulas for time-dependent Liouvillians is provided that might be of independent interest. Published by the American Physical Society 2025

Borras, Evan (ORCID:000900017709037X)↗
DOE OSTI2021

DOE JGI Metagenome Workflow

The DOE Joint Genome Institute (JGI) Metagenome Workflow performs metagenome data processing, including assembly; structural, functional, and taxonomic annotation; and binning of metagenomic data sets that are subsequently included into the Integrated Microbial Genomes and Microbiomes (IMG/M) (I.-M. A. Chen, K. Chu, K. Palaniappan, A. Ratner, et al., Nucleic Acids Res, 49:D751–D763, 2021, https://doi.org/10.1093/nar/gkaa939) comparative analysis system and provided for download via the JGI data portal (https://genome.jgi.doe.gov/portal/). This workflow scales to run on thousands of metagenome samples per year, which can vary by the complexity of microbial communities and sequencing depth. Here, we describe the different tools, databases, and parameters used at different steps of the workflow to help with the interpretation of metagenome data available in IMG and to enable researchers to apply this workflow to their own data. We use 20 publicly available sediment metagenomes to illustrate the computing requirements for the different steps and highlight the typical results of data processing. The workflow modules for read filtering and metagenome assembly are available as a workflow description language (WDL) file (https://code.jgi.doe.gov/BFoster/jgi_meta_wdl). The workflow modules for annotation and binning are provided as a service to the user community at https://img.jgi.doe.gov/submit and require filling out the project and associated metadata descriptions in the Genomes OnLine Database (GOLD) (S. Mukherjee, D. Stamatis, J. Bertsch, G. Ovchinnikova, et al., Nucleic Acids Res, 49:D723–D733, 2021, https://doi.org/10.1093/nar/gkaa983).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Nb3Sn Coating of Twin Axis Cavity for SRF Applications

The twin axis cavity with two identical accelerating beams has been proposed for Energy recovery linac (ERL) applications. Nb3Sn is a superconducting material with a higher critical temperature and a higher critical field as compared to Nb, which promises a lower operating cost due to higher quality factors. Two niobium twin axis cavities fabricated at JLab and were proposed to be coated with Nb3Sn. Due to their more complex geometry, the typical coating process used for basic elliptical cavities needs to be improved to coat these cavities. This devel-opment advances the current coating system at JLab for coating complex cavities. Two twin axis cavities were coated recently for the first time. This contribution dis-cusses initial results from coating of twin axis cavities, RF testing and witness sample analysis with an overview of the current challenges towards high performance Nb3Sn coated twin axis cavities.

Tiskumara, J.↗
DOE OSTI2022

Nb₃Sn Coating of Twin Axis Cavity for SRF Applications

The twin axis cavity with two identical accelerating beams has been proposed for energy recovery linac (ERL) applications. Nb₃Sn is a superconducting material with a higher critical temperature and a higher critical field as compared to Nb, which promises a lower operating cost due to higher quality factors. Two niobium twin axis cavities were fabricated at JLab and were proposed to be coated with Nb₃Sn. Due to their more complex geometry, the typical coating process used for basic elliptical cavi-ties needs to be improved to coat these cavities. This development advances the current coating system at JLab for coating complex cavities. Two twin axis cavities were coated recently for the first time. This contribution dis-cusses initial results from coating of twin axis cavities, RF testing and witness sample analysis with an overview of the current challenges towards high performance Nb₃Sn coated twin axis cavities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Proteomic Analysis of Exosomes for Discovery of Protein Biomarkers for Prostate and Bladder Cancer

Extracellular vesicles (EVs) are released by nearly all cell types as part of normal cell physiology, transporting biological cargo, including nucleic acids and proteins, across the cell membrane. In pathological states such as cancer, EV-derived cargo may mirror the altered state of the cell of origin. Exosomes are the smaller, 50–150 nanometer-sized EVs released from fusion of multivesicular endosomes with the plasma membrane. Exosomes play important roles in cell-cell communication and participate in multiple cancer processes, including invasion and metastasis. Therefore, proteomic analysis of exosomes is a promising approach to discover potential cancer biomarkers, even though it is still at an early stage. Herein, we critically review the advances in exosome isolation methods and their compatibility with mass spectrometry (MS)-based proteomic analysis, as well as studies of exosomes in pathogenesis and progression of prostate and bladder cancer, two common urologic cancers whose incidence rates continue to rise annually. As urological tumors, both urine and blood samples are feasible for noninvasive or minimally invasive analysis. A better understanding of the biological cargo and functions of exosomes via high-throughput proteomics will help provide new insights into complex alterations in cancer and provide potential therapeutic targets and personalized treatment for patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Leveraging Machine Learning Capabilities for the Characterization of Irradiated Uranium: A Case Study of Analysis Methods for Nuclear Safeguards and Nuclear Forensics

Nondestructively determining the initial enrichment of irradiated uranium is a complex and laborious multivariable problem due to the presence of fission products. This work demonstrates the capabilities of machine learning to analyze gamma-ray spectral data to determine initial enrichment without knowledge of the decay time of the sample. The approach developed is agnostic to the particular scenario and is applicable to a wide variety of applications in nuclear forensics and nuclear safeguards. We irradiated 5 mg uranium standard reference materials at discrete enrichment values ranging from 0.02% to 97% 235 U (weight percent) in UT Austin’s Nuclear Engineering Teaching Laboratory TRIGA Mark II 1.1 MW research reactor, allowed each to decay for 8 hours, and then measured each sample via gamma-ray spectrometry for 50 hours post-irradiation yielding 1,400 individual gamma-ray spectra discretized into 8,192 energy bins. We then trained decision trees models to analyze individual gamma-ray spectra and estimate the associated initial enrichment without knowledge of the time since end of irradiation. We evaluated the performance of the models with a reserved test set not used for training or calibrating the model. A decision tree model constructed with this procedure achieved a mean absolute error in initial enrichment determination of 2.3% (weight percent 235 U). Next, we implemented a principal component analysis pre-processing routine of the gamma-ray spectrometry data to reduce the dimensionality of the dataset from 8,192 channels in the spectrum to 10 principal components while retaining over 99% of the inherent variance in the data. Decision tree models constructed with these data demonstrated decreased mean absolute error in enrichment determination, reduced computational time, and decreased complexity. A single decision tree model constructed with this procedure achieved a mean absolute error in initial enrichment determination of 0.05% (weight percent 235 U). Furthermore, we analyzed these models with learning curves to ensure that overfitting did not occur. The capabilities provided by these models can be naturally extended to other application-focused measurements in the fields of nuclear safeguards, nuclear forensics, and nuclear non-proliferation.

Drescher, Adam↗
DOE OSTI2018

MicroRNA-21 promotes wound healing via the Smad7-Smad2/3-Elastin pathway

Highlights: • MicroRNA-21 promotes wound healing. • Smad7 is the target of microRNA-21. • MicroRNA-21 promotes wound healing process via targeting TGF-β pathway. Wound healing is regulated by a complex network of cells, molecules, and cytokines, as well as microRNAs (miRNAs). miRNAs were confirmed to influence the wound healing process, and miR-21, an important member of the miRNA family, was also shown to regulate wound healing. The aim of the present study was to investigate the role of miR-21 in the wound healing process and the possible underlying cell signaling pathways. We isolated GMSCs from WT and miR-21-KO mouse gingiva. Flow cytometric analysis and immunocytofluorescense staining were used to identify the GMSCs acquired from WT and miR-21-KO mice. RT-PCR, western blot analysis and immunohistofluorescence staining were performed to examine the expression of extracellular matrix components and key proteins of cell signaling pathways. TargetScan and pmiR-RB-REPORT vectors were used to verify that Smad7 was a direct target of miR-21. Compared to WT mice, miR-21-KO mice showed slower wound healing. RT-PCR and western blot analysis indicated that Elastin expression was downregulated in miR-21-deficient samples. We confirmed that Smad7 was a direct target of miR-21. miR-21 knockout resulted in increased expression of Smad7 and impaired phosphorylation of the Smad2/3 complex. The expression of the Smad7-Smad2/3-Elastin axis in palate tissues sections acquired from WT and miR-21-KO mice showed the same trend. Based on all these results, we demonstrated that miR-21 promoted the wound healing process via the Smad7-Smad2/3-Elastin pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Sample Preparation for 3D Characterization of Irradiated Fuel

Thorough characterization of nuclear fuel is essential when striving to understand its microstructural evolution in response to varying irradiation conditions. A detailed understanding of the microstructural evolution of irradiated fuel can be useful when predicting the fuel’s response to off-normal conditions and related phenomena such as high burnup fuel fragmentation (HBFF) and fission gas release. This sort of characterization and the study of complex phenomena like HBFF that are related to fuel performance are an important part of the US Department of Energy Office of Nuclear Energy’s Advanced Fuels Campaign (AFC). Multiple characterization techniques are commonly used to perform post-irradiation examination (PIE) analysis on an irradiated fuel sample, but many of these techniques are limited to the 2D surface analysis of the fuel pellet. Although there is a lot of useful information to be gained by analyzing the fuel pellet surface, a 2D analysis provides only an approximation of the nature of the material’s features, such as porosity and grain structure. Therefore, it is critical to analyze the 3D structure of the material, as materials exist and respond to conditions in all three dimensions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Galaxy bias in the era of LSST: perturbative bias expansions

Upcoming imaging surveys will allow for high signal-to-noise measurements of galaxy clustering at small scales. In this work, we present the results of the Rubin Observatory Legacy Survey of Space and Time (LSST) bias challenge, the goal of which is to compare the performance of different nonlinear galaxy bias models in the context of LSST Year 10 (Y10) data. Specifically, we compare two perturbative approaches, Lagrangian perturbation theory (LPT) and Eulerian perturbation theory (EPT) to two variants of Hybrid Effective Field Theory (HEFT), with our fiducial implementation of these models including terms up to second order in the bias expansion as well as nonlocal bias and deviations from Poissonian stochasticity. Here, we consider a variety of different simulated galaxy samples and test the performance of the bias models in a tomographic joint analysis of LSST-Y10-like galaxy clustering, galaxy-galaxy-lensing and cosmic shear. We find both HEFT methods as well as LPT and EPT combined with non-perturbative predictions for the matter power spectrum to yield unbiased constraints on cosmological parameters up to at least a maximal scale of k max = 0.4 Mpc -1 for all samples considered, even in the presence of assembly bias. While we find that we can reduce the complexity of the bias model for HEFT without compromising fit accuracy, this is not generally the case for the perturbative models. We find significant detections of non-Poissonian stochasticity in all cases considered, and our analysis shows evidence that small-scale galaxy clustering predominantly improves constraints on galaxy bias rather than cosmological parameters. These results therefore suggest that the systematic uncertainties associated with current nonlinear bias models are likely to be subdominant compared to other sources of error for tomographic analyses of upcoming photometric surveys, which bodes well for future galaxy clustering analyses using these high signal-to-noise data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Sensitive Top-Down Proteomics Analysis of a Low Number of Mammalian Cells Using a Nanodroplet Sample Processing Platform

Top-down proteomics is a powerful tool for characterizing genetic variations and post-translational modifications at intact protein level. That being said, one significant technical gap of top-down proteomics is the inability to analyze low amount of biological samples, which limits its access to isolated rare cells, fine-needle aspiration biopsies, and tissue substructures. Herein, we developed an ultrasensitive top-down platform by incorporating a microfluidic sample preparation system, termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples), into a top-down proteomics workflow. A unique combination of a nonionic detergent dodecyl-ß-D-maltopyranoside (DDM) with urea as protein extraction buffer significantly improved both protein extraction efficiency and sample recovery. We hypothesize that the DDM detergent improves protein recovery by efficiently reducing non-specific adsorption of intact proteins on container surfaces, while urea serves as a strong denaturant to disrupt noncovalent complexes and release intact proteins for downstream analysis. The nanoPOTS-based top-down platform reproducibly and quantitatively identified ~170 to ~620 proteoforms from ~70 to ~770 HeLa cells containing ~10 to ~115 ng of total protein. A variety of post-translational modifications including acetylation, myristoylation, and iron binding were identified using only less than 800 cells. We anticipate the nanoPOTS top-down proteomics platform will be broadly applicable in biomedical researches, particularly where clinical specimens are not available in amounts amenable to standard workflows.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

XANES reflects coordination change and underlying surface disorder of zinc adsorbed to silica

In this work, zinc K -edge X-ray absorption near-edge structure (XANES) spectroscopy of Zn adsorbed to silica and Zn-bearing minerals, salts and solutions was conducted to explore how XANES spectra reflect coordination environment and disorder in the surface to which a metal ion is sorbed. Specifically, XANES spectra for five distinct Zn adsorption complexes (Zn ads ) on quartz and amorphous silica [SiO 2(am) ] are presented from the Zn–water–silica surface system: outer-sphere octahedral Zn ads on quartz, inner-sphere octahedral Zn ads on quartz, inner-sphere tetrahedral Zn ads on quartz, inner-sphere octahedral Zn ads on SiO 2(am) and inner-sphere tetrahedral Zn ads on SiO 2(am) . XANES spectral analysis of these complexes on quartz versus SiO 2(am) reveals that normalized peak absorbance and K -edge energy position generally decrease with increasing surface disorder and decreasing Zn–O coordination. On quartz, the absorption-edge energy of Zn ads ranges from 9663.0 to 9664.1 eV for samples dominated by tetrahedrally versus octahedrally coordinated species, respectively. On SiO 2(am) , the absorption-edge energy of Zn ads ranges from 9662.3 to 9663.4 eV for samples dominated by tetrahedrally versus octahedrally coordinated species, respectively. On both silica substrates, octahedral Zn ads presents a single K -edge peak feature, whereas tetrahedral Zn ads presents two absorbance features. The energy space between the two absorbance peak features of the XANES K -edge of tetrahedral Zn ads is 2.4 eV for Zn on quartz and 3.2 eV for Zn on SiO 2(am) . Linear combination fitting of samples with a mixture of Zn ads complex types demonstrates that the XANES spectra of octahedral and tetrahedral Zn ads on silica are distinct enough for quantitative identification. These results suggest caution when deciphering Zn speciation in natural samples via linear combination approaches using a single Zn ads standard to represent sorption on a particular mineral surface. Correlation between XANES spectral features and prior extended X-ray absorption fine structure (EXAFS) derived coordination environments for these Zn ads on silica samples provides insight into Zn speciation in natural systems with XANES compatible Zn concentrations too low for EXAFS analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Column separation of tetravalent cerium fission products from trivalent rare earth radio-isotopes

Rapid and efficient isolation of individual rare earth element (REE) radioisotopes from complex mixtures is necessary to support the fields of nuclear forensics, medical isotope production and nuclear physics measurements. The separations must be robust and generate sufficiently high purity samples for subsequent radiological analysis. Current methodologies utilize a laborious two step Ce(IV)-iodate precipitation followed by Ce(IV)-nitrate di-(2-ethylhexyl)phosphoric acid/n-heptane extraction. This work reports an alternative method to isolate Ce fission product isotopes equilibrated with milligrams of cold carrier, from the remaining REE’s using a Ce(IV)/LN-resin (Eichrom Technologies) based separation. Optimization of Ce(IV) loading, REE(III) elution volume and subsequent Ce(III) stripping step utilized 166m Ho tracer. Mixed fission product experiments provided a further test of this LN-resin method, with analysis of purified 141/144 Ce, 147 Nd and 91 Y. Overall, while decontamination factors were lower for the LN-resin method, (vs. the combined precipitation/extraction) the simplicity of the technique and the satisfactory fission product analysis results point to the efficacy of this method.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

The shape recovery conditions for Fe–Mn–Si alloys: An interplay between martensitic transformation and plasticity

Highlights: • Fe15Mn5Si9Cr5Ni samples were rolled at 800 °C and annealed at 650 (C1) and 1000 °C (C2). • TEM analysis was performed. • High density of stacking faults and appropriate density of dislocation appears in C1. • Complex dislocation arrays due to plastic deformation are observed in C2. • Shape memory properties depend on the thermomechanical treatment. - Abstract: This work analyses the improvement of the shape memory properties of Fe-Mn-Si based alloys, and expands upon and deepens recently published developments concerning this topic. We prepared TEM specimens from a Fe-15Mn-5Si-9Cr-5Ni sheet rolled at 800 °C and annealed at 650 °C–92% shape recovery – and from another sheet annealed at 1000 °C–45% shape recovery. Here, we analyse the development of microstructure during the γ ↔ ε martensitic transformation and correlate it with the shape memory behaviour. Among the observed microstructural features, the introduction of complex dislocation arrays due to plastic deformation appears to be critical for shape memory development, since they can arrest the backward movement of Shockley partial dislocations over the original path. Tailoring the microstructure in order to introduce a high stacking-fault density accompanied by an appropriate dislocation density remains a key issue in the design of these kinds of functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Measurement and analysis of GPU-accelerated applications with HPCToolkit

To address the challenge of performance analysis on the US DOE’s forthcoming exascale supercomputers, Rice University has been extending its HPCToolkit performance tools to support measurement and analysis of GPU-accelerated applications. To help developers understand the performance of accelerated applications as a whole, HPCToolkit’s measurement and analysis tools attribute metrics to calling contexts that span both CPUs and GPUs. To measure GPU-accelerated applications efficiently, HPCToolkit employs a novel wait-free data structure to coordinate monitoring and attribution of GPU performance. To help developers understand the performance of complex GPU code generated from high-level programming models, HPCToolkit constructs sophisticated approximations of call path profiles for GPU computations. To support fine-grained analysis and tuning, HPCToolkit uses PC sampling and instrumentation to measure and attribute GPU performance metrics to source lines, loops, and inlined code. To supplement fine-grained measurements, HPCToolkit can measure GPU kernel executions using hardware performance counters. To provide a view of how an execution evolves over time, HPCToolkit can collect, analyze, and visualize call path traces within and across nodes. Finally, on NVIDIA GPUs, HPCToolkit can derive and attribute a collection of useful performance metrics based on measurements using GPU PC samples. Here, we illustrate HPCToolkit’s new capabilities for analyzing GPU-accelerated applications with several codes developed as part of the Exascale Computing Project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Handling and Treatment of Sodium-Potassium Alloy (NaK) after the Loss of Key Personnel – 19002

ABSTRACT In September 2010, during cleanup and removal efforts associated with a glovebox containing a sodium-potassium alloy (NaK) cooling system, a NaK reaction event occurred. Near the end of the evolution, which was at a Materials and Fuels Complex (MFC) research facility at the Idaho National Laboratory, a 2 to 3-ounce sample of NaK was being transferred from a metal can to a polyethylene bottle so it could be sent to the disposal outlet for verification analysis. During the transfer, a reaction of the NaK with ambient air was observed in both the metal can and sample container. The potential for a reaction was identified during the planning of this activity and mitigating steps were included in the procedures. In response, the two containers were flooded with argon, closed, and observed overnight. No additional reaction was noted. The sample container and metal can were packaged into a 10-gallon drum and transferred to a permitted storage location pending disposal. While the other containers generated from the deactivation and decommissioning activity were sent off-site for disposal, the 10-gal drum remained due to concerns by a staff specialist that the material could contain potassium superoxide (KO2) as a result of the reaction event. The intent at that time was to treat the NaK in a Resource Conservation and Recovery Act (RCRA)-permitted treatment facility at MFC, instead of sending it off-site for disposal. The container was labeled, inspected, and managed as a hazardous waste. Due to the complexities associated with safely handling and treating NaK and KO2, the container remained in storage. Treatment and disposal of the NaK and KO2 container was revisited in 2016, when researchers and chemists were consulted regarding the potential for superoxide formation and the best means to safely store and treat the container. The facility came to realize that due to the retirements of key personnel, it needed to provide current employees operational experience with the handling and treatment of NaK. An outside company was identified and contracted to provide training and consulting services. Several Battelle Energy Alliance, Inc. (BEA) personnel then attended an alkali metals safety training class. The training course provided participants with classroom and hands–on instruction associated with: • Hazards associated with handling and using sodium and NaK • Proper personal protection equipment, spill control techniques, and first aid • Common design approaches for buildings, systems, and equipment used to contain sodium and NaK • What to expect in the event of a water reaction and how to respond • How to properly prepare for a fire and contain/extinguish small metal fires • A hands-on demonstration of NaK reaction and controls. Following the training, a procedure was developed to open the container, and inspect and treat the NaK. In June 2017, facility operations personnel successfully completed the inspection and treatment of the NaK drum, eliminating the legacy liability.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Handling and Treatment of Sodium-Potassium Alloy (NaK) after the Loss of Key Personnel - 19002

In September 2010, during cleanup and removal efforts associated with a glovebox containing a sodium-potassium alloy (NaK) cooling system, a NaK reaction event occurred. Near the end of the evolution, which was at a Materials and Fuels Complex (MFC) research facility at the Idaho National Laboratory, a 2 to 3-ounce sample of NaK was being transferred from a metal can to a polyethylene bottle so it could be sent to the disposal outlet for verification analysis. During the transfer, a reaction of the NaK with ambient air was observed in both the metal can and sample container. The potential for a reaction was identified during the planning of this activity and mitigating steps were included in the procedures. In response, the two containers were flooded with argon, closed, and observed overnight. No additional reaction was noted. The sample container and metal can were packaged into a 10-gallon drum and transferred to a permitted storage location pending disposal. While the other containers generated from the deactivation and decommissioning activity were sent off-site for disposal, the 10-gal drum remained due to concerns by a staff specialist that the material could contain potassium superoxide (KO{sub 2}) as a result of the reaction event. The intent at that time was to treat the NaK in a Resource Conservation and Recovery Act (RCRA)-permitted treatment facility at MFC, instead of sending it off-site for disposal. The container was labeled, inspected, and managed as a hazardous waste. Due to the complexities associated with safely handling and treating NaK and KO{sub 2}, the container remained in storage. Treatment and disposal of the NaK and KO{sub 2} container was revisited in 2016, when researchers and chemists were consulted regarding the potential for superoxide formation and the best means to safely store and treat the container. The facility came to realize that due to the retirements of key personnel, it needed to provide current employees operational experience with the handling and treatment of NaK. An outside company was identified and contracted to provide training and consulting services. Several Battelle Energy Alliance, Inc. (BEA) personnel then attended an alkali metals safety training class. The training course provided participants with classroom and hands-on instruction associated with: - Hazards associated with handling and using sodium and NaK; - Proper personal protection equipment, spill control techniques, and first aid; - Common design approaches for buildings, systems, and equipment used to contain sodium and NaK; - What to expect in the event of a water reaction and how to respond; - How to properly prepare for a fire and contain/extinguish small metal fires; - A hands-on demonstration of NaK reaction and controls. Following the training, a procedure was developed to open the container, and inspect and treat the NaK. In June 2017, facility operations personnel successfully completed the inspection and treatment of the NaK drum, eliminating the legacy liability. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Maximizing machine learning interatomic potential transferability for the discovery of the novel stellated octadecagon Bi18-Pt24 cage structure

Achieving true transferability remains the central challenge for Machine Learning Interatomic Potentials (ML-IAPs) in modeling complex bimetallic nanoclusters across their vast potential energy surfaces. We systematically investigate data selection strategies to optimize the Chebyshev Interaction Model for Efficient Simulation (ChIMES) potential for the Bi-Pt nanoclusters by comparing three innovative sampling methods: Principal Component Analysis (PCA)/k-means (structural diversity), t-distributedStochasticNeighborEmbedding (t-SNE)/k-means (force-space diversity), and hierarchical clustering. Quantitatively, the PCA/k-means strategy proved most effective for global accuracy, yielding the lowest force errors and achieving energy root mean square errors (RMSE) values competitive with Density Functional Theory (DFT), demonstrating excellent accuracy (19.16meV/atom). Structural validation on 34 unique DFT-optimized isomers further confirmed the potential’s high fidelity, with the best model PCA/k-means reproducing structures with an average root mean square deviation (RMSD) of 0.10 Å. However, the t-SNE methods, by maximizing diversity in the force space, demonstrated superior extrapolative power, leading to the more precise prediction of a novel stellated octadecagon Bi18⁢Pt24 cage structure, demonstrating the potential for exploring previously unseen morphologies. Our results establish a clear methodology for strategic data sampling that successfully maximizes ML-IAP transferability, providing an accurate and computationally efficient tool that accelerates the theoretical discovery of complex bimetallic architectures.

Vangheluwe, Raphaël [Université Paris-Saclay, CNRS↗