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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Development of a Smart Signal Detection Method for Cyclic Voltammetry via Artificial Neural Intelligence

The electrorefiner (ER) is the heart of pyroprocessing technology which is a high-temperature method for separating uranium from Used Nuclear Fuel (UNF). It is important to improve this technology with respect to nuclear materials detection and accountability. Artificial Neural Intelligence (ANI) is a novel data analysis and simulation method that can be applied to electrochemical data sets. This computational code, which has been performed using the commercial software MATLAB, can be trained to generalize adequate electrical current and potential simulated data sets for the unseen data with a high accuracy of prediction. For this purpose, a massive collection of cyclic voltammetry (CV) data sets by Hoover (2014), for 0.5, 1, 2.5, and 5 wt% of zirconium chloride in LiCl-KCl molten salt with different scan rates at 773 K has been considered. The computer is trained via ANI to predict the unseen data after providing suitable hidden layers and validation numbers. In addition, this work can trace the CV plot for a blind condition by interpolating between two simulated data set. The different hidden layers with various neurons (from 5 to 30) at several validation numbers (from 5 to 30) has been studied and the average percent error between experimental and theoretical data for 0.5 wt% with 200 and 450 mV/s has been calculated. Preliminary results demonstrate that if the number of hidden layers increases from one to three, the average error falls down from 44% to around 8%. The best condition which gives a minimum average percent error has been discovered and the simulated CV graph has been compared with the experimental data. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Active Neutron Interrogation as a Method for Verification of the Absence of Special Nuclear Material in Arms Control Dismantlement

The next step in arms control reductions will deal with both strategic and non-strategic weapons, presenting new and hard challenges for verification. One verification approach that might be used in support of these reductions is the concept of deferred verification, which forgoes inspections at sensitive nuclear sites and relies on an inspection regime having access to the open segment of a State's nuclear sector, in "monitored transfer zones." A component of this approach is the anticipated need for an instrument suite capable of detecting well-shielded highly-enriched uranium or plutonium where it isn't supposed to be. This specific need was recently identified by the United Nations Institute for Disarmament Research in an enabling operating concept they call "contain and dispose." At the foundation of this approach is the idea that items declared as "not nuclear" are, by definition, not treaty limited and are thus "fair-game" for inspection and questioning. Active Neutron Interrogation (ANI), using beta-delayed neutron emissions as the signature for special nuclear material (SNM) detection, is a promising method to address this challenge. The method is quick, has high sensitivity and high specificity for detecting shielded SNM, is robust against changing background radiation environments, is robust against the presence of unknown shielding, and avoids the use of gamma-ray spectrometry which may introduce complications due to the potential release of sensitive information. This paper will present recent research activities exploring technical aspects of using ANI as a FAIRGAME verification method and discuss future prospects and research needs

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2020

Open Chemistry, JupyterLab, REST, and quantum chemistry

Quantum chemistry must evolve if it wants to fully leverage the benefits of the internet age, where the worldwide web offers a vast tapestry of tools that enable users to communicate and interact with complex data at the speed and convenience of a button press. The Open Chemistry project has developed an open-source framework that offers an end-to-end solution for producing, sharing, and visualizing quantum chemical data interactively on the web using an array of modern tools and approaches. These tools build on some of the best open-source community projects such as Jupyter for interactive online notebooks, coupled with 3D accelerated visualization, state-of-the-art computational chemistry codes including NWChem and Psi4, and emerging machine learning and data mining tools such as ChemML and ANI. They offer flexible formats to import and export data, along with approaches to compare computational and experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Dose-Effect Relationships for Individual Pelvic Floor Muscles and Anorectal Complaints After Prostate Radiotherapy

Purpose: To delineate the individual pelvic floor muscles considered to be involved in anorectal toxicity and to investigate dose-effect relationships for fecal incontinence-related complaints after prostate radiotherapy (RT). Methods and Materials: In 48 patients treated for localized prostate cancer, the internal anal sphincter (IAS) muscle, the external anal sphincter (EAS) muscle, the puborectalis muscle (PRM), and the levator ani muscles (LAM) in addition to the anal wall (Awall) and rectal wall (Rwall) were retrospectively delineated on planning computed tomography scans. Dose parameters were obtained and compared between patients with and without fecal urgency, incontinence, and frequency. Dose-effect curves were constructed. Finally, the effect of an endorectal balloon, which was applied in 28 patients, was investigated. Results: The total volume of the pelvic floor muscles together was about three times that of the Awall. The PRM was exposed to the highest RT dose, whereas the EAS received the lowest dose. Several anal and rectal dose parameters, as well as doses to all separate pelvic floor muscles, were associated with urgency, while incontinence was associated mainly with doses to the EAS and PRM. Based on the dose-effect curves, the following constraints regarding mean doses could be deduced to reduce the risk of urgency: {<=}30 Gy to the IAS; {<=}10 Gy to the EAS; {<=}50 Gy to the PRM; and {<=}40 Gy to the LAM. No dose-effect relationships for frequency were observed. Patients treated with an endorectal balloon reported significantly less urgency and incontinence, while their treatment plans showed significantly lower doses to the Awall, Rwall, and all pelvic floor muscles. Conclusions: Incontinence-related complaints show specific dose-effect relationships to individual pelvic floor muscles. Dose constraints for each muscle can be identified for RT planning. When only the Awall is delineated, substantial components of the continence apparatus are excluded.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Multivariate analysis of factors predicting prostate dose in intensity-modulated radiotherapy

We conducted a multivariate analysis to determine relationships between prostate radiation dose and the state of surrounding organs, including organ volumes and the internal angle of the levator ani muscle (LAM), based on cone-beam computed tomography (CBCT) images after bone matching. We analyzed 270 CBCT data sets from 30 consecutive patients receiving intensity-modulated radiation therapy for prostate cancer. With patients in the supine position on a couch with the HipFix system, data for center of mass (COM) displacement of the prostate and the state of individual organs were acquired and compared between planning CT and CBCT scans. Dose distributions were then recalculated based on CBCT images. The relative effects of factors on the variance in COM, dose covering 95% of the prostate volume (D{sub 95%}), and percentage of prostate volume covered by the 100% isodose line (V{sub 100%}) were evaluated by a backward stepwise multiple regression analysis. COM displacement in the anterior-posterior direction (COM{sub AP}) correlated significantly with the rectum volume (δVr) and the internal LAM angle (δθ; R = 0.63). Weak correlations were seen for COM in the left-right (R = 0.18) and superior-inferior directions (R = 0.31). Strong correlations between COM{sub AP} and prostate D{sub 95%} and V{sub 100%} were observed (R ≥ 0.69). Additionally, the change ratios in δVr and δθ remained as predictors of prostate D{sub 95%} and V{sub 100%}. This study shows statistically that maintaining the same rectum volume and LAM state for both the planning CT simulation and treatment is important to ensure the correct prostate dose in the supine position with bone matching.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

Pentavalent Curium, Berkelium, and Californium in Nitrate Complexes: Extending Actinide Chemistry and Oxidation States

Pentavalent actinyl nitrate complexes An V O 2 (NO 3 ) 2 - were produced by elimination of two NO 2 from An III (NO 3 ) 4 - for An = Pu, Am, Cm, Bk, and Cf. Density functional theory (B3LYP) and relativistic multireference (CASPT2) calculations confirmed the AnO 2 (NO 3 ) 2 - as AnVO 2 + actinyl moieties coordinated by nitrates. Computations of alternative An III O 2 (NO 3 ) 2 - and AnI V O 2 (NO 3 ) 2 - revealed significantly higher energies. Previous computations for bare AnO 2 + indicated AnVO 2 + for An = Pu, Am, Cf, and Bk, but Cm III O 2 + : electron donation from nitrate ligands has here stabilized the first Cm V complex, Cm V O 2 (NO 3 ) 2 - . Structural parameters and bonding analyses indicate increasing An-NO 3 bond covalency from Pu to Cf, in accordance with principles for actinide separations. Atomic ionization energies effectively predict relative stabilities of oxidation states; more reliable energies are needed for the actinides.

36 MATERIALS SCIENCE↗
DOE OSTI2025

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗
DOE OSTI2021

Comparing the Expense and Accuracy of Methods to Simulate Atomic Vibrations in Rubrene

Atomic vibrations can inform about materials properties from hole transport in organic semiconductors to correlated disorder in metal–organic frameworks. Currently, there are several methods for predicting these vibrations using simulations, but the accuracy–efficiency tradeoffs have not been examined in depth. In this work, rubrene is used as a model system to predict atomic vibrational properties using six different simulation methods: density functional theory, density functional tight binding, density functional tight binding with a Chebyshev polynomial-based correction, a trained machine learning model, a pretrained machine learning model called ANI-1, and a classical forcefield model. The accuracy of each method is evaluated by comparison to the experimental inelastic neutron scattering spectrum. All methods discussed here show some accuracy across a wide energy region, though the Chebyshev-corrected tight-binding method showed the optimal combination of high accuracy with low expense. We then offer broad simulation guidelines to yield efficient, accurate results for inelastic neutron scattering spectrum prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Development of Density Functional Tight-Binding Parameters Using Relative Energy Fitting and Particle Swarm Optimization

We provide a strategy to optimize density functional tight-binding (DFTB) parameterization for the calculation of the structures and properties of organic molecules consisting of hydrogen, carbon, nitrogen, and oxygen. We utilize an objective function based on similarity measurements and the Particle Swarm Optimization (PSO) method to find an optimal set of parameters. This objective function considers not only the common DFTB descriptors of binding energies and atomic forces but also incorporates relative energies of isomers into the fitting procedure for more chemistry-driven results. The quality in the description of the binding energies and atomic forces is measured based on the Ballester similarity index and relative energies through a similarity index induced by the Levenshtein edit distance to quantify the correct energetic order of isomers. Training and testing datasets were created to include all relevant chemical functional groups. Finally, the accuracy of this strategy is assessed, and its range of applicability is discussed by comparison against our previous parameterization. The improved performance of the new DFTB parameterization is validated with respect to the density functional theory large datasets QM-9 and ANI-1, where excellent agreement is found between the structures and properties available in these datasets, and the ones obtained with DFTB.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

Computational modeling of chemical and biological systems at atomic resolution is a crucial tool in the chemist’s toolset. The use of computer simulations requires a balance between cost and accuracy: quantum-mechanical methods provide high accuracy but are computationally expensive and scale poorly to large systems, while classical force fields are cheap and scalable, but lack transferability to new systems. Machine learning can be used to achieve the best of both approaches. Here we train a general-purpose neural network potential (ANI-1ccx) that approaches CCSD(T)/CBS accuracy on benchmarks for reaction thermochemistry, isomerization, and drug-like molecular torsions. This is achieved by training a network to DFT data then using transfer learning techniques to retrain on a dataset of gold standard QM calculations (CCSD(T)/CBS) that optimally spans chemical space. The resulting potential is broadly applicable to materials science, biology, and chemistry, and billions of times faster than CCSD(T)/CBS calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

2.2.2-Cryptand complexes of neptunium(III) and plutonium(III)

New coordination environments are reported for Np(III) and Pu(III) based on pilot studies of U(III) in 2.2.2-cryptand (crypt). The U(III)-in-crypt complex, [U(crypt)I 2 ][I], obtained from the reaction between UI 3 and crypt, is treated with Me 3 SiOTf (OTf = O 3 SCF 3 ) in benzene to form the [U(crypt)(OTf) 2 ][OTf] complex. Similarly, the isomorphous Np(III) and Pu(III) complexes were obtained similarly starting from [AnI 3 (THF) 4 ]. All three complexes (1-An; An = U, Np, Pu) contain an encapsulated actinide in a THF-soluble complex. Finally, absorption spectroscopy and DFT calculations are consistent with 5f 3 U(III), 5f 4 Np(III), and 5f 5 Pu(III) electron configurations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Macrospin modeling of sub-ns pulse switching of perpendicularly magnetized free layer via spin-orbit torques for cryogenic memory applications

We model, using the macrospin approximation, the magnetic reversal of a perpendicularly magnetized nanostructured free layer formed on a normal, heavy-metal nanostrip, subjected to spin-orbit torques (SOTs) generated by short (≤0.5 ns) current pulses applied to the nanostrip, to examine the potential for SOT-based fast, efficient cryogenic memory. Due to thermal fluctuations, if solely an anti-damping torque is applied, then, for a device with sufficiently low anisotropy (H{sub anis}{sup 0} ∼ 1 kOe) suitable for application in cryogenic memory, a high magnetic damping parameter (α∼0.1−0.2) is required for reliable switching over a significant variation of pulse current. The additional presence of a substantial field-like torque improves switching reliability even for low damping (α≤0.03).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials

Intermolecular interactions are critical to many chemical phenomena, but their accurate computation using ab initio methods is often limited by computational cost. The recent emergence of machine learning (ML) potentials may be a promising alternative. Useful ML models should not only estimate accurate interaction energies but also predict smooth and asymptotically correct potential energy surfaces. However, existing ML models are not guaranteed to obey these constraints. Indeed, systemic deficiencies are apparent in the predictions of our previous hydrogen-bond model as well as the popular ANI-1X model, which we attribute to the use of an atomic energy partition. As a solution, we propose an alternative atomic-pairwise framework specifically for intermolecular ML potentials, and we introduce AP-Net—a neural network model for interaction energies. The AP-Net model is developed using this physically motivated atomic-pairwise paradigm and also exploits the interpretability of symmetry adapted perturbation theory (SAPT). We show that in contrast to other models, AP-Net produces smooth, physically meaningful intermolecular potentials exhibiting correct asymptotic behavior. Initially trained on only a limited number of mostly hydrogen-bonded dimers, AP-Net makes accurate predictions across the chemically diverse S66x8 dataset, demonstrating significant transferability. On a test set including experimental hydrogen-bonded dimers, AP-Net predicts total interaction energies with a mean absolute error of 0.37 kcal mol−1, reducing errors by a factor of 2–5 across SAPT components from previous neural network potentials. The pairwise interaction energies of the model are physically interpretable, and an investigation of predicted electrostatic energies suggests that the model “learns” the physics of hydrogen-bonded interactions.

Glick, Zachary L. (ORCID:0000000309002849)↗
DOE OSTI2022

The IMG/M data management and analysis system v.7: content updates and new features

The Integrated Microbial Genomes & Microbiomes system at the Department of Energy (DOE) Joint Genome Institute (JGI) continues to provide support for users to perform comparative analysis of isolate and single cell genomes, metagenomes, and metatranscriptomes. In addition to datasets produced by the JGI, IMG v.7 also includes datasets imported from public sources such as NCBI Genbank, SRA, and the DOE National Microbiome Data Collaborative (NMDC), or submitted by external users. In the past couple years, we have continued our effort to help the user community by improving the annotation pipeline, upgrading the contents with new reference database versions, and adding new analysis functionalities such as advanced scaffold search, Average Nucleotide Identity (ANI) for high-quality metagenome bins, new cassette search, improved gene neighborhood display, and improvements to metatranscriptome data display and analysis. Here, we also extended the collaboration and integration efforts with other DOE-funded projects such as NMDC and DOE Biology Knowledgebase (KBase).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Reclassification of a Polynucleobacter cosmopolitanus strain isolated from tropical Lake Victoria as Polynucleobacter victoriensis sp. nov.

The genus Polynucleobacter (family Burkholderiaceae ) is phylogenetically subdivided into at least four subclusters. One of those, subcluster PnecC, was recognized as a cryptic species complex. Here we test by comparative genome analyses whether subcluster PnecD, currently solely represented by the species Polynucleobacter cosmopolitanus , also represents such a cryptic species complex. The genome sequences of the two P. cosmopolitanus strains, MWH-MoIso2T and MWH-VicM1, were determined. The latter strain was also characterized in the previous description of P. cosmopolitanus . These two strains originate from a temperate lake located in Austria and from the large tropical Lake Victoria located in East Africa, respectively. Strains MWH-MoIso2T and MWH-VicM1 possess quite small genomes of 1.78 and 1.63 Mbp, respectively, and share similar G+C values of 44.1 and 43.1 mol%, respectively. Both strains encode only a single copy of the ribosomal operon, and their 16S rRNA genes differ only in four positions, equalling a sequence similarity of 99.74 %. Both genomes possess characteristics indicating evolutionary genome streamlining, such as high coding densities of 93.9 and 94.6 % of bases, respectively. Average nucleotide identity (ANI) comparisons of the genomes of the two strains resulted in a value of 78.4 %, suggesting that each of the strains represents a separate species. Our investigation suggests that PnecD represents an additional cryptic species complex within the genus Polynucleobacter that was not resolved by 16S rRNA gene sequence analyses. We propose reclassification of strain MWH-VicM1 as Polynucleobacter victoriensis sp. nov., with type strain MWH-VicM1T(=DSM 21486T=JCM 32005T).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Turicibacter bilis sp. nov., a novel bacterium isolated from the chicken eggshell and swine ileum

Three novel, anaerobic, Gram-positive bacteria were isolated from the eggshell of two separate white leghorn chicken flocks and the ileum of a healthy pig, and designated MMM721 T , ISU324 and PIG517 respectively. Cells were pleomorphic and capable of forming long chains of rods or coccoid clusters. Phylogenetic analysis of the 16S rRNA gene sequences identified these strains to be within the genus Turicibacter, of which only one species, Turicibacter sanguinis, has been formally described. However, whole genome sequencing of novel isolates returned a digital DNA–DNA hybridization value of 22.5% and average nucleotide identity (ANI) values of 76.4% (ANIb) and 86.0% (ANIm), indicating divergence between the type strain MMM721 T and T. sanguinis, suggesting the strains represented a novel species. The major fatty acid methyl esters of strain MMM721 T were C 16:0 , C 18:1 ω7c and C 18:0 . The strains mainly produced the volatile fatty acid lactate, along with smaller amounts of acetate and butyrate. Together, these data indicate that MMM721 T , along with ISU324 and PIG517, represent a novel species within the genus Turicibacter. We propose the name Turicibacter bilis sp. nov. for the species. The type strain is MMM721 T (=ATCC TSD-238 T =CCUG 74757 T ).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multi-choice Viromics Pipeline (MVP) v1

MVP stands for Multi-choice Viromics Pipeline. It is a pipeline that utilizes a suite of state-of-art tools: geNomad to identify viruses, proviruses, and plasmids in sequencing data, CheckV to assess the quality, and completeness of identified viral genomes, including identification of host contamination for integrated proviruses, A custom code for a rapid genome clustering based on pairwise ANI, Bowtie2, Samtools, and CoverM to calculate coverage of individual viral genomes by read mapping, A custom code to create a vOTU table of abundance, MMseqs2 to compare viral proteins to multiple databases. It provides a quick, and intuitive pipeline to get viral sequences and corresponding properties that can be used for downstream analyses.

Roux, Simon↗
DOE OSTI2014

Comparative genomic analysis of nine Sphingobium strains: Insights into their evolution and hexachlorocyclohexane (HCH) degradation pathways

Background: Sphingobium spp. are efficient degraders of a wide range of chlorinated and aromatic hydrocarbons. In particular, strains which harbour the lin pathway genes mediating the degradation of hexachlorocyclohexane (HCH) isomers are of interest due to the widespread persistence of this contaminant. Here, we examined the evolution and diversification of the lin pathway under the selective pressure of HCH, by comparing the draft genomes of six newly-sequenced Sphingobium spp. (strains LL03, DS20, IP26, HDIPO4, P25 and RL3) isolated from HCH dumpsites, with three existing genomes ( S. indicum B90A, S. japonicum UT26S and Sphingobium sp. SYK6). Results: Efficient HCH degraders phylogenetically clustered in a closely related group comprising of UT26S, B90A, HDIPO4 and IP26, where HDIPO4 and IP26 were classified as subspecies with ANI value >98%. Less than 10% of the total gene content was shared among all nine strains, but among the eight HCH-associated strains, that is all except SYK6, the shared gene content jumped to nearly 25%. Genes associated with nitrogen stress response and two-component systems were found to be enriched. The strains also housed many xenobiotic degradation pathways other than HCH, despite the absence of these xenobiotics from isolation sources. In addition, these strains, although non-motile, but posses flagellar assembly genes. While strains HDIPO4 and IP26 contained the complete set of lin genes, DS20 was entirely devoid of lin genes (except linKLMN ) whereas, LL03, P25 and RL3 were identified as lin deficient strains, as they housed incomplete lin pathways. Further, in HDIPO4, linA was found as a hybrid of two natural variants i.e., linA1 and linA2 known for their different enantioselectivity. In conclusion, the bacteria isolated from HCH dumpsites provide a natural testing ground to study variations in the lin system and their effects on degradation efficacy. Further, the diversity in the lin gene sequences and copy number, their arrangement with respect to IS 6100 and evidence for potential plasmid content elucidate possible evolutionary acquisition mechanisms for this pathway. This study further opens the horizon for selection of bacterial strains for inclusion in an HCH bioremediation consortium and suggests that HDIPO4, IP26 and B90A would be appropriate candidates for inclusion.

59 BASIC BIOLOGICAL SCIENCES↗