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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Prediction of Structures and Atomization Energies of Small Silver Clusters, (Ag) n , n < 100

Neutral silver clusters, Ag n , were studied using density functional theory (DFT) followed by high level coupled cluster CCSD(T) calculations to determine the low energy isomers for each cluster size for small clusters. The normalized atomization energy, heats of formation, and average bond lengths were calculated for each of the different isomeric forms of the silver clusters. For n = 2–6, the preferred geometry is planar, and the larger n = 7–8 clusters prefer higher symmetry, three-dimensional geometries. The low spin state is predicted to be the ground state for every cluster size. A number of new low energy isomers for the heptamer and octamer were found. Additional larger Ag n structures, n < 100, were initially optimized using a tree growth-hybrid genetic algorithm with an embedded atom method (EAM) potential. Finally, for n ≤ 20, DFT was used to optimize the geometries. DFT with benchmarked functionals were used to predict that the normalized atomization energies ((AE)s) for Ag n start to converge slowly to the bulk at n = 55. The (AE) for Ag 99 is predicted to be ~50 kcal/mol.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Computing Resonant Inelastic X-Ray Scattering Spectra Using The Density Matrix Renormalization Group Method

We present a method for computing the resonant inelastic x-ray scattering (RIXS) spectra in one-dimensional systems using the density matrix renormalization group (DMRG) method. By using DMRG to address this problem, we shift the computational bottleneck from the memory requirements associated with exact diagonalization (ED) calculations to the computational time associated with the DMRG algorithm. This approach is then used to obtain RIXS spectra on cluster sizes well beyond state-of-the-art ED techniques. Using this new procedure, we compute the low-energy magnetic excitations observed in Cu L-edge RIXS for the challenging corner shared CuO4 chains, both for large multi-orbital clusters and downfolded t-J chains. We are able to directly compare results obtained from both models defined in clusters with identical momentum resolution. In the strong coupling limit, we find that the downfolded t-J model captures the main features of the magnetic excitations probed by RIXS only after a uniform scaling of the spectra is made.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Preliminary Cyber-Informed Dynamic Branch Conditions for Analysis with the Dynamic Simplified Cyber MELCOR Model

Instrumentation and control of nuclear power is transforming from analog to modern digital assets. These control systems perform key safety and security functions. This transformation is occurring in new plant designs as well as in the existing fleet of plants as the operation of those plants is extended to 60 years. This transformation introduces new and unknown exploits involving both digital asset induced safety issues and security exploits. Traditional the open literature of nuclear power risk assessment tools and cyber security assessment methods have not been modified or developed to address the unique nature of cyber failure modes and of cyber security threats. Starting in 2015, Sandia National Laboratories (SNL) embarked on a two year dynamic cyber-risk informed project to facilitate the analysis of unique cyber failure modes and the time sequencing of cyber faults, both malicious and non-malicious, and impose those cyber exploits and cyber faults onto a nuclear power plant accident sequence simulator code to assess how cyber exploits and cyber faults could interact with a plant's digital instrumentation and control (DI and C) system in the absence of digital controls. This will be achieved by coupling SNL's existing dynamic scheduler code (ADAPT), nuclear accident simulator code (MELCOR), and cyber Emulytics code (SCEPTRE) to demonstrate real-time simulation of cyber exploits and their impact on automatic DI and C responses. Studying such potential time-sequenced cyber-attacks and their risks (i.e., the associated impact and the associated degree of difficulty to achieve the attack vector) as they pertain to accident management will provide a risk informed basis for developing effective cyber security controls for nuclear power. This paper will discuss the rationale behind the proposed generic cyber exploits for an abstracted Pressurized Water Reactor that has adopted a unified DI and C System. Other papers related to this project submitted to this conference discuss: - The MELCOR model for this abstracted reactor, called the Dynamic Simplified Cyber (DSC) model, - Modifications to ADAPT to: Extend the framework for multiple simulators, Incorporation of importance measures into dynamic event tree analysis, Sort and reduce the dynamic event tree based upon inputs to or outputs from the tree, and - A feasibility study for using density based clustering methods with dynamic time wrapping to cluster and prune dynamic event trees. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Effect of Ar Post-irradiations on Magnetic Properties of Cu-Implanted ZnO Single Crystals

Ar{sup +} post-irradiation effects on magnetic behavior of Cu{sup +}-implanted ZnO single crystals were studied. It was found that Cu{sup +}-implanted and Ar{sup +}-irradiated samples, even the primary sample, showed a magnetic moment (M{sub M}), but the saturation magnetization (M{sub S}) of Ar{sup +} post-irradiated on Cu{sup +} as-implanted one drastically decreased. Based on the first-principle method, it was drawn to the incomplete filling electronic configuration of the substituted Cu ion whose 3d orbital hybridized with O-2p contributing to the magnetism. The M{sub M} induced by the substituted Cu{sup +} ion was much less than that induced by the substituted Cu{sup 2+} and Cu{sup 3+} ion, so the ratio of Cu{sup 2+,3+}/Cu{sup +} decreased after Ar{sup +} post-irradiation, leading to the decrease of M{sub S}. The excessive concentration of O vacancy induced by post-irradiation also weakened the M{sub M} by their compensating electrons, and decreased the effective magnetic exchange coupling interaction. Cu-related clusters dissolution was also a critical reason for the reduction of M{sub S}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Ground state of naphthyl cation: Singlet or triplet?

We present a benchmark theoretical investigation on the electronic structure and singlet-triplet(S-T) gap of 1- and 2-naphthyl cations using the CCSD(T) method. Our calculations reveal that the ground states of both the naphthyl cations are singlet, contrary to the results obtained by DFT/B3LYP calculations reported in previous theoretical studies. However, the triplet states obtained in the two structural isomers of naphthyl cation are completely different. The triplet state in 1-naphthyl cation is (π,σ) type, whereas in 2-naphthyl cation it is (σ,σ{sup ′}) type. The S-T gaps in naphthyl cations and the relative stability ordering of the singlet and the triplet states are highly sensitive to the basis-set quality as well as level of correlation, and demand for inclusion of perturbative triples in the coupled-cluster ansatz.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A review on recent machine learning applications for imaging mass spectrometry studies

Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology, chemistry, and materials science fields that continue to expand. IMS provides a qualitative compositional analysis and spatial mapping with high chemical specificity. The spatial mapping information can be 2D or 3D depending on the analysis technique employed. Due to the combination of complex mass spectra coupled with spatial information, large high-dimensional datasets (hyperspectral) are often produced. Therefore, the use of automated computational methods for an exploratory analysis is highly beneficial. The fast-paced development of artificial intelligence (AI) and machine learning (ML) tools has received significant attention in recent years. These tools, in principle, can enable the unification of data collection and analysis into a single pipeline to make sampling and analysis decisions on the go. There are various ML approaches that have been applied to IMS data over the last decade. Here, in this review, we discuss recent examples of the common unsupervised (principal component analysis, non-negative matrix factorization, k-means clustering, uniform manifold approximation and projection), supervised (random forest, logistic regression, XGboost, support vector machine), and other methods applied to various IMS datasets in the past five years. The information from this review will be useful for specialists from both IMS and ML fields since it summarizes current and representative studies of computational ML-based exploratory methods for IMS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Systematics of E 2 strength in the s d shell with the valence-space in-medium similarity renormalization group

Recent developments in ab initio nuclear theory demonstrate promising results in medium- to heavy-mass nuclei. A particular challenge for many of the many-body methodologies, however, is an accurate treatment of the electric-quadrupole, E2, strength associated with collectivity. The valence-space in-medium similarity renormalization group (VS-IMSRG) is a particularly powerful method for accessing medium- and high-mass nuclei but has been found to underpredict E2 strengths. The purpose of this work is to evaluate the isospin dependence of this underprediction. We perform a systematic comparison of VS-IMSRG calculations with available literature. We make use of isoscalar and isovector contributions to the E2 matrix elements to assess isoscalar and isovector contributions to the missing strength. It is found that the E2 strength is consistent throughout T z =|12|, T z =|1|, T z =|32|, and T z =2 pairs within the sd shell. Furthermore, no isovector contribution to the deficiency is identified. A comparison with toy-models and coupled-cluster calculations is used to discuss potential origins of the missing strength, which arises from missing many-particle, many-hole excitations out of the model space. The absence of any significant isovector contribution to the missing E2 strength indicates that the E2 strength discrepancy, and therefore any correction, is largely independent of the isospin of the nuclei in question.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Archaeal Inorganic Pyrophosphatase Displays Robust Activity under High-Salt Conditions and in Organic Solvents

Soluble inorganic pyrophosphatases (PPAs) that hydrolyze inorganic pyrophosphate (PP i ) to orthophosphate (P i ) are commonly used to accelerate and detect biosynthetic reactions that generate PP i as a by-product. Current PPAs are inactivated by high salt concentrations and organic solvents, which limits the extent of their use. Here we report a class A type PPA of the haloarchaeon Haloferax volcanii (HvPPA) that is thermostable and displays robust PP i -hydrolyzing activity under conditions of 25% (vol/vol) organic solvent and salt concentrations from 25 mM to 3 M. HvPPA was purified to homogeneity as a homohexamer by a rapid two-step method and was found to display non-Michaelis-Menten kinetics with a V max of 465 U · mg –1 for PP i hydrolysis (optimal at 42°C and pH 8.5) and Hill coefficients that indicated cooperative binding to PP i and Mg 2+ . Similarly to other class A type PPAs, HvPPA was inhibited by sodium fluoride; however, hierarchical clustering and three-dimensional (3D) homology modeling revealed HvPPA to be distinct in structure from characterized PPAs. In particular, HvPPA was highly negative in surface charge, which explained its extreme resistance to organic solvents. To demonstrate that HvPPA could drive thermodynamically unfavorable reactions to completion under conditions of reduced water activity, a novel coupled assay was developed; HvPPA hydrolyzed the PP i by-product generated in 2 M NaCl by UbaA (a “salt-loving” noncanonical E1 enzyme that adenylates ubiquitin-like proteins in the presence of ATP). Altogether, we demonstrate HvPPA to be useful for hydrolyzing PP i under conditions of reduced water activity that are a hurdle to current PPA-based technologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Leisingera sp. ANG59 & Pseudoalteromonas sp. JC28 Genomes Overview

The Hawaiian bobtail squid, Euprymna scolopes, has a symbiotic bacterial consortium in the accessory nidamental gland (ANG), a female reproductive organ that protects eggs against fouling microorganisms. To test the antibacterial activity of ANG community members, 19 bacterial isolates were screened for their ability to inhibit Gram-negative and Gram-positive bacteria, of which two strains were inhibitory. These two antibacterial isolates, Leisingera sp. ANG59 and Pseudoalteromonas sp. JC28, were subjected to further genomic characterization. Genomic analysis of Leisingera sp. ANG59 revealed a biosynthetic gene cluster encoding the antimicrobial compound indigoidine. The genome of Pseudoalteromonas sp. JC28 had a 14-gene cluster with >95% amino acid identity to a known bromoalterochromide (BAC) cluster. Chemical analysis confirmed production of known BACs, BAC-A/A′ (compounds 1a/1b), as well as two new derivatives, BAC-D/D′ (compounds 2a/2b). Extensive nuclear magnetic resonance (NMR) analyses allowed complete structural elucidation of compounds 2a/2b, and the absolute stereochemistry was unambiguously determined using an optimized Marfey’s method. The BACs were then investigated for in vitro antibacterial, antifungal, and nitric oxide (NO) inhibitory activity. Compounds 1a/1b were active against the marine bacteria Bacillus algicola and Vibrio fischeri, while compounds 2a/2b were active only against B. algicola. Compounds 1a/1b inhibited NO production via lipopolysaccharide (LPS)-induced inflammation in RAW264.7 macrophage cells and also inhibited the pathogenic fungus Fusarium keratoplasticum, which, coupled with their antibacterial activity, suggests that these polyketide-nonribosomal peptides may be used for squid egg defense against potential pathogens and/or fouling microorganisms. These results indicate that BACs may provide Pseudoalteromonas sp. JC28 an ecological niche, facilitating competition against nonsymbiotic microorganisms in the host’s environment.​

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The attractive features of natural gas as well as the growing electric power demand worldwide have created increasing interest in natural-gas-based distributed generation applications for electric distribution networks. Here, this paper investigates the interdependency between a residential natural gas network and an electric distribution network that are linked together via fuel cells. The modeling of the natural gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the natural gas network and the electric distribution grid, subject to the constraints imposed by both networks. In addition, a probabilistic model for both gas and electricity demands is developed based on historical electricity and natural gas demand data. A K-means clustering method is used to determine the hourly load states to solve the joint probabilistic optimization problem. Simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution network and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Best estimate plus uncertainty analysis of departure from nucleate boiling limiting case with CASL core simulator VERA-CS in response to PWR main steam line break event

VERA-CS (Virtual Environment for Reactor Applications, Core Simulator) is a coupled neutron transport and thermal-hydraulics subchannel code under development by the Consortium for Advanced Simulation of Light Water Reactors (CASL). VERA-CS was used to simulate a typical pressurized water reactor (PWR) full core response with 17x17 fuel assemblies for a main steam line break (MSLB) accident scenario with the most reactive rod cluster control assembly stuck out of the core. The accident scenario was initiated at the hot zero power (HZP) at the end of the first fuel cycle with return to power state points that were determined by a system analysis code and the most limiting state point was chosen for core analysis. The best estimate plus uncertainty (BEPU) analysis method was applied using Wilks’ nonparametric statistical approach. In this way, 59 full core simulations were performed to provide the minimum departure from nucleate boiling ratio (MDNBR) at the 95/95 (95% probability with 95% confidence level) tolerance limit. The results show that this typical PWR core remains within MDNBR safety limits for the MSLB accident.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1998

Transport of Light Ions in Matter

A recent set of light ion experiments are analyzed using the Green's function method of solving the Boltzmann equation for ions of high charge and energy (the GRNTRN transport code) and the NUCFRG2 fragmentation database generator code. Although the NUCFRG2 code reasonably represents the fragmentation of heavy ions, the effects of light ion fragmentation requires a more detailed nuclear model including shell structure and short range correlations appearing as tightly bound clusters in the light ion nucleus. The most recent NTJCFRG2 code is augmented with a quasielastic alpha knockout model and semiempirical adjustments (up to 30 percent in charge removal) in the fragmentation process allowing reasonable agreement with the experiments to be obtained. A final resolution of the appropriate cross sections must await the full development of a coupled channel reaction model in which shell structure and clustering can be accurately evaluated.

Wilson, J. W.↗
DOE OSTI2014

The HCO{sup +}–H{sub 2} van der Waals interaction: Potential energy and scattering

We compute the rigid-body, four-dimensional interaction potential between HCO{sup +} and H{sub 2}. The ab initio energies are obtained at the coupled-cluster single double triple level of theory, corrected for Basis Set Superposition Errors. The ab initio points are fit onto the spherical basis relevant for quantum scattering. We present elastic and rotationally inelastic coupled channels scattering between low lying rotational levels of HCO{sup +} and para-/ortho-H{sub 2}. Results are compared with similar earlier computations with He or isotropic para-H{sub 2} as the projectile. Computations agree with earlier pressure broadening measurements.

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

Arrested Phase Separation in Double-Exchange Models: Large-Scale Simulation Enabled by Machine Learning

In this work, we present large-scale dynamical simulations of electronic phase separation in the single-band double-exchange model based on deep-learning neural-network potentials trained from small-size exact diagonalization solutions. We uncover an intriguing correlation-induced freezing behavior as doped holes are segregated from half filled insulating background during equilibration. While the aggregation of holes is stabilized by the formation of ferromagnetic clusters through Hund’s coupling between charge carriers and local magnetic moments, this stabilization also creates confining potentials for holes when antiferromagnetic spin-spin correlation is well developed in the background. The dramatically reduced mobility of the self-trapped holes prematurely disrupts further growth of the ferromagnetic clusters, leading to an arrested phase separation. Implications of our findings for phase separation dynamics in materials that exhibit colossal magnetoresistance effect are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Correlations between Molecular Structure, Solvation Topology, and Transport Properties of Aqueous Organic Flow Battery Electrolyte Solutions

Aqueous organic redox flow batteries (AORFBs) are considered promising technologies for storing energy generated from renewable resources. However, designing organic electrolyte molecules is limited by gaps between fundamental understanding of coupling between solvation structure and dynamics, and macroscopic transport properties like viscosity. Herein, we used molecular dynamics simulations to understand correlations between ionic molecular structures, ion clustering, and transport properties in 2,3-dihydrophenazine (2,3-DHP), a promising AORFB anolyte. We show that experimentally measured viscosity can be reproduced from simulations at relevant concentrations and that the asymmetric structure of 2,3-DHP leads to unique inhomogeneity in the solvation topology. However, order parameters and metrics need to be developed for better correlations over spatiotemporal scales, with careful consideration of the inhomogeneity of organic anolyte molecules. In conclusion, we show that the increased size and asymmetry of the anolyte leads to breakdown of assumptions within methods for determining ion transport mechanisms previously developed for Li-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data Augmentation

In the field of computational chemistry, predicting bond dissociation energies (BDEs) presents well-known challenges, particularly due to the multireference character of reactive systems. Many chemical reactions involve configurations where single-reference methods fall short, as the electronic structure can significantly change during bond breaking. As generating training data for partially broken bonds is a challenging task, even state-of-the-art reactive machine learning interatomic potentials (MLIPs) often fail to predict reliable BDEs and smooth dissociation curves. By contrast, simple and inexpensive physics-based models, such as the well-established Morse potential, do not suffer from any such limitations. This work leverages the Morse potential to improve reactive MLIPs by augmenting the training data set with inexpensive Morse data along the dissociation pathways. Further, this physics-constrained data augmentation (PCDA) approach results in MLIPs with smooth bond dissociation curves as well as near coupled-cluster level BDEs, all without requiring any expensive multireference quantum mechanical calculations. A case study for methane combustion demonstrates how the PCDA approach can improve an existing reactive MLIP, namely, ANI-1xnr. In conclusion, not only are the BDEs and bond dissociation curves for all radicals and molecules significantly improved compared to ANI-1xnr but the PCDA-trained MLIP retains the reliability of ANI-1xnr when performing reactive molecular dynamics simulations.

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

Quorum Quenching of Nitrobacter winogradskyi Suggests that Quorum Sensing Regulates Fluxes of Nitrogen Oxide(s) during Nitrification

ABSTRACT Quorum sensing (QS) is a widespread process in bacteria used to coordinate gene expression with cell density, diffusion dynamics, and spatial distribution through the production of diffusible chemical signals. To date, most studies on QS have focused on model bacteria that are amenable to genetic manipulation and capable of high growth rates, but many environmentally important bacteria have been overlooked. For example, representatives of proteobacteria that participate in nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, produce QS signals called acyl-homoserine lactones (AHLs). Nitrification emits nitrogen oxide gases (NO, NO 2 , and N 2 O), which are potentially hazardous compounds that contribute to global warming. Despite considerable interest in nitrification, the purpose of QS in the physiology/ecology of nitrifying bacteria is poorly understood. Through a quorum quenching approach, we investigated the role of QS in a well-studied AHL-producing nitrite oxidizer, Nitrobacter winogradskyi . We added a recombinant AiiA lactonase to N. winogradskyi cultures to degrade AHLs to prevent their accumulation and to induce a QS-negative phenotype and then used mRNA sequencing (mRNA-Seq) to identify putative QS-controlled genes. Our transcriptome analysis showed that expression of nirK and nirK cluster genes ( ncgABC ) increased up to 19.9-fold under QS-proficient conditions (minus active lactonase). These data led to us to query if QS influenced nitrogen oxide gas fluxes in N. winogradskyi . Production and consumption of NO x increased and production of N 2 O decreased under QS-proficient conditions. Quorum quenching transcriptome approaches have broad potential to identify QS-controlled genes and phenotypes in organisms that are not genetically tractable. IMPORTANCE Bacterial cell-cell signaling, or quorum sensing (QS), is a method of bacterial communication and gene regulation that is well studied in bacteria. However, little is known about the purpose of QS in many environmentally important bacteria. Here, we demonstrate quorum quenching coupled with mRNA-Seq to identify QS-controlled genes and phenotypes in Nitrobacter winogradskyi , a nitrite-oxidizing bacterium. Nitrite oxidizers play an important role in the nitrogen cycle though their participation in nitrification, the aerobic oxidation of ammonia to nitrate via nitrite. Our quorum quenching approach revealed that QS influences production and consumption of environmentally important nitrogen oxide gases (NO, NO 2 , and N 2 O) in N. winogradskyi . This study demonstrated a novel technique for studying QS in difficult-to-work-with microorganisms and showed that nitrite oxidizers might also contribute to nitrification-dependent production of nitrogen oxide gases that contribute to global warming.

Mellbye, Brett L.↗
DOE OSTI2023

Modeling diffusion and types I-V sorption of water vapor in heterogeneous systems

Here, a sorption and diffusion model is developed using a mobile-immobile decomposition of the vapor concentration. Henry’s mode represents the mobile species which diffuses through the solid, while Langmuir and pooling modes represent possible immobilization processes that cause nonlinearities in sorption capacity. The model can simulate the five classical sorption types and can incorporate additional dynamics compared to models based on thermodynamic equilibrium. Additionally, the framework allows for discontinuities in material properties encountered in multi-material systems. The resulting non-linear coupled equations are solved by employing a finite element method to discretize in space, and a backward Euler method to discretize in time. The discretized system of equations is solved via a Newton-type iteration scheme at each time-step. Four different materials are parameterized for the model, which are then used in examples to demonstrate the model’s ability to capture complex sorption processes in multi-material systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗