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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Impact of solvation on the electronic resonances in uracil

Interactions of low-energy electrons with the DNA and RNA nucleobases are known to form metastable states, known as electronic resonances. In this work, we study electron attachment to solvated uracil, an RNA nucleobase, using the orbital stabilization method at the Equation of Motion-Coupled Cluster for Electron Affinities with Singles and Doubles (EOM-EA-CCSD) level of theory with the Effective Fragment Potential (EFP) solvation method. We benchmarked the approach using multireference methods, as well as by comparing EFP and full quantum calculations. The impact of solvation on the first one particle (1p) shape resonance, formed by electron attachment to the π* LUMO orbital, as well as the first two particle one hole (2p1h) resonance, formed by electron attachment to neutral uracil's π–π* excited state, was investigated. We used molecular dynamics simulations for solvent configurations and applied charge stabilization technique-based biased sampling to procure configurations adequate to cover the entire range of the electron attachment energy distribution. The electron attachment energy in solution is found to be distributed over a wide range of energies, between 4.6 eV to 6.8 eV for the 2p1h resonance, and between −0.1 eV to 2 eV for the 1p resonance. The solvent effects were similar for the two resonances, indicating that the exact electron density of the state is not as important as the solvent configurations. Multireference calculations extended the findings showing that solvation effects are similar for the lowest four resonances, further indicating that the specific solute electron density is not as important, but rather the water configurations play the most important role in solvation effects. Lastly, by comparing bulk solvation to clusters of uracil with a few water molecules around it, we find that the impact of microsolvation is very different from that of bulk solvation.

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

A Generic Advanced Computing Framework for Executing Windows-based Dynamic Contingency Analysis Tool in Parallel on Cluster Machines

Dynamic contingency analysis tool (DCAT) has been developed to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. By including more customized protection models and corrective actions into the Windows-based commercial tools, DCAT can help operators understand the cascading behavior and find mitigation approaches to reduce the risk of cascading outages in a more realistic manner. In order to further enhance the capability of DCAT, this paper presents a design of an advanced computing framework that enables DCAT to run on a cluster machine to improve its computational performance. This framework is generic and can be applied to other Windows-based simulation tools to fill the technical gap of applying advanced computing technology to vendors' Windows-based tools. The preliminary tests using medium to large power systems have shown the effectiveness of this framework and its potential for accelerating the adoption of advanced computing in utilities.

Advanced computing, dynamic contingency analysis, ↗
NASA NTRS1999

HST Observations of New Horizontal Branch Structures in the Globular Cluster w Centauri

The globular cluster omega Centauri contains the largest known population of very hot horizontal branch (HB) stars. We have used the Hubble Space Telescope to obtain a far-UV/optical color-magnitude diagram of three fields in omega Cen. We find that over 30% of the HB objects are "extreme" HB or hot post-HB stars. A wide gap in the color distribution of the hot HB stars may correspond to gaps found earlier in several other clusters, which argues for a common mass loss mechanism. The diagram contains a significant population of hot sub-HB stars, which we interpret as the "blue-hook" objects predicted by D'Cruz (1996a). These are produced by late He-flashes in stars which have undergone unusually large giant branch mass loss. Omega Cen has a well-known spread of metal abundance, and the diagram is consistent with a giant branch mass loss efficiency which increases with metallicity. There is no evidence for a dynamical origin of the hot HB stars.

Stecher, Theodore↗
DOE OSTI2020

Tomographic galaxy clustering with the Subaru Hyper Suprime-Cam first year public data release

We analyze the clustering of galaxies in the first public data release of the HSC Subaru Strategic Program. Despite the relatively small footprints of the observed fields, the data are an excellent proxy for the deep photometric datasets that will be acquired by LSST, and are therefore an ideal test bed for the analysis methods being implemented by the LSST DESC. We select a magnitude limited sample with i<24.5 and analyze it in four redshift bins covering 0.15≲z≲1.5. We carry out a Fourier-space analysis of the two-point clustering of this sample, including all auto- and cross-correlations. We demonstrate the use of map-level deprojection methods to account for fluctuations in the galaxy number density caused by observational systematics. Through an HOD analysis, we place constraints on the characteristic halo masses of this sample, finding a good fit up to scales k max = 1Mpc –1 , including both auto- and cross-correlations. Our results show monotonically decreasing average halo masses, which can be interpreted in terms of the drop-out of red galaxies at high redshifts for a flux-limited sample. In terms of photometric redshift systematics, we show that additional care is needed in order to marginalize over uncertainties in the redshift distribution in galaxy clustering, and that these uncertainties can be constrained by including cross-correlations. We are able to make a ~3σ detection of lensing magnification in the HSC data. Our results are stable to variations in σ 8 and Ω c and we find constraints that agree well with measurements from Planck and low-redshift probes. Lastly, we use our pipeline to study the clustering of galaxies as a function of limiting flux, and provide a simple fitting function for the linear galaxy bias for magnitude limited samples as a function of limiting magnitude and redshift.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Enabling Efficient and Accurate Computational Studies of MOF Reactivity via QM/MM and QM/QM Methods

Electronic structure calculations can provide unique insight into metal–organic framework (MOF) reactivity and defect formation. Such calculations can be broadly categorized as utilizing either periodic or cluster models, each with their respective advantages and disadvantages. In the present study, we demonstrate how multiscale methods can leverage the advantages of both approaches to enable high levels of accuracy and computational efficiency in studies of MOF reactivity. Using defect formation in a zeolitic imidazolate framework (ZIF) as a prototypical example, we benchmark a quantum mechanics/molecular mechanics (QM/MM) scheme that enables highly efficient cluster-based calculations on MOFs. We demonstrate the importance of correctly accounting for the influence of both dative bond cleavage in the QM cluster and long-range mechanical coupling to the bulk to achieving accurate QM/MM studies of MOFs. We subsequently leverage these cluster models in a QM/QM scheme that goes beyond standard DFT to yield “gold-standard” correlated wave function results on MOFs at modest computational cost. Crucially, we find several cases in which the incorporation of these correlated corrections yields qualitatively important corrections over conventional DFT values.

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

The Effect of Geometry, Spin, and Orbital Optimization in Achieving Accurate, Correlated Results for Iron–Sulfur Cubanes

Iron–sulfur clusters comprise an important functional motif in the catalytic centers of biological systems, capable of enabling important chemical transformations at ambient conditions. This remarkable capability derives from a notoriously complex electronic structure that is characterized by a high density of states that is sensitive to geometric changes. The spectral sensitivity to subtle geometric changes has received little attention from correlated, large active space calculations, owing partly to the exceptional computational complexity for treating these large and correlated systems accurately. Here, to provide insight into this aspect, we report the first Complete Active Space Self Consistent Field (CASSCF) calculations for different geometries of the [Fe(II/III) 4 S 4 (SMe) 4 ] -2 clusters using two complementary, correlated solvers: spin-pure Adaptive Sampling Configuration Interaction (ASCI) and Density Matrix Renormalization Group (DMRG). We find that the previously established picture of a double-exchange driven magnetic structure, with minute energy gaps (<1 mHa) between consecutive spin states, has a weak dependence on the underlying geometry. However, the spin gap between the singlet and the spin state 2S + 1 = 19, corresponding to a maximal number of Fe-d electrons being unpaired and of parallel spin, is strongly geometry dependent, changing by a factor of 3 upon slight deformations that are still within biologically relevant parameters. The CASSCF orbital optimization procedure, using active spaces as large as 86 electrons in 52 orbitals, was found to reduce this gap compared to typical mean-field orbital approaches. Our results show the need for performing large active space calculations to unveil the challenging electronic structure of these complex catalytic centers and should serve as accurate starting points for fully correlated treatments upon inclusion of dynamical correlation outside the active space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Redshift evolution and covariances for joint lensing and clustering studies with DESI Y1

ABSTRACT Galaxy–galaxy lensing (GGL) and clustering measurements from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) data set promise to yield unprecedented combined-probe tests of cosmology and the galaxy–halo connection. In such analyses, it is essential to identify and characterize all relevant statistical and systematic errors. We forecast the covariances of DESI Y1 GGL + clustering measurements and the systematic bias due to redshift evolution in the lens samples. Focusing on the projected clustering and GGL correlations, we compute a Gaussian analytical covariance, using a suite of N-body and lognormal simulations to characterize the effect of the survey footprint. Using the DESI one percent survey data, we measure the evolution of galaxy bias parameters for the DESI luminous red galaxy (LRG) and bright galaxy survey (BGS) samples. We find mild evolution in the LRGs in $0.4 < z < 0.8$, subdominant to the expected statistical errors. For BGS, we find less evolution for brighter absolute magnitude cuts, at the cost of reduced sample size. We find that for a redshift bin width $\Delta z = 0.1$, evolution effects on DESI Y1 GGL is negligible across all scales, all fiducial selection cuts, all fiducial redshift bins. Galaxy clustering is more sensitive to evolution due to the bias squared scaling. Nevertheless the redshift evolution effect is insignificant for clustering above the 1-halo scale of $0.1h^{-1}$ Mpc. For studies that wish to reliably access smaller scales, additional treatment of redshift evolution is likely needed. This study serves as a reference for GGL and clustering studies using the DESI Y1 sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Carboxylate binding prefers two cations to one

Almost all studies of specific ion binding by carboxylates (–COO - ) have considered only a single cation, but clustering of ions and ligands is a common phenomenon. We apply density functional theory to investigate how variations in the number of acetate ligands in binding to two monovalent cations affects ion binding preferences. We study a series of monovalent (Li + , Na + , K + , Cs + ) ions relevant to experimental work on many topics, including ion channels, battery storage, water purification and solar cells. We find that the preferred optimal structure has 3 acetates except for Cs + , which has 2 acetates. The optimal coordination of the cation by the carboxylate O atoms is 4 for both Na + and K + , and 3 for Li + and Cs + . There is a 4-fold coordination minimum just a few kcal mol -1 higher than the optimal 3-fold structure for Li+. For two cations, multiple minima occur in the vicinity of the lowest free energy state. Here we find that, for Li, Na and K, the preferred optimal structure with two cations is favored over a mixture of single cation complexes, providing a basis for understanding ionic cluster formation that is relevant for engineering proteins and other materials for rapid, selective ion transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Probing degradation at solid-state battery interfaces using machine-learning interatomic potential

Solid-state batteries featuring fast ion-conducting solid electrolytes are promising next-generation energy storage technologies, yet challenges remain for practical deployment due to electro-chemo-mechanical instabilities at solid-solid interfaces. These interfaces, which include homogeneous/internal interfaces such as grain boundaries (GBs) and heterogeneous/external interfaces between solid-electrolyte and electrode materials, can impede Li-ion transport, deteriorate performance, and eventually lead to cell failure. Here, in this study, we leverage large-scale molecular simulations, enabled by validated machine-learning interatomic potentials, to directly probe the onset of interfacial degradation at the garnet Li 7 La 3 Zr 2 O 12 (LLZO) solid-electrolyte/LiCoO 2 (LCO) cathode interface. By surveying different interfacial geometries and compositions, it is found that Li-deficient interfaces can lead to severe interfacial disordering with cation mixing and Co interdiffusion from LCO into LLZO. By contrast, Li-sufficient interfaces are less disordered, although elemental segregation with local ordering is observed. As a consequence of Co interdiffusion, Co-rich regions are formed at the GBs of LLZO due to cation segregation and trapping effects. This behavior is independent of the GB tilting axis, degree of disorder at the GBs, and Co concentration, which implies Co clustering at GBs is a general phenomenon in polycrystalline LLZO and can dictate its overall transport and mechanical properties. Our findings elucidate the underlying fundamental mechanisms that give rise to experimentally observed physicochemical properties and provide guidelines for interface design that can mitigate interfacial degradation and improve cycling performance.

25 ENERGY STORAGE↗
DOE OSTI2021

The critical role of synthesis conditions on small polaron carrier concentrations in hematite—A first-principles study

Achieving highly efficient energy conversion with transition metal oxides necessitates overcoming conductivity limitations due to the formation of small polarons. Detailed understanding of the interplay among intrinsic defects, dopants, and electron polarons can help devise strategies for achieving higher carrier concentrations, therefore improving carrier conductivity. This work employs first-principles calculations to reliably predict electron polaron concentrations in a prominent polaronic oxide, hematite (Fe 2 O 3 ), by resolving interactions between charged defects and electron polarons and keeping charge neutrality condition among all charged species. This work addresses that both V O and Fe i can be primary donors in undoped hematite depending on the synthesis conditions, such as synthesis temperature and oxygen partial pressure, despite the fact that V O owns an extremely high ionization energy compared to k B T. Furthermore, from calculations of a plethora of n-type dopants (group IV and V elements), we find that Ti, Ge, Sb, and Nb are able to raise electron polaron concentrations in hematite significantly without considering dopant clustering. However, the magnitude of electron polaron concentration increase would be smaller if the dopant has a high tendency of clustering, such as Ti. Here we reveal the critical role of synthesis conditions on tuning electron polaron concentrations of both undoped and doped hematite. Our theoretical analysis provides important insights and general design principles for engineering more conductive polaronic oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dark Energy Survey Year 3 results: galaxy sample for BAO measurement

Here, we present and validate the galaxy sample used for the analysis of the baryon acoustic oscillation (BAO) signal in the Dark Energy Survey (DES) Y3 data. The definition is based on a colour and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.5, while ensuring a high-quality determination. The sample covers ~ 4100 square degrees to a depth of i = 22.3 (AB) at 10σ. It contains 7,031,993 galaxies in the redshift range from z = 0.6 to 1.1, with a mean effective redshift of 0.835. Redshifts are estimated with the machine learning algorithm DNF, and are validated using the VIPERS PDR2 sample. We find a mean redshift bias of z bias ~ 0.01 and a mean uncertainty, in units of 1 + z, of σ 68 ~ 0.03$. We evaluate the galaxy population of the sample, showing it is mostly built upon Elliptical to Sbc types. Furthermore, we find a low level of stellar contamination of ≲ 4 %. We present the method used to mitigate the effect of spurious clustering coming from observing conditions and other large-scale systematics. We apply it to the BAO sample and calculate weights that are used to get a robust estimate of the galaxy clustering signal. This paper is one of a series dedicated to the analysis of the BAO signal in DES Y3. In the companion papers, we present the galaxy mock catalogues used to calibrate the analysis and the angular diameter distance constraints obtained through the fitting to the BAO scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Gene and genome duplications have contrasting impacts on biosynthetic and flower developmental pathways in California poppy

Benzylisoquinoline alkaloids (BIAs) represent a vast group of specialized plant metabolites with diverse pharmaceutical applications, synthesized by a variety of gene families. Among the multiple plant lineages that produce BIAs, the most notable is the poppy family (Papaveraceae), with California poppy (Eschscholzia californica) emerging as a model organism. Here, we report a haplotype-resolved genome assembly, in combination with a high-density expression atlas, for California poppy. Genome analyses reveal recent diversification of BIA biosynthesis genes in poppy through localized duplications. Furthermore, we demonstrate that the degree of phylogenetic relatedness among paralogs within BIA biosynthesis-associated gene families correlates with similarities in gene expression. In contrast, gene families involved in carotenoid biosynthesis, which contributes to the intense orange petal pigmentation, are not phylogenetically clustered, and floral developmental regulators exhibit a high degree of retention of gene duplicates associated with ancient polyploidy events. These findings illustrate alternative roles for gene and genome duplications as drivers of trait evolution. Given the position of California poppy in the angiosperm phylogeny, the high-quality genomic resources generated for this work constitute a valuable resource for comparative genomic and transcriptomic analyses for poppies and flowering plants more generally.

Rössner, Le-Han [Justus-Liebig University, Giessen↗
DOE OSTI2022

The emergence and transmission dynamics of HIV-1 CRF07_BC in Mainland China

A total of 1155 partial pol gene sequences of human immunodeficiency virus (HIV)-1 CRF07_BC were sampled between 1997 and 2015, spanning 13 provinces in Mainland China and risk groups [heterosexual, injecting drug users (IDU), and men who have sex with men (MSM)] to investigate the evolution, adaptation, spatiotemporal and risk group dynamics, migration patterns, and protein structure of HIV-1 CRF07_BC. Due to the unequal distribution of sequences across time, location, and risk group in the complete dataset (‘full1155’), subsampling methods were used. Maximum-likelihood and Bayesian phylogenetic analysis as well as discrete trait analysis of geographical location and risk group were carried out. To study mutations of a cluster of HIV-1 CRF07_BC (CRF07-1), we performed a comparative analysis of this cluster to the other CRF07_BC sequences (‘backbone_295’) and mapped the mutations observed in the respective protein structure. Our findings showed that HIV-1 CRF07_BC most likely originated among IDU in Yunnan Province between October 1992 to July 1993 [95 per cent hightest posterior density (HPD): May 1989–August 1995] and that IDU in Yunnan Province and MSM in Guangdong Province likely served as the viral sources during the early and more recent spread in Mainland China. We also revealed that HIV-1 CRF07-1 has been spreading for roughly 20 years and continues to cause local transmission in Mainland China and worldwide. Overall, our study sheds light on the dynamics of HIV-1 CRF07_BC distribution patterns in Mainland China. Our research may also be useful in formulating public health policies aimed at controlling acquired immune deficiency syndrome in Mainland China and globally.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women

Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditional topic modeling, such as Latent Dirichlet Allocation (LDA), faces limitations in capturing the semantic relationships in the text document although it has been widely applied in text mining. BERTopic, created in 2022, leveraged advances in deep learning and can capture the contextual relationships between words. In this work, we integrated Artificial Intelligence (AI) modules to LDA and BERTopic and provided a comprehensive comparison on the analysis of prescription opioid-related cardiovascular risks in women. Opioid use can increase the risk of cardiovascular problems in women such as arrhythmia, hypotension etc. 1,837 abstracts were retrieved and downloaded from PubMed as of April 2024 using three Medical Subject Headings (MeSH) words: “opioid,” “cardiovascular,” and “women.” Machine Learning of Language Toolkit (MALLET) was employed for the implementation of LDA. BioBERT was used for document embedding in BERTopic. Eighteen was selected as the optimal topic number for MALLET and 23 for BERTopic. ChatGPT-4-Turbo was integrated to interpret and compare the results. The short descriptions created by ChatGPT for each topic from LDA and BERTopic were highly correlated, and the performance accuracies of LDA and BERTopic were similar as determined by expert manual reviews of the abstracts grouped by their predominant topics. The results of the t-SNE (t-distributed Stochastic Neighbor Embedding) plots showed that the clusters created from BERTopic were more compact and well-separated, representing improved coherence and distinctiveness between the topics. Our findings indicated that AI algorithms could augment both traditional and contemporary topic modeling techniques. In addition, BERTopic has the connection port for ChatGPT-4-Turbo or other large language models in its algorithm for automatic interpretation, while with LDA interpretation must be manually, and needs special procedures for data pre-processing and stop words exclusion. Therefore, while LDA remains valuable for large-scale text analysis with resource constraints, AI-assisted BERTopic offers significant advantages in providing the enhanced interpretability and the improved semantic coherence for extracting valuable insights from textual data.

Research & Experimental Medicine↗
DOE OSTI2024

Light-Induced Charge Separation in Photosystem I from Different Biological Species Characterized by Multifrequency Electron Paramagnetic Resonance Spectroscopy

Photosystem I (PSI) serves as a model system for studying fundamental processes such as electron transfer (ET) and energy conversion, which are not only central to photosynthesis but also have broader implications for bioenergy production and biomimetic device design. In this study, we employed electron paramagnetic resonance (EPR) spectroscopy to investigate key light-induced charge separation steps in PSI isolated from several green algal and cyanobacterial species. Following photoexcitation, rapid sequential ET occurs through either of two quasi-symmetric branches of donor/acceptor cofactors embedded within the protein core, termed the A and B branches. Using high-frequency (130 GHz) time-resolved EPR (TR-EPR) and deuteration techniques to enhance spectral resolution, we observed that at low temperatures prokaryotic PSI exhibits reversible ET in the A branch and irreversible ET in the B branch, while PSI from eukaryotic counterparts displays either reversible ET in both branches or exclusively in the B branch. Furthermore, we observed a notable correlation between low-temperature charge separation to the terminal [4Fe-4S] clusters of PSI, termed F A and F B , as reflected in the measured F A /F B ratio. These findings enhance our understanding of the mechanistic diversity of PSI’s ET across different species and underscore the importance of experimental design in resolving these differences. Though further research is necessary to elucidate the underlying mechanisms and the evolutionary significance of these variations in PSI charge separation, this study sets the stage for future investigations into the complex interplay between protein structure, ET pathways, and the environmental adaptations of photosynthetic organisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Metalloproteomics Reveals Multi-Level Stress Response in Escherichia coli When Exposed to Arsenite

The arsRBC operon encodes a three-protein arsenic resistance system. ArsR regulates the transcription of the operon, while ArsB and ArsC are involved in exporting trivalent arsenic and reducing pentavalent arsenic, respectively. Previous research into Agrobacterium tumefaciens 5A has demonstrated that ArsR has regulatory control over a wide range of metal-related proteins and metabolic pathways. We hypothesized that ArsR has broad regulatory control in other Gram-negative bacteria and set out to test this. Here, we use differential proteomics to investigate changes caused by the presence of the arsR gene in human microbiome-relevant Escherichia coli during arsenite (AsIII) exposure. We show that ArsR has broad-ranging impacts such as the expression of TCA cycle enzymes during AsIII stress. Additionally, we found that the Isc [Fe-S] cluster and molybdenum cofactor assembly proteins are upregulated regardless of the presence of ArsR under these same conditions. An important finding from this differential proteomics analysis was the identification of response mechanisms that were strain-, ArsR-, and arsenic-specific, providing new clarity to this complex regulon. Given the widespread occurrence of the arsRBC operon, these findings should have broad applicability across microbial genera, including sensitive environments such as the human gastrointestinal tract.

Biochemistry & Molecular Biology↗
NASA NTRS1988

Nonlinear vortex trail dynamics

The nonlinear evolution of periodic disturbances on vortex trails is considered. In addition to following small initial perturbations, large amplitude initial disturbances of the vortex trails are also studied. It is shown that the equations support a rich variety of essentially nonlinear solutions including unbounded and quasisteady ones. These solutions are found to correspond to various modes of vortex clustering in the physical plane. At the close of the paper, comparisons of these results with recent numerical and experimental findings on the wakes behind stationary cylinders, and also transversely oscillating bluff objects, are made.

Lim, Chjan C.↗
NASA NTRS1992

The transition from diffuse to dense clouds

Studies of the relatively diffuse interstellar clouds where variations in the properties of the diffuse interstellar bands occur are reviewed, and the possible relationship between dust properties, as indicated by UV extinction, and other cloud characteristics is explored, with emphasis placed on relatively dense diffuse clouds. Some results from the literature on transitional or intermediate clouds are reviewed, and some recent findings are presented on one particular cloud, in front of the star BD+31 deg 643, in the small open cluster IC348, which is part of the Perseus II complex of dark clouds and OB associations. Tentative speculations about the possible status of the transitional clouds are discussed.

Snow, Theodore P.↗