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DOE OSTI2014

A self-interaction-free local hybrid functional: Accurate binding energies vis-à-vis accurate ionization potentials from Kohn-Sham eigenvalues

We present and test a new approximation for the exchange-correlation (xc) energy of Kohn-Sham density functional theory. It combines exact exchange with a compatible non-local correlation functional. The functional is by construction free of one-electron self-interaction, respects constraints derived from uniform coordinate scaling, and has the correct asymptotic behavior of the xc energy density. It contains one parameter that is not determined ab initio. We investigate whether it is possible to construct a functional that yields accurate binding energies and affords other advantages, specifically Kohn-Sham eigenvalues that reliably reflect ionization potentials. Tests for a set of atoms and small molecules show that within our local-hybrid form accurate binding energies can be achieved by proper optimization of the free parameter in our functional, along with an improvement in dissociation energy curves and in Kohn-Sham eigenvalues. However, the correspondence of the latter to experimental ionization potentials is not yet satisfactory, and if we choose to optimize their prediction, a rather different value of the functional's parameter is obtained. We put this finding in a larger context by discussing similar observations for other functionals and possible directions for further functional development that our findings suggest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Thermal weights for semiclassical vibrational response functions

Semiclassical approximations to response functions can allow the calculation of linear and nonlinear spectroscopic observables from classical dynamics. Evaluating a canonical response function requires the related tasks of determining thermal weights for initial states and computing the dynamics of these states. A class of approximations for vibrational response functions employs classical trajectories at quantized values of action variables and represents the effects of the radiation-matter interaction by discontinuous transitions. Here, we evaluate choices for a thermal weight function which are consistent with this dynamical approximation. Weight functions associated with different semiclassical approximations are compared, and two forms are constructed which yield the correct linear response function for a harmonic potential at any temperature and are also correct for anharmonic potentials in the classical mechanical limit of high temperature. Approximations to the vibrational linear response function with quantized classical trajectories and proposed thermal weight functions are assessed for ensembles of one-dimensional anharmonic oscillators. This approach is shown to perform well for an anharmonic potential that is not locally harmonic over a temperature range encompassing the quantum limit of a two-level system and the limit of classical dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Methane dissociation on Pt(111): Searching for a specific reaction parameter density functional

The theoretical description of methane dissociating on metal surfaces is a current frontier in the field of gas-surface dynamics. Dynamical models that aim at achieving a highly accurate description of this reaction rely on potential energy surfaces based on density functional theory calculations at the generalized gradient approximation. We focus here on the effect that the exchange-correlation functional has on the reactivity of methane on a metal surface, using CHD{sub 3} + Pt(111) as a test case. We present new ab initio molecular dynamics calculations performed with various density functionals, looking also at functionals that account for the van der Waals (vdW) interaction. While searching for a semi-empirical specific reaction parameter density functional for this system, we find that the use of a weighted average of the PBE and the RPBE exchange functionals together with a vdW-corrected correlation functional leads to an improved agreement with quantum state-resolved experimental data for the sticking probability, compared to previous PBE calculations. With this semi-empirical density functional, we have also investigated the surface temperature dependence of the methane dissociation reaction and the influence of the rotational alignment on the reactivity, and compared our results with experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

TRISO Fuel’s Safety Functions, Contributions to Reactor Safety, and Necessary Safety Limits

Safety functions are the actions, passive or active, that structures, systems, and components of nuclear facility that contribute to the safety of the workers, the public, or the environment. Well-defined safety functions are the foundation of a solid safety case for a reactor. For reactors that use TRISO-coated particles, the TRISO fuel plays an important part of the safety case because of its ability to contain radionuclides in the fuel itself. This ability enables the use of a functional containment strategy for the reactor where radionuclide retention is the primary safety function supported by the safety functions of controlling reactivity control and controlling heat rejection. This paper establishes at a deeper level the role that TRISO fuel plays in each of these safety functions and associated quality assurance and testing requirements for TRISO particle manufacturing to ensure these safety functions. Safety limits necessary to protect these safety functions include: operational limits, time at temperature limits, and fission gas release activity limits. In conclusion, this approach demonstrates the role that specific aspects of TRISO fuel play in protecting the safety of workers, the public, and the environment.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2011

MASS FUNCTION PREDICTIONS BEYOND {Lambda}CDM

The statistics of dark matter halos is an essential component of precision cosmology. The mass distribution of halos, as specified by the halo mass function, is a key input for several cosmological probes. The sizes of N-body simulations are now such that, for the most part, results need no longer be statistics-limited, but are still subject to various systematic uncertainties. Discrepancies in the results of simulation campaigns for the halo mass function remain in excess of statistical uncertainties and of roughly the same size as the error limits set by near-future observations; we investigate and discuss some of the reasons for these differences. Quantifying error sources and compensating for them as appropriate, we carry out a high-statistics study of dark matter halos from 67 N-body simulations to investigate the mass function and its evolution for a reference {Lambda}CDM cosmology and for a set of wCDM cosmologies. For the reference {Lambda}CDM cosmology (close to WMAP5), we quantify the breaking of universality in the form of the mass function as a function of redshift, finding an evolution of as much as 10% away from the universal form between redshifts z = 0 and z = 2. For cosmologies very close to this reference we provide a fitting formula to our results for the (evolving) {Lambda}CDM mass function over a mass range of 6 x 10{sup 11}-3 x 10{sup 15} M{sub sun} to an estimated accuracy of about 2%. The set of wCDM cosmologies is taken from the Coyote Universe simulation suite. The mass functions from this suite (which includes a {Lambda}CDM cosmology and others with w {approx_equal} -1) are described by the fitting formula for the reference {Lambda}CDM case at an accuracy level of 10%, but with clear systematic deviations. We argue that, as a consequence, fitting formulae based on a universal form for the mass function may have limited utility in high-precision cosmological applications.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

The Hubbard dimer: a density functional case study of a many-body problem

This review explains the relationship between density functional theory and strongly correlated models using the simplest possible example, the two-site Hubbard model. The relationship to traditional quantum chemistry is included. Even in this elementary example, where the exact ground-state energy and site occupations can be found analytically, there is much to be explained in terms of the underlying logic and aims of density functional theory. Although the usual solution is analytic, the density functional is given only implicitly. We overcome this difficulty using the Levy–Lieb construction to create a parametrization of the exact function with negligible errors. The symmetric case is most commonly studied, but we find a rich variation in behavior by including asymmetry, as strong correlation physics vies with charge-transfer effects. We explore the behavior of the gap and the many-body Green's function, demonstrating the 'failure' of the Kohn–Sham (KS) method to reproduce the fundamental gap. We perform benchmark calculations of the occupation and components of the KS potentials, the correlation kinetic energies, and the adiabatic connection. We test several approximate functionals (restricted and unrestricted Hartree–Fock and Bethe ansatz local density approximation) to show their successes and limitations. Here, we also discuss and illustrate the concept of the derivative discontinuity. Useful appendices include analytic expressions for density functional energy components, several limits of the exact functional (weak- and strong-coupling, symmetric and asymmetric), various adiabatic connection results, proofs of exact conditions for this model, and the origin of the Hubbard model from a minimal basis model for stretched H 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Density functional theory of material design: fundamentals and applications—II

Abstract This is the second and the final part of the review on density functional theory (DFT), referred to as DFT-II. In the first review, DFT-I, we have discussed wavefunction-based methods, their complexity, and basics of density functional theory. In DFT-II, we focus on fundamentals of DFT and their implications for the betterment of the theory. We start our presentation with the exact DFT results followed by the concept of exchange-correlation (xc) or Fermi-Coulomb hole and its relationship with xc energy functional. We also provide the exact conditions for the xc-hole, xc-energy and xc-potential along with their physical interpretation. Next, we describe the extension of DFT for non-integer number of electrons, the piecewise linearity of total energy and discontinuity of chemical potential at integer particle numbers, and derivative discontinuity of the xc potential, which has consequences on fundamental gap of solids. After that, we present how one obtains more accurate xc energy functionals by going beyond the LDA. We discuss the gradient expansion approximation (GEA), generalized gradient approximation (GGA), and hybrid functional approaches to designing better xc energy functionals that give accurate total energies. However, these functionals fail to predict properties like the ionization potential and the band gap. Thus, we next describe different methods of modelling these potentials and results of their application for calculation of the band gaps of different solids to highlight accuracy of different xc potentials. Finally, we conclude with a glimpse on orbital-free density functional theory and the machine learning approach.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Opening band gaps of low-dimensional materials at the meta-GGA level of density functional approximations

The quasiparticle band structure can be properly described by Hedin's GW approximation (GW), at a high computational cost. For band gaps, semilocal density functionals up to the generalized gradient approximation (GGA) level cannot compete with the accuracy of hybrid-based approximations or GW. Meta-GGA density functionals with a strong dependence on the kinetic energy density ingredient can potentially give wider band gaps compared with GGAs. The recent TASK meta-GGA density functional from Aschebrock and Kümmel [ Phys. Rev. Research 1 , 033082 (2019) ], is constructed with an enhanced nonlocality in the generalized Kohn-Sham scheme and therefore harbors great opportunities for band gap prediction. Although this approximation was found to yield excellent band gaps of bulk solids, this accuracy cannot be straightforwardly transferred to low-dimensional materials. Additionally, the reduced screening of these materials results in larger band gaps compared with their bulk counterparts, as an additional barrier to overcome. In this paper we demonstrate how the alteration of this functional affects the band gaps of monolayers and nanoribbons and present accurate band gaps competing with the revised Heyd-Scuseria-Ernzerhof (HSE06) approximation. In order to achieve this goal, we have modified the TASK functional (a) by changing the tight upper bound for one- or two-electron systems ( h X 0 ) from 1.174 to 1.29 and (b) by changing the limit of the interpolation function f X ( α → ∞ ) of the TASK functional that interpolates the exchange enhancement factor F X ( s , α ) from α = 0 to 1. The resulting modified TASK (mTASK) was tested for various materials from three dimensions to two dimensions to one dimension (nanoribbons) and was compared with the results of the higher-level hybrid functional HSE06 or with the G 0 W 0 approximation within many-body perturbation theory. We find that mTASK systematically improves the band gaps and band structures of two-dimensional (2D) and 1D systems, without significantly affecting the accuracy of the original TASK for the bulk 3D materials, when compared with the Perdew-Burke-Ernzerhof (PBE) GGA and the strongly constrained and appropriately normed (SCAN) meta-GGA. We further demonstrate the applicability of mTASK by assessing the band structures of transition metal dichalcogenide nanoribbons with respect to various bending curvatures.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs

The effects of plants on the biosphere, atmosphere and geosphere are key determinants of terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we are still only beginning to explore the complex relationships between root traits and functions. Drawing on the literature in plant physiology, ecophysiology, ecology, agronomy and soil science, we reviewed 24 aspects of plant and ecosystem functioning and their relationships with a number of root system traits, including aspects of architecture, physiology, morphology, anatomy, chemistry, biomechanics and biotic interactions. Based on this assessment, we critically evaluated the current strengths and gaps in our knowledge, and identify future research challenges in the field of root ecology. Most importantly, we found that belowground traits with the broadest importance in plant and ecosystem functioning are not those most commonly measured. Also, the estimation of trait relative importance for functioning requires us to consider a more comprehensive range of functionally relevant traits from a diverse range of species, across environments and over time series. Finally, we also advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with the strongest links on functions, and to link genotypes to plant and ecosystem functioning.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Experimental Evidence that Stochasticity Contributes to Bacterial Composition and Functioning in a Decomposer Community

ABSTRACT Stochasticity emerging from random differences in replication, death, mutation, and dispersal is thought to alter the composition of ecological communities. However, the importance of stochastic effects remains somewhat speculative because stochasticity is not directly measured but is instead inferred from unexplained variations in beta-diversity. Here, we performed a field experiment to more directly disentangle the role of stochastic processes, environmental selection, and dispersal in the composition and functioning of a natural bacterial decomposer community in the field. To increase our ability to detect these effects, we reduced initial biological and environmental heterogeneity using replicate nylon litterbags in the field. We then applied two treatments: ambient/added precipitation and bacterial and fungal dispersal using “open” litterbags (made from 18.0-μm-pore-size mesh) (“open bacterial dispersal”) versus bacterial and fungal dispersal using “closed” litterbags (made from 22.0-μm-pore-size mesh) (“closed bacterial dispersal”). After 5 months, we assayed composition and functioning by the use of three subsamples from each litterbag to disentangle stochastic effects from residual variation. Our results indicate that stochasticity via ecological drift can contribute to beta-diversity in bacterial communities. However, residual variation, which had previously been included in stochasticity estimates, accounted for more than four times as much variability. At the same time, stochastic effects on beta-diversity were not attenuated at the functional level, as measured by genetic functional potential and extracellular enzyme activity. Finally, dispersal was found to interact with precipitation availability to influence the degree to which stochasticity contributed to functional variation. Together, our results demonstrate that the ability to quantify stochastic processes is key to understanding microbial diversity and its role in ecosystem functioning. IMPORTANCE Randomness can alter the diversity and composition of ecological communities. Such stochasticity may therefore obscure the relationship between the environment and community composition and hinder our ability to predict the relationship between biodiversity and ecosystem functioning. This study investigated the role of stochastic processes, environmental selection, and dispersal in microbial composition and its functioning on an intact field community. To do this, we used a controlled and replicated experiment that was similar to that used to study population genetics in the laboratory. Our study showed that, while the stochastic effects on taxonomic composition are smaller than expected, the degree to which stochasticity contributes to variability in ecosystem processes may be much higher than previously assumed.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

J functions for the process ud→WA

In this paper we present a description of the universal approach for analytic calculations for a certain class of J functions for six topologies of the boxes for the process ud → WA. These functions J arise at the reduction of the infrared divergent box diagrams. The standard Passarino–Veltman reduction of the four-point box diagram with an internal photon line connecting two external lines on the mass shell leads to infrared-divergent and mass-singular D{sub 0} functions. In the system SANC a systematic procedure is adopted to separate both types of singularities into the simplest objects, namely C{sub 0} functions. The functions J, in turn, are represented as certain linear combinations of the standard D{sub 0} and C{sub 0} functions. The subtracted J functions are free of both types of singularities and are expressed as explicit and compact linear combinations of dilogarithm functions. We present extensive comparisons of numerical results of SANC with those obtained with the aid of the LoopTools package.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

How structural elements evolving from bacterial to human SLC6 transporters enabled new functional properties

Background. Much of the structure-based mechanistic understandings of the function of SLC6A neurotransmitter transporters emerged from the study of their bacterial LeuT-fold homologs. It has become evident, however, that structural differences such as the long N- and C-termini of the eukaryotic neurotransmitter transporters are involved in an expanded set of functional properties to the eukaryotic transporters. These functional properties are not shared by the bacterial homologs, which lack the structural elements that appeared later in evolution. However, mechanistic insights into some of the measured functional properties of the eukaryotic transporters that have been suggested to involve these structural elements are sparse or merely descriptive. Results. To learn how the structural elements added in evolution enable mechanisms of the eukaryotic transporters in ways not shared with their bacterial LeuT-like homologs, we focused on the human dopamine transporter (hDAT) as a prototype. We present the results of a study employing large-scale molecular dynamics simulations and comparative Markov state model analysis of experimentally determined properties of the wild-type and mutant hDAT constructs. These offer a quantitative outline of mechanisms in which a rich spectrum of interactions of the hDAT N-terminus and C-terminus contribute to the regulation of transporter function (e.g., by phosphorylation) and/or to entirely new phenotypes (e.g., reverse uptake (efflux)) that were added in evolution. Conclusions. The findings are consistent with the proposal that the size of eukaryotic neurotransmitter transporter termini increased during evolution to enable more functions (e.g., efflux) not shared with the bacterial homologs. The mechanistic explanations for the experimental findings about the modulation of function in DAT, the serotonin transporter, and other eukaryotic transporters reveal separate roles for the distal and proximal segments of the much larger N-terminus in eukaryotic transporters compared to the bacterial ones. The involvement of the proximal and distal segments — such as the role of the proximal segment in sustaining transport in phosphatidylinositol 4,5-bisphosphate-depleted membranes and of the distal segment in modulating efflux — may represent an evolutionary adaptation required for the function of eukaryotic transporters expressed in various cell types of the same organism that differ in the lipid composition and protein complement of their membrane environment.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Metaproteomics reveals persistent and phylum-redundant metabolic functional stability in adult human gut microbiomes of Crohn’s remission patients despite temporal variations in microbial taxa, genomes, and proteomes

The gut microbiome plays a fundamental role in the human host’s overall health by contributing key biological functions such as expanded metabolism and pathogen defense/immune control. In a healthy individual, the gut microbiome co-exists within the human host in a symbiotic, non-inflammatory relationship that enables mutual benefits, such as microbial degradation of indigestible food products into small molecules that the host can utilize, and enhanced pathogen defense. In abnormal conditions, such as Crohn’s disease, this favorable metabolic relationship breaks down and a variety of undesirable activities result, including chronic inflammation and other health-related issues. It has been difficult, however, to elucidate the overall functional characteristics of this relationship because the microbiota can vary substantially in composition for healthy humans and possibly even more in individuals with gut disease conditions such as Crohn’s disease. Overall, this suggests that microbial membership composition may not be the best way to characterize a phenotype. Alternatively, it seems to be more informative to examine and characterize the functional composition of a gut microbiome. Towards that end, this study examines 25 metaproteomes measured in several Crohn’s disease patients’ post-resection surgery across the course of 1 year, in order to examine persistence of microbial taxa, genes, proteins, and metabolic functional distributions across time in individuals whose microbiome might be more variable due to the gut disease condition. As a result, the measured metaproteomes were highly personalized, with all the temporally-related metaproteomes clustering most closely by individual. In general, the metaproteomes were remarkably distinct between individuals and to a lesser extent within individuals. This prompted a need to characterize the metaproteome at a higher functional level, which was achieved by annotating identified protein groups with KEGG orthologous groups to infer metabolic modules. At this level, similar and redundant metabolic functions across multiple phyla were observed across time and between individuals. Tracking through these various metabolic modules revealed a clear path from carbohydrate, lipid, and amino acid degradation to central metabolism and finally the production of fermentation products. In conclusion, the human gut metaproteome can vary quite substantially across time and individuals. However, despite substantial intra-individual variation in the metaproteomes, there is a clear persistence of conserved metabolic functions across time and individuals. Additionally, the persistence of these core functions is redundant across multiple phyla but is not always observable in the same sample. Finally, the gut microbiome’s metabolism is not driven by a set of discrete linear pathways but a web of interconnected reactions facilitated by a network of enzymes that connect multiple molecules across multiple pathways.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Modest functional diversity decline and pronounced composition shifts of microbial communities in a mixed waste-contaminated aquifer

Background: Microbial taxonomic diversity declines with increased environmental stress. Yet, few studies have explored whether phylogenetic and functional diversities track taxonomic diversity along the stress gradient. Here, we investigated microbial communities within an aquifer in Oak Ridge, Tennessee, USA, which is characterized by a broad spectrum of stressors, including extremely high levels of nitrate, heavy metals like cadmium and chromium, radionuclides such as uranium, and extremely low pH (< 3). Results: Both taxonomic and phylogenetic α-diversities were reduced in the most impacted wells, while the decline in functional α-diversity was modest and statistically insignificant, indicating a more robust buffering capacity to environmental stress. Differences in functional gene composition (i.e., functional β-diversity) were pronounced in highly contaminated wells, while convergent functional gene composition was observed in uncontaminated wells. The relative abundances of most carbon degradation genes were decreased in contaminated wells, but genes associated with denitrification, adenylylsulfate reduction, and sulfite reduction were increased. Compared to taxonomic and phylogenetic compositions, environmental variables played a more significant role in shaping functional gene composition, suggesting that niche selection could be more closely related to microbial functionality than taxonomy. Conclusions: Overall, we demonstrated that despite a reduced taxonomic α-diversity, microbial communities under stress maintained functionality underpinned by environmental selection.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Constructing Networks of Organelle Functional Modules in Arabidopsis

With the rapid accumulation of gene expression data, gene functional module identification has become a widely used approach in functional analysis. However, tools to identify organelle functional modules and analyze their relationships are still missing. We present a soft thresholding approach to construct networks of functional modules using gene expression datasets, in which nodes are strongly co-expressed genes that encode proteins residing in the same subcellular localization, and links represent strong inter-module connections. Our algorithm has three steps. First, we identify functional modules by analyzing gene expression data. Next, we use a self-adaptive approach to construct a mixed network of functional modules and genes. Finally, we link functional modules that are tightly connected in the mixed network. Analysis of experimental data from Arabidopsis demonstrates that our approach is effective in improving the interpretability of high-throughput transcriptomic data and inferring function of unknown genes.

Arabidopsis thaliana↗

DOE OSTI2016

Dramatic Increases of Soil Microbial Functional Gene Diversity at the Treeline Ecotone of Changbai Mountain

The elevational and latitudinal diversity patterns of microbial taxa have attracted great attention in the past decade. Recently, the distribution of functional attributes has been in the spotlight. Here, we report a study profiling soil microbial communities along an elevation gradient (500-2200 m) on Changbai Mountain. Using a comprehensive functional gene microarray (GeoChip 5.0), we found that microbial functional gene richness exhibited a dramatic increase at the treeline ecotone, but the bacterial taxonomic and phylogenetic diversity based on 16S rRNA gene sequencing did not exhibit such a similar trend. However, the β-diversity (compositional dissimilarity among sites) pattern for both bacterial taxa and functional genes was similar, showing significant elevational distance-decay patterns which presented increased dissimilarity with elevation. The bacterial taxonomic diversity/structure was strongly influenced by soil pH, while the functional gene diversity/structure was significantly correlated with soil dissolved organic carbon (DOC). This finding highlights that soil DOC may be a good predictor in determining the elevational distribution of microbial functional genes. The finding of significant shifts in functional gene diversity at the treeline ecotone could also provide valuable information for predicting the responses of microbial functions to climate change.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2022

Functional Allocation Approach for Separation Assurance for Remotely Piloted Aircraft

A functional analysis framework is employed with the objective of exploring the separation assurance function for the remotely piloted aircraft system. The architecture of the remotely piloted aircraft system—highlighting several of the component systems and the functions resident onboard the remotely piloted aircraft and in the ground control station—is described to provide the context for understanding the complexity of the said system for a detailed functional analysis. The interactions between the agents of the separation assurance function belonging to the air traffic service provider, remotely piloted aircraft system operator and remotely piloted aircraft are described. Separation assurance by air traffic control, remain well clear by the remotely piloted aircraft system and collision avoidance onboard the remotely piloted aircraft are briefly discussed. The functional analysis framework is illustrated by relating the agents to the actions of (a) acquiring the surveillance information, (b) checking for conflicts, (c) creating the solutions for resolving conflicts and (d) implementing the conflict resolution solutions. This example is offered as a template by which a more detailed functional analysis of this and other functions could be developed. The architecture of the remotely piloted aircraft system is described to aid this process.

functional analysis↗

NASA NTRS2022

Functional Allocation Approach for Separation Assurance for Remotely Piloted Aircraft

Functional analysis↗