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At least 415 records · Page 23

Monte Carlo Explicitly Correlated Second-Order Many-Body Green’s Function Calculations of Semiconductor Band Gaps

A systematically converging series of ab initio, post-density-functional, size-consistent, electron-correlated approximations is desired for predictive computing of felectronic band structures of insulating, semiconducting, and metallic solids. A series that meets all of these desiderata (except the applicability to metals) is ab initio many-body Green's function theory based on Gaussian-type-orbital (GTO) basis sets. Here, its leading-order approximation, the second-order Green's function (GF2) method in the diagonal and frequency-independent approximations with the aug-cc-pVDZ basis set, is applied to the fundamental band gaps of three semiconductors (diamond, silicon, and silicon carbide in the zincblende structure) using cluster models. Corrections are made to the basis-set-incompleteness errors by the explicit-correlation (F12) ansatz (GF2-F12) for the valence band edges. The crystals are modeled as surface-passivated clusters of increasing sizes, whose wave functions are expanded by up to 2709 GTO basis functions. Immense computational costs of these calculations are overcome by the highly scalable stochastic algorithm of the Monte Carlo GF2-F12 method, whose operation cost per state increases only as a cubic power of system size, which has a tiny memory footprint and easily achieves near-perfect parallel efficiency on thousands of CPUs or on hundreds of GPUs. The correlated, F12-corrected highest-occupied and lowest-unoccupied molecular-orbital energy (HOMO-LUMO) gap is 5.78 ± 0.07 eV for C 87 H 76 as compared with the experimental value of the fundamental (indirect) band gap of bulk diamond at 5.48 eV. The correlated, F12-corrected HOMO-LUMO gaps for Si 75 H 76 and Si 32 C 43 H 76 are 2.56 ± 0.15 eV and 3.50 ± 0.12 eV, respectively, which are expected to decrease further with increasing cluster sizes. As a result, the experimental fundamental (indirect) band gaps of bulk silicon and silicon carbide are 1.17 eV and 2.42 eV, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Functionalized Silicon Particles for Enhanced Half- and Full-Cell Cycling of Si-Based Li-Ion Batteries

Vinylene carbonate (VC) and polyethylene oxide (PEO) have been investigated as functional agents that mimic the solid electrolyte interphase (SEI) chemistry of silicon (Si). VC and PEO are known to contribute to the stability of Si-based lithium-ion batteries as an electrolyte additive and as a SEI component, respectively. In this work, covalent surface functionalization was achieved via a facile route, which involves ball-milling the Si particles with sacrificial VC and PEO. Thermogravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), and magic angle spinning nuclear magnetic resonance (MAS NMR) spectroscopy indicate that the additives are strongly bound to Si. In particular, MAS NMR shows Si–R or Si–O–R groups, which confirm functionalization of the Si after milling in VC or PEO. Particle size analysis by dynamic light scattering reveals that the additives facilitate particle size reduction and that the functionalized particles result in more stable dispersions based on zeta potential measurements. Raman mapping of the electrodes fabricated from the VC and PEO-coated active material with a polyacrylic acid (PAA) binder reveals a more homogenous distribution of Si and the carbon conductive additive compared to the electrodes prepared from the neat Si. Furthermore, the VC-milled Si strikingly exhibited the highest capacity in both half- and full-cell configurations, with more than 200 mAh g –1 measured capacity compared to the neat Si in the half-cell format. This is linked to an improved electrode processing based on the Raman and zeta potential measurements as well as a thinner SEI (with more organic components for the functionalized Si relative to the neat Si) based on XPS analysis of the cycled electrodes. In conclusion, the effect of binder was also investigated by comparing PAA with P84 (polyimide type), where an increased capacity is observed in the latter case.

25 ENERGY STORAGE↗

Carbene Functionalization of Monolayer Tungsten Disulfide for Enhanced Quantum Emission

Semiconducting two-dimensional (2D) transition metal dichalcogenides (TMDs) are promising materials for an array of applications, ranging from conventional field-effect transistors, photodetectors, and light-emitting diodes to their more recent use in quantum photonic technologies. Chemical functionalization of 2D TMDs with organic ligands and adlayers provides an additional means for customizing their electronic and optical properties. While many pathways have been reported for the chemical functionalization of 2D TMDs, their frequent reliance on solution-based methods results in limited control over adlayer thickness and coverage, thus hindering utility in high-performance applications. Here, in this study, we describe the vapor-phase functionalization of a 2D TMD with carbene ligands, specifically tungsten disulfide (WS 2 ) with N-heterocyclic carbenes (NHCs), resulting in molecularly smooth, thin, and uniform adlayers. Reacting NHCs with monolayer WS 2 reduces the broad photoluminescence background observed at cryogenic temperatures by 58%, which facilitates the detection of single-photon emitters from strained monolayer WS 2 , as indicated by second order correlation values ( g (2) ) as low as 0.17 ± 0.07. Chemical characterization coupled with density functional theory calculations suggests that the NHC adlayer has a dual defect-passivation and doping effect on monolayer WS 2 that results in enhanced single-photon emission. Overall, this study establishes vapor-phase carbene functionalization as a homogeneous surface modification scheme for tailoring the quantum emission properties of semiconducting 2D TMDs.

N-heterocyclic carbenes↗

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning

Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barcoding strategy with nanopore sequencing to rapidly generate sequence-function data for entire protein-coding genes. LevSeq integrates into existing protein engineering workflows and comes with open-source software for data analysis and visualization. The pipeline facilitates data-driven protein engineering by consolidating sequence-function data to inform directed evolution and provide the requisite data for machine learning-guided protein engineering (MLPE). LevSeq enables quality control of mutagenesis libraries prior to screening, which reduces time and resource costs. Simulation studies demonstrate LevSeq’s ability to accurately detect variants under various experimental conditions. Lastly, we show LevSeq’s utility in engineering protoglobins for new-to-nature chemistry. Widespread adoption of LevSeq and sharing of the data will enhance our understanding of protein sequence-function landscapes and empower data-driven directed evolution.

59 BASIC BIOLOGICAL SCIENCES↗

Ultraconserved enhancer function does not require perfect sequence conservation

Ultraconserved enhancer sequences show perfect conservation between human and rodent genomes, suggesting that their functions are highly sensitive to mutation. However, current models of enhancer function do not sufficiently explain this extreme evolutionary constraint. We subjected 23 ultraconserved enhancers to different levels of mutagenesis, collectively introducing 1,547 mutations, and examined their activities in transgenic mouse reporter assays. Overall, we find that the regulatory properties of ultraconserved enhancers are robust to mutation. Upon mutagenesis, nearly all (19/23, 83%) still functioned as enhancers at one developmental stage, as did most of those tested again later in development (5/9, 56%). Replacement of endogenous enhancers with mutated alleles in mice corroborated results of transgenic assays, including the functional resilience of ultraconserved enhancers to mutation. Furthermore, our findings show that the currently known activities of ultraconserved enhancers do not necessarily require the perfect conservation observed in evolution and suggest that additional regulatory or other functions contribute to their sequence constraint.

59 BASIC BIOLOGICAL SCIENCES↗

Assessing density functionals for describing methane dissociative chemisorption on Pt(110)-(2×1) surface

In this work, we explore the suitability of several density functionals with the generalized gradient approximation (GGA) and beyond for describing the dissociative chemisorption of methane on the reconstructed Pt(110)-(2×1) surface. The bulk and surface structures of the metal, methane adsorption energy, and dissociation barrier are used to assess the functionals. A van der Waals corrected GGA functional (optPBE-vdW) and a metaGGA functional with van der Waals correction (MS PBEl-rVV10) are selected for ab initio molecular dynamics calculations of the sticking probability. Our results suggest that the use of these two functionals may lead to a better agreement with existing experimental results, thus serving as a good starting point for future development of reliable machine-learned potential energy surfaces for the dissociation of methane on the Pt(110)-(2×1) surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Work function lowering of LaB 6 by monolayer hexagonal boron nitride coating for improved photo- and thermionic-cathodes

We report a lowering of work function for lanthanum hexaboride (LaB 6 ) by monolayer hexagonal boron nitride (hBN) coating. Photoemission electron microcopy (PEEM) and thermionic emission electron microscopy (TEEM) both revealed that the hBN coated region of a LaB 6 (100) single crystal has a lower work function compared to the bare (i.e., non-coated) and graphene coated regions. A broad and uniform brighter image of the hBN coated region in PEEM was quantitatively supported by a 0.4 eV decrease in the work function in photoelectron spectra compared to the bare region. TEEM results were consistent in that the hBN coated region exhibited thermionic emission at 905 °C, whereas the bare and graphene coated regions did not. A larger decrease in the work function for hBN coated LaB 6 (100) compared to graphene coated LaB 6 (100) was qualitatively supported by our density functional theory calculations. Adding an oxide layer in the calculations improved consistency between the calculation and experimental results. We followed up our calculations with synchrotron-radiation x-ray photoelectron spectroscopy and confirmed the presence of an oxide layer on our LaB 6 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying the contribution of Fc-mediated effector functions to the antiviral activity of anti–HIV-1 IgG1 antibodies in vivo

In combating viral infections, the Fab portion of an antibody could mediate virus neutralization, whereas Fc engagement of Fc-γ receptors (FcγRs) could mediate an array of effector functions. Evidence abounds that effector functions are important in controlling infections by influenza, Ebola, or HIV-1 in animal models. However, the relative contribution of virus neutralization versus effector functions to the overall antiviral activity of an antibody remains unknown. To address this fundamental question in immunology, here we utilized our knowledge of HIV-1 dynamics to compare the kinetics of the viral load decline (ΔVL) in infected animals given a wild-type (WT) anti–HIV-1 immunoglobulin G1 (IgG1) versus those given a Fc-Null variant of the same antibody. In three independent experiments in HIV-1–infected humanized mice and one pivotal experiment in simian–human immunodeficiency virus (SHIV)-infected rhesus macaques, an earlier and sharper decline in viral load was consistently detected for the WT antibody. Quantifications of the observed differences indicate that Fc-mediated effector functions accounted for 25–45% of the total antiviral activity in these separate experiments. In this study, Fc-mediated effector functions have been quantified in vivo relative to the contribution of virus neutralization mediated by the Fab.

60 APPLIED LIFE SCIENCES↗

Therapeutic efficacy of a potent anti-Venezuelan equine encephalitis virus antibody is contingent on Fc effector function

The development of specific, safe, and potent monoclonal antibodies (Abs) has led to novel therapeutic options for infectious disease. In addition to preventing viral infection through neutralization, Abs can clear infected cells and induce immunomodulatory functions through engagement of their crystallizable fragment (Fc) with complement proteins and Fc receptors on immune cells. Little is known about the role of Fc effector functions of neutralizing Abs in the context of encephalitic alphavirus infection. To determine the role of Fc effector function in therapeutic efficacy against Venezuelan equine encephalitis virus (VEEV), we compared the potently neutralizing anti-VEEV human IgG F5 (hF5) Ab with intact Fc function (hF5-WT) or containing the loss of function Fc mutations L234A and L235A (hF5-LALA) in the context of VEEV infection. We observed significantly reduced binding to complement and Fc receptors, as well as differential in vitro kinetics of Fc-mediated cytotoxicity for hF5-LALA compared to hF5-WT. The in vivo efficacy of hF5-LALA was comparable to hF5-WT at -24 and + 24 h post infection, with both Abs providing high levels of protection. However, when hF5-WT and hF5-LALA were administered + 48 h post infection, there was a significant decrease in the therapeutic efficacy of hF5-LALA. Together these results demonstrate that optimal therapeutic Ab treatment of VEEV, and possibly other encephalitic alphaviruses, requires neutralization paired with engagement of immune effectors via the Fc region.

59 BASIC BIOLOGICAL SCIENCES↗

Electron capture of superheavy nuclei with realistic lepton wave functions

The superheavy nuclei push the periodic table of the elements and the chart of the nuclides to their limits, providing a unique laboratory for studies of the electron-nucleus interactions. The most important weak decay mode in known superheavy nuclei is electron capture (EC). In the standard calculations of EC, the lepton wave functions are usually considered in the lowest-order approximation. In this work, we investigate the sensitivity of EC rates on the choice of the electron wave functions by (i) assuming the single-particle approximation for the electron wave functions, and (ii) carrying out Dirac-Hartree-Fock (DHF) calculations. The nuclear response is generated based on the state-of-the-art quasiparticle random phase approximation employing relativistic nuclear energy density functional theory. Here, we show that using the improved lepton wave functions reduces the EC rates up to 40% in the superheavy nucleus oganesson (𝑍=118). Interestingly, because of screening effects, the difference between the EC rates obtained with the DHF and single-particle calculations is fairly small.

Atomic orbital↗

Iterated projected position algorithm for constructing exponentially localized generalized Wannier functions for periodic and nonperiodic insulators in two dimensions and higher

Localized bases play an important role in understanding electronic structure. In periodic insulators, a natural choice of localized basis is given by the Wannier functions which depend on a choice of unitary transform known as a gauge transformation. Over the past few decades, there have been many works that have focused on optimizing the choice of the gauge so that the corresponding Wannier functions are maximally localized or reflect some symmetry of the underlying system. In this work, we consider fully nonperiodic materials where the usual Wannier functions are not well defined and gauge optimization is impractical. To tackle the problem of calculating exponentially localized generalized Wannier functions in both periodic and nonperiodic systems, we discuss the ‘iterated projected position (IPP)” algorithm. Here, the IPP algorithm is based on matrix diagonalization and therefore unlike optimization-based approaches, it does not require initialization and cannot get stuck at a local minimum. Furthermore, the IPP algorithm is guaranteed by a rigorous analysis to produce exponentially localized functions under certain mild assumptions. We numerically demonstrate that the IPP algorithm can be used to calculate exponentially localized bases for the Haldane model, the Kane-Mele model (in both Z 2 invariant even and Z 2 invariant odd phases), and the p x + ip y model on a quasicrystal lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Comparison of the canonical transformation and energy functional formalisms for ab initio calculations of self-localized polarons

In materials with strong electron-phonon (e-ph) interactions, charge carriers can distort the surrounding lattice and become trapped, forming self-localized (small) polarons. We recently developed an ab initio approach based on canonical transformations to efficiently compute the formation and energetics of small polarons A different approach based on a Landau-Pekar energy functional has been proposed in the recent literature. Here in this work, we analyze and compare these two methods in detail. We show that the small polaron energy is identical in the two formalisms when using the same polaron wave function. We also show that our canonical transformation formalism can predict polaron band structures and can properly treat zero- and finite-temperature lattice vibration effects, although at present using a fixed polaron wave function. Conversely, the energy functional approach can compute the polaron wave function, but as we show here, it neglects lattice vibrations and cannot address polaron self-localization and thermal band narrowing. Taken together, this work relates two different methods developed recently to study polarons from first-principles, highlighting their merits and shortcomings and discussing them both in a unified formalism.

36 MATERIALS SCIENCE↗

Real-space Green's function approach for intrinsic losses in x-ray spectra

Intrinsic inelastic losses in x-ray spectra originate from excitations in an interacting electron system due to a suddenly created core-hole. These losses characterize the features observed in x-ray photoemission spectra (XPS), as well as many-body effects such as satellites and edge-singularities in x-ray absorption spectra (XAS). However, they are usually neglected in practical calculations. As shown by Langreth these losses can be treated within linear response in terms of a cumulant Green's function in momentum space. Here we present a complementary ab initio real-space Green's function generalization of the Langreth cumulant in terms of the dynamically screened core-hole interaction W c (ω) and the independent particle response function. Here we find that the cumulant kernel β⁡(ω) is analogous to XAS, but with the transition operator replaced by the core-hole potential with monopole selection rules. The behavior reflects the analytic structure of the loss function, with peaks near the zeros of the dielectric function, consistent with delocalized quasiboson excitations. The approach simplifies when W c (ω) is localized and spherically symmetric. In conclusion, illustrative results and comparisons are presented for the electron gas, sodium, and some early transition metal compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Sensitivity of time-dependent density functional theory to initial conditions

Time-dependent density-functional theory is mathematically formulated through nonlinear coupled time-dependent three-dimensional partial differential equations, and it is natural to expect a strong sensitivity of its solutions to variations of the initial conditions, akin to the butterfly effect ubiquitous in classical dynamics. Since the Schrödinger equation for an interacting many-body system is, however, linear and mathematically the exact equations of the density-functional theory reproduce the corresponding one-body properties, it would follow that the Lyapunov exponents are also vanishing within a density-functional theory framework. Whether for realistic implementations of the time-dependent density-functional theory the question of the absence of the butterfly effect and whether the dynamics provided is indeed a predictable theory was never discussed. At the same time, since the time-dependent density-functional theory is a unique tool allowing us to study the nonequilibrium dynamics of strongly interacting many-fermion systems, the question of predictability of this theoretical framework is of paramount importance. Here our analysis, for a number of quantum superfluid many-body systems (unitary Fermi gas, nuclear fission, and heavy-ion collisions) with a classical equivalent number of degrees of freedom O(10 10 ) and larger, suggests that its maximum Lyapunov exponents are negligible for all practical purposes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Further steps toward the next generation of covariant energy density functionals

The present study aims at further development of covariant energy density functionals (CEDFs) towards more accurate description of binding energies across the nuclear chart. Infinite basis corrections to binding energies in the fermionic and bosonic sectors of the covariant density functional theory are taken into account in the fitting protocol within the covariant density functional theory. In addition, total electron binding energies are used in the conversion of atomic binding energies into nuclear ones. Their dependence on neutron excess is investigated across the nuclear chart within the atomic approach. Furthermore, these factors were disregarded in the previous generation of covariant energy density functionals, but their omission leads to substantial global calculation errors for physical quantities of interest. For example, these errors for binding energies are of the order of 0.8 MeV or higher for the three major classes of covariant energy density functionals.

Binding energy & masses↗

A functional modeling approach for quality assurance in metal additive manufacturing

Purpose: Due to the complexity of and variations in additive manufacturing (AM) processes, there is a level of uncertainty that creates critical issues in quality assurance (QA), which must be addressed by time-consuming and cost-intensive tasks. This deteriorates the process repeatability, reliability and part reproducibility. So far, many AM efforts have been performed in an isolated and scattered way over several decades. Here, a systematically integrated holistic view is proposed to achieve QA for AM. Design/methodology/approach: A systematically integrated view is presented to ensure the predefined part properties before/during/after the AM process. It consists of four stages, namely, QA plan, prospective validation, concurrent validation and retrospective validation. As a foundation for QA planning, a functional workflow and the required information flows are proposed by using functional design models: Icam DEFinition for Function Modeling. Findings: The functional design model of the QA plan provides the systematically integrated view that can be the basis for inspection of AM processes for the repeatability and qualification of AM parts for reproducibility. Research limitations/implications: A powder bed fusion process was used to validate the feasibility of this QA plan. Feasibility was demonstrated under many assumptions; real validation is not included in this study. Social implications: This study provides an innovative and transformative methodology that can lead to greater productivity and improved quality of AM parts across industries. Furthermore, the QA guidelines and functional design models provide the foundation for the development of a QA architecture and management system. Originality/value: This systematically integrated view and the corresponding QA plan can pose fundamental questions to the AM community and initiate new research efforts in the in-situ digital inspection of AM processes and parts.

36 MATERIALS SCIENCE↗

Entropy-Infused Deep Learning Loss Function for Capturing Extreme Values in Wind Power Forecasting

Extreme scenarios in wind power generation occur with higher frequency and larger magnitude in the recent years due to the ever-increasing extreme meteorological factors. Accurate forecasting of the occurrence of extreme values in wind power generation is of great concern to ensure reliable power system operation. Recently, deep learning models have surged in popularity for wind power forecasting, with the mean squared error (MSE) loss function being commonly used. However, the MSE loss function, being sensitive to extreme values, disproportionately penalizes larger errors, cannot adequately capture the extreme values present in wind energy data, and novel loss functions have seldom been tailored for wind power forecasting. To this end, in this paper, we introduce a novel loss function specifically crafted to capture extreme values in wind power forecasting. The experimental results with four fundamental deep learning methods on open source wind power dataset validate that the new loss function is efficient and superior in all cases compared to MSE in capturing extreme values while maintaining forecasting performance.

17 WIND ENERGY↗

Metagenomic clustering links specific metabolic functions to globally relevant ecosystems

ABSTRACT Metagenomic sequencing has advanced our understanding of biogeochemical processes by providing an unprecedented view into the microbial composition of different ecosystems. While the amount of metagenomic data has grown rapidly, simple-to-use methods to analyze and compare across studies have lagged behind. Thus, tools expressing the metabolic traits of a community are needed to broaden the utility of existing data. Gene abundance profiles are a relatively low-dimensional embedding of a metagenome’s functional potential and are, thus, tractable for comparison across many samples. Here, we compare the abundance of KEGG Ortholog Groups (KOs) from 6,539 metagenomes from the Joint Genome Institute’s Integrated Microbial Genomes and Metagenomes (JGI IMG/M) database. We find that samples cluster into terrestrial, aquatic, and anaerobic ecosystems with marker KOs reflecting adaptations to these environments. For instance, functional clusters were differentiated by the metabolism of antibiotics, photosynthesis, methanogenesis, and surprisingly GC content. Using this functional gene approach, we reveal the broad-scale patterns shaping microbial communities and demonstrate the utility of ortholog abundance profiles for representing a rapidly expanding body of metagenomic data. IMPORTANCE Metagenomics, or the sequencing of DNA from complex microbiomes, provides a view into the microbial composition of different environments. Metagenome databases were created to compile sequencing data across studies, but it remains challenging to compare and gain insight from these large data sets. Consequently, there is a need to develop accessible approaches to extract knowledge across metagenomes. The abundance of different orthologs (i.e., genes that perform a similar function across species) provides a simplified representation of a metagenome’s metabolic potential that can easily be compared with others. In this study, we cluster the ortholog abundance profiles of thousands of metagenomes from diverse environments and uncover the traits that distinguish them. This work provides a simple to use framework for functional comparison and advances our understanding of how the environment shapes microbial communities.

54 ENVIRONMENTAL SCIENCES↗