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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Real-time coupled-cluster approach for the cumulant Green's function

Green’s function methods within many-body perturbation theory provide a general framework for treating electronic correlations in excited states. Here we investigate the cumulant form of the one-electron Green’s function based on the coupled-cluster equation of motion approach in an extension of our previous study. The approach yields a non-perturbative expression for the cumulant in terms of the solution to a set of coupled first order, non-linear differential equations. The method thereby adds non-linear corrections to traditional cumulant methods linear in the self energy. The approach is applied to the core-hole Green’s function and illustrated for a number of small molecular systems. For these systems we find that the non-linear contributions lead to significant improvements both for quasiparticle properties such as core-level binding energies, as well as the satellites corresponding to inelastic losses observed in photoemission spectra.

Vila, Fernando D.↗
DOE OSTI2021

Methane Adsorption on Heteroatom-Modified Maquettes of Porous Carbon Surfaces

Experimental and theoretical studies disagree on the energetics of methane adsorption on carbon materials. However, this information is critical for the rational design and optimization of the structure and composition of adsorbents for natural gas storage. The delicate nature of dispersion interactions, polarization of both the adsorbent and the adsorbate, interplay between H-bonding and tetrel bonding, and induced dipole/Coulomb interactions inherent to methane physisorption require computational treatment at the highest possible level of theory. In this study, we employed the smallest reasonable computational model, a maquette of porous carbon surfaces with a central site for substitution and methane binding. The most accurate predictions of methane adsorption energetics were achieved by electron-correlated molecular orbital theory CCSD(T) and hybrid density functional theory MN15 calculations employing a saturated, all-electron basis set. Here, the characteristic geometry of methane adsorption on a carbon surface (“lander approach”) arises due to bonding interactions of the adsorbent π-system with the proximal H–C bonds of methane, in addition to tetrel bonding between the antibonding orbital of the distal C–H bond and the central atom of the maquette (C, B, or N). The polarization of the electron density, structural deformations, and the comprehensive energetic analysis clearly indicate a ∼3 kJ mol –1 preference for methane binding on the N-substituted maquette. The B-substituted maquette showed a comparable or lower binding energy than the unsubstituted, pure C model, depending on the level of theory employed. The calculated thermodynamic results indicate a strategy for incorporating electron-enriched substitutions (e.g., N) into carbon materials as a way to increase methane storage capacity over electron-deficient (e.g., B) modifications. The thermochemical analysis was revised for establishing a conceptual agreement between the experimental isosteric heat of adsorption and the binding enthalpies from statistical thermodynamics principles.

03 NATURAL GAS↗
DOE OSTI2023

The Local Electronic Structure of Supercritical CO 2 from X-ray Raman Spectroscopy and Atomistic-Scale Modeling

Supercritical CO 2 is encountered in several technical and natural systems related to biology, geophysics, and engineering. While the structure of gaseous CO 2 has been studied extensively, the properties of supercritical CO 2 , particularly close to the critical point, are not well-known. Here, in this work, we combine X-ray Raman spectroscopy, molecular dynamics simulations, and first-principles density functional theory (DFT) calculations to characterize the local electronic structure of supercritical CO 2 at conditions around the critical point. The X-ray Raman oxygen K-edge spectra manifest systematic trends associated with the phase change of CO 2 and the intermolecular distance. Extensive first-principles DFT calculations rationalize these observations on the basis of the 4sσ Rydberg state hybridization. X-ray Raman spectroscopy is found to be a sensitive tool for characterizing electronic properties of CO 2 under challenging experimental conditions and is demonstrated to be a unique probe for studying the electronic structure of supercritical fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Completely Multipolar Model for Many-Body Water–Ion and Ion–Ion Interactions

This work constructs an advanced force field, the Completely Multipolar Model (CMM), to quantitatively reproduce each term of an energy decomposition analysis (EDA) for aqueous solvated alkali metal cations and halide anions and their ion pairings. We find that all individual EDA terms remain well-approximated in the CMM for ion-water and ion-ion interactions, except for polarization, which shows errors due to the partial covalency of ion interactions near their equilibrium. We quantify the onset of the dative bonding regime by examining the change in molecular polarizability and Mayer bond indices as a function of distance, showing that partial covalency manifests by breaking the symmetry of atomic polarizabilities while strongly damping them at short-range. This motivates an environment-dependent atomic polarizability parameter that depends on the strength of the local electric field experienced by the ions to account for strong damping, with anisotropy introduced by atomic multipoles. The resulting CMM model for ions provides accurate dimer surfaces and three-body polarization and charge transfer compared to EDA, and shows excellent performance on various ion benchmarks including vibrational frequencies and cluster geometries.

Heindel, Joseph P↗
DOE OSTI2025

MODE: A Web Application for Interactive Visualization and Exploration of Omics Data

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as “omics”) data allow researchers to find biomarkers or molecular targets, or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data is multi-dimensional and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries don’t allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to effortlessly sort and filter plots by categorical or numerical variables. MODE allows users to build and share these displays with several options for plot design and meta selection. In conclusion, the MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

lipidomics↗
DOE OSTI2024

Chlorophyllase from Arabidopsis thaliana Reveals an Emerging Model for Controlling Chlorophyll Hydrolysis

Chlorophyll (Chl) is one of Nature’s most complex pigments to biosynthesize and derivatize. This pigment is vital for survival and also paradoxically toxic if overproduced or released from a protective protein scaffold. Therefore, along with the mass production of Chl, organisms also invest in mechanisms to control its degradation and recycling. One important enzyme that is involved in these latter processes is chlorophyllase. This enzyme is employed by numerous photosynthetic organisms to hydrolyze the phytol tail of Chl. Although traditionally thought to catalyze the first step of Chl degradation, recent work suggests that chlorophyllase is instead employed during times of abiotic stress or conditions that produce reactive oxygen species. However, the molecular details regarding how chlorophyllases are regulated to function under such conditions remain enigmatic. Here, we investigate the Arabidopsis thaliana chlorophyllase isoform AtCLH2 using site-directed mutagenesis, mass spectrometry, dynamic light scattering, size-exclusion multiangle light scattering, and both steady-state enzyme kinetic and thermal stability measurements. Through these experiments, we show that AtCLH2 exists as a monomer in solution and contains two disulfide bonds. One disulfide bond putatively maps to the active site, whereas the other links two N-terminal Cys residues together. These disulfide bonds are cleaved by chemical or chemical and protein-based reductants, respectively, and are integral to maintaining the activity, stability, and substrate scope of the enzyme. This work suggests that Cys residue oxidation in chlorophyllases is an emerging regulatory strategy for controlling the hydrolysis of Chl pigments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Reversible Oxidation Quantified by Optical Properties in Epitaxial Fe2CrO4+d Films on (001) MgAl2O4

We report on the structural and optical properties of Fe2CrO4+d epitaxial films grown by molecular beam epitaxy on MgAl2O4 (001) as a function of ?. The average Fe valence can be correlated with the out-of-plane lattice parameter and the extent of light absorption in the infrared spectral region. Over-oxidized films (0 < d < 0.5) exhibit reduced lattice parameters and suppressed infrared absorption. We discuss the behavior of a novel infrared transition at ~0.6 eV in stoichiometric Fe2CrO4 films deposited on MgAl2O4 (MAO) at or above 400 °C. This research provides new insight into the atomic structure, optical processes, oxidation states, electronic structure, and application potentials of Fe2CrO4+d.

ellipsometry, Epitaxy, thin film, oxidation, reduc↗
DOE OSTI2023

Crystal structure of the CoV-Y domain of SARS-CoV-2 nonstructural protein 3

Abstract Replication of the coronavirus genome starts with the formation of viral RNA-containing double-membrane vesicles (DMV) following viral entry into the host cell. The multi-domain nonstructural protein 3 (nsp3) is the largest protein encoded by the known coronavirus genome and serves as a central component of the viral replication and transcription machinery. Previous studies demonstrated that the highly-conserved C-terminal region of nsp3 is essential for subcellular membrane rearrangement, yet the underlying mechanisms remain elusive. Here we report the crystal structure of the CoV-Y domain, the most C-terminal domain of the SARS-CoV-2 nsp3, at 2.4 Å-resolution. CoV-Y adopts a previously uncharacterized V-shaped fold featuring three distinct subdomains. Sequence alignment and structure prediction suggest that this fold is likely shared by the CoV-Y domains from closely related nsp3 homologs. NMR-based fragment screening combined with molecular docking identifies surface cavities in CoV-Y for interaction with potential ligands and other nsps. These studies provide the first structural view on a complete nsp3 CoV-Y domain, and the molecular framework for understanding the architecture, assembly and function of the nsp3 C-terminal domains in coronavirus replication. Our work illuminates nsp3 as a potential target for therapeutic interventions to aid in the on-going battle against the COVID-19 pandemic and diseases caused by other coronaviruses.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Insights into lithium ion deposition on lithium metal surfaces

Lithium metal is among the most promising anodes for the next generation of batteries due to its high theoretical energy density and high capacity. Challenges such as extreme reactivity and lithium dendrite formation have kept lithium metal anodes away from practical applications. However, the underlying mechanisms of Li ion deposition from the electrolyte solution onto the anode surface are still poorly understood due to their inherent complexity. In this work, density functional theory calculations and thermodynamic integration via constrained molecular dynamics simulations are conducted to study the electron and ion transfer between lithium metal slab and the electrolyte in absence of an external field. Here, we explore the effect of the solvent chemistry and structure, distance of the solvated complex from the surface, anion–cation separation, and concentration of Li-salts on the deposition of lithium ions from the electrolyte phase onto the surface. Ethylene carbonate (EC), 1,2-dimethoxyethane (DME), 1,3-dioxolane (DOL), and mixtures of them are used as solvents. These species compete with the salt anion and the Li cation for electron transfer from the surface. It is found that the structure and properties of the solvation shell around the lithium cation has a great influence on the ability of the cation to diffuse as well as on its surrounding electron environment. DME molecules allow easier motion of the lithium ion compared with EC and DOL molecules. The slow growth approach allows the study of energy barriers for the ion diffusion and desolvation during the deposition pathway. This method helps elucidating the underlying mechanisms on lithium-ion deposition and provides a better understanding of the early stages of Li nucleation.

25 ENERGY STORAGE↗
DOE OSTI2022

Functionalized nona-silicide [Si 9 R 3 ] Zintl clusters: a new class of superhalogens

Superatoms, due to their various applications in redox and materials chemistry, have been a major topic of study in cluster science. Superhalogens constitute a special class of superatoms that mimic the chemistry of halogens and serve as building blocks of novel materials such as super and hyper salts, perovskite-based solar cells, solid-state electrolytes, and ferroelectric materials. These applications have led to a constant search for new class of superhalogens. Here, in this study, using density functional theory, we show that recently synthesized [Si 9 {Si ( t Bu) 2 H} 3 ] and [Si 9 {Si (TMS) 3 } 3 ] Zintl clusters not only behave like halogens but also when functionalized with suitable ligands exhibit superhalogen characteristics. Frontier molecular orbital (FMO) analyses give insights into the electron-accepting nature of the Zintl clusters. Additional bonding techniques such as energy density at the bond critical point (BCP) and adaptive natural density partitioning (AdNDP) gives complementary information about the nature of bonding in Si 9 -based Zintl clusters. The potential of these Zintl clusters in the synthesis of new electrolytes in Li-ion batteries is also investigated.

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

Liquid to crystal Si growth simulation using machine learning force field

Machine learning force field (ML-FF) has emerged as a potential promising approach to simulate various material phenomena for large systems with ab initio accuracy. However, most ML-FFs have been used to study the phenomena relatively close to the equilibrium ground states. In this work, we have studied a far from equilibrium system of liquid to crystal Si growth using ML-FF. Here, we found that our ML-FF based on ab initio decomposed atomic energy can reproduce all the aspects of ab initio simulated growth, from local energy fluctuations to transition temperatures, to diffusion constant, and growth rates. We have also compared the growth simulation with the Stillinger-Weber classical force field and found significant differences. A procedure is also provided to correct a systematic fitting bias in the ML-FF training process, which exists in all training models, otherwise critical results like transition temperature will be wrong.

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

Fluorine spillover for ceria- vs silica-supported palladium nanoparticles: A MD study using machine learning potentials

Supported metallic nanoparticles play a central role in catalysis. However, predictive modeling is particularly challenging due to the structural and dynamic complexity of the nanoparticle and its interface with the support, given that the sizes of interest are often well beyond those accessible via traditional ab initio methods. With recent advances in machine learning, it is now feasible to perform MD simulations with potentials retaining near-density-functional theory (DFT) accuracy, which can elucidate the growth and relaxation of supported metal nanoparticles, as well as reactions on those catalysts, at temperatures and time scales approaching those relevant to experiments. Furthermore, the surfaces of the support materials can also be modeled realistically through simulated annealing to include effects such as defects and amorphous structures. We study the adsorption of fluorine atoms on ceria and silica supported palladium nanoparticles using machine learning potential trained by DFT data using the DeePMD framework. We show defects on ceria and Pd/ceria interfaces are crucial for the initial adsorption of fluorine, while the interplay between Pd and ceria and the reverse oxygen migration from ceria to Pd control spillover of fluorine from Pd to ceria at later stages. In contrast, silica supports do not induce fluorine spillover from Pd particles.

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

Analytical harmonic vibrational frequencies with VV10-containing density functionals: Theory, efficient implementation, and benchmark assessments

VV10 is a powerful nonlocal density functional for long-range correlation that is used to include dispersion effects in many modern density functionals, such as the meta-generalized gradient approximation (mGGA), B97M-V, the hybrid GGA, ωB97X-V, and the hybrid mGGA, ωB97M-V. While energies and analytical gradients for VV10 are already widely available, this study reports the first derivation and efficient implementation of the analytical second derivatives of the VV10 energy. The additional compute cost of the VV10 contributions to analytical frequencies is shown to be small in all but the smallest basis sets for recommended grid sizes. Here, this study also reports the assessment of VV10-containing functionals for predicting harmonic frequencies using the analytical second derivative code. The contribution of VV10 to simulating harmonic frequencies is shown to be small for small molecules but important for systems where weak interactions are important, such as water clusters. In the latter cases, B97M-V, ωB97M-V, and ωB97X-V perform very well. The convergence of frequencies with respect to the grid size and atomic orbital basis set size is studied, and recommendations are reported. Finally, scaling factors to allow comparison of scaled harmonic frequencies with experimental fundamental frequencies and to predict zero-point vibrational energy are presented for some recently developed functionals (including r2SCAN, B97M-V, ωB97X-V, M06-SX, and ωB97M-V).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Cryogenic electron tomography by the numbers: Charting underexplored lineages in structural cell biology

Imaging cells and their interactions across the whole biosphere with molecular-scale resolution is key for understanding structure–function relations. Cryogenic electron tomography (cryo-ET) is a powerful method for obtaining this critical information. However, cryo-ET studies are challenging and often limited to a small number of cell types per study. Here, we collate cryo-ET data from hundreds of cells and tissues across the biosphere to i) identify emerging methodological trends, ii) pinpoint strategies to reduce imaging time and costs, iii) quantitatively compare methods for cell freezing and sectioning, and iv) census cryo-ET species coverage across all domains of life. Comparing the fraction of cellular material within a single lamella across all domains of life reveals an order of magnitude difference between eukaryotes (1%) compared to bacteria (9%) and archaea (14%). We calculate the fraction of cellular material which can be imaged using distinct sectioning methods on multicellular communities and tissues—identifying serial lift-out as a powerful approach for obtaining more complete cellular depictions. Finally, we show that the biodiversity of current cryo-ET studies is 2 to 3 orders of magnitude lower than in sequence libraries and 4 to 5 lower than the total predicted on Earth. Our analyses reveal major evolutionary lineages which remain critically understudied and highlight where future cryo-ET research would be most impactful.

HPF↗
DOE OSTI2023

Probing reaction channels via reinforcement learning

Abstract Chemical reactions are dynamical processes involving the correlated reorganization of atomic configurations, driving the conversion of an initial reactant into a result product. By virtue of the metastability of both the reactants and products, chemical reactions are rare events, proceeding fleetingly. Reaction pathways can be modelled probabilistically by using the notion of reactive density in the phase space of the molecular system. Such density is related to a function known as the committor function, which describes the likelihood of a configuration evolving to one of the nearby metastable regions. In theory, the committor function can be obtained by solving the backward Kolmogorov equation (BKE), which is a partial differential equation (PDE) defined in the full dimensional phase space. However, using traditional methods to solve this problem is not practical for high dimensional systems. In this work, we propose a reinforcement learning based method to identify important configurations that connect reactant and product states along chemical reaction paths. By shooting multiple trajectories from these configurations, we can generate an ensemble of states that concentrate on the transition path ensemble. This configuration ensemble can be effectively employed in a neural network-based PDE solver to obtain an approximation solution of a restricted BKE, even when the dimension of the problem is very high. The resulting solution provides an approximation for the committor function that encodes mechanistic information for the reaction, paving a new way for understanding of complex chemical reactions and evaluation of reaction rates.

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

Complexion dictated thermal resistance with interface density in reactive metal multilayers

Multilayers composed of aluminum (A1) and platinum (Pt) exhibit a non-monotonic trend in thermal resistance with bilayer thickness as measured by time domain thermoreflectance. The thermal resistance initially increases with reduced bilayer thickness only to reach a maximum and then decrease with further shrinking of the multilayer period. These observations are attributed to the evolving impact of an intermixed amorphous complexion approximately 10 nm in thickness, which forms at each boundary between Al- and Pt-rich layers. Scanning transmission electron microscopy combined with energy dispersive X-ray spectroscopy find that the elemental composition of the complexion varies based on bilayer periodicity as does the fraction of the multilayer composed of this interlayer. These variations in complexion mitigate boundary scattering within the multilayers as shown by electronic transport calculations employing density functional theory and non-equilibrium Green's functions on amorphous structures obtained via finite temperature molecular dynamics. The lessening of boundary scattering reduces the total resistance to thermal transport leading to the observed non-monotonic trend thereby highlighting the central role of complexion on thermal transport within reactive metal multilayers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Toward an accurate equation of state and B1-B2 phase boundary for magnesium oxide up to terapascal pressures and electron-volt temperatures

By applying auxiliary-field quantum Monte Carlo, we calculate the equation of state (EOS) and B1-B2 phase transition of magnesium oxide (MgO) up to 1 TPa. Here, the results agree with available experimental data at low pressures and are used to benchmark the performance of various exchange-correlation functionals in density functional theory calculations. We determine PBEsol is an optimal choice for the exchange-correlation functional and perform extensive phonon and quantum molecular-dynamics calculations to obtain the thermal EOS. Our results provide a preliminary reference for the EOS and B1-B2 phase boundary of MgO from zero up to 10,500 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗