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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Rethinking the ill-posedness of the spectral function reconstruction — Why is it fundamentally hard and how Artificial Neural Networks can help

Reconstructing hadron spectral functions through Euclidean correlation functions are of the important missions in lattice QCD calculations. However, in a Källen–Lehmann (KL) spectral representation, the reconstruction is observed to be ill-posed in practice. It is usually ascribed to the fewer observation points compared to the number of points in the spectral function. In this paper, by solving the eigenvalue problem of continuous KL convolution, we show analytically that the ill-posedness of the inversion is fundamental and it exists even for continuous correlation functions. We discussed how to introduce regulators to alleviate the predicament, in which include the Artificial Neural Networks (ANNs) representations recently proposed by the Authors in another study. The uniqueness of solutions using ANNs representations is manifested analytically and validated numerically. Reconstructed spectral functions using different regularization schemes are also demonstrated, together with their eigen-mode decomposition. We observe that components with large eigenvalues can be reliably reconstructed by all methods, whereas those with low eigenvalues need to be constrained by regulators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Application of the Condensed Fukui Function to Predict Reactivity in Core–Shell Transition Metal Nanoparticles

Chemical reactivity descriptors are a powerful means for understanding reactivity in a wide variety of chemical compounds. These descriptors, rooted in density functional theory, have found broad application in organic chemical reactions, but have not been as widely applied for other classes of chemical species such as nanoparticles, which are the subject of this article. Specifically, we explore application of the Fukui function, the global hardness and softness, the local softness, and the dual descriptor to pure metallic and core–shell nanoparticles, with and without a CO molecule bound to the surface. We find that the Fukui function is useful in predicting and interpreting chemical reactivity, and that it correlates well with the results of the popular d-band center method. Differences in the Fukui function before and after bonding of a CO molecule to the surface of a nanoparticle reveal interesting information about the reactivity of the nanoparticle surface. The change in the Fukui function when an electric field is applied to the molecule is also considered. Though the results are generally good, some of the limitations of this approach become clear.

Chemical reactivity theory↗
DOE OSTI2020

Microbial functional genes commonly respond to elevated carbon dioxide

Atmospheric CO 2 concentration is increasing, largely due to anthropogenic activities. Previous studies of individual free-air CO 2 enrichment (FACE) experimental sites have shown significant impacts of elevated CO 2 (eCO 2 ) on soil microbial communities; however, no common microbial response patterns have yet emerged, challenging our ability to predict ecosystem functioning and sustainability in the future eCO 2 environment. Here we analyzed 66 soil microbial communities from five FACE sites, and showed common microbial response patterns to eCO 2 , especially for key functional genes involved in carbon and nitrogen fixation (e.g., pcc/acc for carbon fixation, nifH for nitrogen fixation), carbon decomposition (e.g., amyA and pulA for labile carbon decomposition, mnp and lcc for recalcitrant carbon decomposition), and greenhouse gas emissions (e.g., mcrA for methane production, norB for nitrous oxide production) across five FACE sites. Also, the relative abundance of those key genes was generally increased and directionally associated with increased biomass, soil carbon decomposition, and soil moisture. In addition, a further literature survey of more disparate FACE experimental sites indicated increased biomass, soil carbon decay, nitrogen fixation, methane and nitrous oxide emissions, plant and soil carbon and nitrogen under eCO 2 . A conceptual framework was developed to link commonly responsive functional genes with ecosystem processes, such as pcc/acc vs. soil carbon storage, amyA/pulA/mnp/lcc vs. soil carbon decomposition, and nifH vs. nitrogen availability, suggesting that such common responses of microbial functional genes may have the potential to predict ecosystem functioning and sustainability in the future eCO 2 environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The globus compute dataset: An open function-as-a-service dataset from the edge to the cloud

Here we present a unique function-as-a-service (FaaS) dataset capturing the use of the Globus Compute (previously funcX) platform. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, from the edge to high performance computing (HPC) cluster, and they may then invoke Python functions on those endpoints via a reliable cloud -hosted service. The dataset covers 31 weeks and includes 2121472 task submissions from 252 users executed on 580 remote computing endpoints. It includes 277386 registered functions. We describe the dataset and various observations, some that are similar to other FaaS datasets, for example, that 74% of tasks run for less than 1 s, and some that are unique to Globus Compute, for example, that endpoints are used in different ways and that the majority of functions are related to scientific computing and machine learning. To the best of our knowledge, this dataset represents the first federated FaaS dataset that includes user workloads, distributed computing endpoints, and analysis of registered function bodies. We expect the dataset to be useful for researching FaaS architectures, workload modeling, container warming, and other distributed computing architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The developments in modifying functionality of lignin and its application in biocomposites

With the advancement of sustainable material innovations, renewable natural biopolymers are gradually replacing traditional metal and petroleum-based synthetic materials due to their environmental friendliness, biodegradability, and economic advantages. Lignin, the second most abundant natural aromatic polymer in the plant kingdom, has emerged as a key candidate raw material for the development of green polymer systems because of its unique phenylpropane unit network structure, high carbon content, and rich functional group characteristics. However, challenges such as the inherent structural complexity, chemical inertness, and uneven molecular weight distribution of lignin limit its direct application. By employing modification strategies such as chemical functionalization and physical regulation, researchers can precisely control its reactivity, thermal stability, and interfacial compatibility, enabling the preparation of high-performance lignin-based functional composites. Here, this paper systematically reviews the principles and methodological advancements in lignin's multi-dimensional modification technology. It analyzes the mechanisms by which various chemical and physical modification techniques enhance the mechanical properties, functional responsiveness, and environmental adaptability of materials, and discusses innovative applications in fields such as intelligent packaging, biomedical materials, and energy storage devices. Furthermore, this review addresses the key challenges encountered in the high-value transformation of lignin, with the aim of offering a theoretical framework and technical pathway for the transformative development of lignin from agricultural and forestry by-products to functional material platforms.

Functional composites↗
DOE OSTI2021

From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas

Functional data analysis (FDA), which is a branch of statistics on modeling infinite dimensional random vectors resided in functional spaces, has become a major research area for Journal of Multivariate Analysis. We review some fundamental concepts of FDA, their origins and connections from multivariate analysis, and some of its recent developments, including multi-level functional data analysis, high-dimensional functional regression, and dependent functional data analysis. Here, we also discuss the impact of these new methodology developments on genetics, plant science, wearable device data analysis, image data analysis, and business analytics. Two real data examples are provided to motivate our discussions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Third-Order Møller–Plesset Theory Made More Useful? The Role of Density Functional Theory Orbitals

The practical utility of Møller–Plesset (MP) perturbation theory is severely constrained by the use of Hartree–Fock (HF) orbitals. It has recently been shown that the use of regularized orbital-optimized MP2 orbitals and scaling of MP3 energy could lead to a significant reduction in MP3 error. In this work, we examine whether density functional theory (DFT)-optimized orbitals can be similarly employed to improve the performance of MP theory at both the MP2 and MP3 levels. We find that the use of DFT orbitals leads to significantly improved performance for prediction of thermochemistry, barrier heights, noncovalent interactions, and dipole moments relative to the standard HF-based MP theory. Indeed, MP3 (with or without scaling) with DFT orbitals is found to surpass the accuracy of coupled-cluster singles and doubles (CCSD) for several data sets. We also found that the results are not particularly functional sensitive in most cases (although range-separated hybrid functionals with low delocalization error perform the best). As such, MP3 based on DFT orbitals thus appears to be an efficient, noniterative O(N 6 ) scaling wave-function approach for single-reference electronic structure computations. Scaled MP2 with DFT orbitals is also found to be quite accurate in many cases, although modern double hybrid functionals are likely to be considerably more accurate.

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

A Nonorthogonal State-Interaction Approach for Matrix Product State Wave Functions

We present a state-interaction approach for matrix product state (MPS) wave functions in a nonorthogonal molecular orbital basis. Our approach allows us to calculate, for example, transition and spin–orbit coupling matrix elements between arbitrary electronic states, provided that they share the same one-electron basis functions and size of the active orbital space, respectively. The key element is the transformation of the MPS wave functions of different states from a nonorthogonal to a biorthonormal molecular orbital basis representation, by exploiting a sequence of nonunitary transformations, following a proposal by Malmqvist [Int. J. Quantum Chem.1986, 30, 479]. This is well-known for traditional wave function parametrizations but has not yet been exploited for MPS wave functions.

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

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↗
DOE OSTI2018

Enhancing Cooperativity in Bifunctional Acid–Pd Catalysts with Carboxylic Acid-Functionalized Organic Monolayers

Here, cooperative catalysts containing a combination of noble metal hydrogenation sites and Bronsted acid sites are critical for many reactions, including the deoxygenation (DO) of biomass-derived oxygenates in the upgrading of pyrolysis oil. One route toward the design of cooperative catalysts is to tether two different catalytically active functions so that they are in close proximity while avoiding undesirable interactions that can block active sites. Here, we deposited carboxylic acid (CA)-functionalized organophosphonate monolayers onto Al 2 O 3 -supported Pd nanoparticle catalysts to prepare bifunctional catalysts containing both Bronsted acid and metal sites. Modification with phosphonic acids (PAs) improved activity and selectivity for gas-phase DO reactions, but the degree of improvement was highly sensitive to both the presence and positioning of the CA group, suggesting a significant contribution from both the PA and CA sites. Short spacer lengths of 1-2 methylene groups between the phosphonate head and CA tail were found to yield the best DO rates and selectivities, whereas longer chains performed similarly to self-assembled monolayers having alkyl tails. Results from a combination of density functional theory and Fourier transform infrared spectroscopy suggested that the enhanced catalyst performance on the optimally positioned CAs was due to the generation of strong acid sites on the Al 2 O 3 support adjacent to the metal. Furthermore, the high activity of these sites was found to result from a hydrogen-bonded cyclic structure involving cooperativity between the phosphonate head group and CA tail function. More broadly, these results indicate that functional groups tethered to supports via organic ligands can influence catalytic chemistry on metal nanoparticles.

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

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↗
DOE OSTI2017

Plasma-Functionalized Polytetrafluoroethylene Nanoparticles for Improved Wear in Lubricated Contact

Plasma-functionalized polytetrafluoroethylene (PTFE) nanoparticles were employed to evaluate their utility in improving the lubrication property of a group III mineral oil with a significantly low amount of zinc dialkyl dithiophosphate (ZDDP). The particles were coated with two consecutive films; the initial coating contained silica to enhance amorphous glassy tribofilm formation, followed by a methacrylate film to protect the silica coating and enhance dispersibility in the oil. The functionalized nanoparticles were evaluated for their tribological performance using a high-frequency reciprocating rig, in a cylinder-on-flat configuration. The oil formulations containing ZDDP (350 ppm phosphorus level) and the functionalized nanoparticles resulted in dramatic reductions in the friction coefficient and overall wear compared to the samples containing nonfunctionalized PTFE nanoparticles, ZDDP (350 ppm P), and samples devoid of nanoparticles but containing ZDDP with a 700 ppm P treat rate. XPS and XANES spectroscopy were employed to characterize the tribological films formed on the test samples. The samples with functionalized particles and ZDDP clearly exhibited tribofilms with Si- and F-doped polyphosphates of Zn coupled with the presence of ZnS at the metal-tribofilm interface. On the other hand, oils without the functionalized nanoparticles have oxides of Fe and to a lesser extent short-chain phosphates of Zn. The overall results suggest that the synergism between plasma-coated PTFE nanoparticles and ZDDP contributed to the development of protective tribofilms even at reduced amount of phosphorus in the oil. This new method of employing nanoparticles to deliver novel antifriction and antiwear chemistries at the tribological interfaces stands out as a promising approach to further reduce P levels in oils without compromising friction and wear performance.

plasma functionalization↗
DOE OSTI2025

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↗
DOE OSTI2024

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↗
DOE OSTI2013

Simulating One-Photon Absorption and Resonance Raman Scattering Spectra Using Analytical Excited State Energy Gradients within Time-Dependent Density Functional Theory

A parallel implementation of analytical time-dependent density functional theory gradients is presented for the quantum chemistry program NWChem. The implementation is based on the Lagrangian approach developed by Furche and Ahlrichs. To validate our implementation, we first calculate the Stokes shifts for a range of organic dye molecules using a diverse set of exchange-correlation functionals (traditional density functionals, global hybrids, and range-separated hybrids) followed by simulations of the one-photon absorption and resonance Raman scattering spectrum of the phenoxyl radical, the well-studied dye molecule rhodamine 6G, and a molecular host–guest complex (TTFcCBPQT 4+ ). The study of organic dye molecules illustrates that B3LYP and CAM-B3LYP generally give the best agreement with experimentally determined Stokes shifts unless the excited state is a charge transfer state. Absorption, resonance Raman, and fluorescence simulations for the phenoxyl radical indicate that explicit solvation may be required for accurate characterization. For the host–guest complex and rhodamine 6G, it is demonstrated that absorption spectra can be simulated in good agreement with experimental data for most exchange-correlation functionals. Finally, however, because one-photon absorption spectra generally lack well-resolved vibrational features, resonance Raman simulations are necessary to evaluate the accuracy of the exchange-correlation functional for describing a potential energy surface.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2013

Dielectric Properties of Water Ice, the Ice Ih/XI Phase Transition, and an Assessment of Density Functional Theory

The dielectric properties of the hydrogen disordered hexagonal phase (Ih) of water ice have been computed using density functional theory (DFT) based Monte Carlo simulations in the isobaric–isothermal ensemble. Temperature dependent data yield a fit for the Curie–Weiss law of the system and hence a prediction of the temperature of the phase transition from the Ih phase to the hydrogen ordered ice XI phase. Direct simulations around the phase transition temperature confirm and refine the predicted phase transition temperatures and provide data for further properties, such as the linear thermal expansion coefficient. Results have been obtained with both hybrid and semilocal density functionals, which yields insight in the performance of the electronic structure method. In particular, the hybrid functional yields significantly more realistic dielectric constants than the semilocal variant, namely ε ≈ 116 as opposed to ε ≈ 151 at 273 K (ε experiment = 95). This can be attributed to the tendency of semilocal functionals to be biased to configurations with a large dipole moment, and their overestimation of the dipole moments of these configurations. This is also reflected in the estimates of the Ih/XI transition temperature, which is 70–80 and 90–100 K for the hybrid and semilocal functional respectively. Finally, DFT based sampling of the millions of configurations necessary for this work has been enabled by a Tree Monte Carlo algorithm, designed for massively parallel computers.

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

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↗
DOE OSTI2013

Refined algebraic quantisation in a system with nonconstant gauge invariant structure functions

In a previous work [J. Louko and E. Martínez-Pascual, “Constraint rescaling in refined algebraic quantisation: Momentum constraint,” J. Math. Phys. 52, 123504 (2011)], refined algebraic quantisation (RAQ) within a family of classically equivalent constrained Hamiltonian systems that are related to each other by rescaling one momentum-type constraint was investigated. In the present work, the first steps to generalise this analysis to cases where more constraints occur are developed. The system under consideration contains two momentum-type constraints, originally abelian, where rescalings of these constraints by a non-vanishing function of the coordinates are allowed. These rescalings induce structure functions at the level of the gauge algebra. Providing a specific parametrised family of real-valued scaling functions, the implementation of the corresponding rescaled quantum momentum-type constraints is performed using RAQ when the gauge algebra: (i) remains abelian and (ii) undergoes into an algebra of a nonunimodular group with nonconstant gauge invariant structure functions. Case (ii) becomes the first example known to the author where an open algebra is handled in refined algebraic quantisation. Challenging issues that arise in the presence of non-gauge invariant structure functions are also addressed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗