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Metallic behavior and negative differential resistance properties of (InAs){sub n} (n = 2 − 4) molecule cluster junctions via a combined non–equilibrium Green's function and density functional theory study

In this present work, the geometric structures and electronic transport properties of (InAs){sub n} (n = 2, 3, 4) molecule cluster junctions are comparatively investigated using NEGF combined with DFT. Results indicate that all (InAs){sub n} molecule cluster junctions present metallic behavior at the low applied biases ([−2V, 2V]), while NDR appears at a certain high bias range. Our calculation shows that the current of (InAs){sub 4} molecule cluster–based junction is almost the largest at any bias. The mechanisms of the current–voltage characteristics of all the three molecule cluster junctions are proposed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Continued Development of Expert System Tools for NPSS Engine Diagnostics

The objectives of this grant were to work with previously developed NPSS (Numerical Propulsion System Simulation) tools and enhance their functionality; explore similar AI systems; and work with the High Performance Computing Communication (HPCC) K-12 program. Activities for this reporting period are briefly summarized and a paper addressing the implementation, monitoring and zooming in a distributed jet engine simulation is included as an attachment.

Lewandowski, Henry↗

Density Functionals for Hydrogen Storage: Defining the H2Bind275 Test Set with Ab Initio Benchmarks and Assessment of 55 Functionals

Efficient and high-capacity storage materials are indispensable for a hydrogen-based economy. In silico tools can accelerate the process of discovery of new adsorbent materials with optimal hydrogen adsorption enthalpies. Density functional theory is well-poised to become a very useful tool for enabling high-throughput screening of potential materials. In this work, we have identified density functional approximations that provide good performance for hydrogen binding applications following a two-pronged approach. First, we have compiled a data set (H2Bind275) that comprehensively represents the hydrogen binding problem capturing the chemical and mechanistic diversity in the binding sites encountered in hydrogen storage materials. We have also computed reference interaction energies for this data set using coupled-cluster theory. Second, we have assessed the performance of 55 density functional approximations for predicting H 2 interaction energies and have identified two hybrid density functionals (ωB97X-V and ωB97M-V), two double hybrid density functionals (DSD-PBEPBE-D3(BJ) and PBE0-DH), and one semilocal density functional (B97M-V) as the best performing ones. We have recommended the addition of empirical dispersion corrections to systematically underbinding density functionals such as revPBE, BLYP, and B3LYP for improvements in performance at negligible additional cost. We have also recommended the usage of the def2-TZVPP basis set as it represents a good compromise between accuracy and cost, limiting the finite basis set errors to less than 1 kJ/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A de novo matrix for macroscopic living materials from bacteria

Engineered living materials (ELMs) embed living cells in a biopolymer matrix to create materials with tailored functions. While bottom-up assembly of macroscopic ELMs with a de novo matrix would offer the greatest control over material properties, we lack the ability to genetically encode a protein matrix that leads to collective self-organization. Here we report growth of ELMs from Caulobacter crescentus cells that display and secrete a self-interacting protein. This protein formed a de novo matrix and assembled cells into centimeter-scale ELMs. Discovery of design and assembly principles allowed us to tune the composition, mechanical properties, and catalytic function of these ELMs. This work provides genetic tools, design and assembly rules, and a platform for growing ELMs with control over both matrix and cellular structure and function.

59 BASIC BIOLOGICAL SCIENCES↗

A comparative study of calibration techniques for finite strain elastoplasticity: Numerically-exact sensitivities for FEMU and VFM

Accurate identification of material parameters is crucial for predictive modeling in computational mechanics. Here, the two primary approaches in the experimental mechanics community for calibration from full-field digital image correlation data are known as finite element model updating (FEMU) and the virtual fields method (VFM). In VFM, the objective function is a squared mismatch between internal and external virtual work or power. In FEMU, the objective function quantifies the weighted mismatch between model predictions and corresponding experimentally measured quantities of interest. It is minimized by iteratively updating the parameters of an FE model. While FEMU is seen as more flexible, VFM is commonly used instead of FEMU due to its considerably greater computational expense. However, comparisons between the two methods usually involve approximations of gradients or sensitivities with finite difference schemes, thereby making direct assessments difficult. Hence, in this study, we compare VFM and FEMU in the context of numerically-exact sensitivities obtained through local sensitivity analyses and the application of automatic differentiation software. To this end, we conduct a series of test cases to assess both methods under practical challenges using a finite strain elastoplasticity model.

Automatic differentiation↗

Detection of gamma-neutron radiation by solid-state scintillation detectors. Detection of gamma-neutron radiation by novel solid-state scintillation detectors

It is known that solid-state scintillators can be used for detection of both gamma radiation and neutron flux. In the past, neutron detection efficiencies of such solid-state scintillators did not exceed 5-7%. At the same time it is known that the detection efficiency of the gamma-neutron radiation characteristic of nuclear fissionable materials is by an order of magnitude higher than the efficiency of detection of neutron fluxes alone. Thus, an important objective is the creation of detection systems that are both highly efficient in gamma-neutron detection and also capable of exhibiting high gamma suppression for use in the role of detection of neutron radiation. In this work, we present the results of our experimental and theoretical studies on the detection efficiency of fast neutrons from a {sup 239}Pu-Be source by the heavy oxide scintillators BGO, GSO, CWO and ZWO, as well as ZnSe(Te, O). The most probable mechanism of fast neutron interaction with nuclei of heavy oxide scintillators is the inelastic scattering (n, n'γ) reaction. In our work, fast neutron detection efficiencies were determined by the method of internal counting of gamma-quanta that emerge in the scintillator from (n, n''γ) reactions on scintillator nuclei with the resulting gamma energies of ∼20-300 keV. The measured efficiency of neutron detection for the scintillation crystals we considered was ∼40-50 %. The present work included a detailed analysis of detection efficiency as a function of detector and area of the working surface, as well as a search for new ways to create larger-sized detectors of lower cost. As a result of our studies, we have found an unusual dependence of fast neutron detection efficiency upon thickness of the oxide scintillators. An explanation for this anomaly may involve the competition of two factors that accompany inelastic scattering on the heavy atomic nuclei. The transformation of the energy spectrum of neutrons involved in the (n, n'γ) reactions towards lower energies and the isotropic character of scattering of the secondary neutrons may lead to the observed limitation of the length of effective interaction, since a fraction of the secondary neutrons that propagate in the forward direction are not subject to further inelastic scattering because of their substantially lower energy. At these reduced energies, it is the capture cross-section (n, γ) that becomes predominant, resulting in lower detection efficiency. Based on these results, several types of detectors have been envisioned for application in detection systems for nuclear materials. The testing results for one such detector are presented in this work. We have studied the possibility of creation of a composite detector with scintillator granules placed inside a transparent polymer material. Because of the low transparency of such a dispersed scintillator, better light collection conditions are ensured by incorporation of a light guide between the scintillator layers. This guide is made of highly transparent polymer material. The use of a high-transparency hydrogen-containing polymer material for light guides not only ensures optimum conditions of light collection in the detector, but also allows certain deceleration of neutron radiation, increasing its interaction efficiency with the composite scintillation panels; accordingly, the detector signal is increased by 5-8%. When fast neutrons interact with the scintillator material, the resulting inelastic scattering gamma-quanta emerge, having different energies and different delay times with respect to the moment of the neutron interaction with the nucleus of the scintillator material (delay times ranging from 1x10{sup -9} to 1.3x10{sup -6} s). These internally generated gamma-quanta interact with the scintillator, and the resulting scintillation light is recorded by the photo-receiver. Since neutron sources are also strong sources of low-energy gamma-radiation, the use of dispersed ZnSe(Te) scintillator material provides high gamma-radiation detection efficiency in that energy range. This new type of gamma-neutron detector is based on a 'sandwich' structure using a ZnSe composite film and light guide with a fast neutron detection efficiency of about 6%. Its high detection efficiency of low-energy gamma-radiation allows a substantial increase (by an order of magnitude) in the efficiency of detection of neutron sources and transuranic materials by means of simultaneous detection of accompanying gamma-radiation. The design and fabrication technology of this detector allows the creation of gamma-neutron detectors characterized by high sensitivity at relatively low costs (as compared with analogs using oxide scintillators) for portable inspection systems. The sandwich structure can be comprised of any number of plates, with no limitations on thickness or area.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons

Neural networks (NNs) are currently changing the computational paradigm on how to combine data with mathematical laws in physics and engineering in a profound way, tackling challenging inverse and ill-posed problems not solvable with traditional methods. However, quantifying errors and uncertainties in NN-based inference is more complicated than in traditional methods. This is because in addition to aleatoric uncertainty associated with noisy data, there is also uncertainty due to limited data, but also due to NN hyperparameters, overparametrization, optimization and sampling errors as well as model misspecification. Although there are some recent works on uncertainty quantification (UQ) in NNs, there is no systematic investigation of suitable methods towards quantifying the total uncertainty effectively and efficiently even for function approximation, and there is even less work on solving partial differential equations and learning operator mappings between infinite-dimensional function spaces using NNs. In this work, we present a comprehensive framework that includes uncertainty modeling, new and existing solution methods, as well as evaluation metrics and post-hoc improvement approaches. Further, to demonstrate the applicability and reliability of our framework, we present an extensive comparative study in which various methods are tested on prototype problems, including problems with mixed input-output data, and stochastic problems in high dimensions. In the Appendix, we include a comprehensive description of all the UQ methods employed. Further, to help facilitate the deployment of UQ in Scientific Machine Learning research and practice, we present and develop in [1] an open-source Python library (github.com/Crunch-UQ4MI/neuraluq), termed NeuralUQ, that is accompanied by an educational tutorial and additional computational experiments.

11 physics-informed neural networks↗

Hydrogen Bonding Optimizes Singlet Fission in Carboxylic Acid Functionalized Anthradithiophene Films

The rate of singlet fission, the process of generating two triplet excitons with photoexcitation of one singlet exciton, depends on a combination of singlet/triplet energy balance and intermolecular coupling. In this work, we perform carboxylic acid functionalization of anthradithiophene (ADT) derivatives that result in hydrogen bonds that drive molecular orientation and strong electronic coupling of polycrystalline ADT thin films, leading to ultrafast singlet fission without significant enthalpic driving force. ADT with a single carboxylic acid group exhibits weak intermolecular coupling and slow and inefficient singlet fission, much like the parent ADT, and substitution of different alkylsilyl solubilizing groups has little effect. However, the addition of two carboxylic acid groups on either end of the long axis favors significant coupling and crystallinity in as-deposited thin films that increase the effective singlet fission rate by roughly three orders of magnitude. The properties of the triplet pair, particularly its propensity to form long-lived independent triplets, are also influenced by the degree of long-range intermolecular coupling. The enhancement of intermolecular coupling specific to singlet fission using the ubiquitous cyclic hydrogen bonding motif could impact triplet pair utilization schemes in a variety of contexts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

XBoard: A Framework for Integrating and Enhancing Collaborative Work Practices

Teams typically collaborate in different modes including face-to-face meetings, meetings that are synchronous (i. e. require parties to participate at the same time) but distributed geographically, and meetings involving asynchronously working on common tasks at different times. The XBoard platform was designed to create an integrated environment for creating applications that enhance collaborative work practices. Specifically, it takes large, touch-screen enabled displays as the starting point for enhancing face-to-face meetings by providing common facilities such as whiteboarding/electronic flipcharts, laptop projection, web access, screen capture and content distribution. These capabilities are built upon by making these functions inherently distributed by allowing these sessions to be easily connected between two or more systems at different locations. Finally, an information repository is integrated into the functionality to provide facilities for work practices that involve work being done at different times, such as reports that span different shifts. The Board is designed to be extendible allowing customization of both the general functionality and by adding new functionality to the core facilities by means of a plugin architecture. This, in essence, makes it a collaborative framework for extending or integrating work practices for different mission scenarios. XBoard relies heavily on standards such as Web Services and SVG, and is built using predominately Java and well-known open-source products such as Apache and Postgres. Increasingly, organizations are geographically dispersed, and rely on "virtual teams" that are assembled from a pool of various partner organizations. These organizations often have different infrastructures of applications and workflows. The XBoard has been designed to be a good partner in these situations, providing the flexibility to integrate with typical legacy applications while providing a standards-based infrastructure that is readily accepted by most organizations. The XBoard has been used on the Mars Exploration Rovers mission at JPL, and is currently being used or considered for use in pilot projects at Johnson Space Center (JSC) Mission Control, the University of Arizona Lunar and Planetav Laboratory (Phoenix Mars Lander), and MBART (Monterey Bay Aquarium Research Institute).

Shab, Ted↗

Anion Exchange Ionomers: Impact of Chemistry on Thin-Film Properties

Ionomer thin-films (i.e., 20–100 nm) on supports serve as model systems to understand ionomer-catalyst interfacial behavior as well as the confinement-driven deviation in properties from bulk membranes. While ionomer thin-films have been examined for proton exchange ionomers, the thin-film properties of anion exchange ionomers (AEIs) remain largely unexplored. More importantly, delineating the convoluted impact of chemistry and confinement on thin-film morphology and hydration is of interest to advancing the field on functional ionic interfaces. In this work, these aspects are studied by using AEIs of different backbones (perfluorinated, aliphatic, and aromatic) and side chains (various lengths, and single versus dual functional groups). Quartz-crystal microbalance and spectroscopic ellipsometry are used to analyze density and coupled with calculated free volume fraction of thin-films to provide insights on their gas transport properties. AEI side-chain's chemical character plays a key role in how confinement modulates hydration (in thin-film versus bulk). Overall, the results elucidate the effects of backbone, side-chain chemistry versus anion/cation type in the confinement-driven changes in thin-film morphology and swelling. This study also provides new insights for tuning AEI transport functionalities at interfaces via chemistry, which can benefit the design and development of electrode-ionomers for alkaline membrane-based energy systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The boundary entropy function for interface conformal field theories

In 1+1 dimensional conformal field theory with a boundary the boundary contribution to the entanglement entropy is determined by a single number g effectively counting the boundary degrees of freedom. In contrast, in 1+1 dimensional interface CFTs the corresponding quantity is a non-trivial function depending on the position of the interval relative to the interface, giving access to much more detailed information about the defect. In this work we determined this g -function in several examples using holography and derive some of its basic properties from holography and strong subadditivity.

AdS-CFT correspondence↗

Density functional thermodynamic description of spin, phonon and displacement degrees of freedom in antiferromagnetic-to-paramagnetic phase transition in YNiO 3

This work herein demonstrates a direct density functional description of the finite-temperature thermodynamic properties of solids exhibiting phase transitions through positional and spin symmetry breaking degrees of freedom. A classic example addressed here is the rare-earth (R) nickelates RNiO 3 where the ground state is characterized by crystallographic and magnetic (e.g., antiferromagnetic) long-range order (LRO), whereas the higher temperature paramagnetic phase manifests a range of local spin and positional symmetry breaking motifs with short-range order (SRO). Unlike time-dependent simulations of spin and positional degrees of freedom, in the present work, phases are described via a superposition of static configurations constructed by populating a periodic base lattice supercell allowing for the formation of energy lowing distribution of positional and spin local motifs. The thermal populations of the configurations in such a superposition phase are obtained from the energy-minimized Density Functional Theory (DFT)-calculated partition functions at different temperatures. This approach offers flexible inclusion of different physical contributions to the free energy, such as elastic, electronic and phonon free energies, all obtained from the same underlying DFT total energy calculations of periodic structures. The thermodynamic and magnetic properties of both LRO and SRO crystallographic and spin phases, including antiferromagnetic (AFM) to paramagnetic (PM) Néel phase transition in YNiO3 are studied. Including spin and phonon contributions, we find a DFT-calculated Néel temperature to be 144 K in satisfactory agreement with the experimental value of 145 K; whereas omitting the phonon contribution, one obtains a Néel temperature of 81 K. We present phonon contributions to the DFT-calculated temperature-dependent SRO, heat capacities, and the polymorphous distribution of nonzero local magnetic moments in the PM phase. This approach thus extends to finite temperatures the symmetry-broken DFT description of both the AFM and PM phases, demonstrating that a thermodynamic superposition approach based on symmetry broken configurations evaluated by a mean-field like DFT is sufficient to obtain a consistent description of the thermal physics of the AFM, PM phases and their interconversion in 3d oxides illustrated by YNiO 3 .

36 MATERIALS SCIENCE↗

Mechanistic insights into hydrodeoxygenation of phenol on bimetallic phosphide catalysts

Catalytic hydrodeoxygenation (HDO) of phenolics is a necessary step for upgrading bio-oils to transportation fuels. Bimetallic catalysts offer the potential of increased activities and selectivities for desired products. Adding non-metallic elements, such as phosphorous, allows for charge distribution between the metal and nonmetal atoms, which improves Lewis acid character of catalytic surfaces. This work utilizes experimental and density functional theory (DFT) based calculations to identify potential C–O bond cleavage pathways and product selectivities for HDO reactions on FeMoP, RuMoP, and NiMoP catalysts. Our work demonstrates that FeMoP catalyst favors direct deoxygenation pathway due to a lower activation energy barrier for C–O bond cleavage whereas RuMoP and NiMoP catalysts promote ring hydrogenation first, followed by the cleavage of C–O bond. The Bader charge analysis indicates that for these catalytic systems Moδ+ site bears a large positive charge which acts as a Lewis acid site for HDO reactions. Altogether, we find that trends in the experimental product selectivities are in good agreement with that predicted with DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Density Functional Tight Binding Insights into Plasmonic Silver–Platinum Nanoparticles and Alloys for Enhanced Photocatalysis

Developing accurate and efficient Slater-Koster (SK) tight-binding parameter sets is essential for quantum plasmonic studies of alloyed metal nanoparticles, as conventional time dependent density functional theory (TD-DFT) calculations are computationally prohibitive for larger clusters. In this work, we develop and validate density functional tight binding (DFTB) parameter sets for both ground state (GS-SK) and excited state (ES-SK) calculations to study the structural, electronic, and optical properties of silver (Ag), platinum (Pt), and Ag–Pt nanoalloys. Our investigation of the ground state properties demonstrates that the GS-SK parameters enable DFTB to closely reproduce the electronic structures of platinum clusters with diverse sizes and geometries – showing qualitative agreement with DFT for density of states (DOS) profiles and energy levels. The ES-SK parameters accurately describe excited-state properties compared to TD-DFT reference calculations, including the broad, featureless absorption profiles of Pt that are dominated by interband transitions. Using the ES-SK parameters within a real-time TD-DFTB framework, we compute size-dependent optical absorption spectra of Ag, Pt and Ag-Pt nanocubes containing up to 1099 atoms (size ∼4.18 nm). A detailed study of Ag–Pt and Pt-Ag core–shell nanoparticles shows quenching of the Ag plasmon resonance even at monolayer coverage for Ag-Pt, but not for Pt-Ag. We also show how to define submonolayer Ag-core Pt-shell cubic structures that have similar optical properties to those generated experimentally for much larger particles, which offers potential for describing plasmon-enhanced photocatalysis. Collectively, the GS-SK and ES-SK parameter sets provide an accurate, computationally efficient approach for modeling the complex optical and electronic behavior of noble–transition metal nanostructures and their alloys.

SPR↗

Fluctuation removal around spectral and temporal constancy limits via use of an extended space expectation value weight function for singular quantum systems

This work is a new extension to our a very recent work whose paper will appear in the proceedings of a very recent international conference. What we have done in the previous work is the use of a weight operator to suppress the singularities causing nonexistence of some of temporal Maclaurin expansion coefficients. The weight operator has been constructed in such a way that certain number of expectation values of position operator’s first positive integer powers with and without the chosen weight operator match. Therein this match has not been considered for the momentum operator’s corresponding power expectation values and a finite linear combination of the spatial variable’s first reciprocal powers has been used in the construction of the weight operator. Here, that approach is extended to the case where matches for both position and momentum operators are considered and the weight operator involves finite linear combinations of the spatial variable’s both positive integer powers and their reciprocals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Model-independent plotting of the cosmological scale factor as a function of lookback time

In this work we describe a model-independent method of developing a plot of scale factor a(t) versus lookback time t{sub L} from the usual Hubble diagram of modulus data against redshift. This is the first plot of this type. We follow the model-independent methodology of Daly and Djorgovski used for their radio-galaxy data. Once the a(t)data plot is completed, any model can be applied and will display as described in the standard literature. We then compile an extensive data set to z = 1.8 by combining Type Ia supernovae (SNe Ia) data from SNLS3 of Conley et al., high-z SNe data of Riess et al., and radio-galaxy data of Daly and Djorgovski to validate the new plot. We first display these data on a standard Hubble diagram to confirm the best fit for ΛCDM cosmology, and thus validate the joined data set. The scale factor plot is then developed from the data and the ΛCDM model is again displayed from a least-squares fit. The fit parameters are in agreement with the Hubble diagram fit confirming the validity of the new plot. Of special interest is the transition time of the universe, which in the scale factor plot will appear as an inflection point in the data set. Noise is more visible in this presentation, which is particularly sensitive to inflection points of any model displayed in the plot, unlike on a modulus-z diagram, where there are no inflection points and the transition-z is not at all obvious by inspection. We obtain a lower limit of z ≥ 0.6. It is evident from this presentation that there is a dearth of SNe data in the range z = 1-2, exactly the range necessary to confirm a ΛCDM transition-z around z = 0.76. We then compare a 'toy model' wherein dark matter is represented as a perfect fluid with an equation of state p = –(1/3) ρ to demonstrate the plot sensitivity to model choice. Its density varies as 1/t {sup 2} and it enters the Friedmann equations as Ω{sub dark}/t {sup 2}, replacing only the Ω{sub dark}/a {sup 3} term. The toy model is a close match to ΛCDM, but separates from it on the scale factor plot for similar ΛCDM density parameters. It is described in the Appendix. A more complete transition time analysis will be presented in a future paper.

79 ASTRONOMY AND ASTROPHYSICS↗