Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “parallel computational chemistry”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

Water–Hydrocarbon Interactions in Anionic Pyrene Monohydrate

Interactions between water and polycyclic aromatic hydrocarbons are essential in many aspects of chemistry, from interstellar and atmospheric processes to interfacial hydrophobicity and wetting phenomena. Despite their growing importance, the intermolecular potentials of the water-hydrocarbon interactions are underdeveloped compared to water-water potentials, and there are similarly few experimental probes that are sensitive to the details of the water-hydrocarbon potential. We present a combined experimental and computational study of anionic pyrene monohydrate, one of the simplest water/hydrocarbon clusters. The action spectrum in the OH region of the mass-selected cluster ion provides a rigorous benchmark for intermolecular potentials and computational methodologies. We identify missing intermolecular interactions and shortcomings in conventional dynamics calculations by comparing experimental data to density functional theory and classical molecular dynamics calculations. Kinetic trapping is prevalent, even for one water molecule and one pyrene molecule, leading to slow equilibration in conventional molecular dynamics calculations, even on nanosecond timescales and at low temperatures (50 K). At constant energy, temperature fluctuations for the pair of molecules are substantial. Immersing the system in a bath of soft spheres and employing parallel tempering alleviates kinetic trapping and dampens temperature fluctuations, bringing the system closer to the thermodynamic limit. With such augmented sampling, a simple, flexible water model reproduces the linewidth and the asymmetric broadening of the symmetric OH stretching mode, which we assign to spectral diffusion. In the OH stretching region, dynamics calculations predict a more intense antisymmetric peak than experiments observe but do not predict the bimodal split symmetric peak that the experiments show. Furthermore, our work suggests that electronic polarization, missing in the empirical force field, is responsible for the first discrepancy and that quantum nuclear effects, captured neither in density functional theory nor in classical dynamics, may be responsible for the second.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uranium(VI) Sorption onto Montmorillonite Clay in the Presence of Ca2+/Calcite Impurities

The storage of nuclear waste creates a series of significant environmental risks. One attempt to minimize these potential impacts is the use of underground geological repositories, where waste containers are surrounded by geologic buffer materials creating an engineered barrier. One buffer material that has been of interest is bentonite, which is largely composed of montmorillonite clay. These barriers limit the mobility of radioactive contaminants, such as uranium(VI), into environmental systems based on contaminant sorption onto the clay material. System conditions, such as pH, the presence of mineral impurities such as calcite, and the concentrations of U(VI) and atmospheric CO2 also affect the sorption behavior of U(VI) onto these clay barriers. This study focuses on the effects of Ca2+ and calcite (CaCO3), a common impurity found in montmorillonite on the sorption behavior of U(VI). Computer simulations of the chemical solution species (chemical form) of U(VI), in the absence and presence of Ca2+/calcite impurities are performed in parallel with laboratory sorption experiments. Experimental data will be compared to modeling results to help obtain further insights regarding the impacts of Ca2+/calcite impurities on U(VI) solution speciation and sorption behavior onto montmorillonite.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ppdx : Automated modeling of protein–protein interaction descriptors for use with machine learning

This paper describes ppdx, a python workflow tool that combines protein sequence alignment, homology modeling, and structural refinement, to compute a broad array of descriptors for characterizing protein–protein interactions. The descriptors can be used to predict various properties of interest, such as protein–protein binding affinities, or inhibitory concentrations (IC 50 ), using approaches that range from simple regression to more complex machine learning models. The software is highly modular. It supports different protocols for generating structures, and 95 descriptors can be currently computed. More protocols and descriptors can be easily added. The implementation is highly parallel and can fully exploit the available cores in a single workstation, or multiple nodes on a supercomputer, allowing many systems to be analyzed simultaneously. As an illustrative application, ppdx is used to parametrize a model that predicts the IC 50 of a set of antigens and a class of antibodies directed to the influenza hemagglutinin stalk.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective CO Production by Photoelectrochemical Methane Oxidation on TiO 2

The inertness of the C–H bond in CH 4 poses significant challenges to selective CH 4 oxidation, which often proceeds all the way to CO 2 once activated. Selective oxidation of CH 4 to high-value industrial chemicals such as CO or CH 3 OH remains a challenge. Presently, the main methods to activate CH 4 oxidation include thermochemical, electrochemical, and photocatalytic reactions. Of them, photocatalytic reactions hold great promise for practical applications but have been poorly studied. Existing demonstrations of photocatalytic CH 4 oxidation exhibit limited control over the product selectivity, with CO 2 as the most common product. The yield of CO or other hydrocarbons is too low to be of any practical value. In this work, we show that highly selective production of CO by CH4 oxidation can be achieved by a photoelectrochemical (PEC) approach. Under our experimental conditions, the highest yield for CO production was 81.9%. The substrate we used was TiO 2 grown by atomic layer deposition (ALD), which features high concentrations of Ti 3+ species. The selectivity toward CO was found to be highly sensitive to the substrate types, with significantly lower yield on P25 or commercial anatase TiO 2 substrates. Moreover, our results revealed that the selectivity toward CO also depends on the applied potentials. Based on the experimental results, we proposed a reaction mechanism that involves synergistic effects by adjacent Ti sites on TiO 2 . Spectroscopic characterization and computational studies provide critical evidence to support the mechanism. Furthermore, the synergistic effect was found to parallel heterogeneous CO 2 reduction mechanisms. Our results not only present a new route to selective CH 4 oxidation, but also highlight the importance of mechanistic understandings in advancing heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulated evolution of fluorophores for light emitting diodes

Organic light emitting diodes based on fluorophores with a propensity for thermally activated delayed fluorescence (TADF) are able to circumvent limitations imposed on device efficiency by spin statistics. Molecules with a propensity for TADF necessarily have two properties: a small gap between the lowest lying singlet and triplet excited states and a large transition dipole moment for fluorescence. In this work, we demonstrate the use of a genetic algorithm to search a region of chemical space for molecules with these properties. This algorithm is based on a flexible and intuitive representation of the molecule as a tree data structure, in which the nodes correspond to molecular fragments. Our implementation takes advantage of hybrid parallel graphics processing unit accelerated computer clusters to allow efficient sampling while retaining a reasonably accurate description of the electronic structure (in this case, CAM-B3LYP/6-31G{sup ∗∗}). In total, we have identified 3792 promising candidate fluorophores from a chemical space containing 1.26 × 10{sup 6} molecules. This required performing electronic structure calculations on only 7518 molecules, a small fraction of the full space. Several novel classes of molecules which show promise as fluorophores are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a CNS-permeable reactivator for nerve agent exposure: an iterative, multi-disciplinary approach

Nerve agents have experienced a resurgence in recent times with their use against civilian targets during the attacks in Syria (2012), the poisoning of Sergei and Yulia Skripal in the United Kingdom (2018) and Alexei Navalny in Russia (2020), strongly renewing the importance of antidote development against these lethal substances. The current standard treatment against their effects relies on the use of small molecule-based oximes that can efficiently restore acetylcholinesterase (AChE) activity. Despite their efficacy in reactivating AChE, the action of drugs like 2-pralidoxime (2-PAM) is primarily limited to the peripheral nervous system (PNS) and, thus, provides no significant protection to the central nervous system (CNS). This lack of action in the CNS stems from their ionic nature that, on one end makes them very powerful reactivators and on the other renders them ineffective at crossing the Blood Brain Barrier (BBB) to reach the CNS. In this report, we describe the use of an iterative approach composed of parallel chemical and in silico syntheses, computational modeling, and a battery of detailed in vitro and in vivo assays that resulted in the identification of a promising, novel CNS-permeable oxime reactivator. Additional experiments to determine acute and chronic toxicity are ongoing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

HipGISAXS : a high-performance computing code for simulating grazing-incidence X-ray scattering data

This article describes the development of a flexible grazing-incidence small-angle X-ray scattering (GISAXS) simulation code in the framework of the distorted wave Born approximation that effectively utilizes the parallel processing power provided by graphics processors and multicore processors. The code, entitled High-Performance GISAXS , computes the GISAXS image for any given superposition of user-defined custom shapes or morphologies in a material and for various grazing-incidence angles and sample orientations. These capabilities permit treatment of a wide range of possible sample structures, including multilayered polymer films and nanoparticles on top of or embedded in a substrate or polymer film layers. In cases where the material displays regions of significant refractive index contrast, an algorithm has been implemented to perform a slicing of the sample and compute the averaged refractive index profile to be used as the reference geometry of the unperturbed system. A number of case studies are presented, which demonstrate good agreement with the experimental data for a variety of polymer and hybrid polymer/nanoparticle composite materials. The parallelized simulation code is well suited for addressing the analysis efforts required by the increasing amounts of GISAXS data being produced by high-speed detectors and ultrafast light sources.

Chemistry↗

Adjusting process count on demand for petascale global optimization

There are many challenges that need to be met before efficient and reliable computation at the petascale is possible. Many scientific and engineering codes running at the petascale are likely to be memory intensive, which makes thrashing a serious problem for many petascale applications. One way to overcome this challenge is to use a dynamic number of processes, so that the total amount of memory available for the computation can be increased on demand. This paper describes modifications made to the massively parallel global optimization code pVTdirect in order to allow for a dynamic number of processes. In particular, the modified version of the code monitors memory use and spawns new processes if the amount of available memory is determined to be insufficient. The primary design challenges are discussed, and performance results are presented and analyzed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dragonfly : an implementation of the expand–maximize–compress algorithm for single-particle imaging

Single-particle imaging (SPI) with X-ray free-electron lasers has the potential to change fundamentally how biomacromolecules are imaged. The structure would be derived from millions of diffraction patterns, each from a different copy of the macromolecule before it is torn apart by radiation damage. The challenges posed by the resultant data stream are staggering: millions of incomplete, noisy and un-oriented patterns have to be computationally assembled into a three-dimensional intensity map and then phase reconstructed. In this paper, the Dragonfly software package is described, based on a parallel implementation of the expand–maximize–compress reconstruction algorithm that is well suited for this task. Auxiliary modules to simulate SPI data streams are also included to assess the feasibility of proposed SPI experiments at the Linac Coherent Light Source, Stanford, California, USA.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spatially Resolved Mapping of Three-Dimensional Molecular Orientations with ~2 nm Spatial Resolution through Tip-Enhanced Raman Scattering

We record local optical field images of silver nanocubes (75 nm) using tip-enhanced Raman (TER) spectral imaging. The images that we observe are consistent with several recent reports from our group, but here, we demonstrate sub-2 nm spatial resolution in local optical field nanoimaging under ambient laboratory conditions. This is achieved by scanning the substrate (nanocube on Si) relative to a 4-thiobenzonitrile (TBN)-functionalized Ag-coated TER probe. The spatial resolution that we obtain necessitates that only a few molecules govern the recorded optical response; molecular orientation becomes an important consideration in such measurements. We model the orientation through geometry optimization of a TBN molecule chemisorbed onto an Ag79 cluster (sphere with a ~1 nm diameter). Using the computed orientation of the cluster-bound molecule, we then model the optical response using formalism that accounts for the orientation of the molecule relative to vector components of the local optical fields. We find optimal agreement between experiment and theory. In effect, this work reveals the parallels between single-molecule Raman scattering and high-spatial-resolution TER spectroscopy, even when the images themselves cannot be used to visualize a single molecule in real space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enabling Co-Design of Multi-Layer Exascale Storage Architectures

Growing demands for computing power in applications such as energy production, climate analysis, computational chemistry, and bioinformatics have propelled computing systems toward the exascale: systems with 10 18 floating-point operations per second. These systems, to be designed and constructed over the next decade, will create unprecedented challenges in component counts, power consumption, resource limitations, and system complexity. Data storage and access are an increasingly important and complex component in extreme-scale computing systems, and significant design work is needed to develop successful storage hardware and software architectures at exascale. Co-design of these systems will be necessary to find the best possible design points for exascale systems. The goal of this work has been to enable the exploration and co-design of exascale storage systems by providing a detailed, accurate, and highly parallel simulation of exascale storage and the surrounding environment. Specifically, this simulation has (1) portrayed realistic application checkpointing and analysis workloads, (2) captured the complexity, scale, and multilayer nature of exascale storage hardware and software, and (3) executed in a timeframe that enables “what if'” exploration of design concepts. We developed models of the major hardware and software components in an exascale storage system, as well as the application I/O workloads that drive them. We used our simulation system to investigate critical questions in reliability and concurrency at exascale, helping guide the design of future exascale hardware and software architectures. Additionally, we provided this system to interested vendors and researchers so that others can explore the design space. We validated the capabilities of our simulation environment by configuring the simulation to represent the Argonne Leadership Computing Facility Blue Gene/Q system and comparing simulation results for application I/O patterns to the results of executions of these I/O kernels on the actual system.

97 MATHEMATICS AND COMPUTING↗

The Chronus Quantum software package

The Chronus Quantum (ChronusQ) software package is an open source software infrastructure which targets the solution of challenging problems that arise in ab initio electronic structure theory. Special emphasis is placed on the consistent treatment of time dependence and spin in the electronic wave function, as well as the inclusion of relativistic effects in said treatments. In addition, ChronusQ provides support for the inclusion of uniform finite magnetic fields as external perturbations through the use of gauge-including atomic orbitals. ChronusQ is a parallel electronic structure code written in modern C++ which utilizes both message passing implementation and shared memory (OpenMP) parallelism. In addition to the examination of the current state of code base itself, a discussion regarding ongoing developments and developer contributions will also be provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A superstructure optimization approach for process synthesis under complex reaction networks

Here in this work, we present mixed integer linear programming methods for the synthesis of processes that involve complex reaction networks. Specifically, we consider the modeling of reactors and interconnecting streams in systems where the composition of the reactor inlet streams can vary substantially, thereby making the determination of the limiting component as well as the calculation of the stream heating/cooling and power requirements challenging. First, towards the modeling of reactors, we develop an extent-based method which detects the limiting reactant of each reaction occurring in parallel with others, based on the inlet flows of the reactants. Second, we develop a computationally tractable method for the calculation of the work and heating/cooling duty needed to condition any stream of a process based on simple calculations that can be performed offline. Finally, we present how the two aforementioned components can be integrated in an optimization model generated based on a process superstructure. We demonstrate the application of the developed methods for the synthesis of a biorefinery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural, electronic and optical properties of novel carbonate fluorides ABCO{sub 3}F (A=K, Rb, Cs; B=Ca, Sr)

In the present study, we performed first principles calculations on the electronic and optical properties of layered alkali–alkaline earth carbonate fluorides which attract attention in the domain of nonlinear optics. The calculated lattice parameters and volumes with and without inclusion of van der Waals (vdW) correction methods to standard density functional methods were compared with experiments. We observed that vdW interactions are predominant in RbCaCO{sub 3}F and CsCaCO{sub 3}F as compared with other computed compounds. The calculated bulk modulus from single crystal elastic constants reveals that these materials are all relatively harder than the KH{sub 2}PO{sub 4} (KDP) crystal. We also found that these materials are wide band gap insulators as obtained from Tran–Blaha modified Becke–Johnson potential. The linear optical properties such as dielectric function, refractive indices, birefringence and absorption spectra are presented. Finally, the calculated birefringence values indicate that these crystals could be promising for producing phase matching in the deep ultra-violet region. - Graphical abstract: The co- and anti-parallel alignment of CO{sub 3} groups leads to larger and smaller SHG coefficients in (a) KCaCO{sub 3}F, (b) KSrCO{sub 3}F, (c) RbSrCO{sub 3}F, (d) RbCaCO{sub 3}F, and (e) CsCaCO{sub 3}F. - Highlights: • Effect of van der Waals interactions on structural properties. • Single-crystalline elastic constants and mechanical stability. • Electronic properties. • Linear optical properties. • Comparison of present computed compounds with other well known materials in non-linear optical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SCEPTRE 2.2 Quick Start Guide

This report provides a summary of notes for building and running the Sandia Computational Engine for Particle Transport for Radiation Effects (SCEPTRE) code. SCEPTRE is a general- purpose C++ code for solving the li near Boltzmann transport equation in serial or parallel using unstructured spatial finite elements, multigroup energy treatment, and a variety of angular treatments including discrete ordinates and spherical harmonics. Either the first-order form of the Boltzmann equation or one of the second-order forms may be solved. SCEPTRE requires a small number of open-source Third Part y Libraries (TPL) to be available, and example scripts for building these TPLs are provided. The TPLs needed by SCEPTRE are Trilinos, boost, and netcdf. SCEPTRE uses an autotools build system , and a sample configure script is provided. Running the SCEPTRE code requires that the user provide a spatial finite-elements mesh in Exodus format and a cross section library in a format that will be described. SCEPTRE uses an xml-based input, and several examples will be provided.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Probing the Energetics of Molecule–Material Interactions at Interfaces and in Nanopores

During the past decades, advances in interfacial chemistries at the molecular level are shaping our world by playing crucial roles in balancing global scale energy crisis and critical environmental concerns. However, systematic investigations into the binding energies, site distribution and their correlation with the molecular-level surface assemblages and structures at interfaces and in nanopores are rarely documented. In this review, we summarize a set of systematic calorimetric studies on surface energetics we performed during the last decade. These studies demonstrate how thermochemistry can reveal crucial energetic insights into a series of molecule – material interactions relevant to a number of applications, including carbon capture and sequestration, energy production, sustainable chemical processing, catalysis, and nanogeoscience. Calorimetric methodologies developed and applied include direct gas adsorption calorimetry, nearroom temperature solvent immersion/solution calorimetry and high temperature oxide melt solution calorimetry. Using these highly unique techniques, we reveal the thermodynamic complexity of carbon dioxide capture on metal – organic framework (MOF) sorbents with built-in and grafted nucleophilic functional groups (-OH and -NH2). These studies suggest that carbon dioxide adsorption on functionalized MOFs is a complex process involving multiple thermodynamic factors, as reflected by changes in surface phase and structure, chemical bonding and degree of disorder with varying temperature and gas loading. The fundamental insights obtained may help optimize the design, synthesis and application of MOF-based carbon dioxide sorbents for carbon capture and sequestration. In parallel, we also explore the energetics of interaction and competition between small molecules (water, carbon dioxide, methane, simple and complex organics) and inorganic materials (calcite, silica, zirconia, zeolites, mesoporous frameworks, alumina, and uranium), at interfaces and in nanopores. Combined with spectroscopic, diffraction, electron microscopic and computational techniques, the energetics of gas/liquid – solid interactions can be correlated with specific bonds, molecular configurations and nanostructures. Although the energetics evolves continuously from weak association to strong bonding to classical capping, distinct regions of rapidly changing stepwise energetics often separate the different regimes. These phenomena are closely related to the properties of inorganic material surfaces (hydrophobicity and acidity/basicity), the framework architectures, and the chemical nature of adsorbate molecules. These direct thermodynamic insights reinforce our understanding of complex small molecule – inorganic material interactions important to multiple disciplines of chemical engineering, materials science, nanogeoscience and environmental technology, including heterogeneous catalysis, molecular separation, material design and synthesis, biomineralization, contaminant and nutrient transport, carbonate formation, and water – organic competitions on material/mineral surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enabling Modular Autonomous Feedback‐Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration

Abstract Materials acceleration platforms (MAPs) operate on the paradigm of integrating combinatorial synthesis, high‐throughput characterization, automatic analysis, and machine learning. Within a MAP, one or multiple autonomous feedback loops may aim to optimize materials for certain functional properties or to generate new insights. The scope of a given experiment campaign is defined by the range of experiment and analysis actions that are integrated into the experiment framework. Herein, the authors present a method for integrating many actions within a hierarchical experimental laboratory automation and orchestration (HELAO) framework. They demonstrate the capability of orchestrating distributed research instruments that can incorporate data from experiments, simulations, and databases. HELAO interfaces laboratory hardware and software distributed across several computers and operating systems for executing experiments, data analysis, provenance tracking, and autonomous planning. Parallelization is an effective approach for accelerating knowledge generation provided that multiple instruments can be effectively coordinated, which the authors demonstrate with parallel electrochemistry experiments orchestrated by HELAO. Efficient implementation of autonomous research strategies requires device sharing, asynchronous multithreading, and full integration of data management in experimental orchestration, which to the best of the authors’ knowledge, is demonstrated for the first time herein.

36 MATERIALS SCIENCE↗

Valence : A Massively Parallel Implementation of the Variational Subspace Valence Bond Method

This work describes the software package, Valence, for the calculation of molecular energies using the variational subspace valence bond (VSVB) method. VSVB is an ab initio electronic structure method based on nonorthogonal orbitals. Important features of practical value include high parallel scalability, wave functions that can be constructed automatically by combining orbitals from previous calculations, and ground and excited states that can be modeled with a single configuration or determinant. Here, the open-source software package includes tools to generate wave functions, a database of generic orbitals, example input files, and a library build intended for integration with other packages. We also present the interface to an external software package, enabling the computation of optimized molecular geometries and vibrational frequencies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗