Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Mathematical physics methods”

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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tunable Heteroassembly of a Plant Pseudoenzyme–Enzyme Complex

Pseudoenzymes have emerged as key regulatory elements in all kingdoms of life despite being catalytically nonactive. Yet many factors defining why one protein is active while its homologue is inactive remain uncertain. For pseudoenzyme–enzyme pairs, the similarity of both subunits can often hinder conventional characterization approaches. In plants, a pseudoenzyme, PDX1.2, positively regulates vitamin B 6 production by association with its active catalytic homologues such as PDX1.3 through an unknown assembly mechanism. Here we used an integrative experimental approach to learn that such pseudoenzyme–enzyme pair associations result in heterocomplexes of variable stoichiometry, which are unexpectedly tunable. We also present the atomic structure of the PDX1.2 pseudoenzyme as well as the population averaged PDX1.2–PDX1.3 pseudoenzyme–enzyme pair. Finally, we dissected hetero-dodecamers of each stoichiometry to understand the arrangement of monomers in the heterocomplexes and identified symmetry-imposed preferences in PDX1.2–PDX1.3 interactions. In this work, our results provide a new model of pseudoenzyme–enzyme interactions and their native heterogeneity.

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

Sulfur Lone Pairs Control Topology in Heterotrimetallic Complexes: An Experimental and Theoretical Study

Heterotrimetallic complexes with (N 2 S 2 )M metallodithiolates, M = Ni 2+ , [Fe(NO)] 2+ , and [Co(NO)] 2+ , as bidentate chelating ligands to a central trans-Cr(NO)(MeCN) unit were characterized as the first members of a new class, NiCrNi, FeCrFe, CoCrCo. The complexes exhibit a cisoid structural topology, ascribed to the stereoactivity of the available lone pair(s) on the sulfur donors, resulting in a dispersed, electropositive pocket from the N/N and N/S hydrocarbon linkers wherein the Cr-NO site is housed. Computational studies explored alternative isomers (transoid and inverted cisoid) that suggest a combination of electronic and steric effects govern the geometrical selectivity. Electrostatic potential maps readily display the dominant electronegative potential from the sulfurs which force the NO to the electropositive pocket. The available S lone pairs work in synergy with the π-withdrawing ability of NO to lift Cr out of the S 4 plane toward the NO and stabilize the geometry. The metallodithiolate ligands bound to Cr(NO) thus find structural consistency across the three congeners. Although the dinitrosyl [(bme-dach)Co(NO)-Mo(NO)(MeCN)-(bme-dach)Co(MeCN)][PF 6 ] 2 (CoMoCo') analogue displays chemical noninnocence and a partial Mo–Co bond toward (N 2 S 2 )Co'(NCCH 3 ) in an “asymmetric butterfly” topology, the stability of the {Cr(NO)} 5 unit prohibits such bond rearrangement. Magnetism and EPR studies illustrate spin coupling across the sulfur thiolate sulfur bridges.

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

Structure and Synthesizability of Iron–Sulfur Metal–Organic Frameworks

Sulfur-based metal–organic frameworks (MOFs) and coordination polymers (CPs) are an emerging class of hybrid materials that have received growing attention due to their magnetic, conductive, and catalytic properties with potential applications in electrocatalysis and energy storage. In this work, we report a high-throughput virtual screening protocol to predict the synthesizability of candidate metal–sulfur MOFs/CPs by computing the thermodynamically stable structures resulting from a particular combination of metal cluster, linker, cation, and synthetic conditions. Free energies are computed by using all-atom classical mechanical thermodynamic integration. Low-free-energy structures are refined using ab initio density functional theory, and pair distribution functions and powder X-ray diffraction patterns are calculated to complement and guide experimental structure determination. We validate the computational approach by retrospective predictions of the stable structure produced by experimental syntheses, and a subsequent screen predicts Fe 4 S 4 -BDT–TPP as a new thermodynamically stable one-dimensional (1D) CP comprising a redox-active Fe 4 S 4 cluster, a 1,4-benzenedithiolate (BDT) linker, and a tetraphenylphosphonium (TPP) countercation. Furthermore, this material is experimentally synthesized, and the 1D chain structure of the crystal is confirmed using microcrystal electron diffraction. The computational screening pipeline is generically transferable to neutral and ionic MOFs/CPs comprising arbitrary metal clusters, linkers, cations, and synthetic conditions, and we make it freely available as an open source tool to guide and accelerate the discovery and engineering of novel porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Nuclear Data Adjustment with Whisper for Criticality Safety Applications [Slides]

Nuclear data adjustment is used by Whisper to compute residual nuclear data uncertainties within a full suite of benchmarks; in order to do so, a complete set of nuclear data covariances, benchmarks and k-effective sensitivity profiles (for both benchmarks and applications) is required. For applications that are similar to the full benchmark suite, the residual uncertainties add a small margin to the overall USL calculation. For applications that are dissimilar to the full benchmark suite, the residual uncertainties add a reasonable margin to the overall USL calculation (more conservative). This methodology helps to overcome any issues in the released covariance libraries where nuclear data uncertainties appear to be too large.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Comparison of URR Implementations in GNDS Format [Slides]

LLNL implemented infrastructure to include treatment of URR in GNDS. There are two options to store URR probabilities: cross-sections pdf and ACE-like probability tables. Issues were found with both options during verification with criticality benchmarks. Projected future steps include resolving issues in the next year and adding criticality benchmarks sensitive to URR.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Heuristic methods and performance bounds for photonic design

In the photonic design problem, a scientist or engineer chooses the physical parameters of a device to best match some desired device behavior. Many instances of the photonic design problem can be naturally stated as a mathematical optimization problem that is computationally difficult to solve globally. Because of this, several heuristic methods have been developed to approximately solve such problems. These methods often produce very good designs, and, in many practical applications, easily outperform ‘traditional’ designs that rely on human intuition. Yet, because these heuristic methods do not guarantee that the approximate solution found is globally optimal, the question remains of just how much better a designer might hope to do. This question is addressed by performance bounds or impossibility results, which determine a performance level that no design can achieve. We focus on algorithmic performance bounds, which involve substantial computation to determine. We illustrate a variety of both heuristic methods and performance bounds on two examples. In these examples (and many others not reported here) the performance bounds show that the heuristic designs are nearly optimal, and can be considered globally optimal in practice. This review serves to clearly set up the photonic design problem and unify existing approaches for calculating performance bounds, while also providing some natural generalizations and properties.

Angeris, Guillermo (ORCID:0000000249503990)↗
DOE OSTI2022

Computational Aspects of Single-Molecule Kinetics for Coupled Catalytic Cycles: A Spectral Analysis

Catalysis from single active sites is analyzed using methods developed from single molecule kinetics. Using a stochastic Markov state description, the observable properties of general catalytic networks of reactions are expressed using an eigenvalue decomposition of the transition matrix for the Markov process. By the use of a sensitivity analysis, the necessary eigenvalues and eigenvectors are related to the energies of controlling barriers and wells located along the reaction routes. A generalization of the energetic span theory allows the eigenvalues to be computed from several activation energies corresponding to distinct barrier-well pairings. The formalism is demonstrated accurately for model problems for a physically realistic mechanism for an alkene hydrogenation reaction on a single atom catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

HomPINNs: Homotopy physics-informed neural networks for learning multiple solutions of nonlinear elliptic differential equations

Physics-informed neural networks (PINNs) based machine learning is an emerging framework for solving nonlinear differential equations. However, due to the implicit regularity of neural network structure, PINNs can only find the flattest solution in most cases by minimizing the loss functions. In this paper, we combine PINNs with the homotopy continuation method, a classical numerical method to compute isolated roots of polynomial systems, and propose a new deep learning framework, named homotopy physics-informed neural networks (HomPINNs), for solving multiple solutions of nonlinear elliptic differential equations. The implementation of an HomPINN is a homotopy process that is composed of the training of a fully connected neural network, named the starting neural network, and training processes of several PINNs with different tracking parameters. The starting neural network is to approximate a starting function constructed by the trivial solutions, while other PINNs are to minimize the loss functions defined by boundary condition and homotopy functions, varying with different tracking parameters. These training processes are regraded as different steps of a homotopy process, and a PINN is initialized by the well-trained neural network of the previous step, while the first starting neural network is initialized using the default initialization method. Finally, several numerical examples are presented to show the efficiency of our proposed HomPINNs, including reaction-diffusion equations with a heart-shaped domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High-Precision Calculation of Nanoparticle (Nanocrystal) Potentials of Mean Force and Internal Energies

Thermodynamic stability assessment of nanocrystal systems requires precise free energy calculations. This study highlights the importance of meticulous control over various factors, including the thermostat, time step, potential cutoff, initial configuration, sampling method, and overall simulation duration. Free energy computations in dry (solvent-free) systems are on the order of several hundred $k_BT$ but can be obtained with consistent accuracy. However, calculation of internal energies becomes challenging, as they are typically much larger in magnitude than free energies and exhibit significant noise and reduced reliability. To address this limitation, we propose a new internal energy estimate that drastically reduces the noise. Here, we also present formulas that enable the optimization of the parameters of the harmonic bias potential for optimal convergence. Finally, we discuss the implications of these findings for the computation of free energies in nanocrystal clusters and superlattices.

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

Computational shock formation & development: An arbitrary Lagrangian-Eulerian characteristics approach [Slides]

We propose a new computational shock formation-development algorithm. We use a “good” geometry adapted to the evolving solution, along with a good set of variables defined in this geometry. We are able to: (1) Accurately capture the pre-shock; (2) Track distinguished characteristics and capture weak discontinuities; (3) Approximate solutions to classical Riemann problems; and (4) Accurately solve challenging problems for which standard methods fail.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Oak Ridge National Laboratory NCSP Analytical Methods Subtask 3, AMPX Development and Maintenance, and NCSP Nuclear Data Subtask 6, SAMMY Modernization

The modernization of SAMMY continued with consolidation of access to covariance information for adjusted parameters and data in SAMMY. This consolidation allowed for removal of many scratch files. In addition, work was initiated to make the 0K cross section calculation more modular and less dependent on SAMMY global parameters. An initial application programming interface (API) was added to expose cross sections (including resolution broadening) generated by SAMMY to external fitting routines. The processing for thermal moderators in AMPX was updated for selected moderators for which the generated grid was not fine enough. Updated libraries were generated for SCALE. In addition, work continued to fully support new Evaluated Nuclear Data File (ENDF) formats, including the Generalized Nuclear Database Structure (GNDS) in AMPX.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

The XtalOpt Evolutionary Algorithm for Crystal Structure Prediction

Significant progress has been made in the field of a priori crystal structure prediction, with a number of recent remarkable success stories. Herein, we briefly outline the methods that have been developed for finding the global minimum structure and interesting local minima without the need for experimental information. Focus is placed on describing the XTALOPT evolutionary algorithm (EA) developed in our group towards this end. XTALOPT is published under well-known open-source licenses, and the EA searches can be analyzed via the AVOGADRO chemical editor and visualizer. We describe new algorithmic developments that have made it possible to predict the structures of ever-more complex crystalline lattices. Benchmark tests, which clearly illustrate how the new developments improve the success rate and accelerate the discovery of the global minimum structure, are carried out. Lastly, we describe how XTALOPT has been employed to predict novel ternary hydrides that have the propensity for high-temperature superconductivity under pressure.

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

Competition between Hückel’s Rule and Jahn–Teller Distortion in Small Carbon Rings: A Quantum Monte Carlo Study

Structural properties and energetics of carbon rings are studied with the diffusion Monte Carlo (DMC) method. Our DMC-based geometry optimization reveals that both polyynic C 4n and cumulenic C 4n+2 rings exhibit bond length alternations for n >= 3, which is understood to be due to Jahn-Teller distortions. The bond length alternation even in a cumulenic (4n + 2) carbon ring was experimentally observed in a recently synthesized C 18 molecule. From a comparison of the DMC cohesive energies of C 4n with those of C 4n + 2 , we present a comprehensive picture of the competition between Huckel's rule and Jahn-Teller distortion in small carbon rings; the former is more dominant than the latter for n < 5 where C 4n + 2 rings are more stable than C 4n , while C 4n rings are as stable as C 4n + 2 for n < 5 where dimerization effects due to Jahn-Teller distortion are more important.

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

A scalable matrix-free spectral element approach for unsteady PDE constrained optimization using PETSc/TAO

In this work, we provide a new approach for the efficient matrix-free application of the transpose of the Jacobian for the spectral element method for the adjoint-based solution of partial differential equation (PDE) constrained optimization. This results in optimizations of nonlinear PDEs using explicit integrators where the integration of the adjoint problem is not more expensive than the forward simulation. Solving PDE constrained optimization problems entails combining expertise from multiple areas, including simulation, computation of derivatives, and optimization. The Portable, Extensible Toolkit for Scientific computation (PETSc) together with its companion package, the Toolkit for Advanced Optimization (TAO), is an integrated numerical software library that contains an algorithmic/software stack for solving linear systems, nonlinear systems, ordinary differential equations, differential algebraic equations, and large-scale optimization problems and, as such, is an ideal tool for performing PDE-constrained optimization. This paper describes an efficient approach in which the software stack provided by PETSc/TAO can be used for large-scale nonlinear time-dependent problems. Time integration can involve a range of high-order methods, both implicit and explicit. The PDE-constrained optimization algorithm used is gradient-based and seamlessly integrated with the simulation of the physical problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantum Orbital Minimization Method for Excited States Calculation on a Quantum Computer

Herein we propose a quantum-classical hybrid variational algorithm, the quantum orbital minimization method (qOMM), for obtaining the ground state and low-lying excited states of a Hermitian operator. Given parametrized ansatz circuits representing eigenstates, qOMM implements quantum circuits to represent the objective function in the orbital minimization method and adopts a classical optimizer to minimize the objective function with respect to the parameters in ansatz circuits. The objective function has an orthogonality constraint implicitly embedded, which allows qOMM to apply a different ansatz circuit to each input reference state. We carry out numerical simulations that seek to find excited states of H 2 , LiH, and a toy model consisting of four hydrogen atoms arranged in a square lattice in the STO-3G basis with UCCSD ansatz circuits. Comparing the numerical results with existing excited states methods, qOMM is less prone to getting stuck in local minima and can achieve convergence with more shallow ansatz circuits.

97 MATHEMATICS AND COMPUTING↗