Search NASA⌕ Search

SEARCH · Search NASA

Results for “Structural Optimization”

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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

The Enzymatic and Structural Basis for Inhibition of Echinococcus granulosus Thioredoxin Glutathione Reductase by Gold(I)

Aims: New drugs are needed to treat flatworm infections that cause severe human diseases such as schistosomiasis. The unique flatworm enzyme thioredoxin glutathione reductase (TGR), structurally different from the human enzyme, is a key drug target. Structural studies of the flatworm Echinococcus granulosus TGR, free and complexed with AuI-MPO, a novel gold inhibitor, together with inhibition assays were performed. Results: AuI-MPO is a potent TGR inhibitor that achieves 75% inhibition at a 1:1 TGR:Au ratio and efficiently kills E. granulosus in vitro. The structures revealed salient insights: (i) unique monomer–monomer interactions, (ii) distinct binding sites for thioredoxin and the glutaredoxin (Grx) domain, (iii) a single glutathione disulfide reduction site in the Grx domain, (iv) rotation of the Grx domain toward the Sec-containing redox active site, and (v) a single gold atom bound to Cys519 and Cys573 in the AuI-TGR complex. Structural modeling suggests that these residues are involved in the stabilization of the Sec-containing C-terminus. Consistently, Cys→Ser mutations in these residues decreased TGR activities. Mass spectroscopy confirmed these cysteines are the primary binding site. Innovation: The identification of a primary site for gold binding and the structural model provide a basis for gold compound optimization through scaffold adjustments. Conclusions: The structural study revealed that TGR functions are achieved not only through a mobile Sec-containing redox center but also by rotation of the Grx domain and distinct binding sites for Grx domain and thioredoxin. The conserved Cys519 and Cys573 residues targeted by gold assist catalysis through stabilization of the Sec-containing redox center. Antioxid. Redox Signal. 27, 1491–1504.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

SNoGloDe: A Structured Nonlinear Global Decomposition Solver

Large-scale optimization problems often require decomposition strategies and customized algorithms to achieve optimal solutions within a reasonable time. Building on the work of Cao and Zavala (2019) for solving nonlinear two-stage stochastic programs to global optimality, we implement and extend their approach. We generalize to optimization problems reformulated with a block-angular constraint structure (e.g., temporal decomposition). Our framework, written in Python using Pyomo, is highly customizable and enables parallel execution of the decomposition. SNoGloDe allows tailored branching strategies, lower bounding problems, and candidate generators to leverage problem-specific knowledge. To demonstrate effectiveness, we compare SNoGloDe’s performance with Gurobi on a temporally decomposed produced water case study.

algorithms↗
DOE OSTI2020

Algorithms in Diffraction Profile Analysis

This chapter introduces several approaches to crystallographic structure refinement from diffraction profile data including the Rietveld method, global optimization methods, and Bayesian modeling. First, the Rietveld method and related nonlinear least squares approaches to analyzing diffraction profiles are briefly discussed. We then review the most common algorithms within global optimization as alternative methods of structure solution: grid search, simulated annealing, and genetic algorithms. As the Rietveld method is the standard tool for analyzing diffraction profile data, we catalogue its challenges and limitations. A Bayesian approach to diffraction profile analysis is presented as an alternative, along with several sampling algorithms including Gibbs sampling, variants of Metropolis sampling, Hamiltonian Monte Carlo, and approximate Bayesian computing. These sampling algorithms are applied to the fitting of a neutron diffraction profile from a National Institute of Standards and Technology silicon standard reference material, and their results are compared.

Singh, Susheela↗
DOE OSTI2024

Structural anisotropy in Sb thin films

Sb thin films have attracted wide interest due to their tunable band structure, topological phases, high electron mobility, and thermoelectric properties. We successfully grow epitaxial Sb thin films on a closely lattice-matched GaSb(001) surface by molecular beam epitaxy. We find a novel anisotropic directional dependence on their structural, morphological, and electronic properties. The origin of the anisotropic features is elucidated using first-principles density functional theory (DFT) calculations. The growth regime of crystalline and amorphous Sb thin films was determined by mapping the surface reconstruction phase diagram of the GaSb(001) surface under Sb 2 flux, with confirmation of structural characterizations. Crystalline Sb thin films show a rhombohedral crystal structure along the rhombohedral (211) surface orientation parallel to the cubic (001) surface orientation of the GaSb substrate. At this coherent interface, Sb atoms are aligned with the GaSb lattice along the [1̄10] crystallographic direction but are not aligned well along the [110] crystallographic direction, which results in anisotropic features in reflection of high-energy electron diffraction patterns, misfit dislocation formation, surface morphology, and transport properties. Our DFT calculations show that the preferential orientation of the rhombohedral Sb (211) plane may originate from the GaSb surface, where Sb atoms align with the Ga and Sb atoms on the reconstructed surface. The formation energy calculations confirm the stability of the experimentally observed structures. Our results provide optimal film growth conditions for further studies of novel properties of Bi 1-x Sb x thin films with similar lattice parameters and an identical crystal structure, as well as functional heterostructures of them with III–V semiconductor layers along the (001) surface orientation, supported by a theoretical understanding of the anisotropic film orientation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Design Rules of the Mixing Phase and Impacts on Device Performance in High-Efficiency Organic Photovoltaics

In nonfullerene acceptor- (NFA-) based solar cells, the exciton splitting takes place at both domain interface and donor/acceptor mixture, which brings in the state of mixing phase into focus. The energetics and morphology are key parameters dictating the charge generation, diffusion, and recombination. It is revealed that tailoringthe electronic properties of the mixing region by doping with larger-bandgap components could reduce the density of state but elevate the filling state level, leading to improved open-circuit voltage ( V OC ) and reduced recombination. The monomolecular and bimolecular recombinations are shown to be intercorrelated, which show a Gaussian-like relationship with V OC and linear relationship with short-circuit current density ( J SC ) and fill factor (FF). The kinetics of hole transfer and exciton diffusion scale with J SC similarly, indicating the carrier generation in mixing region and crystalline domain are equally important. From the morphology perspective, the crystalline order could contribute to V OC improvement, and the fibrillar structure strongly affects the FF. These observations highlight the importance of the mixing region and its connection with crystalline domains and point out the design rules to optimize the mixing phase structure, which is an effective approach to further improve device performance.

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

Single particle impact explorations on the role of powder heat treatments in cold spray: Effects of strength and oxide structure

In cold spray, the optimization of the powder feedstock for improving the final properties of the coating and for improving the process itself are two different objectives. This paper explores the latter, studying the relationship between powder pre-heat treatment and the kinetic bonding between the individual particles and the substrate. Using a laser-induced particle impact test (LIPIT), we investigate the effect of different heat treatments on the critical adhesion velocity of Al 6061. Although heat treatments change the strength of the powders as well as the thickness of the native oxide layer each by as much as ∼50 %, the critical adhesion velocity remains constant to within only ∼10 %. A deeper analysis reveals that these two factors change in somewhat complementary ways for the heat treatments explored here, leading to counteracting effects. By quantitatively evaluating these two microstructural factors in tandem, we find that they are roughly equally important in determining the critical adhesion velocity. These observations thus provide insight for the development of new heat treatment regimens that might lower the adhesion velocity.

Al 6061↗
DOE OSTI2023

Machine learning unifies flexibility and efficiency of spinodal structure generation for stochastic biomaterial design

Abstract Porous biomaterials design for bone repair is still largely limited to regular structures (e.g. rod-based lattices), due to their easy parameterization and high controllability. The capability of designing stochastic structure can redefine the boundary of our explorable structure–property space for synthesizing next-generation biomaterials. We hereby propose a convolutional neural network (CNN) approach for efficient generation and design of spinodal structure—an intriguing structure with stochastic yet interconnected, smooth, and constant pore channel conducive to bio-transport. Our CNN-based approach simultaneously possesses the tremendous flexibility of physics-based model in generating various spinodal structures (e.g. periodic, anisotropic, gradient, and arbitrarily large ones) and comparable computational efficiency to mathematical approximation model. We thus successfully design spinodal bone structures with target anisotropic elasticity via high-throughput screening, and directly generate large spinodal orthopedic implants with desired gradient porosity. This work significantly advances stochastic biomaterials development by offering an optimal solution to spinodal structure generation and design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Distance‐based reconstruction of protein quaternary structures from inter‐chain contacts

Abstract Predicting the quaternary structure of protein complex is an important problem. Inter‐chain residue‐residue contact prediction can provide useful information to guide the ab initio reconstruction of quaternary structures. However, few methods have been developed to build quaternary structures from predicted inter‐chain contacts. Here, we develop the first method based on gradient descent optimization (GD) to build quaternary structures of protein dimers utilizing inter‐chain contacts as distance restraints. We evaluate GD on several datasets of homodimers and heterodimers using true/predicted contacts and monomer structures as input. GD consistently performs better than both simulated annealing and Markov Chain Monte Carlo simulation. Starting from an arbitrarily quaternary structure randomly initialized from the tertiary structures of protein chains and using true inter‐chain contacts as input, GD can reconstruct high‐quality structural models for homodimers and heterodimers with average TM‐score ranging from 0.92 to 0.99 and average interface root mean square distance from 0.72 Å to 1.64 Å. On a dataset of 115 homodimers, using predicted inter‐chain contacts as restraints, the average TM‐score of the structural models built by GD is 0.76. For 46% of the homodimers, high‐quality structural models with TM‐score ≥ 0.9 are reconstructed from predicted contacts. There is a strong correlation between the quality of the reconstructed models and the precision and recall of predicted contacts. Only a moderate precision or recall of inter‐chain contact prediction is needed to build good structural models for most homodimers. Moreover, GD improves the quality of quaternary structures predicted by AlphaFold2 on a Critical Assessment of Techniques for Protein Structure Prediction–Critical Assessments of Predictions of Interactions dataset.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Optimal Harvesting in a Periodic Food Chain Model with Size Structures in Predators

In this paper, we investigate a periodic food chain model with harvesting, where the predators have size structures and are described by first-order partial differential equations. First, we establish the existence of a unique non-negative solution by using the Banach fixed point theorem. Then, we provide optimality conditions by means of normal cone and adjoint system. Finally, we derive the existence of an optimal strategy by means of Ekeland’s variational principle. Here the objective functional represents the net economic benefit yielded from harvesting.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Heat transfer optimization of uo 2 -mo fuel using genetic algorithms

Two genetic algorithm (GA) methods were applied to thermal finite element models to optimize the heat transfer efficacy of a UO 2 -Mo composite fuel pellet with typical pressurized water reactor fuel geometry. Mo additions to UO 2 have been shown to increase the thermal conductivity, thus reducing centerline temperatures and temperature gradients. Previous studies evaluated uniformly dispersed Mo or continuous Mo internal geometries (e.g., fins, plates, discs) that were selected using engineering intuition. The current study uses two different implementations of the same GA to optimize Mo placement and minimize the fuel temperature with the only constraint being a maximum 10% Mo volume fraction. One approach superimposed Mo line elements onto the monolithic UO 2 pellet model, and the other converted entire UO 2 volume elements to Mo. The former method generated 1D heat transfer connections between nodes, whereas the latter method allowed for the formation of 3D structures. Features of the optimal fuel design produced by the GAs included dispersed Mo near the centerline that shifted the peak fuel temperature outward by 0.6 mm, Mo chains in the high-heat-flux region in the mid-to-outer radial zone, and a large continuous structure that spanned the full radius and height of the pellet and accounted for 87.7 % of the total Mo in the pellet. Analysis of this design indicates that the optimal Mo configuration is a balance between creating continuous heat transfer pathways and optimally dispersing Mo to minimize the heat transfer distance through UO 2 . This architecture ultimately produced an effective thermal conductivity of 11.3 W/m·K under the assumed boundary conditions. This result is higher than any previous values from the literature. In conclusion, potential fabrication methods and challenges are discussed in addition to the implications on fuel performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Limits of multifunctionality in tunable networks

Nature is rife with networks that are functionally optimized to propagate inputs to perform specific tasks. Whether via genetic evolution or dynamic adaptation, many networks create functionality by locally tuning interactions between nodes. Here we explore this behavior in two contexts: strain propagation in mechanical networks and pressure redistribution in flow networks. By adding and removing links, we are able to optimize both types of networks to perform specific functions. We define a single function as a tuned response of a single “target” link when another, predetermined part of the network is activated. Using network structures generated via such optimization, we investigate how many simultaneous functions such networks can be programed to fulfill. We find that both flow and mechanical networks display qualitatively similar phase transitions in the number of targets that can be tuned, along with the same robust finite-size scaling behavior. We discuss how these properties can be understood in the context of constraint–satisfaction problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Investigating the Impact of Thickness, Calendering and Channel Structures of Printed Electrodes on the Energy Density of LIBs - 3D Simulation and Validation

Current lithium ion batteries (LIBs) are expensive and bulky, limited by relatively low charging rates. To increase the rate of charging and reduce weight, thin electrodes with high energy density are required. The increase in energy density can be achieved by several techniques including boosting electrolyte transport, high loading/utilization of active material, employing high conductive electrolytes and electrodes with advanced architectures, and increasing cell temperature. In this paper, a 3D physics-based electrochemical model of LIBs is developed in COMSOL simulation software for different thickness, calendering steps as well as channel structures (conical, cylindrical) to optimize the electrode design and in turn maximize volumetric energy density. The simulation results demonstrated that calendering the electrodes with high initial porosity increases the volumetric energy density of the cell. In addition, cylindrical channel structures with relatively lower edge-to-edge distance also results in increased volumetric energy density. The simulation results of the 3D model was validated by comparing it with experimental results.

improving volumetric energy density↗
DOE OSTI2017

Structural Evaluation of Complex Subcomponents Manufactured by Large Scale Extrusion Deposition of Carbon Fiber Reinforced ABS

The large scale extrusion deposition process has recently been commercialized in the form of additive manufacturing machines such as the BAAM from Cincinnati Inc., which enables layered production of chopped fiber reinforced thermoplastic polymer systems. The application of this process to the automotive market is being pursued by Local Motors to enable rapid design to market cycles and build on-demand capability for a wide range of vehicle styles from a distributed network of micro-factories. This endeavor will require an understanding of the structural performance of components with complex geometries, where the properties are known to vary as a function of printing conditions, as well as orientation and shape. In order to rapidly build a database of structural performance, a beam specimen with outer dimensions of 914 x 305 x 64 mm3 was selected to be subjected to bending, torsion, and shear loading with full field displacement measurement by digital image correlation (DIC). A total of 25 different specimen configurations were designed including variation of print geometry, reinforcement by foam filling, and overwrapping with advanced composites. This work documents the results of the study and presents the relative performance of the structures in addition to the approach to simulation that is being initiated to serve as a framework for efficient design of structures manufactured in this way. The results are presented as a table of structural efficiency including stiffness and strength as functions of mass for each design. Additional results will also be provided in the form of surface displacements from DIC; future work will utilize this data to better optimize simulations for predicting structural performance of articles manufactured by this process.

Bedsole, Robert↗
DOE OSTI2018

Tuning the Core–Shell Structure of Au 144 @Fe 2 O 3 for Optimal Catalytic Activity for CO Oxidation

Core–shell heterostructures have been utilized as a catalyst that is thermally stable and exhibits a synergistic effect between core and shell, resulting in increased catalytic activity. We report on the synthetic procedure involving a Au 144 core with an iron oxide shell which can be varied in thickness. The Au 144 @Fe 2 O 3 particles with Au:Fe mass ratios of 1:2, 1:4, and 1:6 were synthesized and then deposited onto silica via colloidal deposition. Using CO oxidation, each Au 144 @Fe 2 O 3 /SiO 2 catalyst gave varying degrees of full CO conversion depending on the thickness of the iron oxide layer. The 1:4 Au 144 @Fe 2 O 3 /SiO 2 catalyst produced the best catalytic activity and was further investigated via thermal treatments, where calcination at 300 °C presented the best results, and the 1:4 ratio was still active at 100 °C after thermal treatments.

2-propanol conversion↗
DOE OSTI2020

Optimized Al Doping Improves Both Interphase Stability and Bulk Structural Integrity of Ni-Rich NMC Cathode Materials

Ni-rich layered transition metal oxide (NMC, LiNi1-x-yMxCoyO2, 1 – x – y = 0.6) is promising for high-energy-density lithium-ion batteries, but its large-scale application is still hindered by several technical challenges, including secondary particle cracking, interfacial instability, and cell degassing during cycling. Here, we report a facile wet-chemical method to modify both the surface and the bulk of the LiNi0.76Mn0.14Co0.10O2 (NMC76) cathode with Al doping to effectively improve the structural/interfacial stability of the cathode, and hence its long-term cycling capability. With only 1 mol% Al doping, the Al-NMC76 electrode delivers a good capacity retention of 79.2% after 500 cycles at a high voltage limit of 4.5 V, which is far better than those of undoped NMC76 under the similar condition. The enhanced performance can be attributed to the Al doping in the NMC76, which not only strengthens the bulk structural stability through doping into the lattice, but also suppresses acidic attack from the electrolyte through altered surface structure of NMC76.

Al doping, capacity retention, high voltage, elect↗
DOE OSTI2023

Active Learning Guided Computational Discovery of Plant-Based Redoxmers for Organic Nonaqueous Redox Flow Batteries

Organic nonaqueous redox flow batteries (ONRFBs) are promising energy storage devices due to their scalability and reliance on sourceable materials. However, finding suitable redox-active organic molecules (redoxmers) for these batteries remains a challenge. Using plant-based compounds as precursors for these redoxmers can decrease their costs and environmental toxicity. In this computational study, flavonoid molecules have been examined as potential redoxmers for ONRFBs. Flavone and isoflavone derivatives were selected as catholyte (positive charge carrier) and anolyte (negative charge carrier) molecules, respectively. To drive their redox potentials to the opposite extremes, in silico derivatization was performed using a novel algorithm to generate a library of > 40000 candidate molecules that penalizes overly complex structures. A multiobjective Bayesian optimization based active learning algorithm was then used to identify best redoxmer candidates in these search spaces. Furthermore, our study provides methodologies for molecular design and optimization of natural scaffolds and highlights the need of incorporating expert chemistry awareness of the natural products and the basic rules of synthetic chemistry in machine learning.

25 ENERGY STORAGE↗
DOE OSTI2021

Comparing crystal structures with symmetry and geometry

Abstract Measuring the similarity between two arbitrary crystal structures is a common challenge in crystallography and materials science. Although there are an infinite number of ways to mathematically relate two crystal structures, only a few are physically meaningful. Here we introduce both a geometry-based and a symmetry-adapted similarity metric to compare crystal structures. Using crystal symmetry and combinatorial optimization we describe an algorithm to arrive at the structural relationship that minimizes these similarity metrics across all possible maps between any pair of crystal structures. The approach makes it possible to (i) identify pairs of crystal structures that are identical, (ii) quantitatively measure the similarity between crystal structures, and (iii) find and rank structural transformation pathways between any pair of crystal structures. We discuss the advantages of using the symmetry-adapted cost metric over the geometric cost. Finally, we show that all known structural transformation pathways between common crystal structures are recovered with the mapping algorithm. The methodology presented in this study will be of value to efforts that seek to catalogue crystal structures, identify structural transformation pathways or prune large first-principles datasets used to parameterize on-lattice Hamiltonians.

36 MATERIALS SCIENCE↗