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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.

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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Computational Redesign of Acyl-ACP Thioesterase with Improved Selectivity toward Medium-Chain-Length Fatty Acids

Enzyme and metabolic engineering offer the potential to develop biocatalysts for converting natural resources to a wide range of chemicals. To broaden the scope of potential products beyond natural metabolites, methods of engineering enzymes to accept alternative substrates and/or perform novel chemistries must be developed. DNA synthesis can create large libraries of enzyme-coding sequences, but most biochemistries lack a simple assay to screen for promising enzyme variants. Our solution to this challenge is structure-guided mutagenesis, in which optimization algorithms select the best sequences from libraries based on specified criteria (i.e., binding selectivity). We demonstrate this approach by identifying medium-chain (C8–C12) acyl-ACP thioesterases through structure-guided mutagenesis. Medium-chain fatty acids, which are products of thioesterase-catalyzed hydrolysis, are limited in natural abundance, compared to long-chain fatty acids; the limited supply leads to high costs of C6–C10 oleochemicals such as fatty alcohols, amines, and esters. Here, we applied computational tools to tune substrate binding of the highly active ‘TesA thioesterase in Escherichia coli. We used the IPRO algorithm to design thioesterase variants with enhanced C12 or C8 specificity, while maintaining high activity. After four rounds of structure-guided mutagenesis, we identified 3 variants with enhanced production of dodecanoic acid (C12) and 27 variants with enhanced production of octanoic acid (C8). The top variants reached up to 49% C12 and 50% C8 while exceeding native levels of total free fatty acids. A comparably sized library created by random mutagenesis failed to identify promising mutants. The chain length-preference of ‘TesA and the best mutant were confirmed in vitro using acyl-CoA substrates. Molecular dynamics simulations, confirmed by resolved crystal structures, of ‘TesA variants suggest that hydrophobic forces govern ‘TesA substrate specificity. Finally, we expect the design rules that we uncovered and the thioesterase variants that we identified will be useful to metabolic engineering projects aimed at sustainable production of medium-chain-length oleochemicals.

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

Retinal microvascular and neuronal pathologies probed in vivo by adaptive optical two-photon fluorescence microscopy

The retina, behind the transparent optics of the eye, is the only neural tissue whose physiology and pathology can be non-invasively probed by optical microscopy. The aberrations intrinsic to the mouse eye, however, prevent high-resolution investigation of retinal structure and function in vivo. Optimizing the design of a two-photon fluorescence microscope (2PFM) and sample preparation procedure, we found that adaptive optics (AO), by measuring and correcting ocular aberrations, is essential for resolving putative synaptic structures and achieving three-dimensional cellular resolution in the mouse retina in vivo. Applying AO-2PFM to longitudinal retinal imaging in transgenic models of retinal pathology, we characterized microvascular lesions with sub-capillary details in a proliferative vascular retinopathy model, and found Lidocaine to effectively suppress retinal ganglion cell hyperactivity in a retinal degeneration model. Tracking structural and functional changes at high-resolution longitudinally, AO-2PFM enables microscopic investigations of retinal pathology and pharmacology for disease diagnosis and treatment in vivo.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A simplified, efficient approach to hybrid wind and solar plant site optimization

Abstract. Wind plant layout optimization is a difficult, complex problem with a large number of variables and many local minima. Layout optimization only becomes more difficult with the addition of solar generation. In this paper, we propose a parameterized approach to wind and solar hybrid power plant layout optimization that greatly reduces problem dimensionality while guaranteeing that the generated layouts have a desirable regular structure. Thus far, hybrid power plant optimization research has focused on system sizing. We go beyond sizing and present a practical approach to optimizing the physical layout of a wind–solar hybrid power plant. We argue that the evolution strategy class of derivative-free optimization methods is well-suited to the parameterized hybrid layout problem, and we demonstrate how hard layout constraints (e.g., placement restrictions) can be transformed into soft constraints that are amenable to optimization using evolution strategies. Next, we present experimental results on four test sites, demonstrating the viability, reliability, and effectiveness of the parameterized evolution strategy approach for generating optimized hybrid plant layouts. Completing the tool kit for parameterized layout generation, we include a brief tutorial describing how the parameterized evolutionary approach can be inspected, understood, and debugged when applied to hybrid plant layouts.

14 SOLAR ENERGY↗
DOE OSTI2018

Economics of Indoor Air Quality

Buildings represent a major end use of energy throughout the world and are typically the dominant sector for electricity. The use of that energy is to provide buildings services, the most important of which is Indoor Environmental Quality (IEQ). Heating and air conditioning systems typically handle the thermal comfort aspects of IEQ; the energy impacts and economics of such systems is well studied. The most important remaining aspect of IEQ is Indoor Air Quality (IAQ). IAQ combines health aspects odour and moisture but is typically not represented by a health-based performance metric. As a result, ventilation rates are used as a surrogate for IAQ. Recent research has developed “Smart Ventilation” technologies that economically optimize ventilation by considering utility rate structures, exposure to outdoor contaminants, as well as peak loads and total energy demand. Enabling this optimization of Smart Ventilation requires IAQ performance metrics that can be monetized. Lawrence Berkeley National Laboratory and others have used Disability Adjusted Life Years (DALYs) to quantify health impacts of contaminant exposure, which shows IAQ may be a critical economic driver. This paper reviews these general concepts and presents some of the most recent work we have done on both Smart Ventilation and economic metrics for IAQ.

Walker, Iain↗
DOE OSTI2023

Enhancing lithium storage performance of bimetallic oxides anode by synergistic effects

Spinel bimetallic transition metal oxide anode such as ZnMn 2 O 4 , has drawn increasing interest due to attractive bimetal interaction and high theoretical capacity. While it suffers from huge volume expansion and poor ionic/electronic conductivity. Nanosizing and carbon modification can alleviate these issues, while the optimal particle size within host is unclear yet. We here propose an in-situ confinement growth strategy to fabricate pomegranate-structured ZnMn 2 O 4 nanocomposite with calculated optimal particle size in mesoporous carbon host. Theoretical calculations reveal favorable interatomic interactions between the metal atoms. Further, by the synergistic effects of structural merits and bimetal interaction, the optimal ZnMn 2 O 4 composite achieves greatly improved cycling stability (811 mAh g -1 at 0.2 A g -1 after 100 cycles), which can maintain its structural integrity upon cycling. X-ray absorption spectroscopy analysis further confirms delithiated Mn species (Mn 2 O 3 but little MnO). Briefly, this strategy brings new opportunity to ZnMn 2 O 4 anode, which could be adopted to other conversion/alloying-type electrodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Rheo-electric measurements of carbon black suspensions containing polyvinylidene difluoride in N -methyl-2-pyrrolidone

Lithium-ion battery cathode slurries have a microstructure that depends sensitively on how they are processed due to carbon black's (CB) evolving structure when subjected coating flows. While polyvinylidene difluoride (PVDF), one of the main components of the cathode slurry, plays an important role in modifying the structure and rheology of CB, a quantitative understanding is lacking. In this work, we explore the role of PVDF in determining the structural evolution of Super C65 CB in N-methyl-2-pyrrolidinone (NMP) with rheo-electric measurements. We find that PVDF enhances the viscosity of NMP resulting in a more extensive structural erosion of CB agglomerates with increasing polymer concentration and molecular weight. We also show that the relative viscosity of all suspensions can be collapsed by the fluid Mason number (Mnf), which compares the hydrodynamic forces imposed by the medium to cohesive forces holding CB agglomerates together. Using simultaneous rheo-electric measurements, we find at high Mnf, the dielectric strength (Δε) scales with Mnf, and the power-law scaling can be quantitatively predicted by considering the self-similar break up of CB agglomerates. The collapse of the relative viscosity and scaling of Δε both suggest that PVDF increases the hydrodynamic force of the suspending medium without directly changing the CB agglomerate structure. These findings are valuable for optimizing the rheology of lithium ion battery cathode slurries. We also anticipate that these findings can be extended to understand the microstructure of similar systems under flow.

Mechanics↗
DOE OSTI2019

Optimized oxygen deprived low temperature sputtered WO3 thin films for crystalline structures

In this work, we report a detailed analysis on the effects of processing parameters for sputtered tungsten trioxide (WO 3 ) thin nanoscale films on their structural, vibrational and electrical properties. The research aims to understand the fundamental aspects of WO3 sputtering at relatively low temperatures and in an oxygen deprived environment targeting applications of temperature and oxygen sensitive substrates. Structural analysis indicates that films deposited at room temperature, or substrate temperatures at or below 400 degrees C with low oxygen partial pressure are amorphous. Furthermore, crystallization of the films was observed with distinct Raman peaks when the films were annealed at 300 degrees C or above using rapid thermal annealing for 10 min. Films revealed monoclinic phases of WO 3 with the presence of W-O-W stretching, bending and lattice vibrational modes in the Raman spectra. Interestingly, a change of transport behavior from insulating to semiconducting was observed for as deposited films on post annealing. Annealed films revealed stoichiometric WO 3 phases with no external defects detected. The present study adopts a route to intercalate WO 3 in a variety of applications from electrochromic coloration to a nanocrystalline thin film for electronic devices sensitive to higher temperatures and gas flow in the sputtering system.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

An overview of process systems engineering approaches for process intensification: State of the art

Process intensification offers the potential to drastically reduce the energy consumption and cost of producing chemicals from both bulk and distributed feedstocks. This review article aims to offer an extensive survey on state-of-the-art process systems engineering (PSE) approaches for process intensification. From both academic and industrial perspectives, this paper provides an overview of the development of various process intensification technologies, specifically those under the categories of separation, reaction, hybrid reaction/separation, and alternative energy sources. A current status analysis in the areas of modeling and simulation is then provided. An indicative list of PSE publications specialized on process intensification is presented to illustrate the progresses made so far towards the deployment of novel process intensification technologies. We also highlight some recent advances for the modeling, design, and synthesis of intensified systems, as well as for the assessment of their controllability/operability/safety performance. As a result, key open questions in these areas include: (i) how to systematically derive intensified designs, and (ii) how to ensure the operability and optimality of the derived intensified structures while delivering their expected functionality.

42 ENGINEERING↗
DOE OSTI2026

CoSn-type NiIn1–xSbx (0 ≤ x ≤ 0.17): Site-Selective Substitution, Electronic Structure, Chemical Bonding, and Structural Transformation

CoSn-type intermetallic compounds have emerged as a model platform for Kagome-derived flat-band physics, where subtle chemical perturbations can strongly influence electronic structure and phase stability. Here, we present a combined experimental and theoretical study of Sb-substitution in CoSn-type NiIn1–xSbx (0 ≤ x ≤ 0.17) to elucidate the interplay between site selectivity, solubility limit, chemical bonding, and electronic structure. Rietveld refinements on Neutron powder diffraction data confirmed the selective Sb-substitution at the electron-rich In2 (2d) site forming the honeycomb substructure, while the In1 (1a) site within the Kagome layer remains exclusively occupied by In. Density functional theory (DFT) calculations revealed that pristine CoSn-type NiIn hosts Ni 3d-dominated flat bands near the Fermi level (EF), originating from the Kagome-like Ni substructure. Partial replacement of In by Sb within the honeycomb layer alters these flat-band features below EF, reducing the density of states and suppressing the flat-band topology near the Fermi level. Orbital-resolved electronic structure and chemical-bonding analyses show that Sb-substitution enhances Ni-p-block (In/Sb) covalency and optimizes charge compensation, stabilizing the CoSn-type structure up to the solubility limit x ≈ 0.17. Beyond the limit, the higher-Sb compositions show satellite reflections consistent with an incommensurately modulated phase. These results establish a link between site-selective chemical substitution, bonding optimization, and flat-band electronic structure evolution, providing fundamental insights into how chemical substitution influences the electronic properties of Kagome-based intermetallic compounds.

Roy, Nilanjan [National Institute of Technology Si↗
DOE OSTI2023

Additive Manufacturing for Powering the Blue Economy Applications: A Tidal Turbine Blade Case Study: Preprint

As the marine renewable energy industry continues to expand, innovation in the manufacturing space must grow accordingly to reduce costs and ensure the economic feasibility of new technologies. Additive manufacturing, more commonly known as 3D printing, provides an alternative for rapid prototyping of marine hydrokinetic technologies, particularly supporting Powering the Blue Economy initiatives of the U.S. Department of Energy Water Power Technologies Office. This study explores the application of additive manufacturing in the development of marine hydrokinetic structures, focusing on material and printing method selection, design, and analysis of a 3D-printed spar for an axial-flow tidal turbine blade. Corrosion-resistant metals were deemed ideal due to the loads and harsh marine environment the blade would experience. Laser metal deposition methods were determined to be the most effective and scalable for the considered scale. The designed spar adapts its geometry to the blade - a feature uniquely suited to additive manufacturing - and is intended to serve as the blade's primary structural component. A finite element model was used to study stresses and deformations under loading conditions. The spar was manufactured using 316L stainless steel through direct energy deposition, and defects were assessed and recorded. Future efforts will include mechanical testing of the spar. This research establishes a benchmark process for using additive manufacturing in developing marine hydrokinetic structures, paving the way for future optimization and techno-economic analysis.

additive manufacturing↗
DOE OSTI2021

TEQUILA: a platform for rapid development of quantum algorithms

Variational quantum algorithms are currently the most promising class of algorithms for deployment on near-term quantum computers. In contrast to classical algorithms, there are almost no standardized methods in quantum algorithmic development yet, and the field continues to evolve rapidly. As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in a high demand for flexible and reliable ways to implement, test, and share new ideas. In this paper, inspired by this demand, we introduce TEQUILA, a development package for quantum algorithms in PYTHON, designed for fast and flexible implementation, prototyping and deployment of novel quantum algorithms in electronic structure and other fields. TEQUILA operates with abstract expectation values which can be combined, transformed, differentiated, and optimized. On evaluation, the abstract data structures are compiled to run on state of the art quantum simulators or interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Ultrahigh thermoelectric power factor in flexible hybrid inorganic-organic superlattice

Hybrid inorganic–organic superlattice with an electron-transmitting but phonon-blocking structure has emerged as a promising flexible thin film thermoelectric material. However, the substantial challenge in optimizing carrier concentration without disrupting the superlattice structure prevents further improvement of the thermoelectric performance. Here we demonstrate a strategy for carrier optimization in a hybrid inorganic–organic superlattice of TiS 2 [tetrabutylammonium] x [hexylammonium] y, where the organic layers are composed of a random mixture of tetrabutylammonium and hexylammonium molecules. By vacuum heating the hybrid materials at an intermediate temperature, the hexylammonium molecules with a lower boiling point are selectively de-intercalated, which reduces the electron density due to the requirement of electroneutrality. The tetrabutylammonium molecules with a higher boiling point remain to support and stabilize the superlattice structure. Furthermore, the carrier concentration can thus be effectively reduced, resulting in a remarkably high power factor of 904 µW m –1 K –2 at 300 K for flexible thermoelectrics, approaching the values achieved in conventional inorganic semiconductors.

14 SOLAR ENERGY↗
DOE OSTI2020

CSB-RNN: A Faster-Than-Realtime RNN Acceleration Framework with Compressed Structured Blocks

Recurrent Neural Networks (RNN) is widely applied to temporal sequence analysis, where real-time performance is usually in demand. However, RNN suffers a heavy computational workload as the model comes with a large weight matrix. To alleviate the pain, model compression (pruning) schemes have been proposed for RNN that pruning the redundant (near-zero) weight-values. On the one hand, the non-structured pruning methods achieve a considerable pruning rate while bringing the computational irregularity, which is un-friendly to parallel-hardware. On the other hand, the existing structured pruning methods consider the hardware parallelism; However, they suffer a poor pruning rate due to the restrict constraints on pruning structure. This paper presents CSB-RNN, an optimized full-stack RNN framework with the novel compressed structured block (CSB) technique. The CSB-pruned RNN model comes with both fine-granularity that benefits the pruning rate and regular structure that facilitates the hardware-parallelism. Further, we propose a novel hardware architecture for inferencing the CSB-pruned model. Different from conventional parallel hardware, this architecture solves the block-workload imbalance issue and achieves an over 95% hardware utilization. With the experiments on 10 RNN models in 5 application domains, the CSB-RNN realizes 7×-20× lossless compression and up to 50× acceptable lossy-compression, which is 2×-7× to the prior art. With the addition of the novel hardware, the compressed-RNN inference reaches a super real-time latency of 10-400µs with FPGA implementation.

Shi, Runbin↗
DOE OSTI2022

Epitaxial growth, magnetoresistance, and electronic band structure of GdSb magnetic semimetal films

Motivated by observations of extreme magnetoresistance (XMR) in bulk crystals of rare-earth monopnictide (RE-V) compounds and emerging applications in novel spintronic and plasmonic devices based on thin-film semimetals, we have investigated the electronic band structure and transport behavior of epitaxial GdSb thin films grown on III-V semiconductor surfaces. The Gd 3 + ion in GdSb has a high spin S=7/2 and no orbital angular momentum, serving as a model system for studying the effects of antiferromagnetic order and strong exchange coupling on the resulting Fermi surface and magnetotransport properties of RE-Vs. Here, we present a surface and structural characterization study mapping the optimal synthesis window of thin epitaxial GdSb films grown on III-V lattice-matched buffer layers via molecular-beam epitaxy. To determine the factors limiting XMR in RE-V thin films and provide a benchmark for band-structure predictions of topological phases of RE-Vs, the electronic band structure of GdSb thin films is studied, comparing carrier densities extracted from magnetotransport, angle-resolved photoemission spectroscopy (ARPES), and density-functional theory (DFT) calculations. ARPES shows a hole-carrier rich, topologically trivial, semimetallic band structure close to complete electron-hole compensation, with quantum confinement effects in the thin films observed through the presence of quantum-well states. DFT-predicted Fermi wave vectors are in excellent agreement with values obtained from quantum oscillations observed in magnetic field-dependent resistivity measurements. An electron-rich Hall coefficient is measured despite the higher hole-carrier density, attributed to the higher electron Hall mobility. The carrier mobilities are limited by surface and interface scattering, resulting in lower magnetoresistance than that measured for bulk crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Isopod (inverse Optimization And Design): Moose-based Application For Performing Inverse Optimization On Multiphysics Modeling And Simulation

ISOPOD (InverSe OPtimizatiOn and Design) will be a MOOSE (Multiphysics Object Oriented Simulation Environment)-based framework which will iteratively estimate the parameters by minimizing the difference between simulated and experimental observables. While inverse optimization has long been used for parameter estimation, the unique feature of ISOPOD is rapid solution of new inverse problems, leading to accelerated Research, Development and Demonstration (RD&D) for complex parameter estimation problems. This will be achieved by extending the software structure of MOOSE to inverse optimization, as well as building on the unique automatic differentiation feature of MOOSE.

Munday, LynnB↗
DOE OSTI2026

Intrusive Uncertainty Quantification and Optimal Experiment Design in the Open-Source Pyomo Ecosystem

This contribution describes ParmEst and Pyomo.DoE, two pillars of the open-source Python-based Pyomo ecosystem for computational optimization with (partial differential) algebraic equation mathematical models. Specifically, ParmEst facilitates intrusive frequentist parameter estimation (PE) and uncertainty quantification (UQ) through built-in features, such as covariance matrix estimation, bootstrapping, and likelihood ratio tests. Complementary, Pyomo.DoE enables optimal experiment design by maximizing various metrics of the Fisher information matrix, such as A-optimality (trace), D-optimality (determinant), E-optimality (minimum eigenvalue), and ME-optimality (condition number). ParmEst and Pyomo.DoE can solve high-dimensional optimization problems by leveraging the model structure and exact derivative information. Finally, we will discuss future opportunities to integrate PE and UQ capabilities with optimization under uncertainty, including robust optimization with non-convex models via PyROS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Generation of High-Power, Reversed-Cherenkov Wakefield Radiation in a Metamaterial Structure

Here, we present the first demonstration of high-power, reversed-Cherenkov wakefield radiation by electron bunches passing through a metamaterial structure. The structure supports a fundamental transverse magnetic mode with a negative group velocity leading to reversed-Cherenkov radiation, which was clearly verified in the experiments. Single 45 nC electron bunches of 65 MeV traversing the structure generated up to 25 MW in 2 ns pulses at 11.4 GHz, in excellent agreement with theory. Two bunches of 85 nC with appropriate temporal spacing generated up to 80 MW by coherent wakefield superposition, the highest rf power that metamaterial structures ever experienced without damage. These results demonstrate the unique features of metamaterial structures that are very attractive for future high-gradient wakefield accelerators, including two-beam and collinear accelerators. Advantages include the high shunt impedance for high-power generation and high-gradient acceleration, the simple and rugged structure, and a large parameter space for optimization.

43 PARTICLE ACCELERATORS↗