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Results for “Lattice 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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Computational design of thermoelectric alloys through optimization of transport and dopability

Alloying is a common technique to optimize the functional properties of materials for thermoelectrics, photovoltaics, energy storage etc. Designing thermoelectric (TE) alloys is especially challenging because it is a multi-property optimization problem, where the properties that contribute to high TE performance are interdependent. In this work, we develop a computational framework that combines first-principles calculations with alloy and point defect modeling to identify alloy compositions that optimize the electronic, thermal, and defect properties. We apply this framework to design n-type Ba 2(1–x) Sr 2x CdP 2 Zintl thermoelectric alloys. Our predictions of the crystallographic properties such as lattice parameters and site disorder are validated with experiments. To optimize the conduction band electronic structure, we perform band unfolding to sketch the effective band structures of alloys and find a range of compositions that facilitate band convergence and minimize alloy scattering of electrons. Here, we assess the n-type dopability of the alloys by extending the standard approach for computing point defect energetics in ordered structures. Through the application of this framework, we identify an optimal alloy composition range with the desired electronic and thermal transport properties, and n-type dopability. Such a computational framework can also be used to design alloys for other functional applications beyond TE.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Gradient-Based Optimization of the Common Research Model Wing Subject to CFD-Based Gust and Flutter Constraints

The linearized frequency-domain method was recently implemented in the stabilized finite element solver in NASA’s FUN3D code. Previous work by the authors used this method for enforcing flutter constraints during gradient-based optimizations. More recently, the solver was expanded to account for continuous (also known as stochastic) gust responses. This paper expands on recent Common Research Model wing optimization work, which demonstrated gradient-based optimization with flutter and stochastic gust constraints, among others. While that work utilized FUN3D for static aeroelastic solutions but relied on doublet lattice aerodynamics for gust and flutter responses, the present work replaces these unsteady aerodynamic analyses with those of FUN3D’s linearized frequency-domain solver. With analytic derivatives available, gradient-based optimization is performed through the use of the OpenMDAO/MPhys libraries with over 700 shape, structural, and aerodynamic design variables and over 10 nonlinear constraints. Comparisons of analysis results and optimized designs are made between doublet lattice and linearized frequency-domain solutions.

aeroelasticity↗
DOE OSTI2022

express: Extensible, high-level workflows for swifter ab initio materials modeling

In this work, we introduce an open-source Julia project, express, an extensible, lightweight, high-throughput, high-level workflow framework that aims to automate ab initio calculations for the materials science community. express is shipped with well-tested workflow templates, including structure optimization, equation of state (EOS) fitting, phonon spectrum (lattice dynamics) calculation, and thermodynamic property calculation in the framework of the quasi-harmonic approximation (QHA). It is designed to be highly modularized so that its components can be reused across various occasions, and customized workflows can be built on top of that. Users can also track the status of workflows in real-time, and rerun failed jobs thanks to the data lineage feature express provides. Finally, two working examples, i.e., all workflows applied to lime and akimotoite, are also presented in the code and this paper.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Modeling and characterizing the elastodynamic response of octet-truss lattice structures using resonance techniques

Characterization of additively manufactured materials and structures is an ongoing effort for the advanced manufacturing community. This article will investigate an approach using resonant spectral ultrasound (RUS) to measure the effective elastic constants of an Octet Truss lattice and apply the results to continuum bases models representing the lattice regions in different structures. The study is focused on simple lattices structures fabricated from Ti5553 using a laser powder bed fusion process (LBPF). Solid and lattice samples are measured to determine RUS estimates for the elastic properties of the bulk material and the effective elastic properties of the lattice structure. The estimated elastic properties are then incorporated into 3d finite element models using a continuum approximation of the physical AM parts. Comparisons show good agreement between the experimentally measured eigen frequencies of the Ti5553 LBPF parts and the eigen frequencies calculated using the continuum approximations based on the effective RUS elastic properties. The current results suggest there is additional physics and geometrical effects that are accounted for in the RUS continuum approximation of the lattice that are not captured in the full 3d finite element model of the parts utilizing only the base material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Engineering the electronic and strained interface for high activity of PdM core @Pt monolayer electrocatalysts for oxygen reduction reaction

Alloyed nanoparticles with core-shell structures provide a favorable model to modulate interfacial interaction and surface structures at the atomic level, which is important for designing electrocatalysts with high activity and durability. Herein, core-shell structured Pd 3 M@Pt/C nanoparticles with binary PdM alloy cores (M = Fe, Ni, and Co) and a monolayer Pt shell were successfully synthesized with diverse interfaces. Among these, Pd 3 Fe@Pt/C exhibited the best oxygen reduction reaction catalytic performance, roughly 5.4 times more than that of the commercial Pt/C catalyst used as reference. The significantly enhanced activity is attributed to the combined effects of strain engineering, interfacial electron transfer, and improved Pt utilization. Density functional theory simulations and extended X-ray absorption fine structure analysis revealed that engineering the alloy core with moderate lattice mismatch and alloy composition (Pd 3 Fe) optimizes the surface oxygen adsorption energy, thereby rendering excellent electrocatalytic activity. Finally, future researches may use this study as a guide on the construction of highly effective core-shell electrocatalysts for various energy conversions and other applications.

25 ENERGY STORAGE↗
DOE OSTI2026

Radiation Damage Mechanisms in Oxide-Based Solid Electrolytes

Ion implantation is a promising approach to mitigate dendrite formation in metal anode solid-state batteries by modifying the chemical and mechanical properties of oxide-based electrolyte surfaces such as Li 7 La 3 Zr 2 O 12 (LLZO). Yet, the detailed atomistic mechanisms and potentially adverse side effects of ion implantation remain poorly understood. In this study, we used molecular dynamics simulations to elucidate the evolution of radiation-induced damage in LLZO. The results reveal that radiation damage is primarily driven by recoils from heavy ions in the lattice, producing antisite defect clusters whose density decreases as recoil energy increases, a counterintuitive finding that highlights complex cascade fragmentation. Radiation-induced disruption to the crystal sublattice connectivity, especially in the La–O network critical for Li-ion transport, leads to degradation in ionic pathways at low energies, while higher energy cascades can form new conduction pathways via enhanced Zr–O network connectivity. These findings provide a mechanistic foundation for optimizing ion implantation strategies that balance disruption of the lattice for surface modification for dendrite resistance with preservation of essential ionic conductivity.

Defects↗
DOE OSTI2026

Surface-Functionalized, Two-Dimensional Polymer Electrochromic Layers as Ultrafast, Multi-State Infrared Optical Gates

Electrochromic devices have widespread application potential, but the currently available switching speeds limit broad real-world implementation of this technology. Here, we report surface-engineered two-dimensional polymers with ionophilic pores that offer unprecedented switching speeds in solid-state, two-terminal, electrochromic devices. In particular, we demonstrate that a crystalline donor–acceptor 2DP functionalized with ethylene glycol oligomers exhibits multistate infrared absorption that is 4× faster (t c = 320 ms) with 3× coloration efficiency (491 cm 2 C –1 ) compared to an alkyl functionalized 2DP constructed from the same chromophores. The functionalized nanoporous surfaces enable rapid switching in these materials under either oxidative or reductive conditions, allowing us to access a range of robust, stable optical responses in a single electrochromic layer. These attributes led us to leverage surface-functionalized 2DPs as multistate infrared logic gates. Collectively, this work demonstrates that surface engineering of nanoporous crystalline lattices is a promising approach to co-optimize the electronic and ionic conductivities required to achieve rapidly switchable electrochromic layers. Beyond speed and efficiency, the demonstration of multistate infrared characteristics shows that electrochromic frameworks are useful in integrated optoelectronic circuits. This positions surface-engineered 2DPs as improved electrochromic coatings and a new material platform for photonic information processing and adaptive devices.

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

Short-depth QAOA circuits and quantum annealing on higher-order ising models

Abstract We present a direct comparison between QAOA (Quantum Alternating Operator Ansatz), and QA (Quantum Annealing) on 127 qubit problem instances. QAOA with p = 1, 2 rounds is executed on the 127 qubit heavy-hex graph gate-model quantum computer ibm_washington, using on-device grid-searches for angle finding, and QA is executed on two Pegasus-chip D-Wave quantum annealers. The problems are random Ising models whose connectivity matches heavy-hex graphs and the Pegasus graph connectivity, and optionally include hardware-compatible cubic terms ( Z Z Z terms). The QAOA circuits are heavily optimized and of extremely short depth, with a CNOT depth of 6 per round, which allows whole chip usage of the heavy-hex lattice. QAOA and QA are both compared against simulated annealing and the optimal solutions are computed exactly using CPLEX. The noiseless mean QAOA expectation values for p = 1, 2 are computed using classical light-cone based simulations. We find QA outperforms QAOA on the evaluated devices.

127 qubits↗
DOE OSTI2017

Increasing the thermoelectric power factor of Ge 17 Sb 2 Te 20 by adjusting the Ge/Sb ratio

Here, we have investigated the thermoelectric properties of Ge 17 Sb 2 Te 20 . This compound is a known phase change material with electronic properties that depend strongly on temperature. The thermoelectric properties of this compound can be tuned by altering the stoichiometry of Ge and Sb without the use of additional foreign elements during synthesis. This tuning results in a 26% increase in the thermoelectric power factor at 723 K. Based on a single parabolic band model we show that the pristine material is optimally doped, and thus, a reduction in the lattice thermal conductivity of pure Ge 17 Sb 2 Te 20 should result in an enhanced thermoelectric figure of merit.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Digital autofocusing of a coded-aperture Laue diffraction microscope

To provide optimal depth resolution with a coded-aperture Laue diffraction microscope, an accurate position of the coded-aperture and its scanning geometry need to be known. However, finding the geometry by trial and error is a time-consuming and often challenging process because of the large number of parameters involved. In this paper, we propose an optimization approach to automate the focusing process after data is collected. Here we demonstrate the robustness and efficiency of the proposed approach with experimental data taken at a synchrotron facility.

47 OTHER INSTRUMENTATION↗
NASA NTRS2019

High Performance GaN/AlGaN Ultraviolet Avalanche Photodiode Detector Technologies

Detection of ultraviolet (UV) bands provides distinct advantages for NASA, defense, and commercial applications, including increased spatial resolution, small pixel sizes, and large format arrays. AlxGa1-xN semiconductor alloys have attracted great interest for detection in the UV spectral region because of their potential for high optical gain, high sensitivity, and low dark current performance in ultraviolet avalanche photodiodes (UV-APDs). We are developing GaN/AlGaN UV-APDs that demonstrate consistent and reliable UV-APD performance and operation. For these UV detectors we have measured gains of above 5×10(exp 6) and high quantum efficiencies at ~350 nm enabled by a strong avalanche multiplication process. These UV-APDs are fabricated through high quality metal organic chemical vapor deposition (MOCVD) growth on lattice-matched, low dislocation density GaN substrates with optimized GaN/AlGaN UV-APD material growth and doping parameters. The high performance, variable-area GaN/AlGaN UV-APD detectors and arrays can be customized to a wide variety of sizes including large-area formats to enable sensing and high-resolution detection over UV bands of interest.

Sood, Ashok K.↗
NASA NTRS2019

GaN/AlGaN Avalanche Photodiode Detectors for High Performance Ultraviolet Sensing Applications

The shorter wavelengths of the ultraviolet (UV) band enable detectors to operate with increased spatial resolution, variable pixel sizes, and large format arrays, benefitting a variety of NASA, defense, and commercial applications. AlxGa1-xN semiconductor alloys, which have attracted much interest for detection in the UV spectral region, have been shown to enable high optical gains, high sensitivities with the potential for single photon detection, and low dark current performance in ultraviolet avalanche photodiodes (UV-APDs). We are developing GaN/AlGaN UV-APDs with large pixel sizes that demonstrate consistent and uniform device performance and operation. These UV-APDs are fabricated through high quality metal organic chemical vapor deposition (MOCVD) growth on lattice-matched, low dislocation density GaN substrates with optimized material growth and doping parameters. The use of these low defect density substrates is a critical element to realizing highly sensitive UV-APDs and arrays with suppressed dark current under high electric fields.Optical gains greater than 5X10 (exp 6) with enhanced quantum efficiencies over the 350-400 nm spectral range have been demonstrated, enabled by a strong avalanche multiplication process. Furthermore, we are developing 6X6 arrays of devices to test high gain UV-APD array performance at ~355 nm. These variable-area GaN/AlGaN UV-APD detectors and arrays enable advanced sensing performance over UV bands of interest with high resolution detection for NASA Earth Science applications.

Sood, Ashok K.↗
DOE OSTI2016

Lattice model for amyloid peptides: OPEP force field parametrization and applications to the nucleus size of Alzheimer’s peptides

Coarse-grained protein lattice models approximate atomistic details and keep the essential interactions. They are, therefore, suitable for capturing generic features of protein folding and amyloid formation at low computational cost. As our aim is to study the critical nucleus sizes of two experimentally well-characterized peptide fragments Aβ{sub 16−22} and Aβ{sub 37−42} of the full length Aβ{sub 1−42} Alzheimer’s peptide, it is important that simulations with the lattice model reproduce all-atom simulations. In this study, we present a comprehensive force field parameterization based on the OPEP (Optimized Potential for Efficient protein structure Prediction) force field for an on-lattice protein model, which incorporates explicitly the formation of hydrogen bonds and directions of side-chains. Our bottom-up approach starts with the determination of the best lattice force parameters for the Aβ{sub 16−22} dimer by fitting its equilibrium parallel and anti-parallel β-sheet populations to all-atom simulation results. Surprisingly, the calibrated force field is transferable to the trimer of Aβ{sub 16−22} and the dimer and trimer of Aβ{sub 37−42}. Encouraged by this finding, we characterized the free energy landscapes of the two decamers. The dominant structure of the Aβ{sub 16−22} decamer matches the microcrystal structure. Pushing the simulations for aggregates between 4-mer and 12-mer suggests a nucleus size for fibril formation of 10 chains. In contrast, the Aβ{sub 37−42} decamer is largely disordered with mixed by parallel and antiparallel chains, suggesting that the nucleus size is >10 peptides. Our refined force field coupled to this on-lattice model should provide useful insights into the critical nucleation number associated with neurodegenerative diseases.

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

Storage ring nonlinear dynamics optimization with multi-objective multi-generation Gaussian process optimizer

Nonlinear beam dynamics optimization is essential in a low emittance storage ring design. Multi-objective optimization algorithms are needed in order to simultaneously optimize the dynamic aperture and the momentum aperture. In this study we demonstrate the application of a highly efficient stochastic optimization algorithm, the multi-generation Gaussian process optimizer (MG-GPO), to storage ring nonlinear dynamics optimization by successfully applying the method to the SPEAR3 upgrade lattice. It is shown that the new method, owing to its capability of selecting high rank candidates from a large number of trial solutions, converges significantly faster than the commonly used traditional algorithms, multi-objective genetic algorithms (MOGA) and particle swarm optimization (PSO).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Digital twin framework for PIP-II linac: AI-driven multi-scale modeling from ion source to 800 MeV

The PIP-II superconducting linac at Fermilab is designed to deliver multi-megawatt proton beams for neutrino physics and other high-intensity applications. To expedite commissioning and enhance operational reliability, we have developed an EPICS-based data flow framework that seamlessly integrates digital twins (DT) with physical twins (PT). These digital twins comprise high-fidelity beam dynamics models or data-driven surrogate models connected to their physical counterparts through real-time diagnostics and advanced machine-learning algorithms.Central to this framework is Linac_Gen, an accelerated simulation tool that incorporates convolutional neural networks, random forests, and genetic algorithms to provide up to a tenfold speedup in optimizing the accelerator geometry model. An EPICS translator layer ensures interoperability by efficiently mapping lattice parameters across diverse simulation platforms.Our EPICS-based framework supports multiple operational modes—monitoring, passive learning, closed-loop control, and online learning—covering the entire machine lifecycle. By leveraging HPC resources and multi-objective optimization techniques, the digital twin enables adaptive trajectory correction, real-time fault detection, and predictive modeling of beam stability. This comprehensive approach paves the way for robust, high-intensity operation and data-driven accelerator R&D at Fermilab.

Pathak, Abhishek [Fermilab]↗
DOE OSTI2019

FTIR and Raman Spectroscopy of Reduced Graphene Oxide Carbon Nanoribbons and Graphene Oxide on Copper (Cu)

In the past couple of decades, carbon nanomaterials produced from graphene and graphite have emerged as one of the more important recently discovered substances. These carbon nanomaterials have been found to exhibit high levels of mechanical strength, thermal resistance, and electrical conductivity, thus having a multitude of applications. Therefore, it is important to identify and analyze their traits in order to maximize their effectiveness. Two spectroscopic techniques employed for such analyses of these materials are Fourier-Transform Infrared (FTIR) and Raman Spectroscopy. The advantages of FTIR and Raman include nondestructive analysis, relatively quick measurements under normal atmospheric conditions, and enhanced sensitivity with high resolution capacity. FTIR Spectroscopy was used in this research project to determine the effects of thermal exfoliation and photoreduction on the functionality groups of a carbon nanomaterial. Raman Spectroscopy was used in this research project to determine the effects of thermal exfoliation and photoreduction on the intensity of the disorder peak, which is greater in intensity if the carbon nanomaterial exhibits greater amounts of functionalities or defects in the graphitic material. There were two sample types which were analyzed with both FTIR and Raman Spectroscopy for the research project: graphene nanoribbons and graphene oxide. The m-grade graphene nanoribbons (GNRs) were produced from m-grade carbon nanotubes (CNTs) via Tour's method. The graphene oxide (GO) was produced from graphene via Tour's method, sonicated and centrifuged, dip-coated onto Copper (Cu) foil, and then photoreduced under a UV light source. FTIR measurements and analyses were conducted using a Jasco FTIR Spectrometer. Raman measurements and analyses were conducted using a Jasco Laser Raman Spectrometer. Tasks and techniques for this project included photoreduction, dip-coating, corrosion testing, FTIR and Raman data collection and analysis, and improvement of data collection for the Raman Spectrometer. GNRs exfoliated and reduced (deoxygenation) at 270 deg. C in air showed a significant decrease in O functionalities according to FTIR. However, Raman revealed that a large increase in graphene planar and edge defects are present as indicated by the disorder band at 1340 cm-1. Further optimization could be performed by thermal exfoliation at lower temperatures assuming a need for fewer structural defects. Graphene oxide coatings showed clear reduction with an increase with photoreduction time. Raman revealed that the reduced graphene oxide films had less disruption in the planar phonon lattice vibrations which indicates that the structure is returning to sp2 hybridization of pristine graphene without adding structural defects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Green’s functions on a renormalized lattice: An improved method for the integer quantum Hall transition

Highlights: • Speed up of numerical calculations by exact renormalization group steps. • Practical approach to handle delicate scaling analysis. • Absence of evidence to prefer marginal corrections over power-law corrections. We introduce a performance-optimized method to simulate localization problems on bipartite tight-binding lattices. It combines an exact renormalization group step to reduce the sparseness of the original problem with the recursive Green’s function method. We apply this framework to investigate the critical behavior of the integer quantum Hall transition of a tight-binding Hamiltonian defined on a simple square lattice. In addition, we employ an improved scaling analysis that includes two irrelevant exponents to characterize the shift of the critical energy as well as the corrections to the dimensionless Lyapunov exponent. We compare our findings with the results of a conventional implementation of the recursive Green’s function method, and we put them into broader perspective in view of recent development in this field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Influence of the Lattice Parameter on the Low-Temperature Brittle Failure of Metals

Abstract—The brittle failure of metals at low temperatures is analyzed. It is shown that the ductile–brittle transition temperature depends on the lattice parameter: with increase in the lattice parameter, the ductile–brittle transition temperature falls. The brittle failure of a material depends on its crystal lattice and its electron structure and on whether impurities are present at the grain boundaries. Increase in brittle strength of steels by optimization of their heat treatment is proposed.

42 ENGINEERING↗