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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Engineering Localized Surface Plasmon Interactions in Gold by Silicon Nanowire for Enhanced Heating and Photocatalysis

The field of plasmonics has attracted considerable attention in recent years because of potential applications in various fields such as nanophotonics, photovoltaics, energy conversion, catalysis, and therapeutics. It is becoming increasing clear that intrinsic high losses associated with plasmons can be utilized to create new device concepts to harvest the generated heat. It is therefore important to design cavities, which can harvest optical excitations efficiently to generate heat. In this paper, we report a highly engineered nanowire cavity, which utilizes a high dielectric silicon core with a thin plasmonic film (Au) to create an effective metallic cavity to strongly confine light, which when coupled with localized surface plasmons in the nanoparticles of the thin metal film produces exceptionally high temperatures upon laser irradiation. Raman spectroscopy of the silicon core enables precise measurements of the cavity temperature, which can reach values as high as 1000 K. The same Si–Au cavity with enhanced plasmonic activity when coupled with TiO 2 nanorods increases the hydrogen production rate by ~40% compared to similar Au–TiO 2 system without Si core, in ethanol photoreforming reactions. Finally, these highly engineered thermoplasmonic devices, which integrate three different cavity concepts (high refractive index core, metallo-dielectric cavity, and localized surface plasmons) along with the ease of fabrication demonstrate a possible pathway for designing optimized plasmonic devices with applications in energy conversion and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

In situ electric field X-ray total scattering reveals composition-dependent electromechanical strain mechanisms in (1 − x )BiFe 2/8 Ti 3/8 Mg 3/8 O 3 – x PbTiO 3 ceramics

Ferroelectric materials find many applications in energy and aerospace industries. A major challenge for ferroelectric materials is maintaining their properties at elevated temperatures. The (1 − x )BiFe 2/8 Ti 3/8 Mg 3/8 O 3 – x PbTiO 3 (BFTM–xPT) ferroelectric solid solution is a promising candidate for high-temperature applications as it has a high piezoelectric response while also maintaining its ferroelectric phase until a high Curie temperature (T C ) of 650 °C. In this work, we investigate the piezoelectric mechanism in BFTM–xPT, a novel high-T C ferroelectric ceramic. To elucidate the origin of its enhanced piezoelectric performance, relative to other piezoceramics of similar T C , in situ electric field X-ray total scattering experiments were performed. Total scattering combines Bragg scattering (diffraction) and diffuse scattering (pair distribution function), providing insight on various length scales. With information spanning different length scales, extrinsic contributions (i.e., domain wall motion and interphase boundary motion) can be separated from intrinsic contributions (i.e., piezoelectric lattice strain). We show that, for compositions within the morphotropic phase boundary (MPB, x = 0.325), the piezoelectric response is dominated by intrinsic piezoelectric lattice strain, whereas outside the MPB (x = 0.375) the major component of the piezoelectric response is from extrinsic mechanisms including an electric-field-induced phase transition and tetragonal domain wall motion. This article reveals that the origin of piezoelectric response in BFTM–xPT is composition-dependent and shows that high-performance materials may also be located outside the MPB. These findings can help guide material design to optimize properties for specific applications.

Richtik, Brooke N. [University of Calgary, AB (Can↗
NASA NTRS2012

Integrated Path Differential Absorption Lidar Optimizations Based on Pre-Analyzed Atmospheric Data for ASCENDS Mission Applications

In this paper a modeling method based on data reductions is investigated which includes pre analyzed MERRA atmospheric fields for quantitative estimates of uncertainties introduced in the integrated path differential absorption methods for the sensing of various molecules including CO2. This approach represents the extension of our existing lidar modeling framework previously developed and allows effective on- and offline wavelength optimizations and weighting function analysis to minimize the interference effects such as those due to temperature sensitivity and water vapor absorption. The new simulation methodology is different from the previous implementation in that it allows analysis of atmospheric effects over annual spans and the entire Earth coverage which was achieved due to the data reduction methods employed. The effectiveness of the proposed simulation approach is demonstrated with application to the mixing ratio retrievals for the future ASCENDS mission. Independent analysis of multiple accuracy limiting factors including the temperature, water vapor interferences, and selected system parameters is further used to identify favorable spectral regions as well as wavelength combinations facilitating the reduction in total errors in the retrieved XCO2 values.

Pliutau, Denis↗
DOE OSTI2026

Diabatization with Electrostatic Embedding for Studying Photophysics in Organic Molecular Crystals

Highly emissive organic molecular crystals find applications in several areas, such as organic electronics, solar cells, and sensors. Understanding the excited-state mechanisms underlying these applications is essential for optimizing and controlling them effectively. Exciton models coupled with nonadiabatic dynamics, particularly quantum dynamics, provide crucial insights into photochemical and photophysical processes in molecular crystals. Nevertheless, there remains a lack of general tools and automated workflows to facilitate such simulations. In this paper, we present a computational strategy to investigate the photoactivated dynamics of organic molecular crystals, bridging methodologies traditionally used for molecular systems and materials science, with a particular focus on the interplay between local excitations and charge transfer (CT) processes. We have implemented an interface between the fromage and Overdia programs, enabling the construction of vibronic Hamiltonians for molecular crystals within an excited-state ONIOM(QM:QM′) framework, incorporating long-range electrostatics through a RESP-based Ewald summation. Fragment-based diabatization provides a route to quantum dynamics simulations in weak-to-intermediate coupling regimes. The method was applied to the photophysics of dibenzo[g,p]chrysene (DBC) crystals using time-dependent DFT. The fromage/ Overdia interface was employed to compute the couplings of local excitations and CT states for 18 unique DBC dimers in the crystal and to quantify the influence of electrostatic embedding, which was found to be modest (10−20%). Simulations on π-stacked dimers reproduced the small red shift observed experimentally from solution to crystal, attributed to electronic interactions among fixed monomers rather than crystal electrostatics. Quantum dynamics simulations revealed ultrafast population transfer from bright local excitations to CT states. This approach establishes a robust framework linking molecular and solid-state excited-state dynamics, with potential applications for studying excitations, defects, and impurities in molecular crystals.

Crystals↗
DOE OSTI2025

Bandgap engineering of SrZrS 3 chalcogenide perovskite via substitutional doping for photovoltaic applications: a first-principles DFT study

Strontium zirconium sulfide (SrZrS 3 ) has garnered significant attention for photovoltaic (PV) applications due to its excellent optoelectronic properties, high chemical and moisture stability, and non-toxicity. However, the bandgaps of both the α- and β-phases lie outside the optimum ranges for both single-junction solar cells (SJSCs) and tandem solar cells (TSCs), thereby limiting their applications in PV technologies. In this study, we employed hybrid density functional theory to engineer the band gaps of α- and β-SrZrS 3 through substitutional doping. We considered three dopants (Hf, Sn, and Ti) at the Zr site of SrZrS 3 with varying doping concentrations and investigated their effects on the structural, electronic, and optical properties of the materials. We found that Sn and Ti doping effectively lowers the band gaps of both α- and β-SrZrS 3 , whereas Hf doping increases them. For x values up to 0.25, the band gaps of the α-SrZr 1−x Sn x S 3 and α-SrZr 1−x Ti x S 3 are within the optimum range for SJSCs, and those of β-SrZr 1−x Sn x S 3 and β-SrZr 1−x Ti x S 3 lie within the optimum range for Si/perovskite as well as perovskite/perovskite TSCs. The three dopants exhibited significant effects on the optical properties of both α- and β-SrZrS 3 , including the absorption coefficient, energy-loss functions, reflectivity, and refractivity spectra. Thermodynamic stability analysis revealed that for both phases, SrZr 1−x Hf x S 3 can be synthesized via exothermic processes, whereas the formation of SrZr 1−x Ti x S 3 and SrZr1−xSn x S 3 is endothermic and hence, not thermodynamically favorable. Further analysis showed that SrZr 1−x Ti x S 3 in both α- and β-phases are stable under thermodynamic equilibrium conditions, whereas SrZr 1−x Sn x S 3 is prone to dissociation into ternary phases (SrZrS 3 and SrSnS 3 ), especially at higher doping concentrations. These results show that Ti doping is effective in tuning the band gaps of α- and β-SrZrS 3 toward the optimal values for PV applications.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Performance Optimization Methods for a Memory-Bound, Unstructured-Grid CFD Application on Massively Parallel GPU Platforms

Computational performance of the FUN3D unstructured-grid computational fluid dynamics (CFD) application on massively parallel GPU environments is memory-bound and highly dependent upon efficient reads from and atomic updates to the irregular cell-, edge-, and node-based data structures. In this talk, we present recent efforts into optimizing select performance-critical kernels on NVIDIA Tesla V100 and A100 GPUs and AMD CDNA MI100 GPUs. A novel use of L2 cache residency controls and asynchronous loads into on-chip shared memory are explored on the A100 GPU for the sparse iterative solver, which is dominated by mixed-precision, sparse matrix vector multiplication. Demonstrations show that these methods improve global memory bandwidth utilization by 13.5% on the A100 GPU. Several techniques are also presented that use registers and/or shared memory to facilitate array transposition and aggregation which combine to reduce the frequency and increase the cache efficiency of floating-point atomic updates to the irregular data structures. These methods are demonstrated to improve the kernel throughput by nearly 500% on select kernels on the AMD MI100 over atomic updates directly to global memory. Overall, both V100 and A100 GPUs outperformed the MI100 GPU on kernels dominated by double-precision atomic updates; however, the techniques demonstrated here reduced the performance gap and improved the MI100 performance.

GPU CPU unstructured CFD memory↗
DOE OSTI2020

The Kalai-Smorodinsky solution for many-objective Bayesian optimization

An ongoing aim of research in multiobjective Bayesian optimization is to extend its applicability to a large number of objectives. While coping with a limited budget of evaluations, recovering the set of optimal compromise solutions generally requires numerous observations and is less interpretable since this set tends to grow larger with the number of objectives. We thus propose to focus on a specific solution originating from game theory, the Kalai-Smorodinsky solution, which possesses attractive properties. In particular, it ensures equal marginal gains over all objectives. We further make it insensitive to a monotonic transformation of the objectives by considering the objectives in the copula space. A novel tailored algorithm is proposed to search for the solution, in the form of a Bayesian optimization algorithm: sequential sampling decisions are made based on acquisition functions that derive from an instrumental Gaussian process prior. Our approach is tested on four problems with respectively four, six, eight, and nine objectives. The method is available in the R package GPGame available on CRAN at https://cran.r-project.org/package=GPGame.

Game theory↗
DOE OSTI2025

Metamorphic Epitaxy Solutions for Thermophotovoltaic and Laser Power Conversion Applications

Metamorphic GaInAs enables photovoltaic devices optimized for a wide range of bandgaps between 0.35 and 1.41 eV. We have developed compositionally graded buffers made of GaInP and AlGaInAs to enable growth of these devices on GaAs substrates with low dislocation densities and high performance. We present results for devices grown on both graded buffer materials with device bandgaps in the range 0.58-1.41 eV and compare the benefits and drawbacks of each material system. These results enable high performance for applications such as thermophotovoltaics and optical power transmission using high power lasers.

III-V↗
DOE OSTI2024

Game Theoretic Orchestration for Cooperation among Power Distribution System Applications

The evolving transformation with the proliferation of distributed energy resources and advanced metering, necessitates advanced distribution systems to integrate and orchestrate a large number of grid-edge devices while also serving multiple system-level objectives such as resilience, decarbonization, equity and other system mandates. The parallel deployment and control of resources towards achieving diverse objectives may lead to conflicts between applications that want to control overlapping sets of device setpoints, potentially leading to oscillatory behavior and suboptimal performance. This work aims at leveraging game theoretic framework to drive cooperative behavior among competitive applications. The work proposes a weighted-consensus based game design to facilitate conflict resolution through consensus-building iterations for modular platform. Simulation-based evaluation on a sample test system demonstrates the performance the proposed deconfliction strategy in resolving operational conflicts and achieving close-to-optimal trade off among the applications. Results also compare the proposed strategy with a distribution optimization approach and illustrate it effectiveness in diverse apps regardless of their design while also incentivizing apps with flexible design.

Advanced distribution operations, cooperation, app↗
DOE OSTI2024

Evaluating integration and performance of containerized climate applications on a Hewlett Packard Enterprise Cray system

Containers have taken over large swaths of cloud computing as the most convenient way of packaging and deploying applications. The features that containers offer for packaging and deploying applications translate to high performance computing (HPC) as well. At The National Oceanic and Atmospheric Administration, containers provide an easy way to build and distribute complex HPC applications, allowing faster collaboration, portability, and experiment computer environment reproducibility amongst the scientific community. The challenge arises when applications rely on message passing interface (MPI). This necessitates investigation into how to properly run these applications with their own unique requirements and produce performance on par with native runs. We investigate the MPI performance for benchmarks and containerized climate models for various containers covering selection of compiler and MPI library combinations from the Cray provided programming environments on the Cray XC supercomputer GAEA. Performance from the benchmarks and the climate models shows that for the most part containerized applications perform on par with the natively built applications when the system optimized Cray MPICH libraries are bound into the container, and the hybrid model containers have poor performance in comparison. We also describe several challenges and our solutions in running these containers, particularly challenges with heterogeneous jobs for the containerized model runs.

Abraham, Subil↗
DOE OSTI2022

Hydration of divalent lanthanides, Sm 2+ and Eu 2+ : A molecular dynamics study with polarizable AMOEBA force field

The chemistry of divalent lanthanides, Ln 2+ , is a growing sub-field of heavy element chemistry owing to new synthetic approaches. However, some theoretical aspects of these unusual cations are currently underdeveloped, especially as they relate to their dynamic properties in solution. In this study, we address the hydration of two of the classical Ln 2+ cations, Sm 2+ and Eu 2+ , using atomic multipole optimized energetic for biomolecular applications (AMOEBA) force fields. These cations have not been parameterized to date with AMOEBA, and few studies are available because of their instability with respect to oxidation in aqueous media. Coordination numbers (CN's) of 8.2 and 8.1 respectively for Sm 2+ and Eu 2+ , and 8.8 for both Sm 3+ and Eu 3+ have been obtained and are in good agreement with the few available AIMD and X-ray absorption fine structures studies. The decreased CN of Ln 2+ compared with Ln 3+ arises from progressive water exchange events that indicates the gradual stabilization of 8-coordinate structures with respect to 9-coordinate geometries. Moreover, the effects of the chloride counter anions on the coordination of Ln 2+ cations have been studied at different chloride concentrations in this work. Lastly, water exchange times of Ln 2+ cations have been calculated to provide a comprehensive understanding of the behavior of Eu 2+ and Sm 2+ in aqueous chloride media.

AMOEBA force field parameterization↗
DOE OSTI2019

Function Maximization with Dynamic Quantum Search

Finding the maximum value of a function in a dynamic model plays an important role in many application settings, including discrete optimization in the presence of hard constraints. We present an iterative quantum algorithm for finding the maximum value of a function in which prior search results update the acceptable response. Our approach is based on quantum search and utilizes a dynamic oracle function to mark items in a specified input set. As a realization of function optimization, we verify the correctness of the algorithm using numerical simulations of quantum circuits for the Knapsack problem. In conclusion, our simulations make use of an explicit oracle function based on arithmetic operations and a comparator subroutine, and we verify these implementations using numerical simulations up to 30 qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Vegetable Oil Based Polyurethane Containing 1,2,3-Triazolium Functional Groups as Antimicrobial Wound Dressing

Preparation of antimicrobial polyurethane wound dressing membranes from a mixture of castor oil and a novel soybean oil-based polyol containing 1,2,3-triazolium rings (QTSBO) was described in this research. QTSBO was prepared through N-alkylation of 1,2,3-triazole functional soybean oil (TSBO) with methyl iodide, and TSBO was synthesized from an azidated soybean oil and propargyl alcohol through click reaction. The excellent tensile strength of these dressings under dry state and minimum deterioration of this property at fully hydrated state guaranteed the mechanical protection of wounds during the entire period of the healing process. The measured quantities of equilibrium water absorption and water vapor transmission rate for the optimized dressings confirmed the applicability of the selected formulations for the preservation of proper moist environment over low exuding wounds. The cyto-compatibility of dressings was verified by the excellent ability of the dressings to support the growth and proliferation of dermal fibroblasts. Due to the presence of 1,2,3-triazolium rings the dressing showed efficient antimicrobial activity against different bacterial and fungal stains. Therefore, these dressing could promote wound healing by preserving moist and hygienic environment over the wound bed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Improved Miniaturized Linear Ion Trap Mass Spectrometer Using Lithographically Patterned Plates and Tapered Ejection Slit

We present a new two-plate linear ion trap mass spectrometer that overcomes both performance-based and miniaturization-related issues with prior designs. Borosilicate glass substrates are patterned with aluminum electrodes on one side and wire-bonded to printed circuit boards. Ions are trapped in the space between two such plates. Tapered ejection slits in each glass plate eliminate issues with charge build-up within the ejection slit and with blocking of ions that are ejected at off-nominal angles. The tapered slit allows miniaturization of the trap features (electrode size, slit width) needed for further reduction of trap size while allowing the use of substrates that are still thick enough to provide ruggedness during handling, assembly, and in-field applications. Plate spacing was optimized during operation using a motorized translation stage. A scan rate of 2300 Th/s with a sample mixture of toluene and deuterated toluene (D8) and xylenes (a mixture of o-, m-, p-) showed narrowest peak widths of 0.33 Th (FWHM). .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Demonstration of gold nanorod systems for enhanced total efficiency: Experimental and numerical analysis

This study investigates the photothermal performance of gold nanorods engineered to exhibit longitudinal plasmon resonances at 695 nm, 780 nm, and 970 nm. The work combines synthesis, structural characterization, extinction measurements, numerical modeling, and controlled temperature experiments to quantify how nanorod geometry, resonance tuning, concentration, and chamber shape jointly influence heat generation. Transmission electron microscopy confirms that increasing nanorod aspect ratio systematically shifts the longitudinal plasmon peak toward the near-infrared region. Extinction measurements show strong agreement with theoretical predictions, validating the numerical model across two independent datasets. Three chamber geometries were tested under laser excitation at 640 nm, 808 nm, and 980 nm: an ascending stepped base, a flat base, and a descending stepped base. Without nanorods, the ascending geometry produced the highest efficiency due to enhanced natural convection. After introducing gold nanorods, all geometries exhibited substantial thermal enhancement, with total efficiencies exceeding 20%. The strongest improvement was obtained for nanorods resonant at 780 nm with a mass concentration of 4.6 mg/mL implemented on the descending stepped-base geometry. This performance resulted from the combined effect of spectral overlapping with the 808 nm laser, the highest nanorod concentration, and localized heat accumulation that intensified buoyancy-driven flow. The findings demonstrate that total efficiency is governed by a synergistic interplay between optical resonance, nanoparticle concentration, and macroscopic chamber design, revealing the system-level coupling between nanoscale plasmonic absorption and macroscale heat-transfer phenomena. The results provide a validated framework for tuning nanoscale plasmonic absorbers and optimizing thermal systems for applications requiring efficient light-to-heat conversion.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Calibrating hypersonic turbulence flow models with the HIFiRE-1 experiment using data-driven machine-learned models.

In this paper we study the efficacy of combining machine-learning methods with projection-based model reduction techniques for creating data-driven surrogate models of computationally expensive, high-fidelity physics models. Such surrogate models are essential for many-query applications e.g., engineering design optimization and parameter estimation, where it is necessary to invoke the high-fidelity model sequentially, many times. Surrogate models are usually constructed for individual scalar quantities. However there are scenarios where a spatially varying field needs to be modeled as a function of the model’s input parameters. Here we develop a method to do so, using projections to represent spatial variability while a machine-learned model captures the dependence of the model’s response on the inputs. The method is demonstrated on modeling the heat flux and pressure on the surface of the HIFiRE-1 geometry in a Mach 7.16 turbulent flow. The surrogate model is then used to perform Bayesian estimation of freestream conditions and parameters of the SST (Shear Stress Transport) turbulence model embedded in the high-fidelity (Reynolds-Averaged Navier–Stokes) flow simulator, using shock-tunnel data. The paper provides the first-ever Bayesian calibration of a turbulence model for complex hypersonic turbulent flows. We find that the primary issues in estimating the SST model parameters are the limited information content of the heat flux and pressure measurements and the large model-form error encountered in a certain part of the flow.

42 ENGINEERING↗