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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Shape memory polymers

New shape memory polymer compositions, methods for synthesizing new shape memory polymers, and apparatus comprising an actuator and a shape memory polymer wherein the shape memory polymer comprises at least a portion of the actuator. A shape memory polymer comprising a polymer composition which physically forms a network structure wherein the polymer composition has shape-memory behavior and can be formed into a permanent primary shape, re-formed into a stable secondary shape, and controllably actuated to recover the permanent primary shape. Polymers have optimal aliphatic network structures due to minimization of dangling chains by using monomers that are symmetrical and that have matching amine and hydroxl groups providing polymers and polymer foams with clarity, tight (narrow temperature range) single transitions, and high shape recovery and recovery force that are especially useful for implanting in the human body.

Wilson, Thomas S.↗
DOE OSTI2023

Evaluation of adsorption and mechanical strength of 13X zeolite mixtures with phyllosilicate binders using molecular dynamics simulation and positron annihilation spectroscopy

There is growing interest in developing zeolites with novel internal structures that have optimal adsorptive capacity and high mechanical strength, while offering advantages, such as being light weight. We integrate computational and experimental methods to explore the effect of binder/zeolite types, and weight percentages on the mechanical strength of 13X zeolite and adsorption capacities of N 2 , H 2 O, and CO 2 for additive manufacturing (AM) applications with the goal of maximizing both adsorption and strength. Zeolite 13X mixtures and phyllosilicate binders (either bentonite or kaolin) are combined using molecular dynamics (MD) simulations to create structures with various binder/zeolite weight percentages. Further, adsorption capabilities and mechanical strength are assessed using the grand canonical Monte Carlo (GCMC) and ReaxFF modules, respectively. Our modeling shows that an optimized zeolite/binder ratio for N 2 adsorption is around 15 wt% for kaolin and roughly 10 wt% for bentonite. The resulting parameters can be applied to facilitate macro-scale computational fluid dynamics (CFD) and finite element method (FEM) simulations of an AM zeolite structure. We also performed Positron Annihilation Lifetime Spectroscopy (PALS) measurements on zeolite samples to explore the effect of changes in the internal volume. The results show an inverse relationship between the free volume and the solid loading and adding a binder changes the morphology of the zeolite-binder compound and decreases open-volume area significantly.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: a tomographic measurement of cosmic structure growth and expansion rate based on optimal redshift weights

We develop a new method, which is based on the optimal redshift weighting scheme, to extract the maximal tomographic information of baryonic acoustic oscillations (BAO) and redshift space distortions (RSD) from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 14 quasar (DR14Q) survey. We validate our method using the Extended Zel’dovich mocks, and apply our pipeline to the eBOSS DR14Q sample in the redshift range of 0.8 < z < 2.2. We report a joint measurement of fσ8 and two-dimensional BAO parameters D A and H at four effective redshifts of z eff = 0.98, 1.23, 1.52, and 1.94, and provide the full data covariance matrix. Using our measurement combined with BOSS DR12, Main Galaxy Sample (MGS), and 6 degree Field Galaxy Survey (6dFGS) BAO measurements, we find that the existence of dark energy is supported by observations at a 7.4σ significance level. Combining our measurement with BOSS DR12 and Planck observations, we constrain the gravitational growth index to be γ = 0.580 ± 0.082, which is fully consistent with the prediction of general relativity. This paper is part of a set that analyses the eBOSS DR14 quasar sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Impact of n -Butylammonium Bromide on the Chemical and Electronic Structure of Double-Cation Perovskite Thin Films

2D/3D perovskite heterostructures have emerged as a promising material composition to reduce nonradiative recombination in perovskite-based LEDs and solar cells. Such heterostructures can be created by a surface treatment with large organic cations, for example, n-butylammonium bromide (BABr). To understand the impact of the BABr surface treatment on the double-cation (Cs 0.17 FA 0.83 Pb(I 0.6 Br 0.4 ) 3 ) (FA = formamidinium) perovskite thin film and further optimize the corresponding structures, an in-depth understanding of the chemical and electronic properties of the involved surfaces, interfaces, and bulk is required. We study the impact of the BABr treatment with a combination of surface-sensitive X-ray photoelectron spectroscopy and bulk-sensitive resonant inelastic soft X-ray scattering (RIXS). A quantitative analysis of the BABr-treated perovskite thin film shows a modified chemical perovskite surface environment of carbon, nitrogen, bromine, iodine, and lead, indicating that the treatment leads to a perovskite surface with a modified composition and bonding structure. With K-edge RIXS, the local environment at the nitrogen and carbon atoms is probed, allowing us to identify the presence of BABr in the perovskite bulk albeit with a modified bonding environment. This, in turn, identifies a "hidden parameter" for the optimization of the BABr treatment and overall performance of 2D/3D perovskite solar cell absorbers.

2D/3D perovskite heterostructure↗
DOE OSTI2026

Developing cathode infiltration processes for all-solid-state bilayer LLZO cells

To realize the bilayer architecture of lithium lanthanum zirconate (LLZO) for application in solid-state batteries (SSBs), the scaffold structure must be optimized, and effective cathode infiltration strategies must be established. In this study, we fabricate a modified bilayer LLZO using a sacrificial layer to enhance surface porosity, and systematically investigate various cathode infiltration techniques to fill the scaffold with oxide cathode active materials (CAM). Structural characterizations showed that the sacrificial layer significantly increased open surface porosity, enabling the surface of the scaffold to be filled with CAM. To further increase infiltration depth, applying vacuum or vibration was compared, with the full-depth infiltration achieved using a sonicator-based vibration. Full cells prepared using the modified bilayer LLZO and vibration-assisted technique demonstrated successful operation. This work demonstrates a practical and scalable approach for engineering bilayer LLZO structures and integrating oxide cathodes into porous scaffolds, offering a promising pathway toward high-performance solid-state batteries.

Bilayer↗
DOE OSTI2023

Computationally Efficient Control Co-Design Optimization Framework with Mixed-Fidelity Fluid and Structure Analysis: OpenTurbineCoDe (OTCD) - ARPA-E ATLANTIS Phase I Project (Final Technical Report)

The goal of the Department of Energy (DOE) Advanced Research Projects Agency-Energy (ARPA-E) Aerodynamic Turbines Lighter and Afloat with Nautical Technologies and Integrated Servo-control (ATLANTIS) Program is to develop new technologies for floating offshore wind turbines, or wind farms, using the discipline of control co-design (CCD.) In this context, our goal is to develop a computationally efficient optimization framework for design of floating offshore wind turbines. Our specific aim is to utilize high-fidelity structural, aerodynamic, aero-structural tools, and to derive control-oriented reduced- or low-order models directly from the high-fidelity tools. We proposed a mixed-fidelity modeling approach which means that we are also using low- and mid-fidelity tools when necessary. This research is conducted by a multidisciplinary team consisting of Rutgers University, University of Michigan, Brigham Young University, and the National Renewable Energy Laboratory (NREL). The computational framework, called OpenTurbineCoDe, is designed to integrate, where possible, traditional structural, aerodynamic, aeroelastic models (e.g., OpenFAST) and advanced control algorithms with higher fidelity simulation tools including Reynolds-averaged Navier–Stokes (RANS) solvers, and three-dimensional structural finite element solvers. All the high-fidelity tools used in this research provide numerically exact gradients to facilitate both efficient optimization and local linearization for control implementation.

17 WIND ENERGY↗
DOE OSTI2024

Active Learning for Metamaterial Optimization on HPC and QC Integrated Systems

Active learning algorithms, integrating machine learning, quantum computing and optics simulation in an iterative loop, offer a promising approach to optimizing metamaterials. However, these algorithms can face difficulties in optimizing highly complex structures due to computational limitations. High-performance computing (HPC) and quantum computing (QC) integrated systems can address these issues by enabling parallel computing. In this study, we develop an active learning algorithm working on HPC-QC integrated systems. We evaluate the performance of optimization processes within active learning (i.e., training a machine learning model, problem-solving with quantum computing, and evaluating optical properties through wave-optics simulation) for highly complex metamaterial cases. Our results showcase that utilizing multiple cores on the integrated system can significantly reduce computational time, thereby enhancing the efficiency of optimization processes. Therefore, we expect that leveraging HPC-QC integrated systems helps effectively tackle large-scale optimization challenges in general.

Kim, Seongmin↗
DOE OSTI2019

Noise analysis of optimized Ge/Ge{sub 1−x}Sn{sub x}/Ge p–n–p heterojunction phototransistors for long-wavelength optical receivers

Present literature investigates noise analysis and optimal design for Ge/Ge{sub 1−x}Sn{sub x}/Ge based p–n–p heterojunction phototransistors (HPT) for long-wavelength optical receivers. We calculate gain, noise powers, signal-to-noise ratio, absorption coefficient and optical responsivity of proposed GeSn-based HPT and investigate their dependence on various structural parameters to optimize the design. The proposed HPT incorporates Ge{sub 1−x}Sn{sub x} alloy in the base layer as the active layer, allow to extend the photo detection range from near infrared to mid-infrared to achieve a wide range of detection. The results show that the signal-to-noise ratio (SNR) is strongly dependent on the operating frequency and the introduction of Sn in the base layer can improve the signal-to-noise ratio in the high-frequency region. The calculated results also show that even in the presence of small defects and misfit dislocations at the heterointerfaces, high SNR is still achievable for the proposed structure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Optimal arrangements of 1,3-diphenylisobenzofuran molecule pairs for fast singlet fission

A simplified version of the frontier orbital model has been applied to pairs of C 2 , C 2v , C s , and C 1 symmetry 1,3-diphenylisobenzofuran rotamers to determine their best packing for fast singlet fission (SF). For each rotamer the square of the electronic matrix element for SF was calculated at 2.2 × 10 9 pair geometries and a few thousand most significant physically accessible local maxima were identified in the six-dimensional space of mutual arrangements. At these pair geometries, SF energy balance was evaluated, relative SF rate constants were approximated using Marcus theory, and the SF rate constant k SF was maximized by further optimization of the geometry of the molecular pair. The process resulted in 142, 67, 214, and 291 unique geometries for the C 2 , C 2v , C s , and C 1 symmetry molecular pairs, respectively, predicted to be superior to the C 2 symmetrized known crystal pair structure. Furthermore, these optimized pair geometries and their triplet biexciton binding energies are reported as targets for crystal engineering and/or covalent dimer synthesis, and as possible starting points for high-level pair geometry optimizations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Structural Validation at the NWTC Helps Improve Component Design and Increase System Reliability

Since 1990, the National Wind Technology Center (NWTC) at the National Renewable Energy Laboratory (NREL) has validated more than 150 wind turbine blades, as well as blades and components for marine energy devices. Researchers at the NWTC can experimentally validate full-scale and subcomponent articles, conduct data analyses, and provide engineering expertise to optimize design practices. Structural evaluation of turbine blades enables designers, manufacturers, and owner operators t o assess designs and structural performance under specific extreme loading and dynamic conditions. Rigorous structural validation can reveal design and manufacturing problems at an early state of development that lead to improvements in component design and increase system reliability.

17 WIND ENERGY↗
DOE OSTI2025

Micropolar deep material network

This study extends the Deep Material Network (DMN), a physics-informed machine learning framework, to predict the homogenized mechanical response of composite materials with micropolar (Cosserat-type) constitutive behavior. This extension incorporates microstructure-dependent size effects, enabling accurate, efficient, and size-aware predictions for composites with complex internal architectures. While traditional, direct numerical simulation micropolar models effectively capture size effects by introducing extra local degrees of freedom, they bring significant computational challenges, particularly for multiscale analyses relevant to engineering applications. The micropolar DMN developed in this paper achieves high accuracy while significantly reducing computation time compared to micropolar direct numerical simulations. This advancement enables multiscale analyses and parameter studies that were previously impractical, such as high-cycle fatigue simulations and comprehensive investigations of internal length scale effects notably in size-dependent plastic response and the optimization of lattice structures. By uniting microstructure-sensitive modeling, physics-driven learning, and scalable surrogate modeling, the micropolar DMN paves the way for accelerated material design, large-scale parametric studies, and the reliable incorporation of size-dependent effects across a wide range of engineering applications, including optimization and next-generation composite design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Magneto-Mechanical Optimization of Cross-Sections for $ \text{cos}(\theta)$Accelerator Magnets

The cross-section design of cos (θ) superconducting magnets is historically developed in a two-step process: initially, the coil geometry is defined on the basis of magnetic optimizations; then, the structure is designed around the coil. The first step searches for the best coil cross-section maximizing the magnetic field, margin, field quality and conductor efficiency. The latter step aims at limiting the coil stresses and deformations. However, the coil design, defined with the initial magnetic optimization, can influence the mechanical behaviour of the magnet, altering, for example, the peak stress during operation. As the critical current is a function of the applied strain, the mechanical implications of the coil cross-section design can limit the achievable performance. In this paper we propose an integrated optimization process that targets the peak stress on the conductor in addition to the magnetic objectives. Here the results are presented for a sample high-field Nb 3 Sn dipole: a 4-layer design aiming at ultimate conductor performance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Parallelization and Performance Portability in Hydrodynamics Codes

With the eve of Exascale computing, performance and portability are at the forefront of all scientific codes. Adding more cores and more energy to a system is no longer a sustainable way to achieve performance, and extra effort must now be made to improve performance in all areas of code and code development. Using hydrodynamic codes as a basis, this work explores numerous techniques to achieve performance in different ways. Adaptive mesh refinement (AMR) is a necessary technique to improve memory optimization in mesh-based simulations. However it is invasive and conventionally difficult to integrate into existing applications, so we present a new branch of AMR to create a smooth transition to these optimizations, which not only improves performance, but also greatly reduces developer effort. We introduce the concept of this improvement as Phantom-Cell AMR, and assess theoretically the improvements, as well as present an application of its use. Other work included involves and investigation into an efficient data structure that ensures optimal memory layout for cache performance, with a target of making codes performant and portable across all architectures. All of the work targets both performance and portability, not just on CPU hardware, but specifically across GPU architectures. Parallel performance is key to all of the methods presented, but the research makes a great effort to improve the portability of all applications to prepare for current high performance computing systems and those on the horizon.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Adsorption of Iron(III) and Copper(II) by Bacterial Cellulose from Rhodococcus sp. MI 2

Modified cellulose from the pellicle produced by Rhodococcus sp. MI 2 was more efficient at removing Fe(III) and Cu(II) from aqueous solution than similarly modified cellulose from Komagataeibar xylinus TISTR 998. This study first describes the modification of the cellulose to produce mercerized bacterial cellulose (MBC), phosphorylated bacterial cellulose (PBC), acid–base cellulose and diethylenetriamine bacterial cellulose (EABC). Their efficacy as adsorbents to adsorb Fe(III) and Cu(II) was then determined. In aqueous solution at pH 4 at initial Fe(III) concentration of 20 mg/L, PBC reached adsorption equilibrium within 195 min. At pH 5 in an initial Cu(II) concentration of 75 mg/L, EABC reached adsorption equilibrium within 210 min. Molecular structures and chemical bonds were examined by Fourier transform infrared spectroscopy (FT-IR) and physical morphologies by scanning electron microscopy. The adsorption kinetics of MBC, PBC and EABC showed good agreement with the proposed pseudo-second order model and the adsorption isotherm was best described by the Freundlich model. Our study determined optimal conditions, molecular structures, physical morphologies and adsorption kinetics. The cellulose produced by the new strain Rhodococcus sp. MI 2 was highly efficient at adsorbing and removing metal ions from aqueous solution.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Genetic algorithm-based optimisation of the few-group structure for lead fast reactors analysis

The optimal choice of the few-group structure for full-core transient analyses is still an open issue in reactor physics, especially for fast system like the lead fast reactor. One possible approach to select the group boundaries is represented by heuristic search algorithms, such as evolutionary ones. In this paper, a genetic algorithm coupled with the SIMMER code is employed to determine optimized six-group boundaries for the analysis of the ALFRED reactor. The Serpent Monte Carlo code is adopted to produce both the fine-group cross section library and the fine-group flux, used as a figure of merit to drive the genetic optimisation. The results show that the algorithm is indeed able to find satisfactory solutions that comply with the set objectives and can be reasonably interpreted in light of the underlying physics of the considered core. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Water alternative gas (WAG) optimization for a heterogeneous Brazilian pre-salt carbonate reservoir

Water alternating gas (WAG) is a cyclical process that involves alternating water and gas injections with the primary goal to improve sweep efficiency by maintaining initial high pressure, slowing water and gas breakthrough, and lowering oil viscosity. The objective of this work is to apply and optimize a WAG strategy on a carbonate field with light oil, compare it to the initially planned water-flooding strategy, and investigate the capability of WAG to improve field production. In this research, a compositional reservoir simulator was used to model a WAG process by injecting produced gas into the reservoir, using the same well structure as an optimized water-flooding strategy. Subsequently, a WAG strategy was created, optimizing the number and locations of wells, to facilitate a comparative analysis of the two recovery methods. The WAG optimization involved a detailed assessment of variables such as bottom hole pressure (BHP), WAG cycle duration, maximum gas oil ratio (GOR), and well positioning, to achieve a high net present value (NPV). The study focuses on the application of WAG optimization modeling in unconventional reservoirs, specifically pre-salt carbonate reservoirs, and investigates its implications on production strategy and forecast, emphasizing its potential for maximizing NPV and oil recovery in a recently producing field. The results showed that WAG improved reservoir performance when compared to water injection and produced a greater amount of oil. This solution showed potential to be tested under uncertainties (reservoir heterogeneity, faults, fractures, karsts, vugs, etc.) as future steps.

54 ENVIRONMENTAL SCIENCES↗