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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Shear localization in metallic materials at high strain rates

Three factors govern adiabatic shear localization: strain hardening (or softening), strain-rate hardening, and thermal softening. It is typically associated with large shear strains (>1), high strain rates (10 3 –10 7 s –1 ), and high temperatures (40–100% of melting point), all of which happen within narrow regions with widths of about 1–200 μm. It is often an undesirable phenomenon, leading to failure, but there are situations where it is desirable, e. g., the generation of machining chips. Here, we review the development of both theoretical and experimental achievements, from the initiation of shear bands to their propagation with emphasis on three aspects: novel experimental techniques, novel materials, and nano/microstructural effects. The principal characteristics of adiabatic shear bands in metallic materials at the nano- and micro-scale are described. Bands that were formerly identified as transformed actually consist of nanocrystalline/ultrafine grains. These grains result from the breakup of the microstructure by a rotational recrystallization process. The evolution of the microstructure inside shear bands and their interactions for hcp, bcc, and fcc alloys, high-entropy alloys, nanocrystalline alloys, and metallic glasses are analyzed mechanistically. In conclusion, the gaps in the field and opportunities for future research are identified. Modern experimental characterization and computational techniques enable a more profound and predictive understanding of adiabatic shear localization and its avoidance in advanced materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multi-level optimization with the koopman operator for data-driven, domain-aware, and dynamic system security

Cyber-Physical Systems (CPSs) like the power grid are critically important but also increasingly vulnerable; ensuring reliable system operation in the face of disruptions is becoming more and more challenging. Multi-Level Optimization (MLO) is a powerful way to model adversarial interactions, which naturally makes it applicable to studying CPS security. However, MLO typically does not address underlying system dynamics, and incorporating nonlinear dynamics is generally infeasible. In this paper, we show how to combine MLO with the Koopman Operator (KO) to remedy this. The KO maps nonlinear dynamics to a lifted space in which those dynamics are linear, thus making it ideal for use with MLO. Moreover, the structure of the KO also provides convenient ways to incorporate domain knowledge into the data-driven process of learning the KO representation of a given system. Here we then demonstrate the use of MLO-KO on a small example problem taken from the power grid domain, discuss the scalability and computational cost of MLO-KO, and identify future research directions for this work.

42 ENGINEERING↗
DOE OSTI2018

Assessing High-Throughput Descriptors for Prediction of Transparent Conductors

The growth of materials databases has offered significant quantities of data to mine for new energy materials using high-throughput screening methodologies. One application of interest to energy and optoelectronics is the prediction of new high performing p-type transparent conductors (TCs). Yet, screening methods for such materials have never been validated over the breadth of computed materials properties. In this study, we compile an experimental data set of 74 bulk crystal structures corresponding to known state-of-the-art n-type and p-type TCs and compute a series of corresponding computational descriptor properties. Our goals are to (1) compare computational descriptors to experimentally demonstrated properties of real materials in the data set, (2) determine the ability of ground state, density functional theory (DFT)-based computational screening methodologies to identify these experimentally realized TCs, and (3) use this understanding to estimate reasonable screening cutoffs for four commonly used descriptors. First, stability calculations demonstrate that most materials in the data set have an energy above the convex hull ( E hull ) of <100 meV/atom, and we also propose a Pourbaix analysis technique to estimate moisture stability. Second, we find a lenient cutoff for the DFT PBE band gap of 0.5 eV is sufficient to include a majority of the wide gap candidates and exclude narrow gap compounds. Next, the effective mass, m *, is found to correlate weakly to conductivity in the p-type materials as compared with n-type materials, which may motivate an increase in the m * cutoff as well. Lastly, we perform an uncertainty analysis and literature comparison for the branch point energy (BPE), a qualitative descriptor for dopability. We discover the BPEs of most n-type materials to lie near the conduction band and those of most p-type materials to lie at midgap; this is a significant distinction, implying BPE to be a more definitive descriptor for n-type TC materials. By assessing the validity of this simple screening methodology via comparing experimental data to computational descriptors, we aim to motivate and strengthen future materials discovery efforts in the field of transparent conductors and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Bayesian Model Averaging for Ensemble-Based Estimates of Solvation Free Energies

This paper applies the Bayesian Model Averaging (BMA) statistical ensemble technique to estimate small molecule solvation free energies. There is a wide range methods for predicting solvation free energies, ranging from empirical statistical models to {\it ab initio} quantum mechanical approaches. Each of these methods are based on a set of conceptual assumptions that can affect a method's predictive accuracy and transferability. Using an iterative statistical process, we have selected and combined solvation energy estimates using an ensemble of 17 diverse methods from the SAMPL4 blind prediction study to form a single, aggregated solvation energy estimate. The ensemble design process evaluates the statistical information in each individual method as well as the performance of the aggregate estimate obtained from the ensemble as a whole. Methods that possess minimal or redundant information are pruned from the ensemble and the evaluation process repeats until aggregate predictive performance can no longer be improved. We show that this process results in a final aggregate estimate that outperforms all individual methods by reducing estimate errors by as much as 91% to 1.2 kcal/mol accuracy. We also compare our iterative refinement approach to other statistical ensemble approaches and demonstrate that this iterative process reduces estimate errors by as much as 61%. This work provides a new approach for accurate solvation free energy prediction and lays the foundation for future work on aggregate models that can balance computational cost with predictive accuracy.

solvation, Bayesian model averaging, Electrostatic↗
DOE OSTI2019

Electronic Structure and Optical Properties of Designed Photo-Efficient Indoline-Based Dye-Sensitizers with D–A–π–A Framework

Seven D–A–π–A-based indoline (IND) dyes that were designed via quantitative-structure–property relationship modeling have been comprehensively investigated using computational approaches to evaluate their prospect of application in future dye-sensitized solar cells (DSSCs). An array of optoelectronic properties of the isolated dye and dyes adsorbed on a TiO 2 cluster that simulates the semiconductor were explored by density functional theory (DFT) and time-dependent DFT methods. Light absorption spectra, vertical dipole moment, shift of the conduction band of semiconductor, excited state lifetime, driving force of electron injection, photostability of the excited state, and exciton binding energy were computed. Our study showed that the presence of an internal acceptor such as pyrido[3,4-b]pyrazine (pyrazine) would influence greater the open circuit voltage (VOC), compared to the benzothiadiazole moiety. Considering the balance between the VOC and J SC (short circuit current) along with the all calculated characteristics, the IND3, IND5, and IND10 are the most suited among the designed dyes to be used as potential candidates for the photo-efficient DSSCs. Finally, the present study provides the results of rational molecular design followed by exploration of photophysical properties to be used as a valuable reference for the synthesis of photo-efficient dyes for DSSCs.

14 SOLAR ENERGY↗
DOE OSTI2017

Intrinsic magnetism and spontaneous band gap opening in bilayer silicene and germanene

It has been long sought to create magnetism out of simple non-magnetic materials, such as silicon and germanium. Here we show that intrinsic magnetism exists in bilayer silicene and germanene with no need to cut, etch, or dope. Unlike bilayer graphene, strong covalent interlayer bonding formed in bilayer silicene and germanene breaks the original π-bonding network of each layer, leaving the unbonded electrons unpaired and localized to carry magnetic moments. These magnetic moments then couple ferromagnetically within each layer while antiferromagnetically across two layers, giving rise to an infinite magnetic sheet with structural integrity and magnetic homogeneity. Furthermore, this unique magnetic ordering results in fundamental band gaps of 0.55 eV and 0.32 eV for bilayer silicene and germanene, respectively. The integration of intrinsic magnetism and spontaneous band gap opening makes bilayer silicene and germanene attractive for future nanoelectronics as well as spin-based computation and data storage.

Wang, Xinquan↗
DOE OSTI2025

Integrating magnetic Co-nanopillars in a NbN-based VAN thin film as a multifunctional hybrid metamaterial

NbN thin films are considered as a promising alternative candidate to conventional Al superconducting electrodes for Josephson junction devices, superconducting qubits and quantum logic circuits. Herein, by co-growing ferromagnetic Co with superconducting NbN, self-assembled NbN–Co vertically aligned nanocomposite (VAN) thin films have been successfully deposited on a MgO substrates, with NbN in its cubic superconducting phase. The obtained VAN metamaterials exhibit epitaxial growth of NbN with uniformly dispersed Co nanoplates. Further physical property characterization reveals that the NbN–Co VAN presents ferromagnet properties with strong out-of-plane magnetic anisotropy and optical anisotropy. This hybrid metamaterial system could find future applications in superconducting spintronic devices and quantum computing devices.

Zhang, Yizhi [Purdue Univ., West Lafayette, IN (Un↗
DOE OSTI2020

A Customizable Metric to Provide a Comprehensive Picture of the Mobility Potential of a Location

Accessibility in a geo-spatial context refers to the ease of reaching a variety of opportunities from a given location. Accessibility theories (and resulting metrics) have traditionally focused on quantifying access to specific opportunities (such as jobs), or focused on specific modes (such as car, bike, etc.). Such approaches often fall short of providing a comprehensive picture of the true accessibility potential of a location as a combination of multiple modes to multiple types of destinations. Addressing this drawback, a novel metric labeled the ‘Mobility Energy Productivity (MEP) Metric’ was developed at the National Renewable Energy Laboratory to quantify the mobility potential of a location to connect people to goods, services, and employment using a variety of modes, while accounting for time, energy, and affordability. The MEP metric has been integrated with advance travel behavior models to compute the changes in mobility potential for various future scenarios, such as introduction of automated vehicles, and/or electric vehicles—but does so at the aggregate, or average-citizen level. The MEP in its initial iteration is not customized to the particular socio-economic contingents, or even to an individual whose modal availability or pattern of trip making may substantially differ from the average. Addressing this gap, this research effort extends the MEP framework from a static state to a more tailored and dynamic state, one in which an individual, or group can customize the metric for their unique characteristics, such as modes, activity patterns, and time-of-day preferences. The extended MEP metric framework can now be integrated to assess the customized mobility energy productivity of an individual.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2022

Image feature extraction and galaxy classification: a novel and efficient approach with automated machine learning

ABSTRACT In this work, we explore the possibility of applying machine learning methods designed for 1D problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly steps, such as the point spread function deconvolution and the training and application of complex Convolutional Neural Networks of thousands or even millions of parameters. In our approach, we extract features from the galaxy images by analysing the elliptical isophotes in their light distribution and collect the information in a sequence. The sequences obtained with this method present definite features allowing a direct distinction between galaxy types. Then, we train and classify the sequences with machine learning algorithms, designed through the platform Modulos AutoML. As a demonstration of this method, we use the second public release of the Dark Energy Survey (DES DR2). We show that we are able to successfully distinguish between early-type and late-type galaxies, for images with signal-to-noise ratio greater than 300. This yields an accuracy of $86{{\ \rm per\ cent}}$ for the early-type galaxies and $93{{\ \rm per\ cent}}$ for the late-type galaxies, which is on par with most contemporary automated image classification approaches. The data dimensionality reduction of our novel method implies a significant lowering in computational cost of classification. In the perspective of future data sets obtained with e.g. Euclid and the Vera Rubin Observatory, this work represents a path towards using a well-tested and widely used platform from industry in efficiently tackling galaxy classification problems at the peta-byte scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Coincidence of collective relaxation anomaly and specific heat peak in a bulk metallic glass-forming liquid

The study of multicomponent metallic liquids' relaxational behavior is still the key to understanding and improving the glass-forming abilities of bulk metallic glasses. Here, we report measurements of the collective relaxation times in a melted bulk metallic glass (LM601Zr 51 Cu 36 Ni 4 Al 9 ) in the kinetic regime (Q: 1.5–4.0Å –1 ) using quasielastic neutron scattering. The results reveal an unusual slope change in the Angell plots of this metallic liquid's collective relaxation time around 950°C, beyond the material's melting point. Measurement of specific heat capacity also reveals a peak around the same temperature. Adams-Gibbs theory is used to rationalize the coincidence, which motivates more careful experimental and computational studies of the metallic liquids in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantum real-time evolution using tensor renormalization group methods

We introduce an approach for approximate real-time evolution of quantum systems using tensor renormalization group (TRG) methods originally developed for imaginary time. We use higher-order TRG to generate a coarse-grained time evolution operator for a 1+1⁢D transverse Ising model with a longitudinal field. We show that the standard tensor norm used for the singular value decomposition-based truncation is degenerate and propose an alternate method to discriminate. We show that it is effective and efficient in evolving Gaussian wave packets for one and two particles in the disordered phase, while ordered phase behavior is more challenging to capture. We compare our algorithm with local simulators for universal quantum computers and discuss possible benchmarking in the near future.

lattice gauge theory↗
DOE OSTI2019

Beyond Hosting Capacity: Using Shortest-Path Methods to Minimize Upgrade Cost Pathways

This paper presents a graph-based forward looking algorithm applied to distribution planning in the context of distributed photovoltaic penetration. We study the target hosting capacity problem where the objective is to find the least-cost sequence of system upgrades to reach a predefined hosting capacity target value. We show that commonly used short-term cost minimization approaches often lead to suboptimal long-term solutions. By comparing our method against such myopic techniques on real distribution systems, we show that our algorithm is able to reduce the overall integration costs by looking at future decisions. Because hosting capacity is hard to compute, this problem requires efficient methods to search the space. We demonstrate that heuristics using domain-specific knowledge can be efficiently used to improve the algorithm performance, such that real distribution systems can be studied.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Atomically Thin CBRAM Enabled by 2-D Materials: Scaling Behaviors and Performance Limits

Reducing the energy and power dissipation of conductive bridge random access memory (CBRAM) cells is of critical importance for their applications in future Internet of Things (IoT) device and neuromorphic computing platforms. Atomically thin CBRAMs enabled by 2-D materials are studied theoretically by using 3-D kinetic Monte Carlo simulations together with experimental characterization. The results indicate the performance potential of attoJoule energy dissipation for intrinsic filament formation and a filament size of a single atomistic chain in such a CBRAM cell. The atomically thin CBRAM cells also show qualitatively different features from conventional CBRAM cells, including complete rupture of the filament in the reset stage and comparable forming and set voltages. The scaling and variability of the CBRAM cells down to sub-nanometer size of the switching layer as realized in the experiment are systematically studied, which indicates performance improvement and increased relative variability as the switching layer scales down. Finally, the results establish the ultimate limits of the size and energy scaling for CBRAM cells and illustrate the unique application of 2-D materials in ultralow power memory devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Improving the efficiency of Rubisco by resurrecting its ancestors in the family Solanaceae

Plants and photosynthetic organisms have a remarkably inefficient enzyme named Rubisco that fixes atmospheric CO 2 into organic compounds. Understanding how Rubisco has evolved in response to past climate change is important for attempts to adjust plants to future conditions. In this study, we developed a computational workflow to assemble de novo both large and small subunits of Rubisco enzymes from transcriptomics data. Next, we predicted sequences for ancestral Rubiscos of the (nightshade) family Solanaceae and characterized their kinetics after coexpressing them inEscherichia coli. Predicted ancestors of C 3 Rubiscos were identified that have superior kinetics and excellent potential to help plants adapt to anthropogenic climate change. Our findings also advance understanding of the evolution of Rubisco’s catalytic traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Statistical Regularities of Formation of a Main Crack in a Structurally Inhomogeneous Material under Various Deformation Conditions

The peculiarities of the formation of a main crack in the Westerly granite samples under quasistatic uniaxial compression without any lateral upthrust have been studied using the data of acoustic emission (AE) and X-ray computer microtomography (CT). The multifractal analysis of pauses between acoustic emission events and the analysis of the energy distribution functional forms of the AE signal have been performed. According to the computer tomography data, defects form only near a future main crack; i.e., no stage of disperse accumulation of defects over entire sample volume has been revealed. Two stages of the main crack formation have been observed: the first stage is characterized by an exponential energy distribution of AE signals and the second stage is characterized by a power low of the AE signal energy distribution. The multifractal analysis of the pauses between neighboring AE signals demonstrate the transition from the multifractal dynamics of the acoustic emission to the monofractal dynamics when approaching a fracture moment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

My Spring with Graphene

Graphene is a two-dimensional structure, one atom thick, with many uses in the world of technology. It has many useful electrical properties, is a very strong and durable material, and can be used to protect different types of substances. The world would be able to use these properties to further the strength of cars, protect metals from oxidation, increase computer speeds, use to improve superconductors, and whatever future uses that scientist invent or discover. We sought to optimize the growth and transfer of graphene. We grew graphene on copper foils by heating the foil in a furnace, and having various gases flow through a tube, where the copper foil was placed. We varied some of the concentrations of gases, along with having different times for heating the copper foil, different times for graphene growth, or a combination of the two. The focus of our experiment was to specifically grow monolayer single crystal graphene, which means that we do not want multiplayers of graphene, and do not want multiple crystals growing to form a bigger crystal. Our goal was to grow large single crystals from the growth experiment. We used a few different types of transfer methods that ranged from: using heat and pressure to press the graphene on different materials, using a polymer to cover the graphene with a method to destroy the copper, but leave the graphene and polymer intact, and using a type of heat tape with a combination of varying pressures to transfer the graphene, and then destroy the copper foil. To discover if we grew graphene we used different techniques involving lasers and microscopes to take different types of measurements. Discovering the best way of growing and transferring graphene will help with managing the cost of the future uses of graphene.

36 MATERIALS SCIENCE↗
DOE OSTI2018

NEAMS Workbench 1.0 Beta

The mission of the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems. This is accomplished using computing architectures that range from laptops to leadership-class facilities. The NEAMS Workbench is a new initiative that will facilitate the transition from conventional tools to high-fidelity tools by providing a common user interface for model creation, review, execution, output review, and visualization for integrated codes. The Workbench can use common user input, including engineering scale specifications that are expanded into application-specific input requirements through the use of customizable templates. The templating process enables multi-fidelity analysis of a system from a common set of input data. Additionally, the common user input processor can provide an enhanced alternative application input that provides additional conveniences over the native input, especially for legacy codes. Expansion of the integrated codes and application templates available in the Workbench will broaden the NEAMS user community and will facilitate system analysis and design. Current and planned capabilities of the NEAMS Workbench are detailed here.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

HEP Software Foundation Community White Paper Working Group - Detector Simulation

A working group on detector simulation was formed as part of the high-energy physics (HEP) Software Foundation's initiative to prepare a Community White Paper that describes the main software challenges and opportunities to be faced in the HEP field over the next decade. The working group met over a period of several months in order to review the current status of the Full and Fast simulation applications of HEP experiments and the improvements that will need to be made in order to meet the goals of future HEP experimental programmes. The scope of the topics covered includes the main components of a HEP simulation application, such as MC truth handling, geometry modeling, particle propagation in materials and fields, physics modeling of the interactions of particles with matter, the treatment of pileup and other backgrounds, as well as signal processing and digitisation. The resulting work programme described in this document focuses on the need to improve both the software performance and the physics of detector simulation. The goals are to increase the accuracy of the physics models and expand their applicability to future physics programmes, while achieving large factors in computing performance gains consistent with projections on available computing resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗