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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Prospects of Nanoscience with Nanocrystals: 2025 Edition

Abstract Nanocrystals (NCs) of various compositions have made important contributions to science and technology, with their impact recognized by the 2023 Nobel Prize in Chemistry for the discovery and synthesis of semiconductor quantum dots (QDs). Over four decades of research into NCs has led to numerous advancements in diverse fields, such as optoelectronics, catalysis, energy, medicine, and recently, quantum information and computing. The last 10 years since the predecessor perspective “Prospect of Nanoscience with Nanocrystals” was published in ACS Nano have seen NC research continuously evolve, yielding critical advances in fundamental understanding and practical applications. Mechanistic insights into NC formation have translated into precision control over NC size, shape, and composition. Emerging synthesis techniques have broadened the landscape of compounds obtainable in colloidal NC form. Sophistication in surface chemistry, jointly bolstered by theoretical models and experimental findings, has facilitated refined control over NC properties and represents a trusted gateway to enhanced NC stability and processability. The assembly of NCs into superlattices, along with two-dimensional (2D) photolithography and three-dimensional (3D) printing, has expanded their utility in creating materials with tailored properties. Applications of NCs are also flourishing, consolidating progress in fields targeted early on, such as optoelectronics and catalysis, and extending into areas ranging from quantum technology to phase-change memories. In this perspective, we review the extensive progress in research on NCs over the past decade and highlight key areas where future research may bring further breakthroughs.

Chemistry↗
DOE OSTI2019

Reverse-Mode Algorithmic Differentiation of an OpenMP-Parallel Compressible Flow Solver

y Reverse-mode algorithmic differentiation (AD) is an established method for obtaining adjoint derivatives of computer simulation applications. In computational fluid dynamics (CFD), adjoint derivatives of a cost function output such as drag or lift with respect to design parameters such as surface coordinates or geometry control points are a key ingredient for shape optimization, uncertainty quantification and flow control. The computational cost of CFD applications and their derivatives makes it essential to use high-performance computing hardware efficiently, including multi- and many-core architectures. Nevertheless, OpenMP is not supported in most AD tools, and previously shown methods achieve poor scalability of the derivative code. We present the AD of an OpenMP-parallelized finite volume compressible flow solver for unstructured meshes. Our approach enables us to reuse the parallelization of the original code in the computation of adjoint derivatives. The method works by identifying code segments that can be differentiated in reverse-mode without changing their memory access pattern. The OpenMP parallelization is integrated into the derivative code during the build process in a way that is robust to modifications of the original code and independent of the OpenMP support of the differentiation tool. We show the scalability of our adjoint CFD solver on test cases ranging from thousands to millions of finite volume mesh cells on CPUs with up to 16 threads as well as on an Intel XeonPhi card with 236 threads. We demonstrate that our approach is more practical to implement for production-sized CFD codes and produces more efficient adjoint derivative code than previously shown AD methods.

Huckelheim, Jan↗
NASA NTRS2003

Some Advanced Concepts in Discrete Aerodynamic Sensitivity Analysis

An efficient incremental iterative approach for differentiating advanced flow codes is successfully demonstrated on a two-dimensional inviscid model problem. The method employs the reverse-mode capability of the automatic differentiation software tool ADIFOR 3.0 and is proven to yield accurate first-order aerodynamic sensitivity derivatives. A substantial reduction in CPU time and computer memory is demonstrated in comparison with results from a straightforward, black-box reverse-mode applicaiton of ADIFOR 3.0 to the same flow code. An ADIFOR-assisted procedure for accurate second-rder aerodynamic sensitivity derivatives is successfully verified on an inviscid transonic lifting airfoil example problem. The method requires that first-order derivatives are calculated first using both the forward (direct) and reverse (adjoinct) procedures; then, a very efficient noniterative calculation of all second-order derivatives can be accomplished. Accurate second derivatives (i.e., the complete Hesian matrices) of lift, wave drag, and pitching-moment coefficients are calculated with respect to geometric shape, angle of attack, and freestream Mach number.

Taylor, Arthur C., III↗
DOE OSTI2019

Stable Metallic Enrichment in Conductive Filaments in TaO x –Based Resistive Switches Arising from Competing Diffusive Fluxes

Oxide–based resistive–switching devices hold promise for solid–state memory technology. Information encoding is accomplished by electrically switching the device between two nonvolatile states with low and high resistance states (LRS/HRS). It is generally accepted that the change between these states is due to the motion of oxygen vacancies forming a continuous (LRS) or gapped (HRS) filament between the electrodes. Direct assessments of filaments are rare due to their small size and the difficulty of locating the filament. Electron microscopy experiments reveal the filament structure and chemistry in TaO 2.0 ± 0.2 –based 150 × 150 nm 2 devices with cross–sectional geometry after forming with power dissipation lower than 1 mW. The filaments appear to be roughly hourglass–shaped with a diameter of less than 10 nm and are composed of Ta–rich and O–poor mostly amorphous material with local compositions as Ta–rich as TaO 0.4 . The as–formed HRS has a gap up to 10 nm wide located next to the anode and composed of nearly stoichiometric TaO 2.5 . The tantalum and oxygen distribution is consistent with filaments formed by the motion of both Ta and O driven by temperature gradients (Soret effect) and an electric field. As a result, this interpretation points towards a new compact model of resistive–switching devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Editorial: Generation, detection and manipulation of skyrmions in magnetic nanostructures

Due to their compact shape and small size down to a few nanometers, good thermal stability, and low driven current density, magnetic skyrmions have become promising building blocks for high-density storage and fast information processing applications. In a dozen years, this field dubbed as skyrmionics has attracted significant attention for exploring fundamental physics as well as for practical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effect of Synthesis Temperature on Structural, Optical, and Magnetic Properties of ZnO Nanoparticles Synthesized by Combustion Method

ZnO nanoparticles at different temperatures were synthesized by using the combustion method. The effect of synthesis temperature on the properties of the nanoparticles was studied by using XRD, FESEM, EDS, TEM, photoluminescence (PL), Raman, diffuse reflectance spectra (DRS), and VSM characterization techniques. The XRD results reveal that the grown nanoparticles have a hexagonal wurtzite structure without any impurities and agreed with EDS results. FESEM and TEM micrographs show that the ZnO nanoparticles possess a spherical shape with agglomeration free, and the size increases with increase of synthesis temperature. From DRS studies, it was noticed that the band gap decreases with increase of synthesis temperature. In PL studies, blue peak at 465 nm may be due to defect-related transitions. A sharp intense peak in Raman spectra at 485 cm{sup −1} represents E{sub 2}H mode is a characteristic of a hexagonal wurtzite structure. The magnetic studies show that the magnetization decreases from 0.0172 to 0.0042 emu/g as the synthesis temperature increases from 400 to 550 °C. ZnO synthesized at 500 °C has a large squareness ratio. These materials are potential candidates for memory devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2001

Some Advanced Concepts in Discrete Aerodynamic Sensitivity Analysis

An efficient incremental-iterative approach for differentiating advanced flow codes is successfully demonstrated on a 2D inviscid model problem. The method employs the reverse-mode capability of the automatic- differentiation software tool ADIFOR 3.0, and is proven to yield accurate first-order aerodynamic sensitivity derivatives. A substantial reduction in CPU time and computer memory is demonstrated in comparison with results from a straight-forward, black-box reverse- mode application of ADIFOR 3.0 to the same flow code. An ADIFOR-assisted procedure for accurate second-order aerodynamic sensitivity derivatives is successfully verified on an inviscid transonic lifting airfoil example problem. The method requires that first-order derivatives are calculated first using both the forward (direct) and reverse (adjoint) procedures; then, a very efficient non-iterative calculation of all second-order derivatives can be accomplished. Accurate second derivatives (i.e., the complete Hessian matrices) of lift, wave-drag, and pitching-moment coefficients are calculated with respect to geometric- shape, angle-of-attack, and freestream Mach number

Taylor, Arthur C., III↗
DOE OSTI2020

Perpendicular magnetic anisotropy in half-metallic thin-film Co 2 CrAl

Magnetocrystalline anisotropy (MCA) is one of the key parameters investigated in spin-based electronics (spintronics), e.g. for memory applications. Here, we employ first-principles calculations to study MCA in thin film full Heusler alloy Co 2 CrAl. This material was studied in the past, and has been reported to exhibit half-metallic electronic structure in bulk geometry. In our recent work, we showed that it retains a 100% spin-polarization in thin-film geometry, at CrAl atomic surface termination. Here, we show that the same termination results in a perpendicular magnetic anisotropy, while Co surface termination not only destroys the half-metallicity, but also results in in-plane magnetization orientation. In addition, for films thicker than around 20 nm the contribution from magnetic shape anisotropy may become decisive, resulting in in-plane magnetization orientation. To the best of our knowledge, this is one of the first reports of half-metallic thin-film surfaces with perpendicular magnetic anisotropy. Furthermore, this result may be of interest for potential nano-device applications, and may stimulate a further experimental study of this and similar materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Antiferromagnetic-ferromagnetic phase domain development in nanopatterned FeRh islands

The antiferromagnetic-to-ferromagnetic phase transition in B2-ordered FeRh is imaged in laterally confined nanopatterned islands using photoemission electron microscopy with x-ray magnetic circular dichroism contrast. The resulting magnetic images directly detail the progression in the shape and size of the FM phase domains during heating and cooling through the transition. In 5-μm-square islands this domain development during heating is shown to proceed in three distinct modes - nucleation, growth, and merging - each with subsequently greater energy costs. In 0.5-μm islands, which are smaller than the typical final domain size, the growth mode is stunted and the transition temperature is found to be reduced by 20 K. The modification to the transition temperature is found by high-resolution scanning transmission electron microscopy to be due to a 100-nm chemically disordered edge grain present as a result of ion implantation damage during the patterning. FeRh has unique possibilities for magnetic memory applications; the inevitable changes to its magnetic properties due to subtractive nanofabrication will need to be addressed in future work in order to progress from sheet films to suitable patterned devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Anisotropic MagnetoMemristance

Abstract In the last decade, nanoscale resistive devices with memory have been the subject of intense study because of their possible use in brain-inspired computing. However, operational endurance is one of the limiting factors in the adoption of such technology. For this reason, we discuss the emergence of current-induced memristance in magnetic materials, known for their durability. We show analytically and numerically that a single ferromagnetic layer can possess GHz memristance, due to a combination of two factors: a current-induced transfer of angular momentum (Zhang-Li torque) and the anisotropic magnetoresistance (AMR). We term the resulting effect the anisotropic magneto-memristance (AMM). We connect the AMM to the topology of the magnetization state, within a simple model of a one-dimensional annulus-shaped magnetic layer, confirming the analytical results with micromagnetic simulations for permalloy. Our results open a new path towards the realization of single-layer magnetic memristive devices operating at GHz frequencies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Effect of sintering temperature on the optical properties of BiFeO{sub 3} nanoparticles

BiFeO{sub 3} is a multiferroic material which exhibits excellent optical properties. BiFeO{sub 3} nanoparticles are synthesized by using sol-gel method. The prepared samples are sintered at 500°C, 600°C, 700°C, 800°C and 850°C. In this paper, the effect of sintering temperature on the optical properties in BiFeO{sub 3} nanoparticles is studied. Field emission electron microscopy (FESEM) images show that particles are nearly spherical in shape. It is found that the particles size increases from 37 nm to 51 nm with increasing the sintering temperature. FESEM images also reveal a homogenous size distribution of nanoparticles. All the functional groups are indexed in the Fourier transform infrared spectroscopy (FTIR) spectra. It is found that Fe-O stretching peaks are appeared in the wave number range 447 and 507 cm{sup −1}. The value of energy band gap are found 2.14, 2.26, 2.30, 2.36, and 2.54 eV for the samples sintered at 500°C, 600°C, 700°C, 800°C and 850°C respectively. Thus, the increase in band gap with increasing temperature has been observed. The present samples can be used as photo-catalyst, in non-volatile memories and to make spintronics devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Effective Landau-type model of a Hf x Zr 1 - x O 2 -graphene nanostructure

Here, to describe the charge-polarization coupling in the nanostructure formed by a thin Hf x Zr 1-x O 2 film with a single-layer graphene as a top electrode, we develop the “effective” Landau-Ginzburg-Devonshire model. This approach is based on the parametrization of the Landau expansion coefficients for the polar (FE) and antipolar (AFE) orderings in thin Hf 1-x Zr x O 2 films from a limited number of polarization-field curves and hysteresis loops. The Landau expansion coefficients are nonlinearly dependent on the film thickness h and Zr/[Hf+Zr] ratio x, in contrast to h-independent and linearly x-dependent expansion coefficients of a classical Landau energy. We explain the dependence of the Landau expansion coefficients by the strong nonmonotonic dependence of the Hf 1-x Zr x O 2 film polar properties on the film thickness, grain size and surface energy. The proposed Landau free energy with five “effective” expansion coefficients, which are interpolation functions of x and h, describes the continuous transformation of polarization dependences on applied electric field and hysteresis loop shapes induced by the changes of x and h in the range 0 < x < 1 and 5 nm < h < 35 nm. Using the effective free energy, we demonstrated that the polarization of Hf 1-x Zr x O 2 film influences strongly on the graphene conductivity, and the full correlation between the distribution of polarization and charge carriers in graphene is revealed. In accordance with our modeling, the polarization of the (5 – 25) nm thick Hf 1-x Zr x O 2 films, which are in the ferroelectric-like or antiferroelectric-like states for the chemical compositions 0.35 ≤ x ≤ 0.95, determine the concentration of carriers in graphene and can control its field dependence. The result can be promising for creation of next generation Si-compatible nonvolatile memories and graphene-ferroelectric FETs, because the working voltages applied to the Hf 1-x Zr x O 2 film (which acts as a gate) can be relatively low (less than 2 V). These low voltages are sufficient to induce the pronounced hysteresis of ferroelectric polarization in the Hf 1-x Zr x O 2 gate, which, due to the strong electric coupling, induces the hysteresis of the graphene charge.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fast tree-based algorithms for DBSCAN for low-dimensional data on GPUs

DBSCAN is a well-known density-based clustering algorithm to discover arbitrary shape clusters. While conceptually simple in serial, the algorithm is challenging to efficiently parallelize on manycore GPU architectures. Common pitfalls, such as asynchronous range query calls, result in high thread execution divergence in many implementations. In this paper, we propose a new framework for GPU-accelerated DBSCAN, and describe two tree-based algorithms within that framework. Both algorithms fuse the search for neighbors with updating cluster information, but differ in their treatment of dense regions of the data. We show that the time taken to compute clusters is at most twice that of determination of the neighbors. We compare the proposed algorithms with existing CPU and GPU implementations, and demonstrate their competitiveness and performance using a fast traversal structure (bounding volume hierarchy) for low dimensional data. We also show that the memory usage can be reduced by processing object neighbors dynamically without storing them.

Prokopenko, Andrey↗
DOE OSTI2018

Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)

Land surface models (LSMs), which form the land component of earth system models, rely on numerous processes for describing carbon, water and energy budgets, often associated with highly uncertain parameters. Data assimilation (DA) is a useful approach for optimising the most critical parameters in order to improve model accuracy and refine future climate predictions. In this study, we compare two different DA methods for optimising the parameters of seven plant functional types (PFTs) of the ORCHIDEE LSM using daily averaged eddy-covariance observations of net ecosystem exchange and latent heat flux at 78 sites across the globe. We perform a technical investigation of two classes of minimisation methods – local gradient-based (the L-BFGS-B algorithm, limited memory Broyden–Fletcher–Goldfarb–Shanno algorithm with bound constraints) and global random search (the genetic algorithm) – by evaluating their relative performance in terms of the model–data fit and the difference in retrieved parameter values. We examine the performance of each method for two cases: when optimising parameters at each site independently (“single-site” approach) and when simultaneously optimising the model at all sites for a given PFT using a common set of parameters (“multi-site” approach). We find that for the single site case the random search algorithm results in lower values of the cost function (i.e. lower model–data root mean square differences) than the gradient-based method; the difference between the two methods is smaller for the multi-site optimisation due to a smoothing of the cost function shape with a greater number of observations. The spread of the cost function, when performing the same tests with 16 random first-guess parameters, is much larger with the gradient-based method, due to the higher likelihood of being trapped in local minima. When using pseudo-observation tests, the genetic algorithm results in a closer approximation of the true posterior parameter value in the L-BFGS-B algorithm. We demonstrate the advantages and challenges of different DA techniques and provide some advice on using it for the LSM parameter optimisation.

58 GEOSCIENCES↗
DOE OSTI2018

Memory effect and magnetocrystalline anisotropy impact on the surface magnetic domains of magnetite(001)

The structure of magnetic domains, i.e. regions of uniform magnetization separated by domain walls, depends on the balance of competing interactions present in ferromagnetic (or ferrimagnetic) materials. When these interactions change then domain configurations also change as a result. Magnetite provides a good test bench to study these effects, as its magnetocrystalline anisotropy varies significantly with temperature. Using spin-polarized electron microscopy to map the micromagnetic domain structure in the (001) surface of a macroscopic magnetite crystal (~1 cm size) shows complex domain patterns with characteristic length-scales in the micrometer range and highly temperature dependent domain geometries. Although heating above the Curie temperature erases the domain patterns completely, cooling down reproduces domain patterns not only in terms of general characteristics: instead, complex microscopic domain geometries are reproduced in almost perfect fidelity between heating cycles. A possible explanation of the origin of the high-fidelity reproducibility is suggested to be a combination of the presence of hematite inclusions that lock bulk domains, together with the strong effect of the first order magnetocrystalline anisotropy which competes with the shape anisotropy to give rise to the observed complex patterns.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Imaging of voltage-controlled switching of magnetization in highly magnetostrictive epitaxial Fe–Ga microstructures

The magnetoelectric behavior of epitaxial Fe–Ga microstructures on top of a (001)-oriented PMN–PT piezoelectric substrate is imaged with magnetic X-ray microscopy. Additionally, the micron-scale strain distribution in PMN–PT is characterized by X-ray microdiffraction and examined with respect to the results of the Fe–Ga magnetoelectric switching. The magnetic reorientation of Fe–Ga is found to be strongly correlated with size, shape, and crystallographic orientation of the microstructures. In the case of square-shaped structures, size dictates the influence of the strain distribution on both the initialization of the ground state and on the magnetic reorientation during application of voltage. On the other hand, elliptical microstructures demonstrate completely different magnetic responses depending on the relative orientation of their long axis with respect to the crystallographic directions of the PMN–PT. This study demonstrates that engineering the behavior of highly magnetostrictive epitaxial microdevices is possible. It further elucidates that voltage-induced actuation can be largely tuned to achieve the desired type of magnetic switching ranging from vortex circulation reversal, domain wall motion, to a large rotation of magnetization. Because of the outstanding properties of the investigated material system, the reported findings are expected to be of great interest for the realization of next-generation energy-efficient magnetic memory and logic devices.

42 ENGINEERING↗
DOE OSTI2017

Personalized Infrastructure: Leveraging Behavioral Strategies for Future Mobility

For decades, the transportation system has been built to position the personal automobile at the pinnacle of mobility options. This prominence is strongly reflected in individual and population behaviors, and supported by coevolved transportation policy, social norms, funding, and physical structures. Such has been the status quo for the living memory of the U.S. population. However, with the advent of emergent, technologically driven mobility options, the transportation system is in an era of rapid and disruptive change. No longer is transportation infrastructure an externality predominantly composed of physical elements; it is also now a personalized interface carried in the pockets of the majority of the population. Perceptions of personal mobility are evolving, in large part because of the proliferation of smartphone technology and the related Internet of Things (IoT), which will become increasingly essential within future transportation systems. With the emergence of personalized mobility infrastructure, many intervention approaches to influence transportation behavior do not adequately acknowledge the complexity of the social/digital environment within which transportation decisions are made. Transportation decisions are influenced by multiple facets, including costs and benefits in time and money, but also by sociocultural elements shaped by social norms and diffusion of ideas. Understanding of factors that lead to transportation behaviors can help to identify incentives and leverage points whereby alternative choices may be most accepted by individuals, and which, if well coordinated, may lead to improved transportation energy outcomes. How can change be initiated to shift away from the transportation status quo? Is it possible to use technologically delivered incentives to produce meaningful changes in transportation behavior? What types of incentives and at what perceived value is necessary to induce changes in behavior? As transportation agencies look toward an ever more complex mobility landscape, and with a quickly growing population, we look for answers to these questions as the core of developing strategies for the future of transportation. Using available data from emergent modes, and experiments conducted as part of an Advanced Research Projects Agency - Energy (ARPA-E) Traveler Response Architecture using Novel Signaling for Network Efficiency in Transportation (TRANSNET) project, we look at how the sharing economy and transportation mobility services have begun to radically alter transportation behavior, while operating in parallel with traditional transportation infrastructure. Emerging modes and practices are affecting car dependence and enabling multimodality. We weigh influences on travel behaviors, identify decision breakpoints where inelastic behavior becomes elastic, incentives, and societal leverage points.

25 ENERGY STORAGE↗
DOE OSTI2022

Multiplicative Shot-Noise: A New Route to Stability of Plastic Networks

Fluctuations of synaptic weights, among many other physical, biological, and ecological quantities, are driven by coincident events of two “parent” processes. Here we propose a multiplicative shot-noise model that can capture the behaviors of a broad range of such natural phenomena, and analytically derive an approximation that accurately predicts its statistics. We apply our results to study the effects of a multiplicative synaptic plasticity rule that was recently extracted from measurements in physiological conditions. Using mean-field theory analysis and network simulations, we investigate how this rule shapes the connectivity and dynamics of recurrent spiking neural networks. The multiplicative plasticity rule is shown to support efficient learning of input stimuli, and it gives a stable, unimodal synaptic-weight distribution with a large fraction of strong synapses. The strong synapses remain stable over long times but do not “run away.” Our results suggest that the multiplicative shot-noise offers a new route to understand the tradeoff between flexibility and stability in neural circuits and other dynamic networks.

59 BASIC BIOLOGICAL SCIENCES↗