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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

QCAD Simulation and Optimization of Semiconductor Double Quantum Dots

We present the Quantum Computer Aided Design (QCAD) simulator that targets modeling quantum devices, particularly silicon double quantum dots (DQDs) developed for quantum qubits. The simulator has three differentiating features: (i) its core contains nonlinear Poisson, effective mass Schrodinger, and Configuration Interaction solvers that have massively parallel capability for high simulation throughput, and can be run individually or combined self-consistently for 1D/2D/3D quantum devices; (ii) the core solvers show superior convergence even at near-zero-Kelvin temperatures, which is critical for modeling quantum computing devices; (iii) it couples with an optimization engine Dakota that enables optimization of gate voltages in DQDs for multiple desired targets. The Poisson solver includes MaxwellBoltzmann and Fermi-Dirac statistics, supports Dirichlet, Neumann, interface charge, and Robin boundary conditions, and includes the effect of dopant incomplete ionization. The solver has shown robust nonlinear convergence even in the milli-Kelvin temperature range, and has been extensively used to quickly obtain the semiclassical electrostatic potential in DQD devices. The self-consistent Schrodinger-Poisson solver has achieved robust and monotonic convergence behavior for 1D/2D/3D quantum devices at very low temperatures by using a predictor-correct iteration scheme. The QCAD simulator enables the calculation of dot-to-gate capacitances, and comparison with experiment and between solvers. It is observed that computed capacitances are in the right ballpark when compared to experiment, and quantum confinement increases capacitance when the number of electrons is fixed in a quantum dot. In addition, the coupling of QCAD with Dakota allows to rapidly identify which device layouts are more likely leading to few-electron quantum dots. Very efficient QCAD simulations on a large number of fabricated and proposed Si DQDs have made it possible to provide fast feedback for design comparison and optimization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Optimizing legacy molecular dynamics software with directive-based offload

The directive-based programming models are one solution for exploiting many-core coprocessors to increase simulation rates in molecular dynamics. They offer the potential to reduce code complexity with offload models that can selectively target computations to run on the CPU, the coprocessor, or both. In our paper, we describe modifications to the LAMMPS molecular dynamics code to enable concurrent calculations on a CPU and coprocessor. We also demonstrate that standard molecular dynamics algorithms can run efficiently on both the CPU and an x86-based coprocessor using the same subroutines. As a consequence, we demonstrate that code optimizations for the coprocessor also result in speedups on the CPU; in extreme cases up to 4.7X. We provide results for LAMMAS benchmarks and for production molecular dynamics simulations using the Stampede hybrid supercomputer with both Intel (R) Xeon Phi (TM) coprocessors and NVIDIA GPUs: The optimizations presented have increased simulation rates by over 2X for organic molecules and over 7X for liquid crystals on Stampede. The optimizations are available as part of the "Intel package" supplied with LAMMPS. (C) 2015 Elsevier B.V. All rights reserved.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Electronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence–structure–function relations remain poorly characterized. Here, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically active π-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylenevinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20 3 = 8000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

The Modeling of Advanced BWR Fuel Designs with the NRC Fuel Depletion Codes PARCS/PATHS

The PATHS (PARCS Advanced Thermal Hydraulic Solver) code was developed at the University of Michigan in support of U.S. Nuclear Regulatory Commission research to solve the steady-state, two-phase, thermal-hydraulic equations for a boiling water reactor (BWR) and to provide thermal-hydraulic feedback for BWR depletion calculations with the neutronics code PARCS (Purdue Advanced Reactor Core Simulator). The simplified solution methodology, including a three-equation drift flux formulation and an optimized iteration scheme, yields very fast run times in comparison to conventional thermal-hydraulic systems codes used in the industry, while still retaining sufficient accuracy for applications such as BWR depletion calculations. Lastly, the capability to model advanced BWR fuel designs with part-length fuel rods and heterogeneous axial channel flow geometry has been implemented in PATHS, and the code has been validated against previously benchmarked advanced core simulators as well as BWR plant and experimental data. We describe the modifications to the codes and the results of the validation in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Maximizing the Catalytic Performance of Pd@Au x Pd 1- x Nanocubes in H 2 O 2 Production by Reducing Shell Thickness to Increase Compositional Stability

We report a simple route based upon seed-mediated growth to the synthesis of Pd@Au x Pd 1-x (0.8≤x≤1) core–shell nanocubes. Benefiting from the well-defined {100} facets and an optimal Au/Pd ratio for the surface, the nanocubes bearing a shell made of Au 0.95 Pd 0.05 work as an efficient electrocatalyst toward H 2 O 2 production, with high selectivity of 93–100 % in the low-overpotential region of 0.4–0.7 V. When the Au 0.95 Pd 0.05 alloy is confined to a shell of only three atomic layers in thickness, the electrocatalyst is able to maintain its surface structure and elemental composition, endowing continuous and stable production of H2O2 during oxygen reduction at a high rate of 1.62 mol g( Pd+Au ) -1 h -1 . This work demonstrates a versatile route to the rational development of active and durable electrocatalysts based upon alloy nanocrystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Demonstration of cathode emittance dominated high bunch charge beams in a DC gun-based photoinjector

We present the results of transverse emittance and longitudinal current profile measurements of high bunch charge (≥100 pC) beams produced in the DC gun-based Cornell energy recovery linac photoinjector. In particular, we show that the cathode thermal and core beam emittances dominate the final 95% and core emittances measured at 9–9.5 MeV. Additionally, we demonstrate excellent agreement between optimized 3D space charge simulations and measurement, and show that the quality of the transverse laser distribution limits the optimal simulated and measured emittances. These results, previously thought achievable only with RF guns, demonstrate that DC gun based photoinjectors are capable of delivering beams with sufficient single bunch charge and beam quality suitable for many current and next generation accelerator projects such as Energy Recovery Linacs and Free Electron Lasers.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Transport and spatial energy deposition of relativistic electrons in copper-doped fast ignition plasmas

Fast electron transport and spatial energy deposition are investigated in integrated cone-guided Fast Ignition experiments by measuring fast electron induced copper K-shell emission using a copper tracer added to deuterated plastic shells with a geometrically reentrant gold cone. Experiments were carried out at the Laboratory for Laser Energetics on the OMEGA/OMEGA-EP Laser where the plastic shells were imploded using 54 of the 60 OMEGA60 beams (3ω, 20 kJ), while the high intensity OMEGA-EP (BL2) beam (1 ω, 10 ps, 500 J, I peak > 10 19 W/cm 2 ) was focused onto the inner cone tip. Here, a retrograde analysis using the hybrid-PIC electron transport code, ZUMA, is performed to examine the sensitivity of the copper Kα spatial profile on the laser-produced fast electrons, facilitating the optimization of new target point designs and laser configurations to improve the compressed core areal density by a factor of 4 and the fast electron energy coupling by a factor of 3.5.

42 ENGINEERING↗
DOE OSTI2017

Search for excited states in O 25

Theoretical calculations suggest the presence of low-lying excited states in 25 O. Previous experimental searches by means of proton knockout on 26 F produced no evidence for such excitations. We search for excited states in 25 O using the 24 O(d,p) 25 O reaction. The theoretical analysis of excited states in unbound 25,27 O is based on the configuration interaction approach that accounts for couplings to the scattering continuum. We use invariant-mass spectroscopy to measure neutron-unbound states in 25 O. For the theoretical approach, we use the complex-energy Gamow Shell Model and Density Matrix Renormalization Group method with a finite-range two-body interaction optimized to the bound states and resonances of 23–26 O, assuming a core of 22 O. Here we predict energies, decay widths, and asymptotic normalization coefficients. Our calculations in a large spdf space predict several low-lying excited states in 25 O of positive and negative parity, and we obtain an experimental limit on the relative cross section of a possible J π = 1/2 + state with respect to the ground state of 25 O at σ 1/2+ /σ g.s. = 0.25$^{+1.0}_{-0.25}$. We also discuss how the observation of negative parity states in 25 O could guide the search for the low-lying negative parity states in 27 O. Previous experiments based on the proton knockout of 26 F suffered from the low cross sections for the population of excited states in 25 O because of low spectroscopic factors. In this respect, neutron transfer reactions carry more promise.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

The Reverse Cuthill-McKee Algorithm in Distributed-Memory

Ordering vertices of a graph is key to minimize fill-in and data structure size in sparse direct solvers, maximize locality in iterative solvers, and improve performance in graph algorithms. Except for naturally parallelizable ordering methods such as nested dissection, many important ordering methods have not been efficiently mapped to distributed-memory architectures. In this paper, we present the first-ever distributed-memory implementation of the reverse Cuthill-McKee (RCM) algorithm for reducing the profile of a sparse matrix. Our parallelization uses a two-dimensional sparse matrix decomposition. We achieve high performance by decomposing the problem into a small number of primitives and utilizing optimized implementations of these primitives. Our implementation shows strong scaling up to 1024 cores for smaller matrices and up to 4096 cores for larger matrices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I

Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G} for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient parallel computation of particle and fluid dynamics simulations. These problems occur throughout DOE, military and commercial sectors: the potential payoff is high. We plan to license or sell the solution to contractors for military and domestic applications such as disaster simulation (aerodynamic and hydrodynamic), Government agencies (hydrological and environmental simulations), and medical applications (e.g., in tomographic image reconstruction). Keywords - High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation. Summary for Members of Congress - Department of Energy has many simulation codes that must compute faster, to be effective. The Phase I research parallelized particle/fluid simulations for rocket combustion, for high-performance computing systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Collaborative Research: Continuous Dynamic Grid Adaptation in a Global Atmospheric Model - Application and Refinement

This project had goals of advancing the performance capabilities of the numerical general circulation model EULAG and using it to produce a fully operational atmospheric global climate model (AGCM) that can employ either static or dynamic grid stretching for targeted phenomena. The resulting AGCM combined EULAG's advanced dynamics core with the "physics" of the NCAR Community Atmospheric Model (CAM). Effort discussed below shows how we improved model performance and tested both EULAG and the coupled CAM-EULAG in several ways to demonstrate the grid stretching and ability to simulate very well a wide range of scales, that is, multi-scale capability. We leveraged our effort through interaction with an international EULAG community that has collectively developed new features and applications of EULAG, which we exploited for our own work summarized here. Overall, the work contributed to over 40 peer-reviewed publications and over 70 conference/workshop/seminar presentations, many of them invited. 3a. EULAG Advances EULAG is a non-hydrostatic, parallel computational model for all-scale geophysical flows. EULAG's name derives from its two computational options: EULerian (flux form) or semi-LAGrangian (advective form). The model combines nonoscillatory forward-in-time (NFT) numerical algorithms with a robust elliptic Krylov solver. A signature feature of EULAG is that it is formulated in generalized time-dependent curvilinear coordinates. In particular, this enables grid adaptivity. In total, these features give EULAG novel advantages over many existing dynamical cores. For EULAG itself, numerical advances included refining boundary conditions and filters for optimizing model performance in polar regions. We also added flexibility to the model's underlying formulation, allowing it to work with the pseudo-compressible equation set of Durran in addition to EULAG's standard anelastic formulation. Work in collaboration with others also extended the demonstrated range of validity of soundproof models, showing that they are more broadly applicable than some had previously thought. Substantial testing of EULAG included application and extension of the Jablonowski-Williamson baroclinic wave test - an archetype of planetary weather - and further analysis of multi-scale interactions arising from collapse of temperature fronts in both the baroclinic wave test and simulations of the Held-Suarez idealized climate. These analyses revealed properties of atmospheric gravity waves not seen in previous work and further demonstrated the ability of EULAG to simulate realistic behavior over several orders of magnitude of length scales. Additional collaborative work enhanced capability for modeling atmospheric flows with adaptive moving meshes and demonstrated the ability of EULAG to move into petascale computing. 3b. CAM-EULAG Advances We have developed CAM-EULAG in collaboration with former project postdoc, now University of Cape Town Assistant Professor, Babatunde Abiodun. Initial study documented good model performance in aqua-planet simulations. In particular, we showed that the grid adaptivity (stretching) implemented in CAM-EULAG allows higher resolution in selected regions without causing anomalous behavior such as spurious wave reflection. We then used the stretched-grid version to analyze simulated extreme precipitation events in West Africa, comparing the precipitation and event environment with observed behavior. The model simulates fairly well the spatial scale and the interannual and intraseasonal variability of the extreme events, although its extreme precipitation intensity is weaker than observed. In addition, both observations and the simulations show possible forcing of extreme events by African easterly waves. 3c. Other Contributions Through our collaborations, we have made contributions to a wide range of outcomes. For research focused on terrestrial behavior, these have included (1) upwind schemes for gas dynamics, (2) a nonlinear perspective on the dynamics of the Madden-Julian Oscillation, (3) numerical realism of thermal convection, (4) extreme precipitation processes, (5) unstructured meshes, (6) porous-media analogies for simulating flow in urban environments, (7) Monge-Ampere enhancements of semi-Lagrangian methods and (8) further extensions of the generality of EULAG applications to geophysical problems. The generality of EULAG for multi-scale flow was also demonstrated through solar applications. Simulations of solar magnetohydrodynamics showed that EULAG produces the solar cycle fairly well. Although the model's solar cycle is significantly longer than observed, it shows remarkable agreement with observations in features of spatial evolution. These efforts in environments that are extreme from a geophysical perspective have helped to establish the robustness of EULAG as an all-scale code for geophysical applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

High-efficiency photovoltaics based on semiconductor nanostructures

The objective of this project was to exploit a variety of semiconductor nanostructures, specifically semiconductor quantum wells, quantum dots, and nanowires, to achieve high power conversion efficiency in photovoltaic devices. In a thin-film device geometry, the objectives were to design, fabricate, and characterize quantum-well and quantum-dot solar cells in which scattering from metallic and/or dielectric nanostructures was employed to direct incident photons into lateral, optically confined paths within a thin (~1-3um or less) device structure. Fundamental issues concerning nonequilibrium carrier escape from quantum-confined structures, removal of thin-film devices from an epitaxial growth substrate, and coherent light trapping in thin-film photovoltaic devices were investigated. In a nanowire device geometry, the initial objectives were to engineer vertical nanowire arrays to optimize optical confinement within the nanowires, and to extend this approach to core-shell heterostructures to achieve broad-spectrum absorption while maintaining high open-circuit voltages. Subsequent work extended this approach to include fabrication of nanowire photovoltaic structures on low-cost substrates.

14 SOLAR ENERGY↗
DOE OSTI2016

Cross-scale Efficient Tensor Contractions for Coupled Cluster Computations Through Multiple Programming Model Backends

Coupled-cluster methods provide highly accurate models of molecular structure by explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix-matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy efficient manner. We achieve up to 240 speedup compared with the best optimized shared memory implementation. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures, (Cray XC30&XC40, BlueGene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance. Nevertheless, we preserve a uni ed interface to both programming models to maintain the productivity of computational quantum chemists.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

A detailed study of CO 2 -brine capillary trapping mechanisms as applied to geologic carbon storage. Final Report

The proposed research focuses on improved fundamental understanding of the efficiency of physical trapping mechanisms, and as such will provide the basis for subsequent upscaling efforts. The overarching hypothesis of the proposed research is that capillary pressure plays a significant role in capillary trapping of CO 2 , especially during the water imbibition stage of the sequestration process. We posit that the relevant physics of the sequestration process is more complex than is currently captured in relative permeability models, which are often based on so-called trapping models to represent relative permeability hysteresis. Our 4 main questions, guiding the 4 main tasks of the proposed research, are as follows: (1) What is the morphology of capillary trapped CO 2 at the pore scale as a function of temperature, pressure, brine concentration, interfacial tension, and pore-space morphology under injection and subsequent imbibition? (2) Is it possible to describe the capillary trapping process using formation-dependent, but otherwise unique continuum-scale functions in permeability-capillary pressure, interfacial area and saturation space, rather than hysteretic functions in permeability-saturation or capillary pressure-saturation space? (3) How do continuum-scale relationships between kr-Pc-S-Anw developed based on pore-scale observations compare with traditional models incorporating relative permeability hysteresis (such as Land’s and other models,) and with observations at the core (5-10cm) scale? (4) How can trapped CO 2 volume be optimized via engineered injection and sweep strategies, and as a function of formation type (incl. heterogeneity)?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

SPND Sensitivity Calculations Using MCNP and Experimental Data from ACRR

The use of the Monte Carlo N-Particle Transport Code (MCNP) to calculate detector sensitivity for Self-Powered Neutron Detectors (SPNDs) in the Annular Core Research Reactor (ACRR) could be a vital tool in the effort to optimize the design of next-generation SPNDs. Next-generation SPND designs, which consider specific materials and geometry, may provide experimenters with capabilities for advanced mixed field dosimetry. These detectors will need to be optimized for configuration, materials, and geometries and the ability to model and iterate must be available in order to decide on the ideal. SPND design. SPNDs were modeled in MCNP which closely resembled the dimensions and location of actual detectors used in the ACRR. Tallies were used to calculate detector sensitivity. Using metrics from a previous report, oscilloscope data from pulses were manipulated in a Matrix Laboratory computing environment (MATLAB) script to calculate experimental detector sensitivity. This report outlines the process in which experimental data from ACRR pulses verified results from tallies in an MCNP ACRR model. The sensitivity values from experiments and MCNP calculations agreed within one standard deviation. Parametric studies were also performed with MCNP to investigate the effects of materials and dimensions of different SPNDs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Real-Time Monitoring of Temperature Rises of Energized Transformer Cores With Distributed Optical Fiber Sensors

Real-time temperature mapping that solves local overheating problems is important for obtaining an optimized thermal design for high-efficiency power transformers. Internal temperature monitoring of operating power transformers can also be leveraged for asset monitoring applications targeting at fault detection enabling condition-based maintenance. Transformers present a variety of challenging sensing environments such as high levels of electromagnetic interference and limited space for conventional sensors to operate. Immersion of power transformers in insulation oils for thermal management during operation and the presence of relatively large and time-varying electrical and occasional magnetic fields make sensing technologies requiring electrical wires or active power at sensing locations highly undesirable. In this work, we investigate thermal response of a standard telecom fiber instrumented on compact transformer cores by using an optical frequency-domain reflectometry scheme. As a result, correlation between conventional temperature sensing methods and fiber-optic sensing results as well as tradeoffs between spatial resolution and temperature measurement accuracy is discussed and spatially resolved real-time monitoring of temperatures in energized transformers is experimentally demonstrated.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Formation and mechanism of nanocrystalline AZ91 powders during HDDR processing

Grain sizes of AZ91 alloy powders were markedly refined to about 15 nm from 100 to 160 μm by an optimized hydrogenation-disproportionation-desorption-recombination (HDDR) process. The effect of temperature, hydrogen pressure and processing time on phase and microstructure evolution of AZ91 alloy powders during HDDR process was investigated systematically by X-ray diffraction, optical microscopy, scanning electron microscopy and transmission electron microscopy, respectively. The optimal HDDR process for preparing nanocrystalline Mg alloy powders is hydriding at temperature of 350 °C under 4 MPa hydrogen pressure for 12 h and dehydriding at 350 °C for 3 h in vacuum. A modified unreacted core model was introduced to describe the mechanism of grain refinement of during HDDR process. - Highlights: • Grain size of the AZ91 alloy powders was significantly refined from 100 μm to 15 nm. • The optimal HDDR technology for nano Mg alloy powders is obtained. • A modified unreacted core model of grain refinement mechanism was proposed.

36 MATERIALS SCIENCE↗