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All sources NASA NTRS DOE OSTI

DOE OSTI2017

Controlled 3D Carbon Nanotube Architecture Coated with MoO x Material by ALD Technique: A High Energy Density Lithium‐Ion Battery Electrode

Due to its high theoretical capacity, energy density, and excellent reversibility with Li/Li + , molybdenum oxide is one of the vastly studied electrode material in lithium‐ion batteries. However, like most of the oxides, it also suffers from poor cyclic stability because of its low electrical conductivity. In 3D core–shell structure prepared by atomic layer deposition coating, it can provide superiority in nanoscale decoration than other deposition methods because of its extreme conformality and precise thickness control on high aspect ratio surfaces. This report illustrates the electrochemical activity of 3D core–shell type amorphous MoO x material coated by atomic layer deposition technique on conducting carbon nanotubes (CNT) scaffold which exhibits excellent overall cell capacity. The obtained capacity is manifold higher than its planar 2D counterpart and that can become an advanced nanoscale fabrication methodology of such 3D nanostructures for electrode preparation. Such binder free MoO x /CNT core–shell electrode structure shows very high and stable electrochemical activity toward Li/Li + system. An optimal thickness of MoO x on CNT is also found out in order to attain the most stable cyclic performance of this nanostructure. A stable reversible areal capacity of 645 µAh cm −2 with specific capacity of 915 mAh g −1 is achieved from optimized MoO x /CNT assembly.

Dhara, Arpan↗

DOE OSTI2019

Simulation and analysis of different approaches towards fiber optic plasmonic sensing for detection of human-liver tissues

Three types of plasmonic sensors are applied for the detection of five types of human-liver tissues (normal N, metastatic MET, non-cancerous metastatic NMET, hepatocellular carcinoma HCC and non-cancerous hepatocellular carcinoma NHCC). The first type of the fiber with seven layers is made by a ZBLAN core surrounded by NaF, silicon, silver, graphene, Al{sub 2}O{sub 3} and liver layers. The second type of the fiber with six layers is similar to the first one but without the graphene layer. The third type of the fiber with five layers is made by a SiO{sub 2} core surrounded by GaP, gold, Al{sub 2}O{sub 3} and liver layers. For optimized thicknesses of the interior layers at a laser wavelength (1.53 μm) one obtains large values of the figure of merit and amplitude sensitivity at an angle very close to the resonance angle. The advantage of the third (second) type of the fiber for normal liver is a large figure of merit (maximum amplitude sensitivity) in comparison with that for the second (third) type of the sensor. For all variants of the sensors, the figure of merit and maximum of the amplitude sensitivity are decreasing in the same order (N, MET, NMET, NHCC and HCC) for the liver tissues.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2017

Cross-scale efficient tensor contractions for coupled cluster computations through multiple programming model backends

Coupled-cluster methods provide highly accurate models of molecular structure through 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 optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/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, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Petascale solvers for anisotropic PDEs in atmospheric modelling on GPU clusters

Memory bound applications such as solvers for large sparse systems of equations remain a challenge for GPUs. Fast solvers should be based on numerically efficient algorithms and implemented such that global memory access is minimised. To solve systems with trillions ( O ( 10 12 ) ) unknowns the code has to make efficient use of several million individual processor cores on large GPU clusters. We describe the multi-GPU implementation of two algorithmically optimal iterative solvers for anisotropic PDEs which are encountered in (semi-) implicit time stepping procedures in atmospheric modelling. In this application the condition number is large but independent of the grid resolution and both methods are asymptotically optimal, albeit with different absolute performance. In particular, an important constant in the discretisation is the CFL number; only the multigrid solver is robust to changes in this constant. We parallelise the solvers and adapt them to the specific features of GPU architectures, paying particular attention to efficient global memory access. We achieve a performance of up to 0.78 PFLOPs when solving an equation with 0.55 · 10 12 unknowns on 16384 GPUs; this corresponds to about 3% of the theoretical peak performance of the machine and we use more than 40% of the peak memory bandwidth with a Conjugate Gradient (CG) solver. Although the other solver, a geometric multigrid algorithm, has a slightly worse performance in terms of FLOPs per second, overall it is faster as it needs less iterations to converge; the multigrid algorithm can solve a linear PDE with half a trillion unknowns in about one second.

Computer Science↗

DOE OSTI2018

3D field phase-space control in tokamak plasmas

Here, a small relaxation of the axisymmetric magnetic field of a tokamak into a non-axisymmetric three-dimensional (3D) configuration can be effective to control magnetohydrodynamic instabilities, such as edge-localized modes. However, a major challenge to the concept of 3D tokamaks is that there are virtually unlimited possible choices for a 3D magnetic field, and most of them will only destabilize or degrade plasmas by symmetry breaking. Here, we demonstrate the phase-space visualization of the full 3D field-operating windows of a tokamak, which allows us to predict which configurations will maintain high confinement without magnetohydrodynamic instabilities in an entire region of plasmas. We test our approach at the Korean Superconducting Tokamak Advanced Research (KSTAR) facility, whose 3D coils with many degrees of freedom in the coil space make it unique for this purpose. Our experiments show that only a small subset of coil configurations can accomplish edge-localized mode suppression without terminating the discharge with core magnetohydrodynamic instabilities, as predicted by the perturbative 3D expansion of plasma equilibrium and the optimizing principle of local resonance. The prediction provided excellent guidance, implying that our method can substantially improve the efficiency and fidelity of the 3D optimization process in tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Divertor-safe nonlinear burn control based on a SOLPS parameterized core-edge model for ITER

Abstract For ITER operations, the range of desirable burning-plasma regimes with high fusion power output will be restricted by various operational constraints. These constraints include the saturation of ITER’s various heating and fueling actuators such as the neutral beam injectors, the ion and electron cyclotron heating systems, the gas puffing system, and the deuterium–tritium pellet injectors. In addition to these actuator constraints, the H-mode power threshold, divertor detachment, and the heat load on the divertor targets may apply limitations to ITER’s operational space. In this work, Plasma Operation Contour (POPCON) plots that map the aforementioned constraints to the temperature-density space are used to investigate which constraints are most limiting towards accessing regimes with high fusion power output. The presented POPCON plots are based on a control-oriented core-edge model that couples the nonlinear density and energy response models for the core-plasma region with SOLPS4.3 parameterizations for conditions in the edge-plasma regions (scrape-off-layer and divertor). Using this control-oriented core-edge model, a nonlinear burn controller, which aims to regulate the plasma temperature and density in the core-plasma region, is constructed in this work. This controller is augmented with an online optimization scheme that governs the control references such that the plasma can be guided towards regimes with high fusion powers while protecting the divertor targets from dangerously high heat loads. A closed-loop simulation study illustrates the capability of this burn control scheme.

Physics↗

DOE OSTI2023

Scaling Automatic Vector Data Alignment to Satellite Imagery

Given the tremendous volume of accessible Earth Observation (EO) data, there is a need to develop scalable Geospatial Artificial Intelligence (GeoAI) solutions for time-sensitive applications. Scalability in this context refers to rapidly processing large-scale EO data using high performance computing resources. Accurate mapping of the built environment from remote sensing (RS) imagery has been one of the crucial components in GeoAI workflows for a wide spectrum of humanitarian applications. Derived vector data of built environment is often leveraged for disaster preparedness and response activities. However, factors such as differences in ortho-rectification, atmospheric conditions and human error, results in spatial misalignment between vector data and the timely available RS imagery. Model training for downstream tasks such as object detection, change analysis, etc., is negatively impacted due to such spatial misalignment. Although there has been progress towards automatic alignment of vector data, the lack of scalability remains an open research challenge. This paper proposes to leverage parallel computing to optimize an automatic vector data alignment workflow. It further employs CPU-level multi-core parallelism for improving the performance of the workflow for scalable built environment mapping. We report observations and discuss findings from the preliminary experiments performed on the Summit Supercomputer.

Potnis, Abhishek↗

DOE OSTI2019

Improved Time-Stepping Methods in Global to Regional Ocean Modeling

Improvements in time-stepping schemes can provide substantial improvements in the throughput of global ocean-climate models, but is challenging due to large variations in time scales in the dynamics and spatial scales in the global, variable resolution mesh. Two funded projects aim to speed up the Model for Prediction Across Scales-Ocean (MPAS-Ocean). The first will add a variable-timestepping formulation to MPAS-Ocean, which is a critical step towards running efficiently on global variable-resolution meshes with regional and coastal refinement. The second optimizes the barotropic (depth-integrated) mode, which is currently a performance bottleneck at high core counts. The proposed compute time will be used for extensive model validation and parameter studies for both methods.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

HFIR LEU High Density Silicide Dispersion Optimized Design Steady-State Heat Transfer Analyses

Steady-state heat transfer simulations of the Oak Ridge National Laboratory High Flux Isotope Reactor (HFIR) with the low-enriched uranium (LEU) high-density silicide dispersion Optimized fuel design were performed to support comprehensive performance and safety metric studies concerning this design. The LEU Optimized design operates at 95 MW to maintain HFIR’s current highly enriched uranium (HEU) core performance level at 85 MW. Full cycle Mode 1 full flow Case 1 (inlet temperature), Case 2 (flux-to-flow), and Case 3 (inlet pressure) safety limit analyses were performed to assess the margins to critical heat flux. Under the prescribed conditions, this LEU design meets the safety limit and limiting control setting requirements outlined in HFIR’s documented safety analysis; however, the safety margins are less than those for the 85 MW HEU core, and several assumptions were made where fuel fabrication and qualification data are currently lacking for the silicide fuel design. Effects of changes to pertinent fuel fabrication assumptions and uncertainty factors on thermal safety margins were also evaluated, showing that the margins are sensitive to many of these parameters. Power and pressure perturbations were also performed, indicating that significant steady-state thermal margins could be gained by increasing the coolant inlet pressure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2011

Python for Development of OpenMP and CUDA Kernels for Multidimensional Data

Design of data structures for high performance computing (HPC) is one of the principal challenges facing researchers looking to utilize heterogeneous computing machinery. Heterogeneous systems derive cost, power, and speed efficiency by being composed of the appropriate hardware for the task. Yet, each type of processor requires a specific organization of the application state in order to achieve peak performance. Discovering this and refactoring the code can be a challenging and time-consuming task for the researcher, as the data structures and the computational model must be co-designed. We present a methodology that uses Python as the environment for which to explore tradeoffs in both the data structure design as well as the code executing on the computation accelerator. Our method enables multi-dimensional arrays to be used effectively in any target environment. We have chosen to focus on OpenMP and CUDA environments, thus exploring the development of optimized kernels for the two most common classes of computing hardware available today: multi-core CPU and GPU. Python s large palette of file and network access routines, its associative indexing syntax and support for common HPC environments makes it relevant for diverse hardware ranging from laptops through computing clusters to the highest performance supercomputers. Our work enables researchers to accelerate the development of their codes on the computing hardware of their choice.

43 PARTICLE ACCELERATORS↗

DOE OSTI2016

CASL COBRA-TF improvements for PWR DNB analysis

COBRA-TF (CTF) is a thermal hydraulic (T/H) subchannel code using either three-dimensional (3D) Cartesian or subchannel coordinate formulations for two-phase fluid flow and heat transfer solutions. CTF has been improved under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program for Pressurized Water Reactor (PWR) applications, including software optimization, new closure models, pre- and post-processing and parallelization for modeling full reactor core T/H responses under normal operating and accident conditions. As a result of collaboration among CASL partners including the Westinghouse Electric Company, the Oak Ridge National Laboratory (ORNL), and the Sandia National Laboratories, additional modeling improvements were made to CTF specifically for PWR Departure from Nucleate Boiling (DNB) analysis, including a code option to evaluate fuel thermal margin in terms of DNB Ratio (DNBR) and an axial shape factor to account for effect of non-uniform axial power distribution on DNB. Multiple DNB correlations are now linked with CTF for different applications, including the Westinghouse proprietary WRB-1 correlation for fuel designs containing mixing vane grid spacers. The improved CTF code with the WRB-1 correlation (CTF/WRB-1) was validated using the DNB data from the PWR Subchannel Bundle Tests (PSBT). In addition to the comparison with the test data, the CTF/WRB-1 DNBR results and the associated local fluid conditions were compared to the results of the Westinghouse T/H design code, VIPRE-W, which is an enhanced version of the VIPRE-01 code originally developed by the Electric Power Research Institute (EPRI). The comparisons showed that CTF/WRB-1 DNBR predictions are in good agreement with the VIPRE-W results within the applicable range of the DNB correlation. A model sensitivity study was performed to confirm that the CTF void drift model had an insignificant effect on DNBR under the steam line break (SLB) low pressure condition. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Design and Optimization of High-frequency Transformer for Isolated Single-Stage Three-Phase AC/DC Converter using Bidirectional Switches

This paper presents the design and optimization of the high-frequency transformer for an isolated single-stage threephase AC/DC converter enabled by the 4H-SiC BiDirectional Field Effect Transistor (BiDFET). Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to perform a multiobjective optimization to minimize loss, weight, and volume. A 20 kW, 50 kHz hardware prototype based on the selected optimal point is characterized by a power amplifier. The finite element analysis simulation results are also presented to validate the core magnetic flux density and winding electric field strength. The experimental prototype was tested at 800 Vdc/480 Vrms at 10 kW rated power.

BiDFET, High-frequency transformer, Multiobjective↗

DOE OSTI2020

Parallel Time Integration for Constrained Optimization

The number of transistors in an average processor continues to increase, but individual clock speeds have plateaued. Those transistors are instead going into additional cores, increasing the number of different things that a processor can do at once and placing an emphasis on parallel computation. Many problems in scientific computing follow a time-evolution model, and it can be difficult to solve such problems in parallel across the temporal domain. The Multi-Grid Reduction In Time (MGRIT) algorithm, developed at Lawrence Livermore National Laboratory (LLNL), solves differential equations with a method designed specifically to take advantage of extreme numbers of processors by parallelizing across time. The Tri-diagonal MGRIT (TriMGRIT) algorithm, also developed at LLNL, is a generalization of MGRIT which enables parallel-in-time solving of a greater number of problems. Constrained optimization problems, in particular, may be solved in parallel using TriMGRIT. These consist of choosing a control function such that an objective functional is minimized, constrained by a differential-equation. We consider two such problems: applying torque to a pendulum to bring it to a gentle stop and moving a crowd of people from one distribution into another. We also perform some miscellaneous theoretical and practical research, including investigating the use of a line-search subroutine to refine intermediate TriMGRIT results and preliminary work on strategies for choosing operators for TriMGRIT to use.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Appealing sheath‐core spun high‐performance composite carbon molecular sieve membranes

Abstract Carbon molecular sieve (CMS) membranes are attractive candidates to meet requirements for challenging gas separations. The added ability to maintain such intrinsic properties in an asymmetric morphology with a structure that we term a “Pseudo Wheel+Hub & Spoke” asymmetric form offers new opportunities. For CMS membrane, specifically, the structure provides both selective layer support and low flow resistance even for high feed pressures and fluxes in CO 2 removal from natural gas. This capability is unavailable to even rigid glassy polymers due to the much higher modulus of CMS materials. Combining precursor asymmetric hollow fiber formation and optimized pyrolysis creates a defect free CMS proof‐of‐concept membrane for this application. Facile formation of the sheath‐core spun precursor with a 6FDA‐DAM sheath and Matrimid® core also avoids the need to seal defects before or after the carbonization of the precursors. The composite CMS membrane shows CO 2 /CH 4 (50 : 50) mixed gas feed with an attractive CO 2 /CH 4 selectivity of 64.3 and CO 2 permeance of 232 GPU at 35 °C. A key additional benefit of the approach is reduction in use of the more costly high performance 6FDA‐DAM in a composite sheath‐core CMS membrane with the “Pseudo Wheel+Hub & Spoke” structure.

Cao, Yuhe↗

DOE OSTI2013

Low Noble Metal Content Catalysts/Electrodes for Hydrogen Production by Water Electrolysis

Commercial proton exchange membrane (PEM)-based electrolyzers require highly expensive catalyst materials such as platinum group metals due to the acidic environment of the membrane. However, by optimizing the catalyst electrode structure for high utilization and activity, the amount of catalyst required can be reduced to an acceptable amount for both lifecycle and capital cost. In this project, we aim to reduce the Pt content by two orders of magnitude in the cathode catalyst for hydrogen evolution reaction (HER) and significantly reduce the Ir content in the anode catalyst for oxygen evolution reaction (OER). Proton has developed a collaboration over the past year and a half with the BNL electrocatalysis group, which will provide key expertise in design and synthesis of core-shell nanocatalysts and innovative structure integration of catalyst synthesis and electrode fabrication. The Phase 1 STTR will focus on optimization of the cathode catalyst and electrode for the hydrogen evolution reaction, and identifying an effective approach for significantly improving anode performance for the OER with reduced noble metal content. The catalyst design will combine the most active, durable components with atomic-level control of core-shell structure and narrow particle size distribution to maximize specific surface area. The synthesis methods will be developed to produce high quality catalysts at low cost for large scale production. GDEs will be fabricated to maximize the catalyst utilization at the cathode. Proton will conduct performance and durability tests, evaluate the results against current state-of-the-art catalysts/electrodes, and will estimate the production costs including lifecycle costs using the H2A model.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Propagation And Damping Of High Harmonic Fast Waves And Electron Cyclotron Waves In The Nstx-U-Device

For the spherical torus and for conventional tokamaks to be viable means of producing fusion energy there are two important requirements. The first is to heat the plasma in the experimental devices to high temperatures; preferably, to fusion relevant temperatures. The second is to drive a current in the plasma so that the fusion device operates in a steady-state mode. A pulsed fusion reactor for energy production is not desirable. A favored means to achieve both of these requirements is through the use of microwaves, commonly referred to as radio frequency waves. This proposal was to understand observations from the National Spherical Torus Experiment Upgrade (NSTX-U) device on radio frequency wave heating of the confined plasma during operations with high harmonic fast waves. The proposed research was also directed toward assisting in the optimization of the experimental modes of operation so as to maximize the heating efficiency. A detailed analysis of the experiments has shown that about one-third of the input radio frequency power does not make it into the core region of the plasma where heating is required. The losses are believed to occur primarily in the edge region where the radio frequency power is initially coupled into the plasma. Using sophisticated computational codes and theoretical models, that have been developed for the NSTX-U experimental program, this research quantified the physical processes which occur in the edge plasma and lead to a decrease in the heating efficiency. The effect of edge turbulence on the scattering of radio frequency waves was studied for waves in the ion cyclotron and electron cyclotron range of frequencies. For high harmonic fast waves in the ion cyclotron range of frequencies, simulations were carried out using a full-wave solver that was extended to the vacuum vessel wall. These simulations successfully reproduced trends that were observed experimentally. This simulation capability was also used to study the interaction of high harmonic fast waves with the scrape-off layer plasma. More recently, a new technique has been developed for the calculation of radio frequency waves in toroidal geometry that enables the simultaneous incorporation of antenna geometry, plasma facing components, the scrape off-layer, and core propagation in the high harmonic fast wave regime. The effect of turbulent plasmas on the mode conversion of extraordinary electromagnetic waves in the electron cyclotron range of frequencies in the NSTX-U plasma has been studied theoretically. In the over-dense plasmas of NSTX-U, the traditional electromagnetic waves are not effective for delivering energy and momentum to the core plasma. However, electron Bernstein waves generated by mode conversion are efficient carriers of wave energy and momentum to the core. The mode conversion occurs in the turbulent edge region. A theory for mode conversion in such plasmas has been developed. The parameters that can optimize the mode conversion can be readily determined. Also, the model is useful for experimentalists to analyze observation on a shot-to-shot basis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

Propagation And Damping Of High Harmonic Fast Waves And Electron Cyclotron Waves In The Nstx-U-Device

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Engineering Ultrathin Alloy Shell in Au@AuPd Core-Shell Nanoparticles for Efficient Plasmon-Driven Photocatalysis

Bimetallic core-shell nanoparticles (NPs) possessing a synergetic coupling of plasmonic and catalytic metals have emerged as promising prototypes for efficient plasmon-driven photocatalysis. Here, Au@AuPd core-shell NPs composed of Au core NP and ultrathin AuPd shell are introduced to acquire improved light utilization efficiency in photocatalytic selective oxidation. With systematical control of the composition of the ultrathin alloy shell, it reveals that the Au@AuPd core-shell NPs with 10 at% Pd (in the single-atom alloy regime) is an effective nanostructure capable of maximizing the quantum yield of plasmon-induced light absorption and optimizing the surface electronic structure for catalytic reactions. This controlled system provides new insights into shell engineering for enhancing photocatalytic performance via the regulation of energy funneling processes in core-shell nanocatalysts.

36 MATERIALS SCIENCE↗