X-ray imaging and 3D reconstruction of in-flight exploding foil initiator flyers
Abstract not provided
Willey, T. M.↗
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Resolving local structural motifs across the phase evolution of zinc titanates with computational x-ray absorption spectroscopy
Resolving the local structure motifs that characterize phase evolution as a function of composition is a key challenge in structure characterization of complex materials. Here, in this study, we combine first-principles simulations and x-ray absorption near-edge structures (XANES) analysis to gain insights into the structure evolution revealed by measurements across a combinatorial zinc titanate thin film, which was grown with smoothly varying composition over a wide range of the Ti:Zn ratio. Specifically, we propose a cluster blind-signal-separation (cBSS) method for XANES spectral analysis based on a library of the structures and spectra of representative local motifs. In addition to motifs from zinc titanate crystals, two types of Ti-defect models constructed in this study are key to the understanding of the structure characteristics in the Zn-rich region. The cBSS method makes use of both spectral clustering of the simulated site-XANES spectra library and the BSS procedure to construct high-fidelity spectral basis functions from an experimental spectral sequence. The method provides a rigorous measure of the spectral sensitivity and basis completeness. The results of the XANES analysis are corroborated with other experimental modalities, including x-ray diffraction and spectroscopic ellipsometry, to validate the cBSS method. The calculated motif weights resulting from fitting the XANES spectra with the cBSS basis probe the atomic structure characteristics of both crystalline and amorphous phases as a function of the Ti/Zn composition. The insights of the local structure motif evolution are pivotal to the understanding of the nonmonotonic trend in the optical gap, which may lead to potential applications through tuning the optical properties of zinc titanate. The workflow of the XANES spectral analysis developed in this work can be generalized to construct the structure-property relationship in a broad material space.
36 MATERIALS SCIENCE↗
Excited-State Dynamics of a CsPbBr 3 Nanocrystal Terminated with Binary Ligands: Sparse Density of States with Giant Spin–Orbit Coupling Suppresses Carrier Cooling
Fully inorganic lead halide perovskite nanocrystals (NCs) are of interest for photovoltaic and light-emitting devices due to optoelectronic properties that can be tuned/optimized via halide composition, surface passivation, doping, and confinement. Compared to bulk materials, certain excited-state properties in NCs can be adjusted by electronic confinement effects such as suppressed hot carrier cooling and enhanced radiative recombination. In this paper, we use spinor Kohn–Sham orbitals (SKSOs) with spin–orbit coupling (SOC) interaction as a basis to compute excited-state dissipative dynamics simulations on a fully passivated CsPbBr 3 NC atomistic model. Redfield theory in the density matrix formalism is used to describe electron–phonon interactions which drive hot carrier cooling and nonradiative recombination ( k nonrad ). Radiative recombination ( k rad ) is calculated through oscillator strengths using SKSO basis. From k rad and k rad + k nonrad , we compute a theoretical photoluminescence quantum yield (PLQY) of 53%. Computed rates of hot carrier cooling ( k cooling ≈ 10 –1 1/ps) compare favorably with what has been reported in the literature. Interestingly, we observe that hot electron cooling slows down near the band edge, which we attribute to large SOC in the conduction band combined with strong confinement, which creates subgaps above the band edge. This slow carrier cooling could potentially impact hot carrier extraction before complete thermalization in photovoltaics (PVs). Implications of this work suggest that strong/intermediate confined APbX 3 NCs are better suited to applications in PVs due to slower carrier cooling near the conduction band edge, while intermediate/weak confined NCs are more appropriate for light-emitting applications, such as LEDs.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Increasing the applicability of density functional theory. V. X-ray absorption spectra with ionization potential corrected exchange and correlation potentials
Core excitation energies are computed with time-dependent density functional theory (TD-DFT) using the ionization energy corrected exchange and correlation potential QTP(0,0). QTP(0,0) provides C, N, and O K-edge spectra to about an electron volt. A mean absolute error (MAE) of 0.77 and a maximum error of 2.6 eV is observed for QTP(0,0) for many small molecules. TD-DFT based on QTP (0,0) is then used to describe the core-excitation spectra of the 22 amino acids. TD-DFT with conventional functionals greatly underestimates core excitation energies, largely due to the significant error in the Kohn-Sham occupied eigenvalues. To the contrary, the ionization energy corrected potential, QTP(0,0), provides excellent approximations (MAE of 0.53 eV) for core ionization energies as eigenvalues of the Kohn-Sham equations. As a consequence, core excitation energies are accurately described with QTP(0,0), as are the core ionization energies important in X-ray photoionization spectra or electron spectroscopy for chemical analysis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Spike-based graph centrality measures
We derive several spike-based routines that compute or establish bounds on radial centrality measures for undirected graphs and trees without the use of matrix multiplication. These spike-based centrality measures utilize a direct embedding of graph nodes and edges into neurons and synapses, can be implemented with static synapses or plastic synapses, and rely on minimal post-processing of spike rasters. This work contributes to the growing set of graphical applications for neuromorphic hardware.
Hamilton, Kathleen↗
autoGEMM: Pushing the Limits of Irregular Matrix Multiplication on Arm Architectures
This paper presents an open-source library that pushes the limits of performance portability for irregular General Matrix Multiplication (GEMM) on the widely-used Arm architectures. Our library, autoGEMM, is designed to support a wide range of Arm processors: from edge devices to HPC-grade CPUs. autoGEMM generates optimized kernels for various hardware configurations by auto-combining fragments of autogenerated micro-kernels that employ hand-written optimizations to maximize computational efficiency. We optimize the kernel pipeline by tuning the register reuse and the data load/store overlapping. In addition, we use a dynamic tiling scheme to generate balanced tile shapes. Finally, we position autoGEMM on top of the TVM framework where our dynamic tiling scheme prunes the search space for TVM to identify the optimal combination of parameters for code optimization. Evaluations on five different classes of Arm chips demonstrate the advantages of autoGEMM. For small matrices, autoGEMM achieves 98% of peak and up to 2.0x speedup over state-of-the-art libraries such as LIBXSMM and LibShalom. For irregular matrices (i.e. tall skinny and long rectangles), autoGEMM is 1.3-2.0x faster than widely-used libraries such as OpenBLAS and Eigen. autoGEMM is publicly available at: https://github.com/wudu98/autoGEMM.
Wu, Du↗
Toroidal modeling of 3D perturbations generated by current filaments in scrape-off layer in tokamak with biased divertor targets
The divertor biasing technique offers a promising alternative to control the edge localized mode (ELM) as well as the divertor heat load in tokamaks, as compared to the resonant magnetic perturbation (RMP) generated by magnetic coils. The linear resistive MHD code MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) is employed to study the plasma response to the n = 2 (n is the toroidal mode number) field perturbation in HL-2A, produced by the divertor biasing current filaments flowing in the scrape-off layer region. The response field due to biasing currents is compared with the RMP field utilized for ELM control in HL-2A. The strength of the radial resonant field perturbation, produced by the biasing currents of 100 A level, is found to be comparable with RMP generated by several kA of ELM control coil currents for the reference plasma. The plasma normal displacement near the X-point and the associated neoclassical toroidal viscosity torque are also computed to be similar between these two techniques. The modeling results thus strongly suggest that the biasing technique can be applied to control ELMs. Moreover, the biasing currents produce field perturbations, including the plasma response, that are localized more near the plasma edge (compared to the RMP counterpart), thus reducing the chance of mode locking associated with core perturbations. Particle orbit tracing also reveals that the biasing current produced magnetic perturbation tends to widen the heat deposition region and induce the strike point splitting of the ion saturation flow on the outer divertor surface, consistent with experimental observations in HL-2A. These toroidal modeling results confirm the possibility of ELM control and plasma exhaust solution by the divertor biasing technique.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Real-Time Hardware-in-the-Loop Testbed to Evaluate FLISR Implemented with OpenFMB
With the increasing complexity of the distribution smart grid architecture, algorithms such as the fault location, isolation, and service restoration (FLISR) scheme rely on robust communications that are resilient to natural and man-made adverse conditions and exhibit robustness. Existing communications infrastructure for information exchange are centralized at the distribution management system, with very little autonomy or intelligence at the grid-edge. As a first step towards achieving grid-edge self-healing, this paper aims to bridge this shortcoming by implementing a centrally coordinated rules-based FLISR scheme and integrating it with Open Field Message Bus (OpenFMB), which is a flexible publish-subscribe architecture with the potential to enable point-to-multipoint communications and is more robust and resilient to natural and man-made adverse conditions. A proof of concept is developed to validate the centrally coordinated FLISR and OpenFMB mounted on an SEL-3360 computer that interacts with a simple feeder network of five SEL-651R relays, an SEL-3530 RTAC, and a hardware-in-the-loop testbed. Results demonstrate the efficacy of this approach in enabling direct, low-latency information exchange. OpenFMB's publish-subscribe data model also opens new ways to enable grid-edge interoperability among devices of different vendors interacting with different protocols.
Sundararajan, Aditya↗
Theory and Simulation of Ultrafast Multidimensional Nonlinear X-ray Spectroscopy of Molecules (Final Report)
Emerging X-ray free electron laser (XFEL) beam sources offer new types of probes of matter with unprecedented spatial and temporal resolutions. These experimental advances must be met by robust theoretical and computational tools that provide predictive modeling capacity of the underlining electronic and structural dynamics. The latter will be essential for the design of sophisticated multi-pulse experiments and for their interpretation. The proposed research effort will focus on developing cutting- edge simulation tools for nonlinear multidimensional X-ray/optical spectroscopies and aims to address key questions in Priority Research Opportunities 1 (Probing and controlling electron motion within a molecule) and 3 (Capturing rare events and intermediate states in the transformation of matter) as mentioned in the BES Roundtable Report “Opportunities for Basic Research at the Frontiers of XFEL Ultrafast Science”. XFEL multidimensional nonlinear techniques, which combine sequences of X-ray and possibly optical pulses, provide a unique experimental toolbox for probing the dynamics of core and valence electronic excitations, as well as material structure. Predictive modeling of these dynamical processes requires the combination of analytical theory for nonlinear interactions of light and matter, robust quantum-chemical methodologies for the accurate description of electronic structure of various materials, and multiscale ab initio electron and nuclear dynamics techniques operating beyond Born-Oppenheimer approximation. These challenges will be addressed with three research thrusts (i) Develop and implement theoretical apparatus for modeling a broad range of multidimensional spectroscopic techniques enabled by present and upcoming XFEL facilities. This thrust also includes the incorporation of a computational module in the DOE supported open-source NWChem computational chemistry package as well as the development of other open-source codes ready for dissemination across a broad user base; (ii) Propose and design new multi-pulse experiments that make use of the capabilities of the incoming LCLS-II facility; (iii) Perform selected applications to specific molecular systems that can be carried out at LCLS-II and demonstrate how these X-ray sources may be used to study nonadiabatic dynamics through conical interactions, electronic correlations in multi-core excitons, and charge transfer/energy transfer processes. The proposed research will be carried out by a multi-disciplinary four-institution research team which combines academia and national laboratories and spans the broad and necessary expertise in theoretical spectroscopy, nonlinear optics, quantum chemistry, molecular non-adiabatic dynamics and code development. The work will be performed in a highly interactive team environment with junior researchers shared between institutions thus cementing cross- disciplinary interactions. The developed simulation tools will be immediately deployed for XFEL facility users, both experimentalists and theorists, via freely distributed codes and databases. Altogether, this project will facilitate establishing XFEL-based multidimensional spectroscopies as a novel diagnostic tool for monitoring electronic and structural dynamics in molecular materials.
74 ATOMIC AND MOLECULAR PHYSICS↗
High-order methods for wind turbine simulations and moving to next-generation platforms
The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. This milestone represents an effort to increase the fidelity of Nalu-Wind at a fixed resolution through the implementation of a tensor-product based, matrix-free high order scheme. High order finite element methods have increased local work per datum communicated and have the potential to provide significantly more accurate solutions at a fixed number of degrees of freedom. Previous to this milestone, Nalu-Wind had an arbitrary order Control Volume Finite Element Method discretization as a solver option, but it required too much memory and was too slow to be of practical use. The work in this milestone addresses these issues by first implementing an implicit, high order solver that only partially assembles the global system. This reduces the memory footprint of the high-order scheme by orders of magnitude for higher polynomial orders. Second, a faster, tensor-product based method for evaluating the action of the left-hand side was implemented. This reduces the amount of computational work required by the scheme and dramatically enhanced the time-to-solution on example problems. Finally, this milestone is an evaluation of the value of high order methods in the wind application space. With the enhancements to memory and computational cost, accuracy vs. time-to-solution was evaluated for several resolutions on an under-resolved Taylor Green vortex test case. Results show that the high order scheme is cost-competitive with the production low-order schemes in Nalu-Wind, being moderately more expensive than the production edge-based vertex centered finite volume scheme. The evaluation of accuracy on the test case shows a potential benefit to high order at the highest resolution while not deteriorating accuracy on the lowest tested resolution. More work is needed to show value in the wind application, but positive strides have been made.
17 WIND ENERGY↗
Cognition at the Point of Sensing
Over the last 15 years, compressive sensing techniques have been developed which have the potential to greatly reduce the amount of data collected by systems while preserving the amount of information obtained. A cost of this efficiency is that a computationally-intensive optimization routine must be used to put the sensed data into a form that a person can interpret. At the same time, machine learning techniques have experienced tremendous growth as well. Machines have demonstrated the ability learn how to effectively perform tasks such as detection and classification at speeds much faster than humanly possible. Our goal in this project was to study the feasibility of using compressive sensing systems "at the edge." That is, how can compressive sensing sensors be deployed such that information is created at the remote sensor rather than sending raw data to a central processing location? Studies were performed to analyze whether machine learning could be done on the compressively sensed data in its raw form. If a machine is performing the task, is it possible to do so without putting the data into a human interpretable form? We show that this is possible for some systems, in particular a compressive sensing snapshot imaging spectrometer. Machine learning tasks were demonstrated to be more effective and more robust to noise when the machine learning algorithm worked on data in its raw form. This system is shown to outperform a traditional spectrometer. Techniques for reducing the complexity of the reconstruction routine were also analyzed. Techniques for such as data regularization, deep neural networks, and matrix completion were studied and shown to have benefits over traditional reconstruction techniques. In this project we showed that compressive sensing sensors are indeed feasible at the edge. As always, sensors and algorithms must be carefully tuned to work in the constrained environment. In this project we developed tools and techniques to enable those analyses.
47 OTHER INSTRUMENTATION↗
Role of scan strategies on thermal gradient and solidification rate in electron beam powder bed fusion
Local microstructure control in electron beam powder bed fusion (EB-PBF) is of great interest to the additive manufacturing community to realize complex part geometry with targeted performance. The local microstructure control relies on having a detailed understanding of local melt pool physics (e.g., 3-D melt pool shape as well as spatial and temporal variations of thermal gradient (G) and solidification rate (R)). In this research, a new scan strategy referred to as ghost beam is numerically evaluated as a candidate to achieve the targeted G and R of IN718 alloy. The boundary conditions for simulations, including the speed (490 mm/s) and spatial locations of the beam within a given layer, are obtained by using series of snapshot images, recorded at 12,000 frames per second, using a high-speed camera. The heat transfer simulations were performed using TRUCHAS an open-source software deployed within a high-performance computational infrastructure. The simulation results showed that reheating at short beam on-time and time delay decreases both G and R. Local variation of R at the center of the melt pool trailing edge showed periodic temporal fluctuations. Finally, the ghost beam scan strategy was compared to other existing raster and spot scan strategies.
36 MATERIALS SCIENCE↗
A Theoretical Study on Reaction Mechanisms and Kinetics of Thiophene Hydrodesulfurization over MoS 2 Catalysts
In the present work, thiophene hydrodesulphurization (HDS) over the Mo-edge, the S-edge, and the Mo-S connection edge of MoS 2 catalyst with 50% sulfur coverage was studied using first-principles based microkinetic modeling. Two parallel HDS routes, i.e., direct desulfurization (DDS) and hydrogenation (HYD) were taken into account. It has been found that the major reaction route of thiophene HDS on the Mo- and the Mo-S edges is temperature dependent. In the low temperature range of 500~600 K, the HYD route is dominant, leading to the C 4 H 8 formation. As the temperature increases, the DDS route becomes competitive with the HYD route. At the temperature above 650 K, the DDS route will be the dominant HDS reaction route on the Mo- and the Mo-S edges. While the DDS route that leads to the formation of C4H6 is the major thiophene HDS reaction route on the S-edge in the entire temperature range of 500~750 K. The microkinetic modeling results show the overall HDS activity on the S-edge is lower than it on the Mo- and the Mo-S edges. The Mo-S edge also provides a preferential reaction pathway, which facilitates 2-hydrothiophene migration from the Mo-edge to the S-edge, followed by remaining elementary steps with lower activation barriers in the DDS route. The work was financially supported by the National Natural Science Foundation of China (No. 21476012, 21571012, 21407007 and 91534201). The computing time was granted by a scientific theme user proposal in the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL), which is a U.S. Department of Energy national scientific user facility located at Pacific Northwest National Laboratory (PNNL) in Richland, Washington. Part of computing time was provided the National Energy Research Scientific Computing Center (NERSC). D. Mei is supported by the US Department of Energy, Office of Sciences, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences.
Thiophene, hydrodesulphurization, MoS2, DFT, micro↗
Elucidating the Evolving Atomic Structure in Atomic Layer Deposition Reactions with in Situ XANES and Machine Learning
Precision synthesis of thin films requires an improved mechanistic understanding of the structural evolution of materials at the atomic scale. Atomic layer deposition (ALD) is a critical nanofabrication technique that enables fine-tuning of atomic structure and thickness as a result of its layer-by-layer growth behavior. In this study, in situ X-ray absorption spectra of the S K-edge during ALD growth of ZnS thin films on TiO 2 nanoparticles were collected and analyzed. The experimental results show that both sulfide and sulfate species form during the nucleation phase of ZnS on TiO 2 . As film growth proceeds, the S K-edge of the in situ ZnS film converges to that of a representative ex situ ALD ZnS film. By building representative atomistic models, a high-throughput screening method was developed to determine the most probable atomic configurations as the film structure evolves. Specifically, the screening method consisted of a supervised machine learning analysis of thousands of simulated X-ray absorption near edge structure (XANES) spectra. Atomic-level insight was gained into changes in the coordination environment of surface species as they transitioned from the nucleation phase toward the crystalline ZnS phase. The experimental and computational strategies presented herein provide an example of how in situ synchrotron-based characterization can be leveraged using robust modeling approaches to elucidate the ordering of atoms during thin-film growth.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Analysis of Second Target Station Target Removal Dose Rates
The Second Target Station (STS) project at Oak Ridge National Laboratory’s spallation neutron source is a crucial initiative for maintaining U.S. leadership in neutron sciences. The STS aims to create the world’s brightest pulsed cold neutron source, enabling cutting-edge research across various scientific disciplines. To ensure safe and efficient maintenance operations, understanding the effects of shutdown dose rates from activated components within the STS target systems is essential. This study establishes a computational framework for calculating decay gamma sources and subsequent shutdown dose rates utilizing advanced methods to account for all activation channels, including high-energy interactions down to thermal neutron capture. This study describes a novel integration of multiple tools and provides an effective means of analyzing activation and shutdown dose rates at spallation neutron facilities. A custom-developed script automates the decay gamma source generation process, ensuring proper sampling during the variance reduction phase, which is critical for accurate predictions of shutdown dose rates.
Transmutation↗
Exploring the relation between transonic dislocation glide and stacking fault width in FCC metals
Theory predicts limiting gliding velocities that dislocations cannot overcome. Computational and recent experiments have shown that these limiting velocities are soft barriers and dislocations can reach transonic speeds in high rate plastic deformation scenarios. In this paper we systematically examine the mobility of edge and screw dislocations in several face centered cubic (FCC) metals (Al, Au, Pt, and Ni) in the extreme large-applied-stress regime using molecular dynamics simulations. Our results show that edge dislocations are more likely to move at transonic velocities due to their high mobility and lower limiting velocity than screw dislocations. Importantly, among the considered FCC metals, the dislocation core structure determines the dislocation’s ability to reach transonic velocities. This is likely due to the variation in stacking fault width due to relativistic effects near the limiting velocities.
36 MATERIALS SCIENCE↗
Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination
Post-training model compression can reduce the inference costs of deep neural networks, but uncompressed training still consumes enormous hardware resources and energy. To enable low-energy training on edge devices, it is highly desirable to directly train a compact neural network from scratch with a low memory cost. Low-rank tensor decomposition is an effective approach to reduce the memory and computing costs of large neural networks. However, directly training low-rank tensorized neural networks is a very challenging task because it is hard to determine a proper tensor rank a priori, and the tensor rank controls both model complexity and accuracy. Here, this paper presents a novel end-to-end framework for low-rank tensorized training. We first develop a Bayesian model that supports various low-rank tensor formats (e.g., CANDECOMP/PARAFAC, Tucker, tensor-train, and tensor-train matrix) and reduces neural network parameters with automatic rank determination during training. Then we develop a customized Bayesian solver to train large-scale tensorized neural networks. Our training methods shows orders-of-magnitude parameter reduction and little accuracy loss (or even better accuracy) in the experiments. On a very large deep learning recommendation system with over 4.2 ×10 9 model parameters, our method can reduce the parameter number to 1.6 ×10 5 automatically in the training process (i.e., by 2.6 ×10 4 times) while achieving almost the same accuracy. Code is available at https://github.com/colehawkins/bayesian-tensor-rank-determination.
compact neural networks↗
Supplement to LA-UR-17-21218: Application to SSVD
We apply the formalism derived in LA-UR-17-21218 to the prescription for an RMI-based self-similar velocity distribution (SSVD) derived by Ham- merberg et al.. We compute analytically the true [mt(t)] and inferred [mi(t)] ejecta mass arriving at the piezoelectric sensor for several shots de- scribed in the literature and compare the results to the data. We nd that while the \RMI + SSVD" prescription gives rise to decent estimates for the nal accumulated mass at the pin, the time-dependent accumulation rises too sharply and linearly to agree with data. We also compute the time-dependent pressure and voltage at the sensor, and compare the latter to data. The pres- sure does not rise smoothly from zero, instead exhibiting a strong surge as the leading edge of the ejecta cloud arrives, which produces an initial sharp spike in the voltage trace, which is not observed. These inconsistencies result from a discontinuity in the prescribed self-similar velocity distribution at maximum relative velocity.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗