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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

MICCO: An Enhanced Multi-GPU Scheduling Framework for Many-Body Correlation Functions

Calculation of many-body correlation functions is one of the critical kernels utilized in many scientific computing areas, especially in Lattice Quantum Chromodynamics (Lattice QCD). It is formalized as a sum of a large number of contraction terms each of which can be represented by a graph consisting of vertices describing quarks inside a hadron node and edges designating quark propagations at specific time intervals. Due to its computation- and memory-intensive nature, real-world physics systems (e.g., multi-meson or multi-baryon systems) explored by Lattice QCD prefer to leverage multi-GPUs. Different from general graph processing, many-body correlation function calculations show two specific features: a large number of computation-/data-intensive kernels and frequently repeated appearances of original and intermediate data. The former results in expensive memory operations such as tensor movements and evictions. The latter offers data reuse opportunities to mitigate the data-intensive nature of many-body correlation function calculations. However, existing graph-based multi-GPU schedulers cannot capture these data-centric features, thus resulting in a sub-optimal performance for many-body correlation function calculations. To address this issue, this paper presents a multi-GPU scheduling framework, MICCO, to accelerate contractions for correlation functions particularly by taking the data dimension (e.g., data reuse and data eviction) into account. This work first performs a comprehensive study on the interplay of data reuse and load balance, and designs two new concepts: local reuse pattern and reuse bound to study the opportunity of achieving the optimal trade-off between them. Based on this study, MICCO proposes a heuristic scheduling algorithm and a machine-learning-based regression model to generate the optimal setting of reuse bounds. Specifically, MICCO is integrated into a real-world Lattice QCD system, Redstar, for the first time running on multiple GPUs. The evaluation demonstrates MICCO outperforms other state-of-art works, achieving up to 2.25× speedup in synthesized datasets, and 1.49× speedup in real-world correlation functions.

Wang, Qihan↗
DOE OSTI2022

Thermoelectric Performance of the 2D Bi 2 Si 2 Te 6 Semiconductor

Bi 2 Si 2 Te 6 , a 2D compound, is a direct band gap semiconductor with an optical band gap of 0.25 eV, and is a promising thermoelectric material. Single-phase Bi 2 Si 2 Te 6 is prepared by a scalable ball-milling and annealing process and the highly densified polycrystalline samples are prepared by spark plasma sintering. Bi 2 Si 2 Te 6 shows a p-type semiconductor transport behavior and exhibits an intrinsically low lattice thermal conductivity of ~0.48 Wm -1 K -1 (cross-plane) at 573 K. The first-principles density functional theory calculations indicate that such low lattice thermal conductivity is derived from the interactions between acoustic phonons and low-lying optical phonons, local vibrations of Bi, the low Debye temperature and strong anharmonicity result from the unique 2D crystal structure and metavalent bonding of Bi 2 Si 2 Te 6 . The Bi 2 Si 2 Te 6 exhibits an optimal figure of merit ZT of ~0.51 at 623 K, which can be further enhanced by the substitution of Bi with Pb. Pb doping leads to a large increase in power factor S 2 σ, from ~4.0 μWcm -1 K- 2 of Bi 2 Si 2 Te 6 to ~8.0 μWcm -1 K -2 of Bi 1.98 Pb 0.02 Si 2 Te 6 at 775 K, owing to the increase in carrier concentration. Moreover, Pb doping induces a further reduction in the lattice thermal conductivity to ~0.38 Wm -1 K -1 (cross-plane) at 623 K in Bi 1.98 Pb 0.02 Si 2 Te 6 ,. The simultaneous optimization of the power factor and lattice thermal conductivity achieves a peak ZT of ~0.90 at 723 K and a high average ZT of ~0.66 at 400–773 K in Bi 1.98 Pb 0.02 Si 2 Te 6 .

36 MATERIALS SCIENCE↗
DOE OSTI2018

Multiscale topology optimization using neural network surrogate models

In this study, we are concerned with optimization of macroscale elastic structures that are designed utilizing spatially varying microscale metamaterials. The macroscale optimization is accomplished using gradient-based nonlinear topological optimization. But instead of using density as the optimization decision variable, the decision variables are the multiple parameters that define the local microscale metamaterial. This is accomplished using single layer feedforward Gaussian basis function networks as a surrogate models of the elastic response of the microscale metamaterial. The surrogate models are trained using highly resolved continuum finite element simulations of the microscale metamaterials and hence are significantly more accurate than analytical models e.g. classical beam theory. Because the derivative of the surrogate model is important for sensitivity analysis of the macroscale topology optimization, a neural network training procedure based on the Sobolev norm is described. Since the SIMP method is not appropriate for spatially varying lattices, an alternative method is developed to enable creation of void regions. Lastly, the efficacy of this approach is demonstrated via several examples in which the optimal graded metamaterial outperforms a traditional solid structure.

42 ENGINEERING↗
DOE OSTI2016

Thermal transport properties of MoS 2 and MoSe 2 monolayers

Isolation of single to few layer transition metal dichalgogenides open alternate venues in application of 2 dimensional materials to nanoelectronics. Either for general overheating issues or specific application in thermoelectric devices, the characterization of the thermal transport in these new low dimensional materials is needed for their efficient implementation. In this study, lattice thermal conductivities of single layer MoS 2 and MoSe 2 are evaluated using classical molecular dynamics method. The interactions between atoms are defined by Stillinger-Weber type empirical potentials that are developed to represent structural, mechanical, and vibrational properties of the given materials. In parameterization of the potentials, a stochastic optimization algorithm, namely particle swarm optimization is utilized. The final parameter sets produce quite consistent results with DFT in terms of lattice parameters, bond distances, elastic constants and vibrational properties of both single layer MoS 2 and MoSe 2 . The predicted thermal properties of both materials are in very good agreement with earlier first principles calculations. The discrepancies between calculations and experimental measurements are most likely to be caused by pristine nature of the structures in our simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Imaging extended single crystal lattice distortion fields with multi-peak Bragg ptychography

Recent advances in phase-retrieval-based x-ray imaging methods have demonstrated the ability to reconstruct 3D distortion vector fields within a nanocrystal by using coherent diffraction information from multiple crystal Bragg reflections. However, these works do not provide a solution to the challenges encountered in imaging lattice distortions in crystals with significant defect content that result in phase wrapping. Moreover, these methods only apply to isolated crystals smaller than the x-ray illumination, and therefore cannot be used for imaging of distortions in extended crystals. We introduce multi-peak Bragg ptychography which addresses both challenges via an optimization framework that combines stochastic gradient descent and phase unwrapping methods for robust image reconstruction of lattice distortions and defects in extended crystals. Our work uses modern automatic differentiation toolsets so that the method is easy to extend to other settings and easy to implement in high-performance computers. This work is particularly timely given the broad interest in using the increased coherent flux in fourth-generation synchrotrons for innovative material research.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Stochastic Methods for Aircraft Design

The global stochastic optimization method, simulated annealing (SA), was adapted and applied to various problems in aircraft design. The research was aimed at overcoming the problem of finding an optimal design in a space with multiple minima and roughness ubiquitous to numerically generated nonlinear objective functions. SA was modified to reduce the number of objective function evaluations for an optimal design, historically the main criticism of stochastic methods. SA was applied to many CFD/MDO problems including: low sonic-boom bodies, minimum drag on supersonic fore-bodies, minimum drag on supersonic aeroelastic fore-bodies, minimum drag on HSCT aeroelastic wings, FLOPS preliminary design code, another preliminary aircraft design study with vortex lattice aerodynamics, HSR complete aircraft aerodynamics. In every case, SA provided a simple, robust and reliable optimization method which found optimal designs in order 100 objective function evaluations. Perhaps most importantly, from this academic/industrial project, technology has been successfully transferred; this method is the method of choice for optimization problems at Northrop Grumman.

Pelz, Richard B.↗
DOE OSTI2019

Beyond 30% Conversion Efficiency in Silicon Solar Cells: A Numerical Demonstration

We demonstrate through precise numerical simulations the possibility of flexible, thin-film solar cells, consisting of crystalline silicon, to achieve power conversion efficiency of 31%. Our optimized photonic crystal architecture consists of a 15 μm thick cell patterned with inverted micro-pyramids with lattice spacing comparable to the wavelength of near-infrared light, enabling strong wave-interference based light trapping and absorption. Unlike previous photonic crystal designs, photogenerated charge carrier flow is guided to a grid of interdigitated back contacts with optimized geometry to minimize Auger recombination losses due to lateral current flow. Front and back surface fields provided by optimized Gaussian doping profiles are shown to play a vital role in enhancing surface passivation. We carefully delineate the drop in power conversion efficiency when surface recombination velocities exceed 100 cm/s and the doping profiles deviate from prescribed values. These results are obtained by exact numerical simulation of Maxwell’s wave equations for light propagation throughout the cell architecture and a state-of-the-art model for charge carrier transport and Auger recombination.

14 SOLAR ENERGY↗
DOE OSTI2023

Design and additive manufacturing of optimized electrodes for energy storage applications

Supercapacitors exhibit fast charging/discharging ability and have attracted considerable attention within the automotive, aerospace, and telecommunication industries. Porous carbons, prized for their high electrical conductivity and high surface area, have been attractive candidates for supercapacitor electrodes. Moving to thick electrodes is one strategy to further increase energy density due to a higher volume fraction of active material. However, thick electrodes suffer from sluggish charged species transport, which is why thin electrodes are currently favored. In this work, we investigate the use of computational optimization and additive manufacturing to design and fabricate thick porous electrodes with improved performance. Electrode performance was maximized by designing their morphologies via topology optimization and printing by projection micro stereolithography (PμSL) using commercial resin (PR48). The PR48 resin was then pyrolyzed (PR48-P) to create the final conductive electrode. The optimized PR48-P electrodes exhibited 99% improvement in capacitance compared to control electrodes printed with cubic lattice morphologies. To further improve performance, we formulated a resin combining graphene oxide (GO) and trimethylolpropane triacrylate (TMPTA). Electrodes printed with 3 wt% GO in TMPTA exhibited improved capacitance retention after pyrolysis compared to the PR48-P electrodes. Finally, this work demonstrates the benefits of using topology optimization to design electrodes and material development to improve functional properties of 3D printable electrodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Advanced storage ring lattice options based on hybrid six-bend achromat for Stanford Synchrotron Radiation Lightsource upgrade

Three storage ring lattices have been designed as options for a future upgrade of the Stanford synchrotron radiation lightsource (SSRL). The three options differ in circumference and targeted future site, with one to be built in the tunnel of the present SPEAR3 ring, one as a green field ring on the SLAC campus, and the third in the tunnel of the decommissioned PEP-II ring. The lattices are based on the newly proposed hybrid 6-bend achromat (H6BA) lattice cells, which is ideal for pushing the photon beam brightness while achieving excellent nonlinear dynamics performance. The transparent matching conditions are enforced to minimize the negative impact of the loss of periodicity due to insertion of various long straight sections. Numerical optimization is performed to further improve the nonlinear dynamics. Finally, in addition to reaching very low emittances, the lattices can accommodate traditional off-axis injection and achieve beam lifetimes similar to or exceeding that of typical third generation rings.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Quantum Search Approaches to Sampling-Based Motion Planning

In this paper, we present a novel formulation of traditional sampling-based motion planners as database-oracle structures that can be solved via quantum search algorithms. We consider two complementary scenarios: for simpler sparse environments, we formulate the Quantum Full Path Search Algorithm (q-FPS), which creates a superposition of full random path solutions, manipulates probability amplitudes with Quantum Amplitude Amplification (QAA), and quantum measures a single obstacle free full path solution. For dense unstructured environments, we formulate the Quantum Rapidly Exploring Random Tree algorithm, q-RRT, that creates quantum superpositions of possible parent-child connections, manipulates probability amplitudes with QAA, and quantum measures a single reachable state, which is added to a tree. As performance depends on the number of oracle calls and the probability of measuring good quantum states, we quantify how these errors factor into the probabilistic completeness properties of the algorithm. We then numerically estimate the expected number of database solutions to provide an approximation of the optimal number of oracle calls in the algorithm. We compare the q-RRT algorithm with a classical implementation and verify quadratic run-time speedup in the largest connected component of a 2D dense random lattice. We conclude by evaluating a proposed approach to limit the expected number of database solutions and thus limit the optimal number of oracle calls to a given number.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Improved crystal orientation and physical properties from single-shot XFEL stills

X-ray free-electron laser crystallography relies on the collection of still-shot diffraction patterns. New methods are developed for optimal modeling of the crystals’ orientations and mosaic block properties. X-ray diffraction patterns from still crystals are inherently difficult to process because the crystal orientation is not uniquely determined by measuring the Bragg spot positions. Only one of the three rotational degrees of freedom is directly coupled to spot positions; the other two rotations move Bragg spots in and out of the reflecting condition but do not change the direction of the diffracted rays. This hinders the ability to recover accurate structure factors from experiments that are dependent on single-shot exposures, such as femtosecond diffract-and-destroy protocols at X-ray free-electron lasers (XFELs). Here, additional methods are introduced to optimally model the diffraction. The best orientation is obtained by requiring, for the brightest observed spots, that each reciprocal-lattice point be placed into the exact reflecting condition implied by Bragg’s law with a minimal rotation. This approach reduces the experimental uncertainties in noisy XFEL data, improving the crystallographic R factors and sharpening anomalous differences that are near the level of the noise.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Tandem bulk oxygen diffusion and surface reactions in reducible metal oxides control redox cycle dynamics

The interplay between bulk oxygen diffusion and surface reactions in reducible metal oxides is key in heterogeneous catalysts, but direct measurements of oxygen mobility, transient kinetics, and in situ spectroscopies have been lacking. Here, we reveal complex dynamic behavior of ceria-zirconia by H 2 using transient kinetics via mass spectrometry and in situ Raman and near-ambient pressure x-ray photoelectron spectroscopies. Molecular dynamics simulations with a machine learning potential delineate competitive oxygen diffusion mechanisms, with an optimal mobility at intermediate reductions. We expose a compensation between vacancy availability and lattice distortion at intermediate to high reductions and Frenkel defects at low reductions, underscoring a potential deficiency of 16 O/ 18 O exchange experiments in deducing oxygen mobility. Vacancies in proximity require electron localization on Ce atoms further away. The continuous replenishment of surface oxygen results in a varying reduction rate, with H 2 dissociation being the rate-limiting step. Multiscale transient simulations, consistent with experiments, indicate catalysts of potentially spatially varying oxidation states. The approach is broadly applicable to reducible oxide materials.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Determining interface structures in vertically aligned nanocomposite films

Vertically aligned nanocomposites (VANs) films have self-assembled pillar-matrix nanostructures. Owing to their large area-to-volume ratios, interfaces in VAN films are expected to play key roles in inducing functional properties, but our understanding is hindered by limited knowledge about their structures. Motivated by the lack of definitive explanation for the experimentally-found enhanced ionic conductivity in Sm-doped-Ce0 2 /SrTiO 3 VAN films, we determine the structure at vertical interfaces using random structure searching and explore how it can affect ionic conduction. Interatomic potentials are used to perform the initial searching, followed by firstprinciples calculations for refinement. Previously unknown structures are found, with lower energy than that of an optimized hand-built model. We find a strongly distorted oxygen sub-lattice which gives a complex landscape of vacancy energies. The cation lattice remains similar to the bulk phase, but has a localized strain field. The excess energy of the interface is similar to that of a high angle grain boundaries in SrTiO 3 . None of the observations supports ionic conductivity being enhanced locally at the interface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Machine learned interatomic potential for dispersion strengthened plasma facing components

Tungsten (W) is a material of choice for the divertor material due to its high melting temperature, thermal conductivity, and sputtering threshold. However, W has a very high brittle-to-ductile transition temperature, and at fusion reactor temperatures (≥1000 K), it may undergo recrystallization and grain growth. Dispersion-strengthening W with zirconium carbide (ZrC) can improve ductility and limit grain growth, but much of the effects of the dispersoids on microstructural evolution and thermomechanical properties at high temperatures are still unknown. We present a machine learned Spectral Neighbor Analysis Potential for W–ZrC that can now be used to study these materials. In order to construct a potential suitable for large-scale atomistic simulations at fusion reactor temperatures, it is necessary to train on ab initio data generated for a diverse set of structures, chemical environments, and temperatures. Further accuracy and stability tests of the potential were achieved using objective functions for both material properties and high temperature stability. Additionally, validation of lattice parameters, surface energies, bulk moduli, and thermal expansion is confirmed on the optimized potential. Tensile tests of W/ZrC bicrystals show that although the W(110)–ZrC(111) C-terminated bicrystal has the highest ultimate tensile strength (UTS) at room temperature, observed strength decreases with increasing temperature. At 2500 K, the terminating C layer diffuses into the W, resulting in a weaker W–Zr interface. Meanwhile, the W(110)–ZrC(111) Zr-terminated bicrystal has the highest UTS at 2500 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

MOCVD Growth and Characterization of ZnSnN 2

Since the first few reports of its synthesis in 2011 and 20121-3, interest in ZnSnN 2 for diverse applications, including photovoltaics1,3,4, visible light photocatalysis5, and optoelectronics, has been growing. Novel nitride-based LED device designs promise high gains in efficiency at emission wavelengths into the green, amber and even red.6-8 Their realization requires the precise insertion of an ultrathin layer of ZnGeN 2 or ZnSnN 2 into the active region of an InGaAs-GaAs LED structure. While thin films of ZnSnN 2 have been synthesized by RF sputtering1,9 and by MBE 2,10,11, and thin films of ZnGeN 2 , ZnSiN 2 and their alloys by MOCVD, the synthesis of ZnSnN 2 thin films by MOCVD has not yet been reported. It is a challenging goal, given the narrow temperature window between efficient activation of ammonia and the thermal decomposition of ZnSnN 2 at near-atmospheric pressures. We report here the results of studies of ZnSnN 2 films grown on r- and c-plane sapphire substrates, GaN templates on sapphire, and In 0.15 Ga 0.85 N templates on GaN-on-sapphire, at temperatures from 500 °C to 560 °C, using tetramethyltin (TMSn), diethylzinc (DEZn), germane and ammonia. Chamber pressures were varied between 200 and 500 torr. In addition, the ratios of the cation precursors and the total cation-to-anion precursor ratios were varied. Single crystal growth, as evidenced by 2θ-ω x-ray diffraction scans, was achieved on all of these substrates. Wurtzitic (0002) ZnSnN 2 diffraction were observed at 2θ ~ 32.90 for the samples grown on c-sapphire, GaN (0001) and InGaN (0001) templates, and wurtzitic (11-20) peak at 2θ ~ 54.80 for the films grown on r-sapphire. Higher pressures and higher temperatures promoted better crystallinity and more continuous films, as revealed by scanning electron microscopy (SEM) images and 2θ-ω x-ray diffraction peak widths and intensities. Crystal quality was observed to be highly dependent on growth temperature. For example, in one series a 10 °C change in growth temperature resulting in a factor of 15 increase in diffraction peak intensity. SEM images show that films grown on the GaN templates had better uniformity in nucleation than those grown on sapphire. The presence of satellite peaks around the Bragg peak in the XRD 2θ-ω scan for a film grown on a GaN template, and the absence of satellite peaks for the films grown simultaneously on c- and r-sapphire, also indicate superior quality for the film grown on GaN. HAADF-STEM images of films grown on these templates showed smooth interfaces at the film-substrate boundary and show growth rates as high as 167 nm/h, considerably higher than reported previously for MBE growth.9,10 Electron diffraction patterns show single crystallinity. Rocking curves show FWHM as low as 0.100. RMS surfaces roughnesses, measured by atomic force microscopy, are of the order of 3 nm for 1µm x 1µm areas. Current work is focusing on optimizing growth on InGaN templates. These templates are promising for their relatively lower lattice mismatch with ZnSnN 2 . Their use is a next step toward producing LED device structures.

Jayatunga, Benthara Hewage Dinushi↗
DOE OSTI2025

Preliminary Look at the LBEG & MPEG Beam Transmissions between HPSim and Operation Data

This report summarizes recent work on estimating the transmission of LANSCE H- beams from the end of the present DTL to both the PSR stripper foil (LBEG) and WNR target 4 (MPEG). The LBEG beam might be considered a more typical LINAC beam and lends itself to continuous monitoring of transmission through the various stages of the accelerator. For the MPEG, however, the widely-spaced micropulses and lack of the requisite sensitivity current monitors throughout the accelerator make these measurements extremely difficult and more uncertain. Therefore, to assist in estimating the MPEG beam transmission, beam-dynamics simulations using HPSim were employed. These beam transmission estimates from the end of the Drift Tube Linac (DTL) to Target 4 (MPEG) and the PSR stripper foil (LBEG) are vital to determine the charge requirements for LAMP’s front end. In this technote, we demonstrate three major efforts in determining the transmission: (1) Convert the WNR beamline lattice from TRANSPORT to HPSim for use in the simulation; (2) Simulate the optimization process in the Central Control Room (CCR) that brings down the losses by up to a factor of 4000 between the end of the initial physics-based tuneup phase and production beam operation; (3) Analyze operational data to deduce measured transmissions. Table 1 shows the estimated losses with HPSim and operational analysis. Finally, a better measurement and other improvements to refine the results are also proposed.

43 PARTICLE ACCELERATORS↗
NASA NTRS1979

Optimized aerodynamic design process for subsonic transport wing fitted with winglets

The aerodynamic design of a wind-tunnel model of a wing representative of that of a subsonic jet transport aircraft, fitted with winglets, was performed using two recently developed optimal wing-design computer programs. Both potential flow codes use a vortex lattice representation of the near-field of the aerodynamic surfaces for determination of the required mean camber surfaces for minimum induced drag, and both codes use far-field induced drag minimization procedures to obtain the required spanloads. One code uses a discrete vortex wake model for this far-field drag computation, while the second uses a 2-D advanced panel wake model. Wing camber shapes for the two codes are very similar, but the resulting winglet camber shapes differ widely. Design techniques and considerations for these two wind-tunnel models are detailed, including a description of the necessary modifications of the design geometry to format it for use by a numerically controlled machine for the actual model construction.

Kuhlman, J. M.↗
DOE OSTI2025

Ceramic Composite Inert Matrix Fuel Forms in High-Temperature Gas-Cooled Microreactors

Here, this work optimizes micro-prismatic high-temperature gas reactor (HTGR) designs to reduce the energy-normalized mass of spent nuclear fuel (SNF) and high-level waste (HLW) produced. The optimization was performed for the current graphite moderator and an inert matrix fuel (IMF) concept employing different composite moderators in a prismatic design architecture. The fuel matrix is magnesium oxide (MgO) with entrained tristructural-isotropic (TRISO) fuel. The moderator materials, including beryllium oxide (MgO-BeO) and beryllium (MgO-Be) at 40 vol % loading and yttrium hydride (MgO-YH x=1.9 ) and zirconium hydride (MgO-ZrH x=1.9 ) at 15 vol % loading, were entrained within the MgO host matrix. A generic graphite micro-prismatic HTGR is used as the baseline point design where the external dimensions are held constant. The composite moderator designs use 19.9% enriched uranium nitride TRISO fuel and hexagonal assemblies. For each IMF concept, an optimization study was performed to maximize the discharge burnup of the fuel by varying the TRISO packing fraction and the lattice pitch of the assemblies. The mass of SNF and HLW, other waste metrics, fuel cost, environmental impact metrics, and the activity of the SNF and HLW at 100 years and 100 000 years were calculated for the optimized IMF and graphite reference designs. The IMF results were subsequently compared to those of the graphite reference and the values for a light water reactor (LWR) and a small modular LWR. For the SNF and HLW, all the IMF concepts and the graphite reference produced less waste compared to the traditional LWR designs. However, the IMF concepts outperformed the graphite reference regarding the mass of SNF and HLW. For the other waste metrics, the IMF concepts showed reductions in fuel cost with improved environmental metrics relative to the graphite reference. Overall, the IMF concepts significantly reduced the SNF and HLW produced per unit of energy generated compared to traditional LWR designs.

TRISO↗