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At least 109 records · Page 6

A Cerebellar-model Associative Memory as a Generalized Random-access Memory

A versatile neural-net model is explained in terms familiar to computer scientists and engineers. It is called the sparse distributed memory, and it is a random-access memory for very long words (for patterns with thousands of bits). Its potential utility is the result of several factors: (1) a large pattern representing an object or a scene or a moment can encode a large amount of information about what it represents; (2) this information can serve as an address to the memory, and it can also serve as data; (3) the memory is noise tolerant--the information need not be exact; (4) the memory can be made arbitrarily large and hence an arbitrary amount of information can be stored in it; and (5) the architecture is inherently parallel, allowing large memories to be fast. Such memories can become important components of future computers.

Kanerva, Pentti↗

Structural Diversity in Dimension-Controlled Assemblies of Tetrahedral Gold Nanocrystals

Polyhedron packings have fascinated humans for centuries and continue to inspire scientists of modern disciplines. Despite extensive computer simulations and a handful of experimental investigations, understanding of the phase behaviors of synthetic tetrahedra has remained fragmentary largely due to the lack of tetrahedral building blocks with tunable size and versatile surface chemistry. Here, in this study, we report the remarkable richness of and complexity in dimension-controlled assemblies of gold nanotetrahedra. By tailoring nanocrystal interactions from long-range repulsive to hard-particle-like or to systems with short-ranged directional attractions through control of surface ligands and assembly conditions, nearly a dozen of two-dimensional and three-dimensional superstructures including the cubic diamond and hexagonal diamond polymorphs are selectively assembled. We further demonstrate multiply twinned icosahedral supracrystals by drying aqueous gold nanotetrahedra on a hydrophobic substrate. This study expands the toolbox of the superstructure by design using tetrahedral building blocks and could spur future computational and experimental work on self-assembly and phase behavior of anisotropic colloidal particles with tunable interactions.

36 MATERIALS SCIENCE↗

Development of multi-scale computational frameworks to solve fusion materials science challenges

Over the past two decades, the US-DOE has funded multiple projects that rely on high-performance computing and exascale computing platforms to accelerate scientific discoveries and address grand scientific challenges, such as harnessing fusion energy. In this article, we review in detail one of these efforts aimed at enhancing our capability to model plasma-facing materials subject to plasma and high-energy ion/neutron irradiation. The plasma surface interactions project has built a multi-scale modeling framework where many of the plasma- and high-energy ion/neutron irradiation-induced effects occurring in tungsten are explored. Here, this knowledge is used to develop atomistically-informed, high-fidelity continuum and meso-scale models that can be validated against experiments. We review the developments within this project, with attention to experimental validation efforts, and specifically highlight activities associated with: helium bubble bursting and equation of state, and hydrogen-helium interactions in tungsten; atomistically-informed model development for beryllium-tungsten material mixing; coupling of scrape-of-layer plasma, sheath and material models; and coupling of stochastic cluster-dynamics and crystal plasticity models to address radiation effects in tungsten under stress. Finally, we present how the project is preparing for future computational architectures, for instance through efforts to adapt atomistic methods to exascale computing.

36 MATERIALS SCIENCE↗

Subtle metastability of the layered magnetic topological insulator MnBi 2 Te 4 from weak interactions

Abstract Layered quantum materials can host interesting properties, including magnetic and topological, for which enormous computational predictions have been done. Their thermodynamic stability is much less visited computationally, which however determines the existence of materials and can be used to guide experimental synthesis. MnBi 2 Te 4 is one of such layered quantum materials that was predicted to be an intrinsic antiferromagnetic topological insulator, and later experimentally realized but in a thermodynamically metastable state. Here, using a combined first-principles-based approach that considers lattice, charge, and spin degrees of freedom, we investigate the metastability of MnBi 2 Te 4 by calculating the Helmholtz free energy for the reaction Bi 2 Te 3 + MnTe → MnBi 2 Te 4 . We identify a temperature range (~500–873 K) in which the compound is stable with respect to the competing binary phases, consistent with experimental observation. We validate the predictions by comparing the calculated specific heats contributed from different degrees of freedom with experimental results. Our findings indicate that the degrees of freedom responsible for the van der Waals interaction, lattice vibration, magnetic coupling, and nontrivial band topology in MnBi 2 Te 4 not only enable emergent phenomena but also play a crucial role in determining its thermodynamic stability. This conclusion lays the foundation for the future computational material synthesis of novel layered systems.

36 MATERIALS SCIENCE↗

SERPENT 2 and TRIPOLI-4 neutronics benchmarking of the Jules Horowitz reactor

Jules Horowitz Reactor (JHR) is a future center for nuclear material testing in Europe, currently under construction at CEA Cadarache in southern France. It has been modelled extensively with CEA's HORUS3D/N neutron calculation package, that includes a Monte-Carlo neutron transport code TRIPOLI-4. In order to support the future computational analyses on the reactor core physics, VTT's Monte Carlo neutronics code SERPENT 2 has been used to create an alternative model of the JHR, taking advantage of the pre-existing Constructive Solid Geometry (CSG) structures on which the TRIPOLI-4 model was built. This work describes a benchmark, in which two JHR core configurations were analyzed using both of these models. The first configuration is a fresh fuel core at the beginning of life, in which aluminum based dummy-devices are installed in the reactor test positions. The second configuration represents the end-of-cycle equilibrium core with a heterogeneous burnup distribution, in which CALIPSO devices containing cladding material samples are installed at the in-core experimental positions, while the reflector positions are occupied by DEN-REP devices containing UO{sub 2} fuel. Neutron flux spectra and heat deposition are the parameters of interest in this study, due to their high importance in creating the desired experimental irradiation environment. The impact of delayed gamma energy deposition will be studied in detail, since the two models account for it with different methods. This work aims to establish a SERPENT 2 model of JHR, understanding its differences and agreements with TRIPOLI-4, and discussing its potential future applications. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Hydrogen Activation by Silica Supported Metal Ion Catalysts: Catalytic Properties of Metals and Performance of DFT Functionals

Single-site heterogeneous catalysts (SSHC) have received increasing attention due to their well-defined active sites and potentially high specific activity. Detailed computational studies were carried out on a set of potential SSHC’s, i.e., silica-supported metal ions, to investigate the reactivity of these catalysts with H2 as well as to evaluate the performance of density functional theory (DFT) methods in conjunction with triple-ζ quality basis sets (i.e., cc-pVTZ) on reaction energetics. The ions considered include 4d and 5d metals as well as several post-transition metal ions. A representative cluster model of silica is used to calculate reaction free energies of the metal hydride formation that results from the heterolytic cleavage of H2 on the M–O bond. The hydride formation free energy is previously shown to be strongly correlated with the catalytic activity of such catalysts for alkene hydrogenation. ONIOM calculations (CCSD(T)//MP2) are used to assess the accuracy and reliability of the MP2 results and it is found that MP2 is a suitable level of theory for gauging the performance of DFT functionals. The performance of various DFT functionals is assessed relative to MP2 results and it is found that the wB97xd and PBE0 functionals have the lowest standard deviation (STD) value while the MN12SX and PBE functionals have the lowest mean absolute deviation (MAD) values. The B3LYP functional is shown to have similar MAD and STD values as the top performing functionals. Potential active SSHC’s for exergonic hydrogen activation predicted in this study include mostly late and post transition metal ions, i.e., Au3+, Pd2+, Pt4+, Pd4+, Ir4+, Hg2+, Rh3+, Pb4+, Tl3+, In3+, Ir3+, Os4+, Cd2+, Ru2+, and Ga3+. This study provides important guidance to future computational studies of such catalyst systems.

Plascencia, Cesar↗

Designed Spin‐Texture‐Lattice to Control Anisotropic Magnon Transport in Antiferromagnets

Abstract Spin waves in magnetic materials are promising information carriers for future computing technologies due to their ultra‐low energy dissipation and long coherence length. Antiferromagnets are strong candidate materials due, in part, to their stability to external fields and larger group velocities. Multiferroic antiferromagnets, such as BiFeO 3 (BFO), have an additional degree of freedom stemming from magnetoelectric coupling, allowing for control of the magnetic structure, and thus spin waves, with the electric field. Unfortunately, spin‐wave propagation in BFO is not well understood due to the complexity of the magnetic structure. In this work, long‐range spin transport is explored within an epitaxially engineered, electrically tunable, 1D magnonic crystal. A striking anisotropy is discovered in the spin transport parallel and perpendicular to the 1D crystal axis. Multiscale theory and simulation suggest that this preferential magnon conduction emerges from a combination of a population imbalance in its dispersion, as well as anisotropic structural scattering. This work provides a pathway to electrically reconfigurable magnonic crystals in antiferromagnets.

36 MATERIALS SCIENCE↗

Understanding Europium and Terbium Speciation and Ion Pairing in Carbonate Complexes Using Advanced Spectroscopy Techniques

Lanthanide (Ln) elements are critical materials that are typically extracted/mined together. Their separation by solvent extraction from acidic media is well known; however, there are few studies in basic media with carbonate anions. We investigated the complexation of Eu(III) and Tb(III) carbonates as solids and solutions in alkaline K2CO3, wherein we sought to access a Tb(IV) carbonate complex through ozonolysis. L3-edge XANES of Eu and Tb carbonate solids, colorless solutions, and a red-hued Tb solution (obtained by ozonolysis) all showed Ln(III) cations. The absence of evidence for a Tb(IV) complex was confirmed through XAS and EPR analyses, despite the solution exhibiting a deep red color. For solids and solutions, EXAFS results indicate molecular Ln(III)-carbonato anions. In terms of the Eu(III) carbonate coordination number, the coordination does not change upon dissolution of the solid sample. Furthermore, EXAFS for the solutions revealed evidence for the association of potassium cations with the Ln(III)-carbonato anions. Furthermore, this direct observation of contact ion pairing by EXAFS at room temperature is rare. The insights into Ln(III) carbonate complexation and solution speciation afforded by XANES-EXAFS, FT-IR, and EPR provides perspectives that serve as benchmarks for future computational and experimental efforts focused on caustic-side solvent extraction of Ln(III) ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self‐Strain Suppression of the Metal‐to‐Insulator Transition in Phase‐Change Oxide Devices

Strongly correlated materials exhibiting phase transitions which can be controlled through external stimuli, such as electric fields, are promising for future computing technologies beyond conventional semiconductor transistors. Devices that take advantage of structural phase transitions have inherent built‐in memory, reminiscent of synapses and neurons, and are thus natural candidates for neuromorphic computing. Of particular interest are phase‐change oxides, which allow for control over the metal‐to‐insulator transition. Here, X‐ray nano‐diffraction structural imaging of micro‐devices fabricated with the archetypal phase‐change material vanadium sesquioxide (V 2 O 3 ) is reported. The devices contain a Ga ion‐irradiated region where the metal‐to‐insulator transition critical temperature is lowered, a useful feature for controlling neuron‐like spiking behavior. Results show that strain, induced by crystal lattice mismatch between the pristine and irradiated material, leads to a suppression of the metal‐to‐insulator‐transition. Suppression occurs within the irradiated region or along its edges, depending on the defect‐distribution and the size of the region. The observed self‐straining effect can extend to other phase‐change oxides and dominate as device dimensions are reduced and become too small to dissipate strain within the irradiated region. The findings are important for phase engineering in phase‐change devices and highlight the necessity to study phase transitions at the nanoscale.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Nucleation and growth of tungsten nanotendrils grown under divertor-like conditions

Tungsten is the primary candidate for plasma-facing materials in the critical regions of a magnetic fusion energy (MFE) device, such as a tokamak. However, tungsten (and many other metals) grow copious nanotendril "fuzz" when exposed to fusion-relevant He-bearing plasmas, and the impact of this fuzz on reactor operation is still unknown. Further, the mechanism of fuzz growth is also poorly understood at present. In order to experimentally probe the growth mechanisms, we developed a new sample preparation technique to examine the interface of individual nanotendril roots with the substrate (substrate/tendril interface) using electron microscopy and measured the grain boundary character distributions (GBCDs) of substrate/tendril interfaces, the GBs within individual tendrils (tendril/tendril interfaces), and GBs within the substrate (substrate/substrate interfaces). We find the substrate/tendril and tendril/tendril GBCDs are essentially indistinguishable, but very different from the substrate/substrate GBCDs, which implies that tendril growth periodically forms new GBs at the substrate/tendril interface, and these GBs are pushed upward to become tendril/tendril interfaces within the fuzz mat. These results will help guide future computational modelling studies to elucidate the details of the growth mechanisms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hybrid Nanocrystals of Small Molecules and Chemically Disordered Polymers

Organic crystals formed by small molecules can be highly functional but are often brittle or insoluble structures with limited possibilities for use or processing from a liquid phase. A possible solution is the nanoscale integration of polymers into organic crystals without sacrificing long-range order and therefore function. This enables the organic crystals to benefit from the advantageous mechanical and chemical properties of the polymeric component. We report here on a strategy in which small molecules co-crystallize with side chains of chemically disordered polymers to create hybrid nanostructures containing a highly ordered lattice. Synchrotron X-ray scattering, absorption spectroscopy, and coarse-grained molecular dynamics simulations reveal that the polymer backbones form an “exo-crystalline” layer of disordered chains that wrap around the nanostructures becoming a handle for interesting properties. The morphology of this “hybrid bonding polymer” nanostructure is dictated by the competition between the polymers’ entropy and the enthalpy of the lattice allowing for control over the aspect ratio of the nanocrystal by changing the degree of polymer integration. Further, we observed that nanostructures with an exo-crystalline layer of polymer exhibit enhanced fracture strength, self-healing capacity, and dispersion in water, which benefits their use as light-harvesting assemblies in photocatalysis. Guided by computation, future work could also explore these hybrid nanostructures as building blocks for functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tunneling current-controlled spin states in few-layer van der Waals magnets

Abstract Effective control of magnetic phases in two-dimensional magnets would constitute crucial progress in spintronics, holding great potential for future computing technologies. Here, we report a new approach of leveraging tunneling current as a tool for controlling spin states in CrI 3 . We reveal that a tunneling current can deterministically switch between spin-parallel and spin-antiparallel states in few-layer CrI 3 , depending on the polarity and amplitude of the current. We propose a mechanism involving nonequilibrium spin accumulation in the graphene electrodes in contact with the CrI 3 layers. We further demonstrate tunneling current-tunable stochastic switching between multiple spin states of the CrI 3 tunnel devices, which goes beyond conventional bi-stable stochastic magnetic tunnel junctions and has not been documented in two-dimensional magnets. Our findings not only address the existing knowledge gap concerning the influence of tunneling currents in controlling the magnetism in two-dimensional magnets, but also unlock possibilities for energy-efficient probabilistic and neuromorphic computing.

Science & Technology - Other Topics↗

Non-volatile magnon transport in a single domain multiferroic

Antiferromagnets have attracted significant attention in the field of magnonics, as promising candidates for ultralow-energy carriers for information transfer for future computing. The role of crystalline orientation distribution on magnon transport has received very little attention. In multiferroics such as BiFeO 3 the coupling between antiferromagnetic and polar order imposes yet another boundary condition on spin transport. Thus, understanding the fundamentals of spin transport in such systems requires a single domain, a single crystal. We show that through Lanthanum (La) substitution, a single ferroelectric domain can be engineered with a stable, single-variant spin cycloid, controllable by an electric field. The spin transport in such a single domain displays a strong anisotropy, arising from the underlying spin cycloid lattice. Our work shows a pathway to understanding the fundamental origins of magnon transport in such a single domain multiferroic.

30 DIRECT ENERGY CONVERSION↗

Approaches for handling high-dimensional cluster expansions of ionic systems

Disordered multicomponent systems attract great interest due to their engineering design flexibility and subsequent rich space of properties. However, detailed characterization of the structure and atomic correlations remains challenging and hinders full navigation of these complex spaces. A lattice cluster expansion is one tool to obtain configurational and energetic resolution. While in theory a cluster expansion can be applied to any system of any dimensionality, the method has primarily been used in binary systems or ternary alloys. Here we apply cluster expansions in high-component ionic systems, setting up the largest cluster expansion ever attempted to our knowledge. In doing so, we address and discuss challenges specific to high-component ionic systems, namely charge state assignments, structural relaxations, and rank-deficient systems. We introduce practical procedures to make the fitting and analysis of complex systems tractable, providing guidance for future computational studies of disordered ionic systems.

25 ENERGY STORAGE↗

Reinforcement Learning for Load-balanced Parallel Particle Tracing

We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three novel components: (1) a work donation algorithm, (2) a high-order workload estimation model, and (3) a communication cost model. First, we design an RL-based work donation algorithm. Our algorithm monitors workloads of processes and creates RL agents to donate data blocks and particles from high-workload processes to low-workload processes to minimize program execution time. The agents learn the donation strategy on the fly based on reward and cost functions designed to consider processes' workload changes and data transfer costs of donation actions. Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations. Third, we design a communication cost model that considers both block and particle data exchange costs, helping RL agents make effective decisions with minimized communication costs. We demonstrate that our algorithm adapts to different flow behaviors in large-scale fluid dynamics, ocean, and weather simulation data. Our algorithm improves parallel particle tracing performance in terms of parallel efficiency, load balance, and costs of I/O and communication for evaluations with up to 16,384 processors.

Distributed and parallel particle tracing↗

Geomechanical Simulation of Big Hill Strategic Petroleum Reserve - Calibration of Model Containing Shear Zone

A finite element numerical analysis model, that consists of a realistic mesh capturing the geometries of Big Hill (BH) Strategic Petroleum Reserve (SPR) site using the multi-mechanism deformation (MD) salt constitutive model and including data taken daily of the wellhead pressure and level of the oil-brine interface, has been upgraded. The upgraded model contains the shear zone to examine the interbed behavior in a realistic manner. The salt creep rate is not uniform in the salt dome, and creep test data for BH salt is limited. Therefore, a model calibration is necessary to simulate the geomechanical behavior of the salt dome. Cavern volumetric closures of SPR caverns calculated from sonar survey reports are used for the field baseline measurement. The structure factor, A 2 , and transient strain limit factor, K 0 , in the M-D constitutive model are used for model calibration. An A 2 value obtained experimentally from the BH salt and K 0 value of WIPP salt are used as the baseline values. To adjust the magnitude of A 2 and K 0 , multiplication factors A 2 F and K 0 F are defined, respectively. The A 2 F and K 0 F values of the salt dome and salt drawdown layer of elements surrounding each SPR cavern have been determined through a number of back fitting analyses. The trendlines of the predictions and sonar data match up well for BH 101, 103, 104, 106, 110, 111, 112, and 113. The prediction curves are close to the sonar data for BH 102 and 114. However, the prediction curves for BH 105, 107, 108, and 109 are not close to the sonar data. An inconsistency was found in the sonar data, i.e. the volume measured later is larger than that before in some time intervals, even if the leached volume is taken into account, for BH 101, 104, 106, 107, and 112. Project discussions are needed to determine possibilities on how to resolve the issues and determine the best path forward for future computer modeling attempts.

02 PETROLEUM↗

Towards Quantum-Chemical Level Calculations of SARS-CoV-2 Spike Protein Variants of Concern by First Principles Density Functional Theory

The spike protein (S-protein) is a crucial part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with its many domains responsible for binding, fusion, and host cell entry. In this review we use the density functional theory (DFT) calculations to analyze the atomic-scale interactions and investigate the consequences of mutations in S-protein domains. We specifically describe the key amino acids and functions of each domain, which are essential for structural stability as well as recognition and fusion processes with the host cell; in addition, we speculate on how mutations affect these properties. Such unprecedented large-scale ab initio calculations, with up to 5000 atoms in the system, are based on the novel concept of amino acid–amino acid-bond pair unit (AABPU) that allows for an alternative description of proteins, providing valuable information on partial charge, interatomic bonding and hydrogen bond (HB) formation. In general, our results show that the S-protein mutations for different variants foster an increased positive partial charge, alter the interatomic interactions, and disrupt the HB networks. We conclude by outlining a roadmap for future computational research of biomolecular virus-related systems.

60 APPLIED LIFE SCIENCES↗