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At least 811 records · Page 45

Atomically Thin CBRAM Enabled by 2-D Materials: Scaling Behaviors and Performance Limits

Reducing the energy and power dissipation of conductive bridge random access memory (CBRAM) cells is of critical importance for their applications in future Internet of Things (IoT) device and neuromorphic computing platforms. Atomically thin CBRAMs enabled by 2-D materials are studied theoretically by using 3-D kinetic Monte Carlo simulations together with experimental characterization. The results indicate the performance potential of attoJoule energy dissipation for intrinsic filament formation and a filament size of a single atomistic chain in such a CBRAM cell. The atomically thin CBRAM cells also show qualitatively different features from conventional CBRAM cells, including complete rupture of the filament in the reset stage and comparable forming and set voltages. The scaling and variability of the CBRAM cells down to sub-nanometer size of the switching layer as realized in the experiment are systematically studied, which indicates performance improvement and increased relative variability as the switching layer scales down. Finally, the results establish the ultimate limits of the size and energy scaling for CBRAM cells and illustrate the unique application of 2-D materials in ultralow power memory devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Improving the efficiency of Rubisco by resurrecting its ancestors in the family Solanaceae

Plants and photosynthetic organisms have a remarkably inefficient enzyme named Rubisco that fixes atmospheric CO 2 into organic compounds. Understanding how Rubisco has evolved in response to past climate change is important for attempts to adjust plants to future conditions. In this study, we developed a computational workflow to assemble de novo both large and small subunits of Rubisco enzymes from transcriptomics data. Next, we predicted sequences for ancestral Rubiscos of the (nightshade) family Solanaceae and characterized their kinetics after coexpressing them inEscherichia coli. Predicted ancestors of C 3 Rubiscos were identified that have superior kinetics and excellent potential to help plants adapt to anthropogenic climate change. Our findings also advance understanding of the evolution of Rubisco’s catalytic traits.

59 BASIC BIOLOGICAL SCIENCES↗

Statistical Regularities of Formation of a Main Crack in a Structurally Inhomogeneous Material under Various Deformation Conditions

The peculiarities of the formation of a main crack in the Westerly granite samples under quasistatic uniaxial compression without any lateral upthrust have been studied using the data of acoustic emission (AE) and X-ray computer microtomography (CT). The multifractal analysis of pauses between acoustic emission events and the analysis of the energy distribution functional forms of the AE signal have been performed. According to the computer tomography data, defects form only near a future main crack; i.e., no stage of disperse accumulation of defects over entire sample volume has been revealed. Two stages of the main crack formation have been observed: the first stage is characterized by an exponential energy distribution of AE signals and the second stage is characterized by a power low of the AE signal energy distribution. The multifractal analysis of the pauses between neighboring AE signals demonstrate the transition from the multifractal dynamics of the acoustic emission to the monofractal dynamics when approaching a fracture moment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

An Experimental and Kinetic Modeling Study of Premixed Laminar Flames of Methyl Pentanoate and Methyl Hexanoate

Detailed chemical structures of stoichiometric and rich premixed laminar flames of methyl pentanoate and methyl hexanoate were investigated over a flat burner at 20 Torr and for methyl pentanoate at 1 atm. Molecular beam mass spectrometry was used with tunable synchrotron vacuum ultraviolet (VUV) photoionization for low pressure flames of both methyl pentanoate and methyl hexanoate, and soft electron-impact ionization was used for atmospheric pressure flames of methyl pentanoate. Mole fraction profiles of stable and intermediate species, as well as temperature profiles, were measured in the flames. A detailed chemical kinetic high temperature reaction mechanism for small alkyl ester oxidation was extended to include combustion of methyl pentanoate and methyl hexanoate, and the resulting model was used to compare computed values with experimentally measured values. Reaction pathways for both fuels were identified, with good agreement between measured and computed species profiles. Implications of these results for future studies of larger alkyl ester fuels are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

My Spring with Graphene

Graphene is a two-dimensional structure, one atom thick, with many uses in the world of technology. It has many useful electrical properties, is a very strong and durable material, and can be used to protect different types of substances. The world would be able to use these properties to further the strength of cars, protect metals from oxidation, increase computer speeds, use to improve superconductors, and whatever future uses that scientist invent or discover. We sought to optimize the growth and transfer of graphene. We grew graphene on copper foils by heating the foil in a furnace, and having various gases flow through a tube, where the copper foil was placed. We varied some of the concentrations of gases, along with having different times for heating the copper foil, different times for graphene growth, or a combination of the two. The focus of our experiment was to specifically grow monolayer single crystal graphene, which means that we do not want multiplayers of graphene, and do not want multiple crystals growing to form a bigger crystal. Our goal was to grow large single crystals from the growth experiment. We used a few different types of transfer methods that ranged from: using heat and pressure to press the graphene on different materials, using a polymer to cover the graphene with a method to destroy the copper, but leave the graphene and polymer intact, and using a type of heat tape with a combination of varying pressures to transfer the graphene, and then destroy the copper foil. To discover if we grew graphene we used different techniques involving lasers and microscopes to take different types of measurements. Discovering the best way of growing and transferring graphene will help with managing the cost of the future uses of graphene.

36 MATERIALS SCIENCE↗

Fast Dynamic Simulation-Based Small Signal Stability Assessment and Control

Power grid planning and operation decisions are made based on simulation of the dynamic behavior of the system. Enabling substantial energy savings while increasing the reliability of the aging North American power grid through improved utilization of existing transmission assets hinges on the adoption of wide-area measurement systems (WAMS) for power system stabilization. However, adoption of WAMS alone will not suffice if the power system is to reach its full entitlement in stability and reliability. It is necessary to enhance predictability with "faster than real-time" dynamic simulations that will enable the dynamic stability margins, proactive real-time control, and improve grid resiliency to fast time-scale phenomena such as cascading network failures. Present-day dynamic simulations are performed only during offline planning studies, considering only worst case conditions such as summer peak, winter peak days, etc. With widespread deployment of renewable generation, controllable loads, energy storage devices and plug-in hybrid electric vehicles expected in the near future and greater integration of cyber infrastructure (communications, computation and control), monitoring and controlling the dynamic performance of the grid in real-time would become increasingly important. The state-of-the-art dynamic simulation tools have limited computational speed and are not suitable for real-time applications, given the large set of contingency conditions to be evaluated. These tools are optimized for best performance of single-processor computers, but the simulation is still several times slower than real-time due to its computational complexity. With recent significant advances in numerical methods and computational hardware, the expectations have been rising towards more efficient and faster techniques to be implemented in power system simulators. This is a natural expectation, given that the core solution algorithms of most commercial simulators were developed decades ago, when High Performance Computing (HPC) resources were not commonly available.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NEAMS Workbench 1.0 Beta

The mission of the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems. This is accomplished using computing architectures that range from laptops to leadership-class facilities. The NEAMS Workbench is a new initiative that will facilitate the transition from conventional tools to high-fidelity tools by providing a common user interface for model creation, review, execution, output review, and visualization for integrated codes. The Workbench can use common user input, including engineering scale specifications that are expanded into application-specific input requirements through the use of customizable templates. The templating process enables multi-fidelity analysis of a system from a common set of input data. Additionally, the common user input processor can provide an enhanced alternative application input that provides additional conveniences over the native input, especially for legacy codes. Expansion of the integrated codes and application templates available in the Workbench will broaden the NEAMS user community and will facilitate system analysis and design. Current and planned capabilities of the NEAMS Workbench are detailed here.

97 MATHEMATICS AND COMPUTING↗

HEP Software Foundation Community White Paper Working Group - Detector Simulation

A working group on detector simulation was formed as part of the high-energy physics (HEP) Software Foundation's initiative to prepare a Community White Paper that describes the main software challenges and opportunities to be faced in the HEP field over the next decade. The working group met over a period of several months in order to review the current status of the Full and Fast simulation applications of HEP experiments and the improvements that will need to be made in order to meet the goals of future HEP experimental programmes. The scope of the topics covered includes the main components of a HEP simulation application, such as MC truth handling, geometry modeling, particle propagation in materials and fields, physics modeling of the interactions of particles with matter, the treatment of pileup and other backgrounds, as well as signal processing and digitisation. The resulting work programme described in this document focuses on the need to improve both the software performance and the physics of detector simulation. The goals are to increase the accuracy of the physics models and expand their applicability to future physics programmes, while achieving large factors in computing performance gains consistent with projections on available computing resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Survey of DAKOTA's V&V Capabilities in the Simulation of Residual Stresses in a Simple Composite Structure

Process-induced residual stresses occur in composite structures composed of dissimilar materials. As these residual stresses can result in fracture, their consideration when designing composite parts is necessary. However, the experimental determination of residual stresses in prototype parts can be time and cost prohibitive. Alternatively, it is possible for computational tools to predict potential residual stresses. Therefore, a process modeling methodology was developed and implemented into Sandia National Laboratories' SIERRA/SolidMechanics code. This method can be used to predict the process-induced stresses in any composite structure, regardless of material composition or geometric complexity. However, to develop confidence in these predictions, they must be rigorously validated. Specifically, sensitivity studies should be completed to define which model parameters are critical to the residual stress predictions. Then, the uncertainty associated with those critical parameters should be quantified and processed through the model to develop stress-state predictions encompassing the most important sources of physical variability. Numerous sensitivity analysis and uncertainty quantification methods exist, each offering specific strengths and weaknesses. Therefore, the objective of this study is to compare the performance of several accepted sensitivity analysis and uncertainty quantification methods during the manufacturing process simulation of a composite structure. The examined methods include simple sampling techniques as well as more sophisticated surrogate approaches. The computational costs are assessed for each of the examined methods, and the results of the study indicate that the surrogate approaches are the most computationally efficient validation methods and are ideal for future residual stress investigations.

36 MATERIALS SCIENCE↗

NEAMS Workbench and Bison Fuel Performance Remote Application Configuration

The mission of the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems. This is accomplished using computing architectures that range from laptops to leadership class facilities. The NEAMS Workbench [1,2,3] initiative will facilitate the transition from conventional computer codes to high-fidelity ones by providing a common analysis environment and interface for model creation, review, execution, output review, and visualization for integrated codes. The BISON fuel performance code [4] is a finite element method (FEM)-based software being developed by multiple organizations led by the Idaho National Laboratory for the US Department of Energy Office of Nuclear Energy. BISON can simulate a variety of fuel and cladding compositions and geometries in varying dimensionalities, depending upon the problem type and complexity, including one-dimensional (1D), 1.5D, 2D axially symmetric (2D-rz), 2D radial-azimuthal (2D-rθ), or 3D models. The NEAMS Workbench allows execution of the BISON fuel performance code on local and remote compute resources. In this report, the detailed instructions of configuring the NEAMS Workbench for remote execution of the BISON fuel performance code on a portable batch system (PBS)-scheduled compute resource, as well the transfer of associated Bison files, is illustrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

From Structured Solvents to Hybrid Materials (SS2HM) for Chemically Selective Capture and Electromagnetic Release of CO 2 : Mechanisms, Stability and Interfaces (Final Report)

The goal of this research program was to develop high capacity sorbents amenable for alternative regeneration approaches for direct air capture (DAC) of CO 2 . In particular, the research aimed to develop an understanding of CO 2 binding mechanism, thermal and oxidative stability, and regeneration energetics of functionalized ionic liquids (ILs), deep eutectic solvents (DESs), and porous materials. ILs and DESs are high-dielectric solvents with structural tunability that permits the rational-design for energy-efficient regeneration approaches based on electromagnetic (EM) field and moisture-swing. By further incorporating these solvents into polymeric capsules and other structural supports, multi-scale interfaces for targeted CO 2 and energy transfers were achieved. Aspects related to CO 2 capacity, selectivity, stability, dielectric properties, and binding energies were examined through experimental and computational design to identify molecular descriptors to inform future design of structured solvents and hybrid materials for DAC. Enclosed final report details the key findings, science advancements, and workforce development efforts from this project.

36 MATERIALS SCIENCE↗

thornado+FLASH-X: A Hybrid Discontinuous Galerkin–Implicit-explicit and Finite-volume Framework for Neutrino-radiation Hydrodynamics in Core-collapse Supernovae

We present neutrino-transport algorithms implemented in the toolkit for high-order neutrino-radiation hydrodynamics (thornado) and their coupling to self-gravitating hydrodynamics within the adaptive mesh refinement–based multiphysics simulation framework FLASH-X. thornado, developed primarily for simulations of core-collapse supernovae (CCSNe), employs a spectral, six-species two-moment formulation with algebraic closure and special-relativistic observer corrections accurate to $\mathcal{O}(v/c)$, and uses discontinuous Galerkin (DG) methods for phase-space discretization combined with implicit-explicit time stepping. A key development is a nonlinear neutrino–matter coupling algorithm based on nested fixed-point iteration with Anderson acceleration, enabling fully implicit treatment of collisional processes, including energy-coupling interactions such as neutrino–electron scattering and pair production. Coupling to finite-volume (FV) hydrodynamics is achieved through a hybrid DG-FV representation of the fluid variables and operator-split evolution within FLASH-X. The implementation is verified using basic transport tests with idealized opacities and relaxation and deleptonization problems with tabulated microphysics. Spherically symmetric CCSN simulations demonstrate accuracy and robustness of the coupled scheme, including close agreement with the CCSN simulation code Chimera. An axisymmetric CCSN simulation further demonstrates the viability of DG-based neutrino transport for multidimensional supernova modeling within FLASH-X. thornado’s neutrino-transport solver is GPU-enabled using OpenMP offloading or OpenACC, and all CCSN applications included in this work use the GPU implementation. Together, these results establish a foundation for future enhancements in physics fidelity, numerical algorithms, and computational performance, for increasingly realistic large-scale CCSN simulations.

Endeve, Eirik [Oak Ridge National Laboratory (ORNL↗

Computational Thermodynamic Modeling of Hot Corrosion of Alloys Haynes 242 and Hastelloy TM N for Molten Salt Service in Advanced High Temperature Reactors

An evaluation of thermodynamic aspects of hot corrosion of the superalloys Haynes 242 and HastelloyTM N in the eutectic mixtures of KF and ZrF4 is carried out for development of Advanced High Temperature Reactor (AHTR). This work models the behavior of several superalloys, potential candidates for the AHTR, using computational thermodynamics tool (ThermoCalc), leading to the development of thermodynamic description of the molten salt eutectic mixtures, and on that basis, mechanistic prediction of hot corrosion. The results from these studies indicated that the principal mechanism of hot corrosion was associated with chromium leaching for all of the superalloys described above. However, HastelloyTM N displayed the best hot corrosion performance. This was not surprising given it was developed originally to withstand the harsh conditions of molten salt environment. However, the results obtained in this study provided confidence in the employed methods of computational thermodynamics and could be further used for future alloy design efforts. Finally, several potential solutions to mitigate hot corrosion were proposed for further exploration, including coating development and controlled scaling of intermediate compounds in the KF-ZrF4 system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

STEADY STATE MODELING OF THE MINIMUM CRITICAL CORE OF THE TRANSIENT REACTOR TEST FACILITY

With the advent of next generation reactor systems and new fuel designs, the U.S. Department of Energy (DOE) has identified the need for the resumption of transient testing of nuclear fuels. The DOE has decided that the Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) is best suited for future testing. TREAT is a thermal neutron spectrum, air-cooled, nuclear test facility that is designed to test nuclear fuels in transient scenarios. These specific scenarios range from simple temperature transients to full fuel melt accidents. DOE has expressed a desire to develop a simulation capability that will accurately model the experiments before they are irradiated at the facility. It is the aim for this capability to have an emphasis on effective and safe operation while minimizing experimental time and cost. The multi physics platform MOOSE has been selected as the framework for this project. The goals for this work are to identify the fundamental neutronics properties of TREAT and to develop an accurate steady state model for future multiphysics transient simulations. In order to minimize computational cost, the effect of spatial homogenization and angular discretization are investigated. It was found that significant anisotropy is present in TREAT assemblies and to capture this effect, explicit modeling of cooling channels and inter-element gaps is necessary. For this modeling scheme, single element calculations at 293 K gave power distributions with a root mean square difference of 0.076% from those of reference SERPENT calculations. The minimum critical core configuration with identical gap and channel treatment at 293 K resulted in a root mean square, total core, radial power distribution 2.423% different than those of reference SERPENT solutions.

Critical↗

Beyond Hosting Capacity: Using Shortest Path Methods to Minimize Upgrade Cost Pathways: Preprint

We present in this paper a graph based forwardlooking algorithm applied to distribution planning in the context of distributed PV penetration. We study the target hosting capacity (THC) problem where the objective is to find the cheapest sequence of system upgrades to reach a predefined hosting capacity target value. We show in this paper that commonly used short-term cost minimization approaches lead most of the time to suboptimal solutions. By comparing our method against such myopic techniques on real distribution systems, we show that our algorithm is able to reduce the overall integration costs by looking at future decisions. Because hosting capacity is hard to compute, this problem requires efficient methods to search the space. We demonstrate here that heuristics using domain specific knowledge can be efficiently used to improve the algorithm performance such that real distribution systems can be studied.

14 SOLAR ENERGY↗

A Learning-based Supervisory Control Architecture for Electric Vehicle Charging System Paired with Energy Storages

A Machine Learning-based predictive model is developed for optimal dispatching energy storage system integrated with Electric Vehicle battery charger. The model is effectively trained using transfer learning algorithm and successfully validated via measurement data to achieve high fidelity and accuracy. The study findings provide possibilities for future development of the presented approach to implement computational heavy predictive algorithms with multi-step predictions in emerging modular bidirectional charger topologies to realize vehicle-to-grid (V2G) technology. The online tuning can be explored using the new measurements obtained during the operation, henceforth, enhancing the controller performance for integrating multiple DERs into distribution power networks that shows huge interest for the utilities and regulatory agencies. Multiple operation scenatios have been evaluated and simulation results are discussed to verify intended performance of the proposed control solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Precision QCD, Hadronic Structure & Forward QCD, Heavy Ions: Report of Energy Frontier Topical Groups 5, 6, 7 submitted to Snowmass 2021

This report was prepared on behalf of three Energy Frontier Topical Groups of the Snowmass 2021 Community Planning Exercise. It summarizes the status and implications of studies of strong interactions in high-energy experiments and QCD theory. We emphasize the rich landscape and broad impact of these studies in the decade ahead. Hadronic interactions play a central role in the high-luminosity Large Hadron Collider (LHC) physics program, and strong synergies exist between the (HL-)LHC and planned or proposed experiments at the U.S. Electron-Ion Collider, CERN forward physics experiments, high-intensity facilities, and future TeV-range lepton and hadron colliders. Prospects for precision determinations of the strong coupling and a variety of nonperturbative distribution and fragmentation functions are examined. We also review the potential of envisioned tests of new dynamical regimes of QCD in high-energy and high-density scattering processes with nucleon, ion, and photon initial states. The important role of the high-energy heavy-ion program in studies of nuclear structure and the nuclear medium, and its connections with QCD involving nucleons are summarized. We address ongoing and future theoretical advancements in multi-loop QCD computations, lattice QCD, jet substructure, and event generators. Cross-cutting connections between experimental measurements, theoretical predictions, large-scale data analysis, and high-performance computing are emphasized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Integration of Titan supercomputer at OLCF with ATLAS Production System

The PanDA (Production and Distributed Analysis) workload management system was developed to meet the scale and complexity of distributed computing for the ATLAS experiment. PanDA managed resources are distributed worldwide, on hundreds of computing sites, with thousands of physicists accessing hundreds of Petabytes of data and the rate of data processing already exceeds Exabyte per year. While PanDA currently uses more than 200,000 cores at well over 100 Grid sites, future LHC data taking runs will require more resources than Grid computing can possibly provide. Additional computing and storage resources are required. Therefore ATLAS is engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. In this paper we will describe a project aimed at integration of ATLAS Production System with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF). Current approach utilizes modified PanDA Pilot framework for job submission to Titan's batch queues and local data management, with lightweight MPI wrappers to run single node workloads in parallel on Titan's multi-core worker nodes. It provides for running of standard ATLAS production jobs on unused resources (backfill) on Titan. The system already allowed ATLAS to collect on Titan millions of core-hours per month, execute hundreds of thousands jobs, while simultaneously improving Titans utilization efficiency. We will discuss the details of the implementation, current experience with running the system, as well as future plans aimed at improvements in scalability and efficiency.

97 MATHEMATICS AND COMPUTING↗