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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

ClusterCAD: a computational platform for type I modular polyketide synthase design

Here, we present ClusterCAD, a web-based toolkit designed to leverage the collinear structure and deterministic logic of type I modular polyketide synthases (PKSs) for synthetic biology applications. The unique organization of these megasynthases, combined with the diversity of their catalytic domain building blocks, has fueled an interest in harnessing the biosynthetic potential of PKSs for the microbial production of both novel natural product analogs and industrially relevant small molecules. However, a limited theoretical understanding of the determinants of PKS fold and function poses a substantial barrier to the design of active variants, and identifying strategies to reliably construct functional PKS chimeras remains an active area of research. In this work, we formalize a paradigm for the design of PKS chimeras and introduce ClusterCAD as a computational platform to streamline and simplify the process of designing experiments to test strategies for engineering PKS variants. ClusterCAD provides chemical structures with stereochemistry for the intermediates generated by each PKS module, as well as sequence- and structure-based search tools that allow users to identify modules based either on amino acid sequence or on the chemical structure of the cognate polyketide intermediate. ClusterCAD can be accessed at https://clustercad.jbei.org and at http://clustercad.igb.uci.edu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Measuring water fluxes in forests: The need for integrative platforms of analysis

To understand the importance of analytical tools such as those provided by Berdanier et al. (2016) in this issue of Tree Physiology , one must understand both the grand challenges facing Earth system modelers, as well as the minutia of engaging in ecophysiological research in the field. It is between these two extremes of scale that many ecologists struggle to translate empirical research into useful conclusions that guide our understanding of how ecosystems currently function and how they are likely to change in the future. Likewise, modelers struggle to build complexity into their models that match this sophisticated understanding of how ecosystems function, so that necessary simplifications required by large scales do not themselves change the conclusions drawn from these simulations. As both monitoring technology and computational power increase, along with the continual effort in both empirical and modeling research, the gap between the scale of Earth system models and ecological observations continually closes. In addition, this creates a need for platforms of model–data interaction that incorporate uncertainties in both simulations and observations when scaling from one to the other, moving beyond simple comparisons of monthly or annual sums and means.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Thin-film lithium niobate on diamond as a platform for efficient spin-phonon coupling

Negatively charged silicon vacancy (SiV − ) centers in diamond are leading candidates for solid-state quantum memory that can be controlled using electromagnetic or acoustic waves. The latter are particularly promising due to the strong strain response of SiV − , enabling large spin-phonon interaction strengths. Indeed, coherent spin control via surface acoustic waves (SAWs) has been demonstrated and is essential for developing on-chip phononic quantum networks. However, the absence of piezoelectricity in diamond requires an interface with a piezoelectric material for efficient transduction and delivery of acoustic waves to spins in diamonds. Here, we demonstrate a heterogeneously integrated phononic platform that combines thin-film lithium niobate with diamond to enable acoustic control of single SiV − spins. Additionally, leveraging large SAW-induced strain at the location of SiV − , we achieve coherent acoustic control of an electron spin with more than twofold improvement in Rabi frequency compared to state-of-the-art devices based on aluminum nitride on diamond. Furthermore, this work represents a crucial step towards realizing phonon-based quantum information processing systems.

Optically detected magnetic resonance↗
DOE OSTI2021

Cold ion beam in a storage ring as a platform for large-scale quantum computers and simulators: Challenges and directions for research and development

The purpose of this paper is to evaluate the possibility of constructing a large-scale storage-ring-type ion-trap system capable of storing, cooling, and controlling a large number of ions as a platform for scalable quantum computing (QC) and quantum simulations. In such a trap, the ions form a crystalline beam moving along a circular path with a constant velocity determined by the frequency and intensity of the cooling lasers. In this paper, we consider a large leap forward in terms of the number of ions that serve as qubits in QC, from fewer than 100 available in state of the art linear ion-trap devices today to an order of 10 5 crystallized ions in the storage-ring setup. This new trap design unifies two different concepts: the storage rings of charged particles and the linear ion traps used for QC and mass spectrometry. In this paper, we use the language of particle accelerators to discuss the ion state and dynamics. We outline the differences between the above concepts, analyze challenges of the large ring with a revolving chain of ions, and propose goals for the research and development required to enable future quantum computers with 1000 times more qubits than available today. The challenge of creating such a large-scale quantum system while maintaining the necessary coherence of the qubits and the high fidelity of quantum logic operations is significant. Performing analog quantum simulations may be an achievable initial goal for such a device. Quantum calculations and simulations of complex quantum systems will move forward both the fundamental science and the applied research. Nuclear and particle physics, many-body quantum systems, lattice gauge theories, and nuclear structure calculations are just a few examples in which a large-scale quantum simulation system will become a very powerful tool to move forward our understanding of nature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Time-reversal invariant topological moiré flat band: A platform for the fractional quantum spin Hall effect

Motivated by recent observation of the quantum spin Hall effect in monolayer germanene and twisted bilayer transition-metal-dichalcogenides (TMDs), we study the topological phases of moir twisted bilayers with time-reversal symmetry and spin sz conservation. By using a continuum model description which can be applied to both germanene and TMD bilayers, we show that at small twist angles the emergent moir flat bands can be topologically nontrivial due to inversion symmetry breaking. Each of these flat bands admits a lowest-Landau-level description for each spin projection in the chiral limit and at magic twist angle. Furthermore, this allows for the construction of a many-body Laughlin state with time-reversal symmetry which can be stabilized by a short-range pseudopotential, and therefore serves as an ideal platform for realizing the so-far elusive fractional quantum spin Hall effect with emergent spin-1/2 U(1) symmetry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Solid-state platform for cooperative quantum dynamics driven by correlated emission

While traditionally regarded as an obstacle to quantum coherence, recent breakthroughs in quantum optics have shown that the dissipative interaction of a qubit with its environment can be leveraged to protect quantum states and synthesize many-body entanglement. Inspired by this progress, here we set the stage for the—as yet uncharted—exploration of analogous cooperative phenomena in hybrid solid-state platforms. We develop a comprehensive formalism for the quantum many-body dynamics of an ensemble of solid-state spin defects interacting with the magnetic field fluctuations of a common solid-state reservoir. Our framework applies to any solid-state reservoir whose fluctuating spin, pseudospin, or charge degrees of freedom generate magnetic fields. To understand whether correlations induced by dissipative processes can play a relevant role in a realistic experimental setup, we apply our model to a qubit array interacting via the spin fluctuations of a ferromagnetic bath. Our results show that the low-temperature collective relaxation rates of the qubit ensemble can display clear signatures of super- and subradiance, i.e., forms of cooperative dynamics traditionally achieved in atomic ensembles. We find that the solid-state analog of these cooperative phenomena is robust against spatial disorder in the qubit ensemble and thermal fluctuations of the magnetic reservoir, providing a route for their feasibility in near-term experiments. Finally, our work lays the foundation for a multiqubit approach to quantum sensing of solid-state systems and the direct generation of many-body entanglement in spin-defect ensembles. Furthermore, we discuss how the tunability of solid-state reservoirs opens up novel pathways for exploring cooperative phenomena in regimes beyond the reach of conventional quantum optics setups.

NV centers↗
DOE OSTI2019

Direct-drive double-shell implosion: A platform for burning-plasma physics studies

Double-shell ignition designs have been investigated with the indirect-drive inertial confinement fusion (ICF) scheme in both simulations and experiments in which the inner-shell kinetic energy was limited to ~10 to 15 kJ, even driven by megajoule-class lasers such as the National Ignition Facility. Since direct-drive ICF can couple more energy to the imploding shells, we have performed a detailed study on direct-drive double-shell (D 3 S) implosions with state-of-the-art physics models implemented in radiation-hydrodynamic codes (LILAC and DRACO), including nonlocal thermal transport, cross-beam energy transfer (CBET), and first-principles-based material properties. To mitigate classical unstable interfaces, we have proposed the use of a tungsten/beryllium–mixed inner shell with gradient-density layers that can be made by magnetron sputtering. In our D 3 S designs, a 70-μm-thick beryllium outer shell is driven symmetrically by a high-adiabat (α ≥ 10), 1.9-MJ laser pulse to a peak velocity of ~240 km/s. Upon spherical impact, the outer shell transfers ~30 to 40 kJ of kinetic energy to the inner shell filled with deuterium–tritium gas or liquid, giving neutron-yield energies of ~6 MJ in 1-D simulations. Two-dimensional high-mode DRACO simulations indicated that such high-adiabat D 3 S implosions are not susceptible to laser imprint, but the long-wavelength perturbations from the laser port configuration along with CBET can be detrimental to the target performance. Yet, neutron yields of ~0.3- to 1.0-MJ energies can still be obtained from our high-mode DRACO simulations. The robust α-particle bootstrap is readily reached, which could provide a viable platform for burning-plasma physics studies. Once CBET mitigation and/or more laser energy becomes available, we believe that breakeven or moderate energy gain might be feasible with the proposed D 3 S scheme.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Demonstration of a diamond anvil cell platform at the Linac Coherent Light Source: capabilities and outlook

A novel X-ray free electron laser (XFEL) diffraction setup for use with diamond anvil cells (DACs) at the Linac Coherent Light Source (LCLS) is described. The new diamond window at the Matter at Extreme Conditions (MEC) instrument allows hard X-ray experiments on DACs to be performed in air. The platform is described along with alignment and calibration procedures, and details of the X-ray beam and diagnostics. Example data are presented, including a reversible XFEL-induced phase transition in CsPbI 3 . The DAC setup was commissioned at MEC, but is applicable to most LCLS instruments where the unique pulse structures available at LCLS offer access to new ultrafast experimental techniques at high pressure.

Linac Coherent Light Source (LCLS)↗
DOE OSTI2016

Applications of thin-film sandwich crystallization platforms

Crystallization via sandwiches of thin polymer films is presented and discussed. Examples are shown of protein crystallization in, and data collection from, solutions sandwiched between thin polymer films using vapour-diffusion and batch methods. The crystallization platform is optimal for both visualization and in situ data collection, with the need for traditional harvesting being eliminated. In wells constructed from the thinnest plastic and with a minimum of aqueous liquid, flash-cooling to 100 K is possible without significant ice formation and without any degradation in crystal quality. The approach is simple; it utilizes low-cost consumables but yields high-quality data with minimal sample intervention and, with the very low levels of background X-ray scatter that are observed, is optimal for microcrystals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

PRISTINE: An Emulation Platform for PCB-Level Hardware Trojans

Printed circuit Boards (PCBs) are becoming increasingly vulnerable to malicious design alteration, also known as Trojan attacks, due to a distributed business model that often involves various untrusted parties. Such attacks can be mounted at various stages in the PCB life cycle. The relative ease of alteration of PCB hardware even after fabrication (due to physical access to surface-mounted critical components and traces) makes them attractive for an adversary to manipulate their functional/physical behavior for malicious intent. There is a growing need to explore viable Trojan attacks in a PCB, analyze their functional and physical characteristics (e.g., impact on power or delay), and study the effectiveness of countermeasures against these attacks. While simulation-based approaches for PCB Trojan insertion are effective at creating a large population of possible Trojans, they fail to provide functional feasibility analysis with a realistic workload for a trigger circuit. Also, they cannot estimate a Trojan’s side-channel footprint due to the unavailability of physical models of diverse PCB components. To address these deficiencies, in this paper, we present PRISTINE, a PCB-level emulation system for any integrity or physical tampering issues, specifically, hardware Trojan insertion. The need for building such an emulation platform to resolve PCB trust issues in the supply chain is also surveyed and discussed. Both custom Hardware Hacking (HaHa) boards and multiple commercial PCBs are then used to test the ability of the proposed system to emulate various hardware Trojans specially designed to exploit board-specific hardware characteristics. Experimental results on emulated board-level Trojans show that a wide range of Trojans can be successfully activated, thus enabling the expected payload effects on both types of boards to be studied and quantified. The resulting data are further analyzed to create PCB-level Trojan benchmarks. In particular, a comparative evaluation of the experimental results is used to propose a risk level metric that quantifies the probability of detection and degree of payload impact of each Trojan on a given commercial PCB.

47 OTHER INSTRUMENTATION↗
DOE OSTI2011

Software realization of real-time neutrons and {gamma}-rays pulse shape discrimination using CUDA platform

The two pulse shape discrimination methods were implemented in real-time. The pulse gradient analysis method was implemented programmatically on PC. The method based on artificial neural network was programmatically implemented using CUDA platform. It is shown that both implementations can provide up to 10{sup 6} pulses per second processing performance. The results for pulse shape discrimination using polycrystalline stilbene and LiF detectors were shown. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Integration of Multiple Real-time Simulation Platforms with AIO for Scalability

This paper introduces a practical and scalable approach to extend interoperability of Controller Hardware in the Loop (CHIL) validations for large scale microgrids, networked microgrids, and power electronics-based feeders. The work focuses on integrating multiple real-time simulators using Analog Input/Output (AIO) interface techniques in heterogeneous CHIL environment. It explores interfacing methods, highlighting key challenges related to dynamic accuracy and maintaining bidirectional power balance. A comparative evaluation of the Ideal Transformer Method is presented, assessing its effectiveness in multi-CHIL integration scenarios. The feasibility of this setup is demonstrated through a real-time use case involving multiple Typhoon HIL and Opal-RT platforms, showcasing its applicability for distributed system studies.

Khalid, Mohammad [ORNL] (ORCID:0000000179208805)↗
DOE OSTI2017

Scaling Up Data-Parallel Analytics Platforms: Linear Algebraic Operation Cases

Linear algebraic operations such as matrix manipulations form the kernel of many machine learning and other crucial algorithms. Scaling up as well as scaling out such algorithms are key to supporting large scale data analysis that require efficient processing over millions of data samples. To this end, we present, ARION, a hardware acceleration based approach for scaling-up individual tasks of Spark, a popular data-parallel analytics platform. We support both linear algebraic operations of between two dense matrices, and between sparse and dense matrices in distributed environments. ARION provides a flexible control of acceleration according to matrix density, along with efficient scheduling based on runtime resource utilization. We demonstrate the benefit of our approach for general matrix multiplication operations over large matrices with up to four billion elements by using Gramian matrix computation that is commonly used in machine learning. Experiments show that our approach achieves more than 2× and 1.5× end-to-end performance speedups for dense and sparse matrices, respectively, and up to 57.04× faster computation compared to MLlib, a state of the art Spark-based implementation. This work is sponsored in part by the NSF under the grants: CNS-1565314, CNS-1405697, and CNS-1615411. The manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

Xu, Luna↗
DOE OSTI2022

Accelerating Scientific Workflows on HPC Platforms with In Situ Processing

Scientific workflows drive most modern large-scale science breakthroughs by allowing scientists to define their computations as a set of jobs executed in a given order based on their data dependencies. Workflow management systems (WMSs) have become key to automating scientific workflows-executing computational jobs and orchestrating data transfers between those jobs running on complex high-performance computing (HPC) platforms. Traditionally, WMSs use files to communicate between jobs: a job writes out files that are read by other jobs. However, HPC machines face a growing gap between their storage and compute capabilities. To address that concern, the scientific community has adopted a new approach called in situ, which bypasses costly parallel filesystem I/O operations with faster in-memory or in-network communications. When using in situ approaches, communication and computations can be interleaved. In this work, we leverage the Decaf in situ dataflow framework to accelerate task-based scientific workflows managed by the Pegasus WMS, by replacing file communications with faster MPI messaging. We propose a new execution engine that uses Decaf to manage communications within a sub-workflow (i.e., set of jobs) to optimize inter-job communications. We consider two workflows in this study: (i) a synthetic workflow that benchmarks and compares file- and MPI-based communication; and (ii) a realistic bioinformatics workflow that computes mu-tational overlaps in the human genome. Experiments show that in situ communication can improve the bioinformatics workflow execution time by 22% to 30% compared with file communication. Our results motivate further opportunities and challenges for bridging traditional WMSs with in situ frameworks.

Decaf↗
DOE OSTI2017

High-Throughput Computing on High-Performance Platforms: A Case Study

The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan -- a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i) a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner.

Oleynik, D↗
DOE OSTI2018

A Comprehensive Informative Metric for Analyzing HPC System Status Using the LogSCAN Platform

Log processing by Spark and Cassandra-based ANalytics (LogSCAN) is a newly developed analytical platform that provides flexible and scalable data gathering, transformation and computation. One major challenge is to effectively summarize the status of a complex computer system, such as the Titan supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). Although there is plenty of operational and maintenance information collected and stored in real time, which may yield insights about short- and long-term system status, it is difficult to present this information in a comprehensive form. In this work, we present system information entropy (SIE), a newly developed metric that leverages the powers of traditional machine learning techniques and information theory. By compressing the multivariant multi-dimensional event information recorded during the operation of the targeted system into a single time series of SIE, we demonstrate that the historical system status can be sensitively represented concisely and comprehensively. Given a sharp indicator as SIE, we argue that follow-up analytics based on SIE will reveal in-depth knowledge about system status using other sophisticated approaches, such as pattern recognition in the temporal domain or causality analysis incorporating extra independent metrics of the system.

Hui, Yawei↗
DOE OSTI2018

A comparison of Amazon Web Services and Microsoft Azure cloud platforms for high performance computing

Advances in commercial cloud computing necessitate continual evaluation of the cloud's performance on a variety of applications. This work looks at compute oriented instances from Amazon Web Services and Microsoft Azure cloud platforms and evaluates them with several high-performance computing benchmarks, including HPCC and HPCG. These benchmarks illustrate that the most cost competitive solution depends on the application to be run.

Kotas, Charlotte↗