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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 1,189 records · Page 66

All sources NASA NTRS DOE OSTI

DOE OSTI2016

Si:SrTiO 3 -Al 2 O 3 -Si:SrTiO 3 multi-dielectric architecture for metal-insulator-metal capacitor applications

We present that metal-insulator-metal (MIM) capacitors comprised of amorphous Si:SrTiO 3 -Al 2 O 3 -Si:SrTiO 3 multi-dielectric architecture have been fabricated employing a combination of pulsed laser and atomic layer deposition techniques. The voltage linearity, temperature coefficients of capacitance, dielectric and electrical properties upon thickness were studied under a wide range of temperature (200–400 K) and electric field stress (61.5 MV/cm). A high capacitance density of 31 fF/μm 2 , a low voltage coefficient of capacitance of 363 ppm/V 2 , a low temperature coefficient of capacitance of <644 ppm/K, and an effective dielectric constant of 133 are demonstrated in a MIM capacitor with 1.4 nm capacitance equivalent thickness in a 40 nm thick ultra high-k multi-dielectric stack. Finally, all of these properties make this dielectric architecture of interest for next generation, highly scaled MIM capacitor applications.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Distributed deep learning training using silicon photonic switched architectures

The scaling trends of deep learning models and distributed training workloads are challenging network capacities in today’s datacenters and high-performance computing (HPC) systems. We propose a system architecture that leverages silicon photonic (SiP) switch-enabled server regrouping using bandwidth steering to tackle the challenges and accelerate distributed deep learning training. In addition, our proposed system architecture utilizes a highly integrated operating system-based SiP switch control scheme to reduce implementation complexity. To demonstrate the feasibility of our proposal, we built an experimental testbed with a SiP switch-enabled reconfigurable fat tree topology and evaluated the network performance of distributed ring all-reduce and parameter server workloads. The experimental results show up to 3.6× improvements over the static non-reconfigurable fat tree. Our large-scale simulation results show that server regrouping can deliver up to 2.3× flow throughput improvement for a 2× tapered fat tree and a further 11% improvement when higher-layer bandwidth steering is employed. The collective results show the potential of integrating SiP switches into datacenters and HPC systems to accelerate distributed deep learning training.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Subspace recursive Fermi-operator expansion strategies for large-scale DFT eigenvalue problems on HPC architectures

Quantum mechanical calculations for material modeling using Kohn–Sham density functional theory (DFT) involve the solution of a nonlinear eigenvalue problem for N smallest eigenvector-eigenvalue pairs, with N proportional to the number of electrons in the material system. Here, these calculations are computationally demanding and have asymptotic cubic scaling complexity with the number of electrons. Large-scale matrix eigenvalue problems arising from the discretization of the Kohn–Sham DFT equations employing a systematically convergent basis traditionally rely on iterative orthogonal projection methods, which are shown to be computationally efficient and scalable on massively parallel computing architectures. However, as the size of the material system increases, these methods are known to incur dominant computational costs through the Rayleigh–Ritz projection step of the discretized Kohn–Sham Hamiltonian matrix and the subsequent subspace diagonalization of the projected matrix. This work explores the potential of polynomial expansion approaches based on recursive Fermi-operator expansion as an alternative to the subspace diagonalization of the projected Hamiltonian matrix to reduce the computational cost. Subsequently, we perform a detailed comparison of various recursive polynomial expansion approaches to the traditional approach of explicit diagonalization on both multi-node central processing unit and graphics processing unit architectures and assess their relative performance in terms of accuracy, computational efficiency, scaling behavior, and energy efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A hybrid neural architecture: Online attosecond x-ray characterization

The emergence of high-repetition-rate x-ray free-electron lasers (XFELs), such as SLAC’s LCLS-II, serves as our canonical example for autonomous controls that necessitate high-throughput diagnostics paired with streaming computational pipelines capable of single-shot analysis with extremely low latency. We present the deterministic characterization with an integrated parallelizable hybrid resolver architecture, a hybrid machine learning framework designed for fast, accurate analysis of XFEL diagnostics using angular streaking-based sinogram images. This architecture integrates convolutional neural networks and bidirectional long short-term memory models to denoise input, identify x-ray sub-spike features, and extract sub-spike relative delays with sub-30 attosecond temporal resolution. Deployed on low-latency hardware, it achieves over 10 kHz throughput with 168.3 μs inference latency, indicating scalability to 14 kHz with field-programmable gate array integration. By transforming regression tasks into classification problems and leveraging optimized error encoding, we achieve high precision with low-latency performance that is critical for real-time streaming event selection and experimental control feedback signals. This represents a key development in real-time control pipelines for next-generation autonomous science, generally, and high repetition-rate x-ray experiments in particular.

Accelerator Physics (physics.acc-ph)↗

DOE OSTI2025

Phycobilisome core architecture influences photoprotective quenching by the Orange Carotenoid Protein

Photosynthetic organisms rely on sophisticated photoprotective mechanisms to prevent oxidative damage under high or fluctuating solar illumination. Cyanobacteria, which have evolved a unique, water-soluble light-harvesting complex—the phycobilisome—achieve photoprotection through a photoactivatable quencher called the Orange Carotenoid Protein (OCP). Phycobilisomes are highly symmetric and modular, formed by hierarchical assembly of conserved subunits into diverse geometries ranging from simple bundles to elaborate fan- or bouquet-like macromolecular architectures. Although OCP is known to provide photoprotection across species of cyanobacteria with different phycobilisome structures, it is not known whether or how these structural variations relate to changes in the photoprotective function of OCP. For example, OCP was recently discovered to bind as a dimer at two specific instances of an abundant structural motif on the tricylindrical phycobilisome of Synechocystis sp. PCC 6803, yet these sites are sterically inaccessible on a more common pentacylindrical phycobilisome ( Anabaena sp. PCC 7120). To understand how structural modularity and binding specificity contribute to conservation of OCP binding sites and function across different phycobilisome architectures, here we compare experimentally measured photophysical states accessible to these prototypical tricylindrical and pentacylindrical phycobilisomes, with and without OCP, at the single-molecule level. Together with Monte Carlo simulations of exciton transfer in OCP-quenched phycobilisomes, our results suggest that OCP binds at distinct and specific sites in each type of phycobilisome, yet provides nearly identical quenching strength to both phycobilisomes. Our findings highlight the utility of modular phycobilisome structures in balancing robust conservation of photoprotective function with adaptability of site-specific binding across species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Correlational selection and genetic architecture shape the evolution of the leaf economics spectrum in a perennial grass

The generality of the worldwide leaf economics spectrum (LES) has made it a pillar of trait-based ecological research. Yet, few studies have examined the processes shaping the evolution of the LES within species, in part, because most species occupy only a small portion of the LES. Here, to address this gap, we took advantage of the distinct leaf economics strategies present in different ecotypes of the phenotypically diverse perennial grass Panicum virgatum (switchgrass) to generate a genetic mapping population, which we planted in common gardens at three sites spanning 12 degrees of latitude in the central United States. With this genetic mapping population, we evaluated two potentially interacting causes of LES evolution: 1) genetic architecture, where multiple traits are influenced by either the same gene (pleiotropy) or by genes in close physical proximity (genetic linkage), and 2) correlational selection, where selection acts on traits in combination rather than in isolation. We found that shared genetic architecture influenced covariation between photosynthetic rate (A MASS ) and leaf nitrogen (N MASS ) and between A MASS and leaf mass per area (LMA). We also found that correlational selection favored the trait combinations predicted by the LES (e.g., high LMA with low N MASS or low LMA with high N MASS ) and disfavored other, mismatched trait combinations at two of the three sites. Together, these results demonstrate how the evolution of an integrated LES within species can arise from multiple evolutionary causes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Benchmarking high performance computing architectures with CMS’ skeleton framework

Here, in 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta, Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Characterization of an architecture for front-end pixel binning in an integrating pixel array detector

Optimization of an area detector involves compromises between various parameters like frame rate, read noise, dynamic range and pixel size. We have implemented and tested a novel front-end binning design in a photon-integrating hybrid pixel array detector using the MM-PAD- 2.0 pixel architecture. In this architecture, the pixels can be optionally binned in a 2 x 2 pixel configuration using a network of switches to selectively direct the output of 4 sensor pixels to a single amplifier input. Doing this allows a trade-off between frame rate and spatial resolution. Tests show that the binned pixels perform well, but with some degradation on performance as compared to an un-binned pixel. The increased parasitic input capacitance does reduce the signal collected per x-ray as well as increases the noise of the pixel. Here, the increase in noise is, however, less than the factor of 2 increase one would observe for binning in post-processing. Spatial scans across the binned pixels show that no measured signal intensity is lost at the inner binning unit boundaries. In the high flux regime, at a 2 x 2 pixel wide beam spot (FWHM) size, binned mode responds linearly up to a photon flux of 10 7 x-rays/s, and performs comparably with un-binned mode up to a photon flux of 10 8 x-rays/s. While this study demonstrates a proof of concept for front-end binning in integrating detectors, we also identify changes to this early-stage prototype which can further improve the performance of binning pixel structures.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Integration of EDWARD readout architecture in full-field fluorescence imaging detector

Data bandwidth, timing resolution and resource utilization in readouts of radiation detectors are a constant challenge. Event driven solutions are pushing against well-trenched framed solutions. The idea for an asynchronous readout architecture called EDWARD ( E vent- D riven W ith A ccess and R eset D ecoder) was presented at the TWEPP 2021 conference. Here we show the progress of our work which resulted in two chip prototypes. The first one, named 3FI65P1, is a full device with the analog pixel circuitry suited for full-field fluorescence imaging. It is already manufactured, and preliminary results are presented. Finally, the second chip, named EDWARD65P1, contains digital pulse generators with Poisson-exponential distribution in each pixel for extraction of the performance matrix of the EDWARD architecture alone.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

NASMDR: a framework for miRNA-drug resistance prediction using efficient neural architecture search and graph isomorphism networks

Abstract As a frontier field of individualized therapy, microRNA (miRNA) pharmacogenomics facilitates the understanding of different individual responses to certain drugs and provides a reasonable reference for clinical treatment. However, the known drug resistance-associated miRNAs are not yet sufficient to support precision medicine. Although existing methods are effective, they all focus on modelling miRNA-drug resistance interaction graphs, making their performance bounded by the interaction density. In this study, we propose a framework for miRNA-drug resistance prediction through efficient neural architecture search and graph isomorphism networks (NASMDR). NASMDR uses attribute information instead of the commonly used interactive graph information. In the cross-validation experiment, the proposed framework can achieve an AUC of 0.9468 on the ncDR dataset, which is 2.29% higher than the state-of-the-art method. In addition, we propose a novel sequence characterization approach, k-mer Sparse Nonnegative Matrix Factorization (KSNMF). The results show that NASMDR provides novel insights for integrating efficient neural architecture search and graph isomorphic networks into a unified framework to predict drug resistance-related miRNAs. The codes for NASMDR are available at https://github.com/kaizheng-academic/NASMDR.

Zheng, Kai↗

DOE OSTI2024

Architecture of TOI-561 planetary system

ABSTRACT We present new observations from CHEOPS (CHaracterising ExOPlanet Satellite) and TESS (Transiting Exoplanet Survey Satellite) to clarify the architecture of the planetary system hosted by the old Galactic thick disc star TOI-561. Our global analysis, which also includes previously published photometric and radial velocity data, incontrovertibly proves that TOI-561 is hosting at least four transiting planets with periods of 0.44 d (TOI-561 b), 10.8 d (TOI-561 c), 25.7 d (TOI-561 d), and 77.1 d (TOI-561 e) and a fifth non-transiting candidate, TOI-561f with a period of 433 d. The precise characterization of TOI-561’s orbital architecture is interesting since old and metal-poor thick disc stars are less likely to host ultrashort-period super-Earths like TOI-561 b. The new period of planet -e is consistent with the value obtained using radial velocity alone and is now known to be $77.14399\pm 0.00025$ d, thanks to the new CHEOPS and TESS transits. The new data allowed us to improve its radius ($R_p = 2.517 \pm 0.045\,\mathrm{ R}_{\rm{\oplus }}$ from 5 per cent to 2 per cent precision) and mass ($M_p = 12.4 \pm 1.4\, \mathrm{ M}_{\rm{\oplus }}$) estimates, implying a density of $\rho _p = 0.778 \pm 0.097\, \rho _{\rm{\oplus }}$. Thanks to recent TESS observations and the focused CHEOPS visit of the transit of TOI-561 e, a good candidate for exomoon searches, the planet’s period is finally constrained, allowing us to predict transit times through 2030 with 20-min accuracy. We present an updated version of the internal structure of the four transiting planets. We finally performed a detailed stability analysis, which confirmed the long-term stability of the outer planet TOI-561 f.

Piotto, G. (ORCID:0000000299376387)↗

DOE OSTI2018

Thrombopoietin signaling to chromatin elicits rapid and pervasive epigenome remodeling within poised chromatin architectures

Thrombopoietin (TPO) is a critical cytokine regulating hematopoietic stem cell maintenance and differentiation into the megakaryocytic lineage. However, the transcriptional and chromatin dynamics elicited by TPO signaling are poorly understood. Here, we study the immediate early transcriptional and cis-regulatory responses to TPO in hematopoietic stem/progenitor cells (HSPCs) and use this paradigm of cytokine signaling to chromatin to dissect the relationship between cis-regulatory activity and chromatin architecture. We show that TPO profoundly alters the transcriptome of HSPCs, with key hematopoietic regulators being transcriptionally repressed within 30 min of TPO. By examining cis-regulatory dynamics and chromatin architectures, we demonstrate that these changes are accompanied by rapid and extensive epigenome remodeling of cis-regulatory landscapes that is spatially coordinated within topologically associating domains (TADs). Moreover, TPO-responsive enhancers are spatially clustered and engage in preferential homotypic intra- and inter-TAD interactions that are largely refractory to TPO signaling. By further examining the link between cis-regulatory dynamics and chromatin looping, we show that rapid modulation of cis-regulatory activity is largely independent of chromatin looping dynamics. Finally, we show that, although activated and repressed cis-regulatory elements share remarkably similar DNA sequence compositions, transcription factor binding patterns accurately predict rapid cis-regulatory responses to TPO.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Unified architecture for quantum lookup tables

Quantum access to arbitrary classical data encoded in unitary black-box oracles underlies interesting data-intensive quantum algorithms, such as machine learning or electronic structure simulation. The feasibility of these applications depends crucially on gate-efficient implementations of these oracles, which are commonly some reversible versions of the Boolean circuit for a classical lookup table. Here, we present a general parametrized architecture for quantum circuits implementing a lookup table that encompasses all prior work in realizing a continuum of optimal trade-offs between qubits, non-Clifford gates, and error resilience, up to logarithmic factors. Our architecture assumes only local 2D connectivity, yet recovers results, with the appropriate parameters, polylogarithmic error scaling. We also identify regimes, such as simultaneous sublinear scaling, in all parameters. These results enable tailoring implementations of the commonly used lookup table primitive to any given quantum device with constrained resources.

quantum circuits↗

DOE OSTI2019

Electrochemical-Reaction-Driven Interfacial Stress in a Solid-Solid Layered Architecture

Reaction-driven interfacial growth causes significant strain in layered architectures accompanied by mass transfer and moving boundaries. We present an analytical construct of the stress generated in a multilayer film, which incorporates the elastic-plastic strain of the growth layer, which suggests its strong dependence on the mechanical properties and thickness. This analytical formalism is further applied to a layered all-solid-state lithium battery architecture. This study demonstrates that mechanical stability can be enhanced by using a positive electrode material with high stiffness, porous hosts for lithium plating, and small external elastic constraints to buffer the volumetric changes in the electrode material. Furthermore, our results also reveal that small surface flaws in the solid electrolyte and high internal hydrostatic pressure can alleviate lithium dendrite growth through surface cracks.

25 ENERGY STORAGE↗

DOE OSTI2024

Self-assembled reconfigurable pump architectures via magnetic colloidal swarms

Self-assembled swarms of interactive active units, which are adaptive and dynamically reconfigurable to accommodate different functionalities, represent a promising platform for the development of next-generation robotics. Here, we utilize the emergent collective behavior of active magnetic colloids confined in quasi-two-dimensional arrays of overlapping wells to demonstrate the self-organization of a colloidal swarm into a dynamic pump architecture capable of controlled transport of passive cargo particles. This dynamic architecture provides a global unidirectional looping flow pattern along the entire length of the system. We show that the flow direction of the dynamic swarm-based pump can be externally controlled by a phase shift of a driving magnetic field energizing the swarm. The experimental observations are supported by computational modeling based on phenomenological coarse-grained particle dynamics coupled to shallow-water Navier-Stokes hydrodynamics. In conclusion, our findings demonstrate how the emergent collective behavior of a swarm can be orchestrated into a desired functionality by exploiting the interplay between activity and confinement potentials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Fail-Safe Logic Design Strategies Within Modern FPGA Architectures

Fail-safe computing refers to computing systems that revert to a non-operational safe state when a fault occurs. In this paper, we investigate a circuit level technique as mitigation for single event upsets (SEUs) and fault injection attacks on field programmable gate arrays (FPGAs), and analyze the effectiveness of the technique as a fail-safe monitor for an encryption algorithm. The propagation of fault effects through FPGA primitives including lookup tables (LUTs) and programmable interconnect points (PIPs) is assessed within an FPGA architecture created using an open source tool, and validated using fault injection experiments on an FPGA. The analysis reveals additional vulnerabilities exist within reconfigurable architectures over those in equivalent fail-safe application specific integrated circuit (ASIC), thus requiring a more elaborate network of redundant circuits and checking logic. The configuration memory bits (CMBs), which configure routing and designate logic functions within the LUTs of the FPGA, add complexity to fail-safe design strategies by introducing additional fault conditions and fault propagation paths. A resource-efficient fail-safe circuit design technique called DEsign for Fail-safe in reCONfigurable systems (DEFCON) is proposed. The benefits and limitations associated with DEFCON are described in the context of fault injection experiments carried out as simulations and in FPGA hardware.

Bhakta, Priya A. [Univ. of New Mexico, Albuquerque↗

DOE OSTI2016

Kernels for scalable data analysis in science: Towards an architecture-portable future

In this paper, we pose and address some of the unique challenges in the analysis of scientific Big Data on supercomputing platforms. Our approach identifies, implements and scales numerical kernels that are critical to the instantiation of theory-inspired analytic workflows on modern computing architectures. We present the benefits of scalable kernels towards constructing algorithms such as principal component analysis and non-negative matrix factorization on an image-analysis use case at the Oak Ridge Leadership Computing Facility (OLCF). Based on experience with the use-case, we conclude that piecing scalable analytic kernels into user-defined analytic workflows are a flexible, modular and agile way to enable architecture-portable productivity for the data-intensive sciences.

Sukumar, Sreenivas R.↗

DOE OSTI2019

Architecture for Utility-Scale Multi-Chemistry Battery Energy Storage

The next generation of utility-scale energy storage will be composed of modular systems and autoconfiguring software. This is key to incorporating battery management systems (BMS) and power electronic converters (PEC) from multiple manufacturers into a cohesive single system. In this paper, an agent-based architecture which supports the integration of numerous BMSs and PECs is proposed. This architecture supports optimization and control of the entire system and can be used in many different energy storage technologies.

Smith, Mitchell↗