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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 307 records · Page 17

Nickel-incorporated Oxide Composites for Fiber-Optic Based Gas Sensing

Numerous high-value applications within the energy sector involve environmental conditions that are incompatible with traditional sensor technology due to degradation of electrical interconnects, packaging, or the sensors themselves. These can include chemically harsh conditions, high temperature operation, or the presence of electromagnetic interference due to high voltage. The fiber optic platform, constructed of robust, electrically insulating glass or single crystal oxides, offers a versatile and often low cost per node solution to this problem, especially with the integration of distributed sensing techniques such as optical time-domain and frequency-domain reflectometry (OTDR, OFDR). A major challenge of gas and chemical sensing on the optical fiber platform is the fabrication of robust and stable sensing materials that interact quickly and reversibly to the presence of the target analytes. In this work, we discuss the utilization of nickel-incorporated oxides on evanescent-field optical fiber sensors for gas sensing under harsh conditions relevant to multiple energy infrastructure applications. This paper will discuss a Ni/GDC (Ni / Gd-doped ceria) based sensing layer targeting conditions relevant for high-temperature (up to at least 800oC) hydrogen sensing applications (e.g., for operation within a solid oxide fuel cell or electrolyzer). The impact of hydrogen at elevated temperatures on the optical properties of Ni/GDC will be shown and the material mechanisms for the optical response will be discussed.

gas sensors↗

Automatic Data Distribution for CFD Applications on Structured Grids

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAPT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAPT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

Frumkin, Michael↗

Automatic Data Distribution for CFD Applications on Structured Grids

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAFT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAFT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

Frumkin, Michael↗

Providencia Island White Papers: Overview of Technical Requirements for Interconnection

This issue brief provides an overview of key technical requirements for inverter-based resources - including distributed energy resources (DERs) - to support the reliable and safe operation of the Providencia Island electrical grid, and other island or isolated area mini-grid applications. With the planned increase in inverter-based resources and the introduction of energy storage, adopting Institute of Electrical and Electronics Engineers (IEEE) Std 1547-2018, including the more advanced performance capabilities for voltage and frequency ride-through, will simplify interconnection as well as help to maintain a safe, reliable grid on Providencia Island.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Magnetic Solitons and Thickness‐Dependent Magnetization Reversal in Interconnected Helical Nanowire Arrays

By expanding magnetic nanostructures into the third dimension, it is possible to introduce new interactions and realize new forms of magnetic textures and emergent phenomena. Consequently, this unlocks new opportunities for applications in data storage, unconventional computing and sensing by utilizing 3D devices with enhanced functionalities. Connected magnetic nanowires offer a unique platform for applications such as neuromorphic computing due to their tunability and the presence of multiple transport pathways. However to realize this promise, it is necessary to further our understanding of how to locally control the magnetization in 3D, nanowire-based geometries. In this work we show the formation of magnetic domain walls, vortices, anti-vortices, and linked vortex-anti-vortex pairs in interconnected helical nanowire arrays. We show how wire diameter and 3D geometric design can control the states that form and reveal the magnetization reversal mechanism. Hence, we demonstrate this to be a highly tunable system, where the magnetization can be readily reconfigured by an external magnetic field.

3D Nanomagnetism↗

Communication engine for hybrid interconnect technologies

Systems, apparatuses, and methods for dynamically selecting between wired and wireless interconnects for sending packets are disclosed. A system includes at least a hybrid communication engine and a plurality of interconnects for connecting to various end-points. The communication engine dynamically discovers and utilizes the best interconnect technology available in between given end-points. The communication engine dynamically chooses the physical interconnect that is best suited at any given time to send data from one source to one or multiple destinations. This communication can be either on-chip or across nodes. The communication engine makes a decision based on a set of predetermined parameters that can be re-adjusted by the application layer, such as latency of the transmission, message data size, physical distance from source to destination, the energy cost, and the current congestion on the alternative interconnects.

Blagodurov, Sergey↗

Aeroelastic effects in multi-rotor vehicles with application to a hybrid heavy lift system. Part 1: Formulation of equations of motion

This report presents a set of governing coupled differential equations for a model of a hybrid aircraft. The model consists of multiple rotor systems connected by an elastic interconnecting structure, with options to add any combination of or all of the following components; i.e., thrusters, a buoyant hull, and an underslung weight. The dynamic equations are written for the individual blade with hub motions, for the rigid body motions of the whole model, and also for the flexible modes of the interconnecting structure. One of the purposes of this study is to serve as the basis of a numerical study aimed at determining the aeroelastic stability and structural response characteristics of a Hybrid Heavy Lift Airship (HHLA). It is also expected that the formulation may be applicable to analyzing stability and responses of dual rotor helicopters such as a Heavy Lift Helicopter (HLH). Futhermore, the model is capable of representing coupled rotor/body aeromechanical problems of single rotor helicopters.

Venkatesan, C.↗

Simplified interconnection structure based on C 60 /SnO 2-x for all-perovskite tandem solar cells

The efficiencies of all-perovskite tandem devices are improving quickly. However, their complex interconnection layer (ICL) structures – with typically four or more layers deposited by different processes – limit their prospects for applications. Here, we report an ICL in all-perovskite tandem cells consisting merely of a fullerene layer and a SnO 2-x (0 60 layer is unintentionally n-doped by iodine ions from the perovskite and thus acts as an effective electron collecting layer. The SnO 2-x layer, formed by the incomplete oxidization of tin (x=1.76), has ambipolar carrier transport property enabled by the presence of a large density of Sn 2+ . The C 60 /SnO 1.76 ICL forms Ohmic contacts with both wide and narrow bandgap perovskite subcells with low contact resistivity. The ICL boosts the efficiencies of small-area tandem cells (5.9 mm 2 ) and large-area tandem cells (1.15 cm 2 ) to 24.4% and 22.2%, respectively. Lastly, the tandem cells remain 94% of its initial efficiency after continues 1-sun illumination for 1,000 hours.

14 SOLAR ENERGY↗

Effect of Acid Etching Time in Ti 3 C 2 MXene’s Interlayer Spacing and Conductivity

Materials with sheet-like morphologies often form interconnected networks of layers or flakes, offering continuous channels for electron and ion transport in electrochemical energy storage applications. One such material is the recently discovered class of 2-D transition metal carbides/nitrides, called MXene, whose general formula is M n+1 X n T x (where M = transition metal; n = 1, 2, or 3; X = carbon or nitrogen; and T x = termination group such as –F, –OH, and/or =O). Ti 3 C 2 , one of the most studied MXene, can be synthesized by selectively etching the aluminum layer in Ti 3 AlC 2 (also called MAX phase). The most straightforward technique to exfoliate this layer is by wet-chemical etching with high-concentration hydrofluoric acid (HF). In this study, the effect of etching time on the morphology, interlayer spacing, and electrical conductivity of the resultant MXene was studied.

25 ENERGY STORAGE↗

Module-OT: A Hardware Security Module for Operational Technology

Increased penetration levels of renewable energy and other types of distributed energy resources (DERs) on the modern electric grid-combined with technological advancements for electric system monitoring and control-introduce new cyberattack vectors and increase the cyberattack surface of energy systems. According to the IEEE Std. 1547-2018, DERs must use Modbus, Distributed Network Protocol 3 (DNP3), or Smart Energy Profile 2.0 (SEP2) as their communication protocol. Previous research identified several vulnerabilities and security breaches in each one of these communication protocols; despite this, existing standards for DERs do not recommend cybersecurity measures. In order to reduce vulnerabilities in power distribution systems, this paper presents a novel open-source hardware security module that improves both information and operational security to better protect data and communications on the distribution grid. The security hardware is called “module for operational technology,” or simply Module-OT, and it has been validated and tested in an emulated distribution system application. Module-OT is integrated within a communication system in the transport layer of the Open Systems Interconnection (OSI) model. It improves system security through encryption, authentication, authorization, certificate management, and user access control. The main advancement of Module-OT is the addition of hardware cryptographic acceleration that improves the overall communication performance in terms of end-to-end latency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

AI-Enhanced Co-Design for Next-Generation Microelectronics: Innovating Innovation (Workshop Report)

The Artificial Intelligence Enhanced Co-Design for Next Generation Microelectronics virtual workshop was held April 4-5, 2023, and attended by subject matter experts from universities, industry, and national laboratories. This was the third in a series of workshops to motivate the research community to identify and address major challenges facing microelectronics research and production. The 2023 workshop focused on a set of topics from materials to computing algorithms, and included discussions on relevant federal legislation and such as the Creating Helpful Incentives to Produce Semiconductors and Science Act (CHIPS Act) which was signed into law in the summer of 2022. Talks at the workshop included edge computing in radiation environments, new materials for neuromorphic computing, advanced packaging for microelectronics, and new AI techniques. We also received project updates from several of the Department of Energy (DOE) microelectronics co-design projects funded in the fall of 2021, and from three of the Energy Frontier Research Centers (EFRCs) that had been funded in the fall of 2022. The workshop also conducted a set of breakout discussions around the five principal research directions (PRDs) from the 2018 Department of Energy workshop report: 1) define innovative material, device, and architecture requirements driven by applications, algorithms, and software; 2) revolutionize memory and data storage; 3) re-imagine information flow unconstrained by interconnects; 4) redefine computing by leveraging unexploited physical phenomena; 5) reinvent the electricity grid through new materials, devices, and architectures. We tasked each breakout group to consider one primary PRD (and other PRDs as relevant topics arose during discussions) and to address questions such as whether the research community has embraced co-design as a methodology and whether new developments at any level of innovation from materials to programming models requires the research community to reevaluate the PRDs developed back in 2018.

97 MATHEMATICS AND COMPUTING↗

A study of the Space Station Freedom response to the disturbance environment

A relatively general formulation for studying the dynamics and control of an arbitrary spacecraft with interconnected flexible bodies has been developed. This self-contained and comprehensive numerical algorithm using system modes is applicable to a large class of spacecraft configurations of contemporary and future interest. Here, versatility of the approach is demonstrated through the dynamics and control studies aimed at the evolving Space Station Freedom.

Suleman, Afzal↗

Highly Parallel Computing Architectures by using Arrays of Quantum-dot Cellular Automata (QCA): Opportunities, Challenges, and Recent Results

There has been significant improvement in the performance of VLSI devices, in terms of size, power consumption, and speed, in recent years and this trend may also continue for some near future. However, it is a well known fact that there are major obstacles, i.e., physical limitation of feature size reduction and ever increasing cost of foundry, that would prevent the long term continuation of this trend. This has motivated the exploration of some fundamentally new technologies that are not dependent on the conventional feature size approach. Such technologies are expected to enable scaling to continue to the ultimate level, i.e., molecular and atomistic size. Quantum computing, quantum dot-based computing, DNA based computing, biologically inspired computing, etc., are examples of such new technologies. In particular, quantum-dots based computing by using Quantum-dot Cellular Automata (QCA) has recently been intensely investigated as a promising new technology capable of offering significant improvement over conventional VLSI in terms of reduction of feature size (and hence increase in integration level), reduction of power consumption, and increase of switching speed. Quantum dot-based computing and memory in general and QCA specifically, are intriguing to NASA due to their high packing density (10(exp 11) - 10(exp 12) per square cm ) and low power consumption (no transfer of current) and potentially higher radiation tolerant. Under Revolutionary Computing Technology (RTC) Program at the NASA/JPL Center for Integrated Space Microelectronics (CISM), we have been investigating the potential applications of QCA for the space program. To this end, exploiting the intrinsic features of QCA, we have designed novel QCA-based circuits for co-planner (i.e., single layer) and compact implementation of a class of data permutation matrices, a class of interconnection networks, and a bit-serial processor. Building upon these circuits, we have developed novel algorithms and QCA-based architectures for highly parallel and systolic computation of signal/image processing applications, such as FFT and Wavelet and Wlash-Hadamard Transforms.

Fijany, Amir↗

Holographic Optical Data Storage

Although the basic idea may be traced back to the earlier X-ray diffraction studies of Sir W. L. Bragg, the holographic method as we know it was invented by D. Gabor in 1948 as a two-step lensless imaging technique to enhance the resolution of electron microscopy, for which he received the 1971 Nobel Prize in physics. The distinctive feature of holography is the recording of the object phase variations that carry the depth information, which is lost in conventional photography where only the intensity (= squared amplitude) distribution of an object is captured. Since all photosensitive media necessarily respond to the intensity incident upon them, an ingenious way had to be found to convert object phase into intensity variations, and Gabor achieved this by introducing a coherent reference wave along with the object wave during exposure. Gabor's in-line recording scheme, however, required the object in question to be largely transmissive, and could provide only marginal image quality due to unwanted terms simultaneously reconstructed along with the desired wavefront. Further handicapped by the lack of a strong coherent light source, optical holography thus seemed fated to remain just another scientific curiosity, until the field was revolutionized in the early 1960s by some major breakthroughs: the proposition and demonstration of the laser principle, the introduction of off-axis holography, and the invention of volume holography. Consequently, the remainder of that decade saw an exponential growth in research on theory, practice, and applications of holography. Today, holography not only boasts a wide variety of scientific and technical applications (e.g., holographic interferometry for strain, vibration, and flow analysis, microscopy and high-resolution imagery, imaging through distorting media, optical interconnects, holographic optical elements, optical neural networks, three-dimensional displays, data storage, etc.), but has become a prominent am advertising, and security medium as well. The evolution of holographic optical memories has followed a path not altogether different from holography itself, with several cycles of alternating interest over the past four decades. P. J. van Heerden is widely credited for being the first to elucidate the principles behind holographic data storage in a 1963 paper, predicting bit storage densities on the order of 1/lambda(sup 3) with source wavelength lambda - a fantastic capacity of nearly 1 TB/cu cm for visible light! The science and engineering of such a storage paradigm was heavily pursued thereafter, resulting in many novel hologram multiplexing techniques for dense data storage, as well as important advances in holographic recording materials. Ultimately, however, the lack of such enabling technologies as compact laser sources and high performance optical data I/O devices dampened the hopes for the development of a commercial product. After a period of relative dormancy, successful applications of holography in other arenas sparked a renewed interest in holographic data storage in the late 1980s and the early 1990s. Currently, with most of the critical optoelectronic device technologies in place and the quest for an ideal holographic recording medium intensified, holography is once again considered as one of several future data storage paradigms that may answer our constantly growing need for higher-capacity and faster-access memories.

Timucin, Dogan A.↗

Adsorption Hysteresis Under Control: Tuning Host–Guest Interactions via a Genetic Algorithm

Mesoporous adsorbent materials offer a large volumetric capacity; however, cyclic adsorption/desorption processes in these systems often suffer from hysteresis and may require a significant pressure swing to access this capacity. To mitigate hysteresis, a proposed strategy is to include nucleation sites on the walls of the mesoporous material to facilitate droplet and bubble formation, lowering the free energy barriers to the respective phase transitions. It is unclear, however, what combination of adsorbate− adsorbent interactions and spatial patterning would be beneficial for a given application, considering that improvements to some sorption properties may come at the expense of other attributes. To understand these interconnected observables, we examine two model systems, planar-slit and cylindrical pores with tunable interaction sites, using GPU-accelerated transition matrix Monte Carlo simulations. The simulations provide a free energy map of the pressure−adsorption space in a matter of minutes, which we use to track adsorption isotherm characteristics as a function of adsorbent properties. We then leverage the rapid acquisition of simulation data to construct a genetic algorithm to iteratively modify interaction sites of the slit-pore wall to minimize the hysteresis of this system without sacrificing uptake. We find that the adsorption branch of the isotherm is easily modulated via the average host−guest interaction strength, but desorption is only adjustable if there is a suitable bubble nucleation site. Within the context of a slit-pore system, we identify relative interaction strengths and patch sizes required to gain control over both branches of the hysteresis loop.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Analysis of System Balance and Architectural Trends Based on Top500 Supercomputers

Supercomputer design is a complex, multi-dimensional optimization process, wherein several subsystems need to be reconciled to meet a desired figure of merit performance for a portfolio of applications and a budget constraint. However, overall, the HPC community has been gravitating towards ever more FLOPS, at the expense of many other subsystems. To draw attention to overall system balance, in this paper, we analyze balance ratios and architectural trends in the world's most powerful supercomputers. Specifically, we have collected performance characteristics of systems between1993 and 2018 based on the Top500 lists, and then analyzed their architectures from diverse system design perspectives. Notably, our analysis studies the performance balance of the machines, across a variety of subsystems such as compute, memory, I/O, interconnect, intra-node connectivity and power. Our analysis reveals that balance ratios of the various subsystems need to be considered carefully alongside the application workload portfolio to provision the subsystem capacity and bandwidth specifications, which can help achieve optimal performance.

97 MATHEMATICS AND COMPUTING↗

An Analysis of System Balance and Architectural Trends Based on Top500 Supercomputers

Supercomputer design is a complex, multi-dimensional optimization process, wherein several subsystems need to be reconciled to meet a desired figure of merit performance for a portfolio of applications and a budget constraint. However, overall, the HPC community has been gravitating towards ever more Flops, at the expense of many other subsystems. To draw attention to overall system balance, in this paper, we analyze balance ratios and architectural trends in the world’s most powerful supercomputers. Specifically, we have collected the performance characteristics of systems between 1993 and 2019 based on the Top500 lists and then analyzed their architectures from diverse system design perspectives. Notably, our analysis studies the performance balance of the machines, across a variety of subsystems such as compute, memory, I/O, interconnect, intra-node connectivity and power. Our analysis reveals that balance ratios of the various subsystems need to be considered carefully alongside the application workload portfolio to provision the subsystem capacity and bandwidth specifications, which can help achieve optimal performance.

Khan, Awais↗

Characterization of Extremes and Compound Impacts: Applications of Machine Learning and Interpretable Neural Networks

Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.

54 ENVIRONMENTAL SCIENCES↗