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At least 55 records · Page 3

Embedded Thermal Control for Spacecraft Subsystems Miniaturization

Optimization of spacecraft size, weight and power (SWaP) resources is an explicit technical priority at Goddard Space Flight Center. Embedded Thermal Control Subsystems are a promising technology with many cross cutting NSAA, DoD and commercial applications: 1.) CubeSatSmallSat spacecraft architecture, 2.) high performance computing, 3.) On-board spacecraft electronics, 4.) Power electronics and RF arrays. The Embedded Thermal Control Subsystem technology development efforts focus on component, board and enclosure level devices that will ultimately include intelligent capabilities. The presentation will discuss electric, capillary and hybrid based hardware research and development efforts at Goddard Space Flight Center. The Embedded Thermal Control Subsystem development program consists of interrelated sub-initiatives, e.g., chip component level thermal control devices, self-sensing thermal management, advanced manufactured structures. This presentation includes technical status and progress on each of these investigations. Future sub-initiatives, technical milestones and program goals will be presented.

Thermal Control↗

Standardizing Microprocessor and GPU Radiation Test Approaches

Microprocessor, Graphics Processing Units (GPUs) and DDRx memory devices have emerged as promising next-generation technologies that enables both high performance processing and acceleration of complex algorithms for the latest challenges in human spaceflight, autonomous vehicles and artificial intelligence (AI). The feature sets of these devices offer exponential increases to throughput, calculation capability and system autonomy when compared to legacy flight systems. NASA's Electronic Part and Packaging (NEPP) Program has conducted an investigation into the radiation susceptibility of leading edge devices and process technologies by establishing standardized test approaches. Unlike most discrete devices, these require state of the art test systems to induce specific hardware activity similar to application software, thus allowing the characterization of failure modes within the system. To best characterize the tested part, NEPP eliminates variables that may impact device performance under radiation. Simplification of remaining system-level variables leads to an improved understanding of complex computational devices and their intended applications. The failure modes and error signatures that are recorded during testing are used to determine radiation sensitivity of the semiconductor process and the microcode architecture of the design. This presentation will discuss the test methodology that NASA Electronic Parts and Packaging (NEPP) is working to establish for its microprocessor, GPU and DDRx memory test programs to provide guidance on these devices and their underlying technology, in regards to their potential usage in future space flight systems.

GPU↗

Roadmap for unconventional computing with nanotechnology

Abstract In the ‘Beyond Moore’s Law’ era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same time, adopting a variety of nanotechnologies will offer benefits in energy cost, computational speed, reduced footprint, cyber resilience, and processing power. The time is ripe for a roadmap for unconventional computing with nanotechnologies to guide future research, and this collection aims to fill that need. The authors provide a comprehensive roadmap for neuromorphic computing using electron spins, memristive devices, two-dimensional nanomaterials, nanomagnets, and various dynamical systems. They also address other paradigms such as Ising machines, Bayesian inference engines, probabilistic computing with p-bits, processing in memory, quantum memories and algorithms, computing with skyrmions and spin waves, and brain-inspired computing for incremental learning and problem-solving in severely resource-constrained environments. These approaches have advantages over traditional Boolean computing based on von Neumann architecture. As the computational requirements for artificial intelligence grow 50 times faster than Moore’s Law for electronics, more unconventional approaches to computing and signal processing will appear on the horizon, and this roadmap will help identify future needs and challenges. In a very fertile field, experts in the field aim to present some of the dominant and most promising technologies for unconventional computing that will be around for some time to come. Within a holistic approach, the goal is to provide pathways for solidifying the field and guiding future impactful discoveries.

Finocchio, Giovanni (ORCID:0000000210433876)↗

Functional Nano-to-Microstructures by Jet Printing and Direct Ink Writing

Jet-based printing techniques and direct ink writing have emerged as complementary, convergent technologies serving as key platforms in additive manufacturing for functional nano- to microscale architectures. This review highlights how these approaches enable fine feature resolution and three-dimensional structures in advanced electronics and biointerfacing applications. The interplay of fluid mechanics, viscoelastic ink rheology, droplet–substrate interactions, and drying dynamics is examined as a critical determinant of printing fidelity. Application-focused case studies, from flexible thin-film transistors to bioprinted artificial tissues, demonstrate how precise structural control via printing translates to enhanced device performance and new functionality in electronic and biological systems. Finally, we discuss the challenges and future opportunities driving the evolution of these printing platforms toward autonomous, adaptive, and intelligent manufacturing systems.

Luo, Junchen [Sichuan Univ. of Arts and Science (C↗

An electro-optical Mott neuron based on niobium dioxide

Various applications—including brain-like computing and on-chip artificial vision—increasingly demand a combination of electronic and photonic techniques. However, integrating both approaches on a single chip is challenging, and solutions typically rely on disparate components with power-hungry signal conversions. Here, in this paper, we report electro-optical Mott neurons that combine visible light emission with electrical threshold switching, as well as neuron-like oscillations. The devices are based on thin films of sputtered niobium dioxide (NbO 2 ), a Mott insulator–metal transition material, operating at room temperature and emitting light that peaks around 810 nm. Operando measurements reveal an electronic origin to the light emission: charge carrier relaxation initiated by high-field transport in the NbO 2 . Our devices combine electrical and optical functions within a single material, thereby expanding the options available for future artificial intelligence hardware.

electrical engineering↗

Operando microscopy for neuromorphic hardware

Microscopy techniques can uncover the physical properties and dynamic behaviours of materials, driving the discovery of emergent phenomena and guiding the design of next-generation computing hardware. As artificial intelligence becomes pervasive, the demand for high-performance materials to support sustainable information technologies is growing. Here, this Review highlights state-of-the-art imaging from electron and X-ray to optical techniques to probe the dynamics of neuromorphic materials, including operando characterization of devices. We examine design principles for neuromorphic materials, along with obstacles that hinder their development. Emphasis is placed on spatially and temporally resolved approaches that capture state changes including phase transitions, ferroic switching and spin-wave propagation that emulate biological components such as neurons, synapses and their connectivity. We discuss challenges in operando characterization and the integration of artificial intelligence-driven analysis for feedback-guided material discovery. Finally, we outline opportunities for real-time imaging of neuromorphic systems, paving the way towards adaptive, brain-inspired hardware.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

AutoTG: Reinforcement Learning-Based Symbolic Optimization for AI-Assisted Power Converter Design

Power converters are pervasive in modern electronic component design. They can be found in all electronic devices from household appliances and cellphone chargers to vehicles. Currently, designing new circuit topologies is hard because it requires human expertise based on experience and is difficult to automate. However, artificial-intelligence-assisted design can significantly facilitate the development of new power converters and/or improve the final result. Intelligently designed highly efficient power converters can have a significant effect on many important attributes, such as power efficiency, layout size, cost, heat dissemination, energy requirements, etc. We propose Autonomous Topology Generator (AutoTG), a reinforcement-learning-based framework that generates power converter topology candidates based on user specifications, optimized for user preferences. By modeling power converter design as a symbolic optimization problem, we sequentially sample components in an autoregressive manner until new topologies are formed, providing both the topology specification and the sizing (magnitude of each component parameter) of the proposed power converter. Here, we provide an empirical evaluation and show that AutoTG is able to generate varied high-efficiency topologies within component restrictions based on user input and show that previously unknown topologies can be found for further evaluation.

(AI)-based design↗

Spaceborne Processor Array

A Spaceborne Processor Array in Multifunctional Structure (SPAMS) can lower the total mass of the electronic and structural overhead of spacecraft, resulting in reduced launch costs, while increasing the science return through dynamic onboard computing. SPAMS integrates the multifunctional structure (MFS) and the Gilgamesh Memory, Intelligence, and Network Device (MIND) multi-core in-memory computer architecture into a single-system super-architecture. This transforms every inch of a spacecraft into a sharable, interconnected, smart computing element to increase computing performance while simultaneously reducing mass. The MIND in-memory architecture provides a foundation for high-performance, low-power, and fault-tolerant computing. The MIND chip has an internal structure that includes memory, processing, and communication functionality. The Gilgamesh is a scalable system comprising multiple MIND chips interconnected to operate as a single, tightly coupled, parallel computer. The array of MIND components shares a global, virtual name space for program variables and tasks that are allocated at run time to the distributed physical memory and processing resources. Individual processor- memory nodes can be activated or powered down at run time to provide active power management and to configure around faults. A SPAMS system is comprised of a distributed Gilgamesh array built into MFS, interfaces into instrument and communication subsystems, a mass storage interface, and a radiation-hardened flight computer.

Chow, Edward T.↗

Smart connected worker edge platform for smart manufacturing: Part 1—Architecture and platform design

Abstract The challenge of sustainably producing goods and services for healthy living on a healthy planet requires simultaneous consideration of economic, societal, and environmental dimensions in manufacturing. Enabling technology for data driven manufacturing paradigms like Smart Manufacturing (a.k.a. Industry 4.0) serve as the technological backbone from which sustainable approaches to manufacturing can be implemented. Unfortunately, these technologies are typically associated with broader and deeper factory automation that is often too expensive and complex for the small and medium sized manufacturers (SMMs) that comprise the majority of manufacturing business in the USA and for whom their most valuable asset are the people whose jobs automation while replace. This paper describes an edge intelligent platform to integrate internet‐of‐things technologies with computing hardware, software, computational workflows for machine learning, and data ingestion, enabling SMMs to transition into smart manufacturing paradigms by leveraging the intelligence of their people. The platform leverages consumer grade electronics and sensors (affordable and portable), customized software with open source software packages (accessible), and existing communication network infrastructures (scalable). The software systems are implemented via Kubernetes orchestration of Docker containerization to ensure scalability and programmability. The platform is adaptive via computational workflow engines that produce information from data by processing with low‐cost edge computing devices while efficiently accessing resources of cloud servers as needed. The proposed edge platform connects workers to technological resources that provide computational intelligence (i.e., silicon‐based sensing and computation for data collection and contextualization) to enable decision making at the edge of advanced manufacturing.

Kim, Yoon G.↗

Plug-in circuit monitor

Intelligent electronic circuit is used to monitor other circuits within module and to warn of imminent failure of module under surveillance. Monitor is housed in rectangular connector and plugs into mating jack originally designed to terminate flat conductor cables. Device can be made from existing premolded rectangular connectors.

Stringer, E. J.↗

Digital Architecture for a Trace Gas Sensor Platform

A digital architecture has been implemented for a trace gas sensor platform, as a companion to standard analog control electronics, which accommodates optical absorption whose fractional absorbance equivalent would result in excess error if assumed to be linear. In cases where the absorption (1-transmission) is not equivalent to the fractional absorbance within a few percent error, it is necessary to accommodate the actual measured absorption while reporting the measured concentration of a target analyte with reasonable accuracy. This requires incorporation of programmable intelligence into the sensor platform so that flexible interpretation of the acquired data may be accomplished. Several different digital component architectures were tested and implemented. Commercial off-the-shelf digital electronics including data acquisition cards (DAQs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), and microcontrollers have been used to achieve the desired outcome. The most completely integrated architecture achieved during the project used the CPLD along with a microcontroller. The CPLD provides the initial digital demodulation of the raw sensor signal, and then communicates over a parallel communications interface with a microcontroller. The microcontroller analyzes the digital signal from the CPLD, and applies a non-linear correction obtained through extensive data analysis at the various relevant EVA operating pressures. The microcontroller then presents the quantitatively accurate carbon dioxide partial pressure regardless of optical density. This technique could extend the linear dynamic range of typical absorption spectrometers, particularly those whose low end noise equivalent absorbance is below one-part-in-100,000. In the EVA application, it allows introduction of a path-length-enhancing architecture whose optical interference effects are well understood and quantified without sacrificing the dynamic range that allows quantitative detection at the higher carbon dioxide partial pressures. The digital components are compact and allow reasonably complete integration with separately developed analog control electronics without sacrificing size, mass, or power draw.

Gonzales, Paula↗

Communications and Intelligent Systems Division Overview

Provides expertise, and plans, conducts and directs research and engineering development in the competency fields of advanced communications and intelligent systems technologies for applications in current and future aeronautics and space systems.Advances communication systems engineering, development and analysis needed for Glenn Research Center's leadership in communications and intelligent systems technology. Focus areas include advanced high frequency devices, components, and antennas; optical communications, health monitoring and instrumentation; digital signal processing for communications and navigation, and cognitive radios; network architectures, protocols, standards and network-based applications; intelligent controls, dynamics and diagnostics; and smart micro- and nano-sensors and harsh environment electronics. Research and discipline engineering allow for the creation of innovative concepts and designs for aerospace communication systems with reduced size and weight, increased functionality and intelligence. Performs proof-of-concept studies and analyses to assess the impact of the new technologies.

Intelligent Systems↗

Detector Control and Data Acquisition for the Wide-Field Infrared Survey Telescope (WFIRST) with a Custom ASIC

The Wide-Field Infrared Survey Telescope (WFIRST) will have the largest near-IR focal plane ever flown by NASA, a total of 18 4K x 4K devices. The project has adopted a system-level approach to detector control and data acquisition where 1) control and processing intelligence is pushed into components closer to the detector to maximize signal integrity, 2) functions are performed at the highest allowable temperatures, and 3) the electronics are designed to ensure that the intrinsic detector noise is the limiting factor for system performance. For WFIRST, the detector arrays operate at 90 to 100 K, the detector control and data acquisition functions are performed by a custom ASIC at 150 to 180 K, and the main data processing electronics are at the ambient temperature of the spacecraft, notionally approx.300 K. The new ASIC is the main interface between the cryogenic detectors and the warm instrument electronics. Its single-chip design provides basic clocking for most types of hybrid detectors with CMOS ROICs. It includes a flexible but simple-to-program sequencer, with the option of microprocessor control for more elaborate readout schemes that may be data-dependent. All analog biases, digital clocks, and analog-to-digital conversion functions are incorporated and are connected to the nearby detectors with a short cable that can provide thermal isolation. The interface to the warm electronics is simple and robust through multiple LVDS channels. It also includes features that support parallel operation of multiple ASICs to control detectors that may have more capability or requirements than can be supported by a single chip.

data acquisition↗

Guest Editorial Special Section on Advanced Medium-Voltage Power Electronics for Grid Interactive Applications

Medium-voltage power electronics (MVPE) plays essential roles in power grid modernization and links the MV distribution grid with low-voltage consumers and prosumers. Various MVPE devices, such as solid-state transformers or circuit breakers, inverter-based resources, power flow controllers, etc., bring the benefits of voltage conversion and power regulation in small footprint, power quality and efficiency improvements, and enhancements of grid controllability, flexibility, stability, and resilience. The MVPE also makes it possible for sustainable energy systems, such as solar/wind farms and energy storage generating facilities, to directly access to MV grids without multistage conversions. With their intrinsic intelligence and communications, MVPE enables many new smart grid functions and applications, e.g., dc interconnections and electric vehicle charging, which were not envisioned by traditional power grids otherwise. In addition, the integration of physical power processing units with cyber components forms a cyber-physical system, which is essential for long-term sustainability, development, and environmental preservation. Nonetheless, technical challenges on MVPE device reliability, scalable and efficient converter topologies, control stability, large-scale modeling and simulation, to name a few, need to be addressed and advanced to the next level. In conclusion, this Special Section on Advanced MV Power Electronics for Grid Interactive Applications in IEEE Transactions on Power Electronics (TPEL) provides an insight on some of the recent advances in MVPE and emerging challenges and potential solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Market Survey 2020: Commercial Clinical Decision Support Systems and Wellness Tools

For long-duration, deep space exploration missions, current methods for managing and supporting crew health and medical conditions will be unsuitable. Communication and data transmission lags will necessitate the use of a sophisticated clinical decision support system (CDSS) that will tailor diagnosis and treatment guidance that is context-sensitive for anticipated astronaut health, wellness, and medical conditions. A variety of clinical decision support (CDS) and wellness tools (WT) are currently available in the commercial market and a broad-brush survey of this market can provide an initial impression of the current state of the art which, in turn, can inform the roadmap of NASA deep space CDSS development and associated requirements. Such a survey was undertaken during the first six months of 2020 using directed convenience sampling to obtain information provided by vendors on their websites; both commercially available CDS and WT (such as those used to track and monitor nutrition, exercise, and sleep) were included. Areas assessed were item type (e.g., software/application, device); primary purpose of the item (e.g., diagnostic support, nutrition tracking); additional purposes (if any); reported features, capabilities, and functionality; setting of use (e.g., inpatient, outpatient); intended user (e.g., clinician, patient); location and sources of data/information used or produced by the item; integration with patient electronic health record (EHR); compliance with interoperability ontologies and standards (e.g., Health Level 7 [HL7], Systematized Nomenclature of Medicine – Clinical Terminology [SNOMED-CT]); and whether the item is knowledge-based (derived from research findings) or non-knowledge-based (derived through artificial intelligence, machine learning, advanced probability and statistics), among others. Ninety-seven (97) vendor websites describing 196 CDS and 73 WT (269 total) were reviewed and coded. The primary purpose of the majority of CDS reviewed is diagnosis or diagnosis/treatment/drug decision support—targeted for clinician use— and the primary purpose of the majority of WT reviewed is the monitoring of different health metrics, most often through the use of a biosensor device (e.g., blood pressure)—targeted for patient use. Very few CDS or WT appear to comply with major international interoperability standards or can be integrated with a patient’s EHR data. None consider contextual factors, such as conditions of the physical environment (e.g., CO2 levels). The majority of CDS and WT reviewed are non-knowledge, cloud- or web-based applications or software. Forty-three (43) major findings were identified and the implications those findings have for NASA will be discussed. Example major findings include: CDS-WT capabilities range from diagnosis to treatment applications, CDS-WT may be wearable or non-wearable and are technologically advanced and only a few CDS-WT tools referenced compliance to ensure interoperability, among other findings. Recommendations will also be offered that will help to address ExMC Gap, Medical-701: Enhance medical capabilities within an exploration medical system.

market survey↗

High Temperature Wireless Communication And Electronics For Harsh Environment Applications

In order for future aerospace propulsion systems to meet the increasing requirements for decreased maintenance, improved capability, and increased safety, the inclusion of intelligence into the propulsion system design and operation becomes necessary. These propulsion systems will have to incorporate technology that will monitor propulsion component conditions, analyze the incoming data, and modify operating parameters to optimize propulsion system operations. This implies the development of sensors, actuators, and electronics, with associated packaging, that will be able to operate under the harsh environments present in an engine. However, given the harsh environments inherent in propulsion systems, the development of engine-compatible electronics and sensors is not straightforward. The ability of a sensor system to operate in a given environment often depends as much on the technologies supporting the sensor element as the element itself. If the supporting technology cannot handle the application, then no matter how good the sensor is itself, the sensor system will fail. An example is high temperature environments where supporting technologies are often not capable of operation in engine conditions. Further, for every sensor going into an engine environment, i.e., for every new piece of hardware that improves the in-situ intelligence of the components, communication wires almost always must follow. The communication wires may be within or between parts, or from the engine to the controller. As more hardware is added, more wires, weight, complexity, and potential for unreliability is also introduced. Thus, wireless communication combined with in-situ processing of data would significantly improve the ability to include sensors into high temperature systems and thus lead toward more intelligent engine systems. NASA Glenn Research Center (GRC) is presently leading the development of electronics, communication systems, and sensors capable of prolonged stable operation in harsh 500C environments. This has included world record operation of SiC-based transistor technology (including packaging) that has demonstrated continuous electrical operation at 500C for over 2000 hours. Based on SiC electronics, development of high temperature wireless communication has been on-going. This work has concentrated on maturing the SiC electronic devices for communication purposes as well as the passive components such as resistors and capacitors needed to enable a high temperature wireless system. The objective is to eliminate wires associated with high temperature sensors which add weight to a vehicle and can be a cause of sensor unreliability. This paper discusses the development of SiC based electronics and wireless communications technology for harsh environment applications such as propulsion health management systems and in Venus missions. A brief overview of the future directions in sensor technology is given including maturing of near-room temperature "Lick and Stick" leak sensor technology for possible implementation in the Crew Launch Vehicle program. Then an overview of high temperature electronics and the development of high temperature communication systems is presented. The maturity of related technologies such as sensor and packaging will also be discussed. It is concluded that a significant component of efforts to improve the intelligence of harsh environment operating systems is the development and implementation of high temperature wireless technology

Hunter, G. W.↗

Proton Conducting Neuromorphic Materials and Devices

Neuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components and to enable the development of energy-efficient machines. In the biological brain, ionic currents and temporal concentration gradients control information flow and storage. It is therefore of interest to examine materials and devices for neuromorphic computing wherein ionic and electronic currents can propagate. Protons being mobile under an external electric field offers a compelling avenue for facilitating biological functionalities in artificial synapses and neurons. In this review, we first highlight the interesting biological analog of protons as neurotransmitters in various animals. We then discuss the experimental approaches and mechanisms of proton doping in various classes of inorganic and organic proton-conducting materials for the advancement of neuromorphic architectures. Since hydrogen is among the lightest of elements, characterization in a solid matrix requires advanced techniques. We review powerful synchrotron-based spectroscopic techniques for characterizing hydrogen doping in various materials as well as complementary scattering techniques to detect hydrogen. First-principles calculations are then discussed as they help provide an understanding of proton migration and electronic structure modification. Outstanding scientific challenges to further our understanding of proton doping and its use in emerging neuromorphic electronics are pointed out.

36 MATERIALS SCIENCE↗