Search NASA⌕ Search

SEARCH · Search NASA

Results for “on-chip”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

189 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Learning From Failure: Boosting Cycling Endurance of Optical Phase Change Materials

Chalcogenide phase change materials (PCMs) are a unique class of compounds whose switchable optical and electronic properties have fueled an explosion of emerging applications in microelectronics and microphotonics. Key to any application is the ability of PCMs to reliably switch between crystalline and amorphous states over a large number of cycles. While this issue has been extensively studied in the case of microelectronic memories, current PCM-based optical devices suffer from much inferior endurance. To understand the failure mechanisms limiting endurance of PCMs specifically in microphotonic devices, we have developed an on-chip resistive micro-heater platform and an automatic multi-modal characterization system to analyze cycling performance of optical PCMs. Reversible switching of large-area PCM devices over 50,000 cycles was demonstrated.

Optical phase change material↗
NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗
NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗
NASA NTRSDate not supplied

The PCM is Dead! Long Live O-PCM!

The ability to reconfigure the optical behavior of a device enables free-space applications ranging from imaging to sensing and signal control. Such optical devices can be compacted via meta-surfaces, patterned structures with feature sizes below the incident wavelength. Leveraging geometry in addition to material properties and CMOS fabrication techniques has allowed meta-surfaces for lenses, holograms, beam steerers and more. To incorporate multiple optical functions into one device, various methods of device control have been implemented, such as stretching of flexible substrates, tuning the refractive index of the comprising meta-atoms via the electro-optic or the thermo-optic effects, phase transition materials such as VO2 and more. Chalcogenide glasses used as optical phase change materials, such as Ge¬2Sb2Te5 (GST), have gained increased traction in the optics community for potential use in the near infrared (NIR) and mid infrared (MIR) bands, including the telecom bands. Various chalcogenides such as Sb2Se3, Sb2S3, Ge2Sb¬2Se5 and Ge2Sb2Se4Te (GSST) have been investigated due to their broad NIR or MIR transparency window and large changes in refractive index. In their amorphous phase, these materials usually display a lower refractive index and low absorption when compared to their crystalline state which display a higher refractive index and typically larger extinction coefficients. The amorphous-crystalline reversible switching can be done via fast melt-quenching thermal processes triggered by laser or electrical impulses, relying on a substrate as a heat sink. The potential of PCMs in photonic devices can be limited by intrinsic material limitations as well as by device fabrication issues. To explore the cyclability of GSST, a PCM with large refractive index contrast and on-chip electrothermal switching on a silicon-on-insulator platform has been done to analyze potential failure mechanisms from both a material and device perspective. A brief outline of the instrumentation and phase change contrast analysis is provided. Dewetting of the PCM, delamination of and damage in the PECVD SiNx protective layer, elemental migration in the PCM and optical contrast decay have been observed in cycled GSST devices. Guidelines for device performance improvement are proposed, and an improved design with larger endurance is shown in progress.

reconfigurable photonics↗
NASA NTRSDate not supplied

Phase Change Materials for Photonics in NASA Science and Space Missions

Phase change materials (PCMs) such as Ge2Sb2Te5, Ge2Sb2Se4Te1, and Sb2S3have recently emerged as a promising platform to control light on-chip due to their fast, dramatic, and reversible change in refractive index. Significant technical progress in the field has been achieved in terms of improving optical transparency, controlling PCMs both optically and electrically, and integrating with complex photonic circuits, leading to exciting applications. When PCMs are mated with metasurfaces, devices are capable of controlling the phase and amplitude of propagating light with arrays of subwavelength structures. These enhance tunability and reconfigurability and continue to redefine the boundaries of optical sciences. PCM-based metasurface optics also help to accelerate the adoption of new architectures with reduced size, weight, and power (SWaP) for science and space mission platforms at NASA. In this talk, I will introduce two NASA-lead PCM photonic projects: 1. P-ACTIVE (PCM-based actively tunable filter) for broad imaging and sensing applications – from probing molecular vibrations in chemical species to detecting radiant thermal signatures of the space launch system. 2. PROWESS (Phase change reconfigurable optical wavefront synthesis system) as a beam steerer for both Earth and space LiDAR and free space optical communication applications. From this seminar, the attendees will be exposed not only to PCM-based photonic technologies but also NASA missions including the MISSE (Materials on the International Space Station Experiment) test campaign that was conducted to expose PCMs and PCM-based metasurfaces in space for 6 months in 2022.

phase change material↗
NASA NTRS2023

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As the space economy continues to expand through increasingly easy access to advanced and inexpensive technology, space missions themselves have become more ambitious with exploration targets growing ever distant while simultaneously requiring larger guidance and communication budgets. These conflicting desires of distance and control drive the need for advanced on-board intelligent decision making to reduce communication and control limitations by automating as many mission functions as possible in-situ. While the amount of research on such Artificial Intelligence and Machine Learning (AI/ML) software modules has grown exponentially, the capacity to experimentally validate such software modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available bleeding-edge computational platforms via what is programmatically referred to as the BrainStack on the TechEdSat (TES-n) flight series. This on-orbit computational platform provides an evaluation laboratory where advanced software experiments are pre-loaded into memory prior to launch, then executed as payloads during mission operations with results reported back and program tweaks or new training sets uploaded as needed. Processors selected as part of the BrainStack are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and, more recently, neuromorphic processors, in LEO operations. Neuromorphic processors are of particular interest due to their superior power efficiency over GPUs in intelligent automation applications. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on TES-13, January 13, 2022, and continues to operate in orbit despite no significant modifications to harden the processor against the space environment. The Intel Loihi Gen-1 on TES-13 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. The processor is packaged in the Kapoho Bay USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by an Intel Pentium single-board computer to handle scheduling of the software application payloads and communications with the satellite’s primary computer. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the continually evolving BrainStack in the upcoming three TES-n/NOW flights. The Kapoho Point unit will incorporate eight Loihi-2 processors, enabling neural networks of up to one million neurons and one billion synapsis. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space automation applications may be initially tested.

Artificial Intelligence↗
NASA NTRS2024

Superfluid-Tight Cryogenic Receiver With Continuous Sub-Kelvin Cooling for EXCLAIM

The EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) is a balloon-borne telescope designed to survey star formation over cosmological time scales using intensity mapping in the 420 – 540 GHz frequency range. EXCLAIM uses a fully cryogenic telescope coupled to six on-chip spectrometers featuring kinetic inductance detectors (KIDs) to achieve high sensitivity, allowing for fast integration in dark atmospheric windows. The telescope receiver is cooled to ≈ 1.7 K by immersion in a superfluid helium bath and enclosed in a superfluid-tight shell with a meta-material anti-reflection coated silicon window. In addition to the optics and the spectrometer package, the receiver contains the magnetic shielding, the cryogenic segment of the spectrometer readout, and the sub-Kelvin cooling system. A three-stage continuous adiabatic demagnetization refrigerator (CADR) keeps the detectors at 100 mK while a 4He sorption cooler provides a 900 mK thermal intercept for mechanical suspensions and coaxial cables. We present the design of the EXCLAIM receiver and report on the flight-like testing of major receiver components, including the superfluid-tight receiver window and the sub-Kelvin coolers.

continuous adiabatic demagnetization refrigerator↗
NASA NTRS2003

Switch array system for thin film lithium microbatteries

This paper presents a design approach for charging and discharging microbatteries. Maximum flexibility in terms of voltages and currents are also obtained through the use of a switching matrix.

microbattery on-chip power micropower↗