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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 289 records · Page 16

Design and Operation of the Planetary In-Situ Capillary Electrophoresis System (PISCES)

The PISCES instrument is a portable, miniature, modular instrument designed to analyze organic molecular signatures of life. PISCES uses microcapillary electrophoresis (μCE) with laser-induced fluorescence detection (LIFD) to analyze fluorescently-labeled analytes prepared on a multi-layer microfluidic chip. As a modular instrument composed of five independently functioning units, each module can be easily detached from the system and used for subsystem testing in different environments, e.g. low temperature. The pneumatic module contains mechanical and electrical components necessary to control pneumatically-actuated valves for on-chip sample processing. A prototype LabVIEW program and two custom printed circuit boards (PCBs) operate the pneumatics module using an Arduino microcontroller, and a tentative design for the module’s housing has been developed. The high-voltage module contains circuitry required to apply varying electrical potentials to the electrophoretic channel of the microdevice. Work is currently being done to design the circuit and PCB for this module in collaboration with our SBIR partners at Los Gatos Research. The optical electronics module contains the spectrometer, laser, and laser power supply. The mounting components for the electronics and housing for the module have been designed, assembled, and tested. The optical module contains optical components to focus the laser to a 20μm spot in the center of the electrophoretic channel.The housing for this module has been designed and assembled with the aligned optical components inside.

Willis, Peter A.↗

Performance Optimization Methods for a Memory-Bound, Unstructured-Grid CFD Application on Massively Parallel GPU Platforms

Computational performance of the FUN3D unstructured-grid computational fluid dynamics (CFD) application on massively parallel GPU environments is memory-bound and highly dependent upon efficient reads from and atomic updates to the irregular cell-, edge-, and node-based data structures. In this talk, we present recent efforts into optimizing select performance-critical kernels on NVIDIA Tesla V100 and A100 GPUs and AMD CDNA MI100 GPUs. A novel use of L2 cache residency controls and asynchronous loads into on-chip shared memory are explored on the A100 GPU for the sparse iterative solver, which is dominated by mixed-precision, sparse matrix vector multiplication. Demonstrations show that these methods improve global memory bandwidth utilization by 13.5% on the A100 GPU. Several techniques are also presented that use registers and/or shared memory to facilitate array transposition and aggregation which combine to reduce the frequency and increase the cache efficiency of floating-point atomic updates to the irregular data structures. These methods are demonstrated to improve the kernel throughput by nearly 500% on select kernels on the AMD MI100 over atomic updates directly to global memory. Overall, both V100 and A100 GPUs outperformed the MI100 GPU on kernels dominated by double-precision atomic updates; however, the techniques demonstrated here reduced the performance gap and improved the MI100 performance.

GPU CPU unstructured CFD memory↗

Silicon Photonic Transceiver for Spacecraft Navigational Lidar

NASA is developing an entry, descent, and landing (EDL) lidar system, the Navigation Doppler Lidar (NDL), for high-precision landing on the Moon, Mars, and beyond. The current flight NDL systems use 1550 nm fiber-optic components for frequency-modulated continuous wave (FMCW) ranging beyond 5 km, but have reduced performance under vibrational and thermal stresses during EDL. Here we describe recent efforts to develop a breadboard silicon photonic optical transceiver for integration into NDL to reduce instrument size and improve robustness to environment and demonstrate the optical balanced receiver performance during testing with the breadboard NDL unit. Initial testing shows improved suppression of common mode noise by 25 dB over the current receiver, but a 10 dB reduction in signal to noise ratio (SNR) resulting from coupling losses from fiber to the on-chip waveguides. Future work will target reduced coupling loss, hermetic packaging, and co-integration of a single sideband suppressed carrier modulator into the same chip.

Photonic Integrated Circuits↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

A Synthesis Methodology for Intelligent Memory Interfaces in Accelerator Systems

Domain-specific systems improve the performance of a specific set of applications compared to general-purpose processing systems by deploying custom hardware accelerators. These hardware accelerators are generated using high-level synthesis (HLS) tools. The HLS tools enable a comprehensive design space exploration to optimize the compute performance of the generated accelerators. However, they often ignore the challenges of implementing the accelerators in a system-on-chip, particularly how the accelerators access memory. Our work introduces a buffering system design that improves accelerators' memory accesses by intelligently employing burst transactions to prefetch useful data from external memory to on-chip local buffers. Our design is dynamic, parametric, and transparent to the accelerators generated by HLS tools. We derive the buffering system parameters using appropriate compiler-based analysis passes and memory channel latency constraints. The proposed buffering system design results in, on average, 8.8x performance improvements while lowering memory channel utilization on average by 53.2% for a set of PolyBench kernels.

Limaye, Ankur M. (ORCID:0000000194062584)↗

Design and Performance of the SPT-SLIM Receiver Cryostat

The South Pole Telescope Shirokoff Line Intensity Mapper (SPT-SLIM) is a millimeter-wavelength line-intensity mapping experiment, which was deployed on the South Pole Telescope (SPT) during the 2024-2025 Austral summer season. This pathfinder experiment serves to demonstrate the on-sky operation of multi-pixel on-chip spectrometer technology. We report on the cryogenic performance of the SPT-SLIM receiver for the first year of commissioning observations. The SPT-SLIM receiver utilizes an Adiabatic Demagnetization Refrigerator (ADR) for cooling the focal plane of superconducting filterbank spectrometers to a temperature of 150 mK. We demonstrate stable thermal performance of the focal plane module during observations consistent with thermal modeling, enabling a cryogenic operating efficiency above 80%. We also report on the receiver control system design utilizing the Observatory Control System (OCS) platform for automated cryogenic operation on the SPT.

Young, M. R. [Fermilab; Chicago U., KICP]↗

An On-Sky Atmospheric Calibration of SPT-SLIM

We present the methodology and results of the on-sky responsivity calibration of the South Pole Telescope Shirokoff Line Intensity Mapper (SPT-SLIM). SPT-SLIM is a pathfinder line intensity mapping experiment utilizing the on-chip spectrometer technology, and was first deployed during the 2024-2025 Austral Summer season on the South Pole Telescope. During the two-week on-sky operation of SPT-SLIM, we performed periodic measurements of the detector response as a function of the telescope elevation angle. Combining these data with atmospheric opacity measurements from an on-site atmospheric tipping radiometer, simulated South Pole atmospheric spectra, and measured detector spectral responses, we construct estimates for the responsivity of SPT-SLIM detectors to sky loading. We then use this model to calibrate observations of the moon taken by SPT-SLIM, cross-checking the result against the known brightness temperature of the Moon as a function of its phase.

Dibert, K. R. [Chicago U., Astron. Astrophys. Ctr.↗

Obsidian

Obsidian A35 is a compact FPGA carrier board designed to interface with ADCs, DACs or other devices, either stand-alone or as an I/O expansion board. The connectivity includes 1 GigE, 4 SFP, 6 PMOD, FTDI USB and Arduino shield compatible header. The board features also a FPGA boot SPI Flash, on-chip DDR3 memory, VCXO and White Rabbit compatibility.

Moore, Victoria [Lawrence Berkeley National Labora↗

A Sub-electron-noise Skipper-CCD Readout ASIC with Improved Channel-to-channel Isolation and an Integrated Cryogenic Voltage Reference

The MIDNA application specific integrated circuits (ASICs) are a series of skipper-CCD readout chips fabricated in a 65 nm low-power CMOS process that implement a correlated double sampling signal processing chain based on dual-slope integrators. They are capable of working from room to cryogenic temperatures, down to 84 K. The present iteration of the ASIC has been fabricated including several design updates and the addition of an on-chip voltage reference, resulting in improved performance. This work presents the main vulnerabilities solved, the changes carried out, and the resulting performance benefits. Measurements with a skipper-CCD and the ASIC at 140 K showed that the single-electron resolution can be reached by averaging the measured charge in the analog domain using the analog pile-up technique with a readout noise as low as 0.11 erms of equivalent charge for 1200 samples. The channel-to-channel crosstalk was also characterized showing values better than -62 dB.

Alcalde Bessia, Fabricio↗

A Sub-electron-noise Skipper-CCD Readout ASIC with Improved Channel-to-channel Isolation and an Integrated Cryogenic Voltage Reference

The MIDNA application specific integrated circuits (ASICs) are a series of skipper-CCD readout chips fabricated in a 65 nm low-power CMOS process that implement a correlated double sampling signal processing chain based on dual-slope integrators. They are capable of working from room to cryogenic temperatures, down to 84 K. The present iteration of the ASIC has been fabricated including several design updates and the addition of an on-chip voltage reference, resulting in improved performance. This work presents the main vulnerabilities solved, the changes carried out, and the resulting performance benefits. Measurements with a skipper-CCD and the ASIC at 140 K showed that the single-electron resolution can be reached by averaging the measured charge in the analog domain using the analog pile-up technique with a readout noise as low as 0.11 erms of equivalent charge for 1200 samples. The channel-to-channel crosstalk was also characterized showing values better than -62 dB.

Alcalde Bessia, Fabricio↗

A 3D-Printed Millimeter-Wave Inline Waveguide-to-Coplanar-Waveguide Transition to Enable Dense Spectrometer Arrays for Intensity Mapping Surveys

We present a 3D-printed millimeter-wave, octave-bandwidth, in-line waveguide-to-coplanar-waveguide transition designed to enable focal planes with dense arrays of on-chip spectrometers. These arrays will enable compelling surveys of the large-scale structure of the universe through millimeter-wave intensity mapping. The transition consists of a four-step ridge-waveguide transformer that couples light from a rectangular waveguide onto a coplanar waveguide via an electrical connection made with indium bump bonds. We develop a tolerance-aware optimization approach to identify high-performance transition geometries that are robust to manufacturing variations; the same formulation can be applied to other tolerance-sensitive design problems. We also describe the implementation of a custom apparatus and procedure for bump-bonding a silicon chip to a metallized 3D-printed component. We detail the fabrication of the coplanar waveguide chip and three-dimensional waveguide structure, simulations and metrology of a test device, and room temperature reflectance measurements of this device. The room temperature metrology and reflection measurements are consistent with a model that predicts a coupling efficiency of $\mathord{\sim} 95\%$ at cryogenic temperatures in the 85-170 GHz frequency range.

Stover, Austin [Chicago U.; Chicago U., KICP] (ORC↗