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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 487 records · Page 27

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗

Shape Estimation for Elongated Deformable Object using B-spline Chained Multiple Random Matrices Model

In this paper, a B-spline chained multiple random matrix models (RMMs) representation is proposed to model geometric characteristics of an elongated deformable object. The hyper degrees of freedom structure of the elongated deformable object make its shape estimation challenging. Based on the likelihood function of the proposed B-spline chained multiple RMMs, an expectation-maximization (EM) method is derived to estimate the shape of the elongated deformable object. A split and merge method based on the Euclidean minimum spanning tree (EMST) is proposed to provide initialization for the EM algorithm. The proposed algorithm is evaluated for the shape estimation of the elongated deformable objects in scenarios, such as the static rope with various configurations (including configurations with intersection), the continuous manipulation of a rope and a plastic tube, and the assembly of two plastic tubes. The execution time is computed and the accuracy of the shape estimation results is evaluated based on the comparisons between the estimated width values and its ground-truth, and the intersection over union (IoU) metric.

Gang Yao↗

Tutorial: Electrified Aircraft Propulsion Approaches for Modeling and Electrical Hardware-in-the-Loop Testing

This tutorial session outlines capabilities made available by the National Aeronautics and Space Administration for testing electrified aircraft propulsion (EAP) hardware and software prior to using turbomachinery. Removing these components from the experimentation process until necessary significantly reduces the development and testing costs and safety risks. Three facilities, the NASA Electric Aircraft Testbed (NEAT) and the Hybrid Propulsion Emulation Rig (HyPER) are unique facilities that provide the following capabilities: (i) the verification of megawatt-scale electrical and electromechanical system components at altitude, (ii) the verification of EAP control systems on sub-scale representative electromechanical architectures. The importance, operation, and specifications of each facility is described with detail. Provided examples of past testing showcase the abilities of each facility. Simple and complex methods for replicating the steady state and dynamical mechanical loading on the electrical power system are discussed

Electrified Aircraft Propulsion↗

X-Ray Polarimetry of the Accreting Pulsar GX 301-2

The phase- and energy-resolved polarization measurements of accreting X-ray pulsars (XRPs) allow us to test different theoretical models of their emission, and they also provide an avenue to determine the emission region geometry. We present the results of the observations of the XRPGX 301−2 performed with the Imaging X-ray Polarimetry Explorer (IXPE). A persistent XRP, GX 301−2 has one of the longest spin periods known:∼680 s. A massive hyper-giant companion star Wray 977 supplies mass to the neutron star via powerful stellar winds. We did not detect significant polarization in the phase-averaged data when using spectropolarimetric analysis, with the upper limit on the polarization degree (PD)of 2.3% (99% confidence level). Using the phase-resolved spectropolarimetric analysis, we obtained a significant detection of polarization (above99% confidence level) in two out of nine phase bins and a marginal detection in three bins, with a PD ranging between∼3% and∼10% and a polarization angle varying in a very wide range from∼0◦to∼160◦. Using the rotating vector model, we obtained constraints on the pulsar geometry using both phase-binned and unbinned analyses, finding excellent agreement. Finally, we discuss possible reasons for a low observed polarization in GX 301−2.

GX 301-2, polarization, X-ray, X-ray binary, pulsa↗

SUbsonic Single Aft eNgine (SUSAN) Power/Propulsion System Hardware-in-the-Loop Test Results

Electrified Aircraft Propulsion (EAP) technology offers a promising path forward for reducing greenhouse gas emissions and other negative environmental effects from the commercial aviation sector. EAP systems can reduce fuel burn and improve performance over state-of the-art designs, however the increased complexity and highly coupled nature of these systems present challenges that require new control approaches. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a concept aircraft developed by NASA as a reference design for a commercial transport aircraft with a highly integrated hybrid-electric powertrain. This paper summarizes the results of a Hardware-in-the-Loop (HIL) test of a control architecture developed for the SUSAN power/propulsion system (PPS). The test was performed in the Hybrid Propulsion Emulation Rig (HyPER) facility at the NASA Glenn Research Center (GRC) and involved a real-time reference model of the SUSAN PPS and control system running with a sub-scale electro-mechanical system replacing one of the PPS subsystems. A side-by-side comparison of the simulated and real systems in the HIL test results shows that the control architecture functions well in both the simulation and the real-time HIL environment. In both cases the controller is able to simultaneously deliver the required thrust response and balance power levels between the electrical and turbomachinery subsystems.

Jonah J Sachs-Wetstone↗

Enterprise Digital Transformation: Transforming NASA's Workplace

NASA has a long history of serving the Nation and the world, by reaching for new heights and revealing the unknown for the benefit of all humankind. To ensure the agency will deliver on its mission in a hyper-connected, technology-enabled, globally-partnered, and rapidly-changing world, NASA launched a Digital Transformation initiative in late 2020 to modernize the way it works, the experience of its workforce and the agility of its workplace. At the core of its workplace transformation strategy, NASA is on a journey to leverage smart operational technologies, weaving together IoT, AI, intelligent automation, extended reality, and digital twins to build a network of reliable, adaptable and sustainable “Smart Centers” to execute its mission… on planet Earth and beyond. Come hear NASA’s digital strategy, the exciting progress being made, lessons learned from their journey, and how the AIMST community can enable NASA and its partners to serve humanity in a digital future.

Jill Marlowe↗

Machine Learning Based Aerosol and Ocean Color Joint Retrieval Algorithm for Multiangle Polarimeters over Coastal Waters

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, recently launched in February 2024, carries two multiangle polarimeters (MAPs): the UMBC Hyper-Angular Rainbow Polarimeter (HARP2) and SRON Spectropolarimeter for Planetary Exploration One (SPEXone). Measurements from these MAPs will greatly advance ocean ecosystem and aerosol studies as their measurements contain rich information on microphysical properties of aerosols and hydrosols. The Multi-Angular Polarimetric Ocean coLor (MAPOL) joint retrieval algorithm has been developed to retrieve aerosol and ocean color information, which uses a vector radiative transfer (RT) model as the forward model. The RT model is computationally expensive, which makes processing a large amount of data challenging. FastMAPOL was developed to expedite retrieval using neural networks to replace the RT forward models. As a prototype study, FastMAPOL was initially limited to open ocean applications where the ocean Inherent Optical Properties (IOPs) were parameterized in terms of one parameter: chlorophyll-a concentration (Chla). In this study we further expand the FastMAPOL joint retrieval algorithm to incorporate NN based forward models for coastal waters, which use multi-parameter bio-optical models. In addition, aerosols are represented by six components, i.e., fine mode non absorbing insoluble (FNAI), brown carbon (BrC), black carbon (BC), fine mode non absorbing soluble (FNAS), sea salt (SS) and non-spherical dust (Dust). Sea salt and dust are coarse mode aerosols, while the other components are in the fine mode. The sizes and spectral refractive indices are fixed for each aerosol component, while their abundances are retrievable. The multi-parameter bio-optical model and aerosol components are chosen to represent the coastal marine environment. The retrieval algorithm is applied to synthetic measurements in three different configurations ofMAPs in the PACE mission: HARP2 observations only, SPEXone observations only and combined HARP2 and SPEXone observations. The retrieval results from synthetic measurements show that for aerosol retrieval the SPEXone-only configuration works equally well with the HAPR2-only configuration. On the other hand, for ocean color retrieval the SPEXone instrument provides better information due to its larger spectral coverage. For the surface parameters (wind speed), HARP2 measurements provide better information due to its wide field of view. Combined measurement configuration HARP2+SPEXone performed the best to retrieve all aerosol, ocean color and surface parameters. We also studied the impact of sun glint to aerosol and ocean color retrievals. The retrieval test revealed that wind speed and absorbing aerosol retrieval improves significantly when including measurements at glint geometries. Furthermore, the retrieval algorithm is equipped with modules for atmospheric correction and bidirectional reflectance distribution (BRDF) correction to obtain the remote sensing reflectance, which enables ocean biogeochemistry studies using the PACE polarimeter data.

PACE↗

PACE Microphysical Aerosol Properties from Polarimetry (PACE-MAPP)

We present the Plankton, Aerosols, Clouds and Ecosystems Microphysical Aerosol Properties from Polarimetry (PACE-MAPP) polarimetric remote sensing algorithm developed for the newly launched NASA PACE satellite observing system. The objective of PACE-MAPP is to retrieve detailed fine-mode (marine, pollution and smoke) and coarse-mode (sea-salt and dust) aerosol properties over the ocean for a range of light to heavy aerosol loadings using PACE’s polarimetric-imaging capabilities at multiple angles and wavelengths from the ultraviolet (UV) to the near-infrared (NIR). An additional objective for PACE-MAPP is to discriminate aerosols from thin clouds. The PACE-MAPP polarimetric remote sensing retrieval algorithm uses coupled atmosphere-ocean vector radiative transfer, optimal estimation, artificial intelligence and powerful inherent optical property look-up-tables for the Earth’s aerosol, cloud, and hydrosol particles. PACE-MAPP is the only retrieval algorithm designed to invert aerosol/ocean products using both polarimeters onboard PACE. We present results using PACE-MAPP to retrieve aerosol and ocean remote sensing products from measurements by the Hyper-Angular Rainbow Polarimeter #2 (HARP2) and Spectro-polarimeter for Planetary Exploration one (SPEXone) polarimeter instruments onboard PACE.

Snorre Stamnes↗

Urban Air Quality Management at Low-Cost Using Micro Air Sensors: A Case Study From Accra, Ghana

Urban air quality management is dependent on the availability of local air pollution data. In many major urban centers of Africa, there is limited to non-existent information on air quality. This is gradually changing in part due to the increasing use of micro air sensors which have the potential to enable the generation of ground-based air quality data at fine scales for understanding local emission trends. Regional literature on the application of the high-resolution data for emission source identification in this region is limited. In this study a micro air sensor was co-located at the Physics Department, University of Ghana with a reference grade instrument to evaluate its performance for estimating PM2.5 pollution accurately at fine scales and the value of this data in identification of local sources and their behavior over time. For this study 15 weeks of data at hourly resolution with approximately 2500 data pairs are generated and analyzed (June 01, 2023, to September 15, 2023). For this time period a coefficient of determination (r 2 ) of 0.83 was generated with a mean absolute error (MAE) of 5.44 μgm -3 between the pre local calibration micro air sensor (i.e. out of box) and the reference-grade instrument. Following currently accepted best practice methods (see e.g., PAS4023) a domain specific (i.e. local) calibration factor was generated using a multi-linear regression model and when this factor is applied to the micro air sensor data, a reduction i.e., improvement in MAE to 1.43 μgm -3 was found. Daily variation was calculated, a receptor model was applied, and time series plots as a function of wind direction were generated, including PM2.5/PM10 ratio scatter and count plots to explore the utility of this observational approach for local source identification. The 3 data sets were compared (out of box, domain calibrated and reference-grade) and it was found that although there were variations in the data reported, source areas highlighted based on these data were similar, with input from local sources such as traffic emissions and biomass burning. As the temporal resolution of observational data associated with these micro air sensors is higher than for reference grade instruments (primarily due to costs and logistics limitations), they have the potential to provide insight into the complex, often hyper localized sources associated with urban areas, such as those found in major African cities.

Source apportionment↗

Masses of Sunyaev-Zel’dovich Galaxy Clusters Detected by the Atacama Cosmology Telescope: Stacked Lensing Measurements with Subaru HSC Year 3 Data

We present a stacked lensing analysis of 96 galaxy clusters selected by the thermal Sunyaev-Zel’dovich (SZ) effect in maps of the cosmic microwave background (CMB). We select foreground galaxy clusters with a 5σ-level SZ threshold in CMB observations from the Atacama Cosmology Telescope, while we define background source galaxies for the lensing analysis with secure photometric redshift cuts in Year 3 data of the Subaru Hyper Suprime Cam survey. We detect the stacked lensing signal in the range of 0.1 < R[h −1 Mpc] < 100 in each of three cluster redshift bins, 0.092 < z ≤ 0.445, 0.445 < z ≤ 0.695, and 0.695 < z ≤ 1.180, with 32 galaxy clusters in each bin. The cumulative signal-to-noise ratios of the lensing signal are 14.6, 12.0, and 6.6, respectively. Using a halo-based forward model, we then constrain statistical relationships between the mass inferred from the SZ observation (i.e. SZ mass) and the total mass derived from our stacked lensing measurements. At the average SZ mass in the cluster sample (2.1 − 2.4 × 10 14 h −1 M⊙), our likelihood analysis shows that the average total mass differs from the SZ counterpart by a factor of 1.3 ± 0.2, 1.6 ± 0.2, and 1.6 ± 0.3 (68%) in the aforementioned redshift ranges, respectively. Our limits are consistent with previous lensing measurements, and we find that the cluster modeling choices can introduce a 1σ-level difference in our parameter inferences.

Masato Shirasaki↗

Evaluation of Climate Fingerprinting Sounder Product (ClimFiSP) Air Temperature and H2O Trends

Climate fingerprinting Sounder Product (ClimFiSP) provides gridded (0.5x0.5) daily skin temperature, surface emissivity, air temperature, water vapor, trace gases, and cloud properties, which derived from IR hyper-spectral radiance measured by AIRS on Aqua and CrIS on SNPP and JPSS series. In this work, the ClimFiSP daily air temperature and H2O were retrieved on 98 pressure levels by applying the spectral fingerprint algorithm on 0.5x0.5 gridded daily mean radiances from Climate Hyperspectral Infrared Radiance Product (CHIRP). CHIRP is a stable climate-quality radiance time series spanning AIRS and CrIS. The air temperature and H2O monthly data and trends were calculated from the more than two decades long CHIRP AIRS data. Troposphere warming and stratosphere cooling can be seen in both ClimFiSP and ERA5 air temperature data. The ClimFiSP air temperature trends are also compared with the MW sounding air temperature trends to validate the ClimFiSP air temperature results. The H2O trends on upper troposphere are evaluated by comparing with the ERA5 H2O trends, and results show a reasonable agreement with two sets of results. The ClimFiSP algorithm provides a unique and fast way to retrieve the spatial-temporal change in climate variables from the corresponding change in radiances, gridded at the same spatial-temporal scale. This greatly facilitates the procession of long-term climate data records.

ClimFiSP↗

The Hyperspectral Microwave Photonic Instrument (HyMPI) and its NEDT Performance

This work presents an overview of a hyperspectral microwave-photonic spectrometer and demonstrates the system end-to-end noise equivalent delta temperature (NEDT) performance. The system aims at augmenting the remote sensing capability from space, with a focus on the Earth’s planetary boundary layer (PBL) thermal microwave (MW) spectral region (0-200 GHz). Combining a Photonic Integrated Circuit (PIC) channelizer and an application-specific integrated circuit (ASIC) spectrometer, the PIC & ASIC (PICASIC) module is capable of processing 40 GHz spectra at hyperspectral (4 MHz) resolution. The photonic technology is agnostic to the spectral region and multiple photonic modules can cover the entire 200 GHz spectrum. Measured results of the end-to-end system NEDT agree with predicted values confirming that the NEDT is primarily dominated by the noise figure of the MW front-end, with the optical link adding no significant noise. The data also demonstrate that a single module enables simultaneous super- and hyper-spectral resolution channel analysis across a 40 GHz range.

spectrometer↗

Subscale Hardware-In-The-Loop Results for Hybrid Electric Turbofan Controls Use Cases

NASA is investigating hybrid electric turbine engine systems for commercial transport aircraft due to the potentially significant improvements hybrid electric technology offers in performance, fuel consumption, and operational and design flexibility. Recently, the technology has been tested at full scale in partnership with industry and advanced to Technology Readiness Level 4. This presentation will focus on a recent subscale hardware-in-the-loop test of an open source turbofan engine model developed by NASA. The Advanced Geared Turbofan 30,000 lbf – electrified (AGTF30-e) engine is used as a reference model to demonstrate control system design and use cases for an example mild hybrid electric system with no large-scale energy storage. This model is run in real-time in NASA’s Hybrid Propulsion Emulation Rig (HyPER) and is used to drive an emulation of the turbomachinery system using subscale electric machines. This dynamic scaled shaft emulation interacts with a subscale (<100 kW) hybrid system consisting of electric machines, motor controllers, and a programmable electronic load. Specific use cases demonstrated include the use of Turbine Electrified Energy Management to improve operation during transients, megawatt-scale power extraction from the AGTF30-e, and power transfer between engine spools. Results related to the effectiveness of hybrid systems are qualitatively compared to results from industry testing.

Hybrid↗

Validation of the Radiometric Stability of the Atmospheric Infrared Sounder

It has been widely accepted that an infrared sounder in low polar orbit is capable of producing climate quality data, if the spectral brightness temperatures have instrumental trends of less than 10 mK/yr. Achieving measurement stability at this level is not only very demanding of the design of the instrument, it is also pushes the state of art of measuring on orbit what stability is actually achieved. We discuss this using Atmospheric Infrared Sounder (AIRS) L1B data collected between 2002 and 2011. We compare the L1B brightness temperature observed in cloud filtered night tropical ocean spectra (obs) to the brightness temperature calculated based on the known surface emissivity, temperature and water vapor profiles from the ECMWF ReAnalysis (ERA) and the growth rates of CO2, N2O and Ozone. The trend in (obs-calc) is a powerful tool for the evaluation of the stability of the 2378 AIRS channels. We divided the channels into seven classes: All channels which sound in the stratosphere (at pressure levels below 150 hPa), 14 micron CO2 sounding, 4 micron CO2 P-branch sounding, 4 micron CO2 R-branch sounding, water vapor sounding, shortwave surface sounding and longwave surface sounding. The peak in the weighting function at 1050 hPa separates sounding and surface channels. The boundary between shortwave and longwave is 5 microns. Except for the stratosphere sounding channels, the remaining six groups have (obs-calc) trends of less than 20 mK/yr. The longwave surface channels have trends of 2 mK/yr, significantly less than the 8 mK/yr trend seem in the shortwave window channels. Based on the design of the instrument, trends within a group of channels should be the same. While the longwave and shortwave trends are less than the canonical 10 mK/yr, the larger trend in the shortwave channels could be an artifact of using the pre-launch determined calibration coefficients. This is currently under evaluation. The trend in (obs-calc) for the non-surface sounding channels, in particular for stratosphere sounding and upper tropospheric water channels, is dominated by artifacts created in calc, most likely due to changes in the ERA Ozone and water vapor. Based on this argument the best estimate of the trend for the channels within a channel group is given by the surface sensitive channels within the group. Based on this consideration we estimated the trend of all AIRS longwave channels as 2 mK/yr, while the shortwave channels have a trend of 8 mK/yr.

CO2↗

Tuning Neural Network Models for Improved Prediction of Boundary Layer Transition

Boundary layer transition can strongly impact flight vehicle performance as it influences surface skin friction and aerodynamic heating, making accurate transition prediction a key to designing next generation aircraft. Artificial neural networks (ANNs) have shown promise toward predicting laminar-turbulent transition based on linear stability correlations. The computational efficiency of ANNs and the substantially reduced user involvement in relation to direct computations based on the linear stability theory (LST) makes them an attractive methodology for integrating the LST based correlations in computational fluid dynamics codes. Tollmien-Schlichting (TS) waves correspond to the dominant transition mechanism in 2D or weakly 3D subsonic boundary layers, such as those encountered in general aviation applications. Improvements to neural network model accuracy in predicting the amplification rates of TS instability waves have been investigated by leveraging recent machine learning developments in conjunction with surrogate optimization techniques and via suitable augmentation of the data used to train the networks. The optimized models trained on the modified dataset reduced the average transition location errors on different airfoils at several flow conditions by 51% of the original manually-tuned network’s errors on the same flow cases. The actual transition locations were derived from the Langley Stability and Transition Analysis Code (LASTRAC).

Machine Learning↗

Evolvable Hardware for Spacecraft Autonomy

Evolvable hardware is a recently proposed technology in which reconfigurable hardware under the control of and evolutionary (genetic) algorithm can automatically self-reconfigure into sonfigurations with the desired behavior.

digital↗

Monolithic InGaAs JFET Active Pixel Tunable Image Sensor (MAPTIS)

A new Monolithic InGaAs Active Pixel Multispectral Image Sensor is described. This Infrared sensor will utilize high quality InGaAs grown by Molecular Beam Epitaxy on InP substrate for the fabrication of a high speed Junction Field Effect Transistor array.

hyper↗