Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “pixel”

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.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Very-High Dynamic Range, 10,000 Frames/Second Pixel Array Detector for Electron Microscopy

Precision and accuracy of quantitative scanning transmission electron microscopy (STEM) methods such as ptychography, and the mapping of electric, magnetic, and strain fields depend on the dose. Reasonable acquisition time requires high beam current and the ability to quantitatively detect both large and minute changes in signal. A new hybrid pixel array detector (PAD), the second-generation Electron Microscope Pixel Array Detector (EMPAD-G2), addresses this challenge by advancing the technology of a previous generation PAD, the EMPAD. The EMPAD-G2 images continuously at a frame-rates up to 10 kHz with a dynamic range that spans from low-noise detection of single electrons to electron beam currents exceeding 180 pA per pixel, even at electron energies of 300 keV. The EMPAD-G2 enables rapid collection of high-quality STEM data that simultaneously contain full diffraction information from unsaturated bright-field disks to usable Kikuchi bands and higher-order Laue zones. Test results from 80 to 300 keV are presented, as are first experimental results demonstrating ptychographic reconstructions, strain and polarization maps. We introduce a new information metric, the maximum usable imaging speed (MUIS), to identify when a detector becomes electron-starved, saturated or its pixel count is mismatched with the beam current.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Progress in CMOS Active Pixel Image Sensors

Recent research results regarding the investigation of CMOS active pixel image sensors (APS) are reported. An investigation of various designs for the pixel, including photogate devices of various geometries and photodiode devices has been performed. Opto-electronic performance including intra-pixel photoresponse maps taken using a focused laser scanning apparatus are presented. Several imaging arrays have also been investigated. A 128 x 128 image sensor has been fabricated and characterized. Both p-well and n-well implementations have been explored. The demonstrated arrays use 2 micron CMOS design rules and have a 40 x 40 micron pixel pitch.

active↗
DOE OSTI2025

Ultra‐Flexible Pixelated Perovskite Photodetectors Enabled by Honeycomb Polymer Grids for High‐Resolution Imaging

Abstract A nature‐inspired fabrication method based on a photolithography‐free flexible polymer grid is reported for high‐resolution pixelation of perovskite photodiode arrays with exceptional mechanical ductility and a morphology resembling that of natural compound eyes. The resulting pixelated perovskite photosensitive layer has a ≈1 µm pixel size with 2000 Pixels per inch (PPI) resolution when fully assembled as a photodetector array, delivering a detectivity of >10 13 Jones while providing cross‐talk free imaging. Using a polymer grid effectively releases stress on the perovskite platform, greatly increasing the mechanical agility of the otherwise brittle perovskite film. This novel fabrication methodology and device design offer new possibilities for applications in robotics, biomedical imaging, and virtual and augmented reality.

Zheng, Ding [Department of Chemistry and the Mater↗
DOE OSTI2019

Non-targeted discovery-based analysis for gas chromatography with mass spectrometry: A comparison of peak table, tile, and pixel-based Fisher ratio analysis

The ability to discover minute differences between samples or sample classes for gas chromatography coupled to mass spectrometry (GC-MS) can be a challenging endeavor, especially when those differences are not a priori . Fisher ratio (F-ratio) analysis is an apt technique to probe the differences between GC-MS chromatograms. F-ratio analysis is a supervised, non-targeted, discovery-based method that compares two different samples (or sample classes) to reduce the GC-MS dataset into a hit list composed of class distinguishing compounds. Three different F-ratio techniques, peak table, tile, and pixel-based were used to “discover” nine non-native analytes that were spiked into gasoline at four different nominal concentrations of 250, 85, 25, 5 parts-per-million (ppm). For the tile and pixel-based F-ratio calculations, a novel methodology is introduced to improve the sensitivity of the F-ratio calculations while reducing false positives. Furthermore, we use a combinatorial technique using null class comparisons, termed null distribution analysis, to determine a statistical F-ratio cutoff for analysis of the hit lists. The pixel-based algorithm was the most sensitive method and was able to “discover” all nine spiked analytes at a nominal concentration of 250 ppm albeit with one false positive interspersed towards the bottom of the hit list. The pixel-based software was also able to “discover” more of the spiked analytes at the lower concentrations with seven of the spiked analytes “discovered” at 85 ppm, four of the spiked analytes “discovered” at 25 ppm, and one analyte “discovered” at 5 ppm.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Improving Cloud Optical Property Retrievals for Partly Cloudy Pixels Using Coincident Higher-Resolution Single Band Measurements: A Feasibility Study Using ASTER Observations

Clear-sky contamination is a challenging and long-lasting problem for cloud optical thickness (τ) and effective droplet radius (r eff ) retrievals using passive satellite sensors. This study explores the feasibility of improving both τ and r eff retrievals for partly cloudy (PCL) pixels by using available subpixel samples in a visible to near-infrared band, which many satellite sensors offer. Data are provided by high-resolution reflectance (R ) observations and cloud property retrievals by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at horizontal resolutions between 30-960m. For partly cloudy 960-m observations, the clear-sky component of the pixels induces significant underestimations of up to 58% for τ, while overestimations in r eff can exceed 41%. This yields underestimations in the derived liquid water path and cloud droplet number concentration of up to 68% and 72%, respectively. By means of three different assumptions it is shown that subpixel R observations in the visible to near-infrared band can be used to estimate higher-resolution R for the second band in the retrieval scheme, as well as the subpixel cloud cover. Here, the estimated values compare well to actually observed ASTER results and are used to retrieve cloud properties, which are unbiased by the clear-sky component of PCL pixels. While the presented retrieval approach is only evaluated for marine boundary layer clouds, it is computationally efficient and can be easily applied to observations from different imagers. As an example, the PCL retrieval scheme is applied to data by the Moderate Resolution Imaging Spectroradiometer, where similar biases for PCL pixels are observed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantum pixel representations and compression for N-dimensional images

Abstract We introduce a novel and uniform framework for quantum pixel representations that overarches many of the most popular representations proposed in the recent literature, such as (I)FRQI, (I)NEQR, MCRQI, and (I)NCQI. The proposed QPIXL framework results in more efficient circuit implementations and significantly reduces the gate complexity for all considered quantum pixel representations. Our method scales linearly in the number of pixels and does not use ancilla qubits. Furthermore, the circuits only consist of $$R_y$$ R y gates and $$\text {CNOT}$$ CNOT gates making them practical in the NISQ era. Additionally, we propose a circuit and image compression algorithm that is shown to be highly effective, being able to reduce the necessary gates to prepare an FRQI state for example scientific images by up to 90% without sacrificing image quality. Our algorithms are made publicly available as part of , a Quantum Image Pixel Library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Si pixel detectors in the detection of EC/EC decay

The SPT collaboration has been investigating the applicability of pixel detectors in the detection of two neutrino double electron capture (2νEC/EC) in{sup 106}Cd. The collaboration has proposed a Silicon Pixel Telescope (SPT) where a pair of Si pixel detectors with enriched Cd foil in the middle forms the detection unit. The Pixel detector gives spatial information along with energy of the particle, thus helps to identify and remove the background signals. Four units of SPT prototype (using 0.5 and 1 mm Si sensors) were fabricated and installed in the LSM underground laboratory, France. Recent progress in the SPT experiment and preliminary results from background measurements are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Radiation hardness assessment of the charge-integrating hybrid pixel detector JUNGFRAU 1.0 for photon science

JUNGFRAU (adJUstiNg Gain detector FoR the Aramis User station) is a two-dimensional hybrid pixel detector for photon science applications in free electron lasers, particularly SwissFEL, and synchrotron light sources. JUNGFRAU is an automatic gain switching, charge-integrating detector which covers a dynamic range of more than 10{sup 4} photons of an energy of 12 keV with a good linearity, uniformity of response, and spatial resolving power. The JUNGFRAU 1.0 application-specific integrated circuit (ASIC) features a 256 × 256 pixel matrix of 75 × 75 μm{sup 2} pixels and is bump-bonded to a 320 μm thick Si sensor. Modules of 2 × 4 chips cover an area of about 4 × 8 cm{sup 2}. Readout rates in excess of 2 kHz enable linear count rate capabilities of 20 MHz (at 12 keV) and 50 MHz (at 5 keV). The tolerance of JUNGFRAU to radiation is a key issue to guarantee several years of operation at free electron lasers and synchrotrons. The radiation hardness of JUNGFRAU 1.0 is tested with synchrotron radiation up to 10 MGy of delivered dose. The effect of radiation-induced changes on the noise, baseline, gain, and gain switching is evaluated post-irradiation for both the ASIC and the hybridized assembly. The bare JUNGFRAU 1.0 chip can withstand doses as high as 10 MGy with minor changes to its noise and a reduction in the preamplifier gain. The hybridized assembly, in particular the sensor, is affected by the photon irradiation which mainly shows as an increase in the leakage current. Self-healing of the system is investigated during a period of 11 weeks after the delivery of the radiation dose. Annealing radiation-induced changes by bake-out at 100 °C is investigated. It is concluded that the JUNGFRAU 1.0 pixel is sufficiently radiation-hard for its envisioned applications at SwissFEL and synchrotron beam lines.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

The high dynamic range pixel array detector (HDR-PAD): Concept and design

Experiments at storage ring light sources as well as at next-generation light sources increasingly require detectors capable of high dynamic range operation, combining low-noise detection of single photons with large pixel well depth. XFEL sources in particular provide pulse intensities sufficiently high that a purely photon-counting approach is impractical. The High Dynamic Range Pixel Array Detector (HDR-PAD) project aims to provide a dynamic range extending from single-photon sensitivity to 10{sup 6} photons/pixel in a single XFEL pulse while maintaining the ability to tolerate a sustained flux of 10{sup 11} ph/s/pixel at a storage ring source. Achieving these goals involves the development of fast pixel front-end electronics as well as, in the XFEL case, leveraging the delayed charge collection due to plasma effects in the sensor. A first prototype of essential electronic components of the HDR-PAD readout ASIC, exploring different options for the pixel front-end, has been fabricated. Here, the HDR-PAD concept and preliminary design will be described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Ultrafast processing of pixel detector data with machine learning frameworks

Modern photon science performed at high repetition rate free-electron laser (FEL) facilities and beyond relies on 2D pixel detectors operating at increasing frequencies (towards 100 kHz at LCLS-II) and producing rapidly increasing amounts of data (towards TB/s). This data must be rapidly stored for offline analysis and summarized in real time for online feedback to the scientists. While at LCLS all raw data has been stored, at LCLS-II this would lead to a prohibitive cost; instead, enabling real time processing of pixel detector data (dark, gain, common mode, background, charge summing, subpixel position, photon counting, data summarization) allows reducing the size and cost of online processing, offline processing and storage by orders of magnitude while preserving full photon information. This could be achieved by taking advantage of the compressibility of sparse data typical for LCLS-II applications. Faced with a similar big data challenge a decade ago, computer vision stimulated revolutionary advances in machine learning hardware and software. We investigated if these developments are useful in the field of data processing for high speed pixel detectors and found that typical deep learning models and autoencoder architectures failed to yield useful noise reduction while preserving full photon information, presumably because of the very different statistics and feature sets in computer vision and radiation imaging. However, the raw performance of modern frameworks like Tensorflow inspired us to redesign in Tensorflow mathematically equivalent versions of the state-of-the-art, “classical” algorithms used at LCLS. The novel Tensorflow models resulted in elegant, compact and hardware agnostic code, gaining 1 to 2 orders of magnitude faster processing on an inexpensive consumer GPU, reducing by 3 orders of magnitude the projected cost of online analysis and compression without photon loss at LCLS-II. The novel Tensorflow models also enabled ongoing development of a pipelined hardware system expected to yield an additional 3 to 4 orders of magnitude speedup, necessary for meeting the data acquisition and storage requirements at LCLS-II, potentially enabling acquiring every single FEL pulse at full speed. Computer vision a decade ago was dominated by hand-crafted filters; their structure inspired the deep learning revolution resulting in modern deep convolutional networks; similarly, our novel Tensorflow filters provide inspiration for designing future deep learning models for ultrafast and efficient processing and classification of pixel detector images at FEL facilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Billion-pixel x-ray camera (BiPC-X)

The continuing improvement in quantum efficiency (above 90% for single visible photons), reduction in noise (below 1 electron per pixel), and shrink in pixel pitch (less than 1 μm) enable billion-pixel x-ray cameras (BiPC-X) based on commercial complementary metal–oxide–semiconductor (CMOS) imaging sensors. We describe BiPC-X designs and prototype construction based on flexible tiling of commercial CMOS imaging sensors with millions of pixels. Device models are given for direct detection of low energy x rays (<10 keV) and indirect detection of higher energies using scintillators. Modified Birks’s law is proposed for light yield non-proportionality in scintillators as a function of x-ray energy. Single x-ray sensitivity and spatial resolution have been validated experimentally using a laboratory x-ray source and the Argonne Advanced Photon Source. Possible applications include wide field-of-view or large x-ray aperture measurements in high-temperature plasmas, the state-of-the-art synchrotron, x-ray free electron laser, and pulsed power facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Beam test results of the dependence of signal size on incident particle flux in diamond pixel and pad detectors

Here, we present results of beam tests of charged particle detectors based on single-crystal and poly-crystalline Chemical Vapor Deposition (CVD) diamond. We measured the signal pulse height dependence on the particle flux. The detectors were tested over a range of particle fluxes from 2 kHz/cm 2 to 20 MHz/cm 2 . The pulse height of the sensors was measured with pad and pixel readout electronics. The pulse height of the non-irradiated single-crystal CVD diamond pad sensors was stable with respect to flux, while the pulse height of irradiated single-crystal CVD diamond pad sensors decreased with increasing particle flux. The pulse height of the non-irradiated single-crystal CVD diamond pixel detectors decreased slightly with increasing particle flux while the pulse height of the irradiated single-crystal CVD diamond pixel detectors decreased significantly with increasing particle flux. The observed sensitivity to flux is similar in both the diamond pad sensors constructed using diamonds from the Pixel Luminosity Telescope (PLT) irradiated during its pilot run in the Compact Muon Solenoid (CMS) detector and in neutron irradiated diamond pad sensors from the same manufacturer irradiated to the same fluence of neutrons. The pulse height for irradiated poly-crystalline CVD diamond pad sensors proved to be stable with respect to particle flux.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Test beam performance measurements for the Phase I upgrade of the CMS pixel detector

A new pixel detector for the CMS experiment was built in order to cope with the instantaneous luminosities anticipated for the Phase~I Upgrade of the LHC. The new CMS pixel detector provides four-hit tracking with a reduced material budget as well as new cooling and powering schemes. A new front-end readout chip mitigates buffering and bandwidth limitations, and allows operation at low comparator thresholds. Here in this paper, comprehensive test beam studies are presented, which have been conducted to verify the design and to quantify the performance of the new detector assemblies in terms of tracking efficiency and spatial resolution. Under optimal conditions, the tracking efficiency is $99.95\pm0.05\,\%$, while the intrinsic spatial resolutions are $4.80\pm0.25\,\mu \mathrm{m}$ and $7.99\pm0.21\,\mu \mathrm{m}$ along the $100\,\mu \mathrm{m}$ and $150\,\mu \mathrm{m}$ pixel pitch, respectively. The findings are compared to a detailed Monte Carlo simulation of the pixel detector and good agreement is found.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

The construction of the phase-1 upgrade of the CMS pixel detector

The innermost layers of the original CMS tracker were built out of pixel detectors arranged in three barrel layers and two forward disks in each endcap. The original CMS detector was designed for the nominal instantaneous LHC luminosity of 1×10 34 cm -2 s -1 . Under the conditions expected in the coming years, which will see an increase of a factor two of the instantaneous luminosity, the CMS pixel detector would have seen a dynamic inefficiency caused by data losses due to buffer overflows. For this reason the CMS collaboration has installed a replacement pixel detector during the recent extended end of year shutdown. The phase-1 upgrade of the CMS pixel detector will operate at high efficiency at an instantaneous luminosity of 2×10 34 cm -2 s -1 with increased detector acceptance and additional redundancy for the tracking, while at the same time reducing the material budget. These goals are achieved using a new read-out chip and modified powering and read-out schemes, one additional tracking layer both in the barrel and in the disks, and new detector supports including a CO 2 based evaporative cooling system, that contribute to the reduction of the material in the tracking volume. This contribution will review the design and technological choices of the phase-1 detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Testbeam results of irradiated ams H18 HV-CMOS pixel sensor prototypes

HV-CMOS pixel sensors are a promising option for the tracker upgrade of the ATLAS experiment at the LHC, as well as for other future tracking applications in which large areas are to be instrumented with radiation-tolerant silicon pixel sensors. We present results of testbeam characterisations of the 4 th generation of Capacitively Coupled Pixel Detectors (CCPDv4) produced with the ams H18 HV-CMOS process that have been irradiated with different particles (reactor neutrons and 18 MeV protons) to fluences between 1×10 14 and 5×10 15 1–MeV– n eq . The sensors were glued to ATLAS FE-I4 pixel readout chips and measured at the CERN SPS H8 beamline using the FE-I4 beam telescope. Results for all fluences are very encouraging with all hit efficiencies being better than 97% for bias voltages of 85 V. The sample irradiated to a fluence of 1×10 15 neq—a relevant value for a large volume of the upgraded tracker—exhibited 99.7% average hit efficiency. Furthermore, the results give strong evidence for the radiation tolerance of HV-CMOS sensors and their suitability as sensors for the experimental HL-LHC upgrades and future large-area silicon-based tracking detectors in high-radiation environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Argonne Pixel Tracking Telescope at the Fermilab Test Beam Facility

The Argonne Pixel Tracking Telescope is installed at the Fermilab Test Beam Facility. The telescope consists of six planar n + -in-n silicon sensors with a pixel size of 250 × 50 μm 2 . The instrumentation of the telescope is described including the electrical and mechanical setups. A 120 GeV proton beam is used to evaluate the telescope performance using criteria such as cluster size, pixel tracking efficiency, and spatial resolution. The spatial resolution of the telescope is measured to be 72 μm × 13 μm and is consistent with the resolution determined from the simulation. In conclusion, this telescope will be used to test the performance of the various silicon pixel technology as well as to study the effects and the performance of the detectors after being irradiated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

High-Voltage CMOS Active Pixel Sensor

The high-voltage CMOS (HVCMOS) sensors are a novel type of CMOS active pixel sensors for ionizing particles that can be implemented in CMOS processes with deep n-well option. The pixel contains one sensor electrode formed with a deep n-well implanted in a p-type substrate. CMOS pixel electronics, embedded in shallow wells, are placed inside the deep n-well. By biasing the substrate with a high negative voltage and by the use of a lowly doped substrate, a depleted region depth of at least 30 µm can be achieved. The electrons generated by a particle are collected by drift, which induces fast detectable signals. This publication presents a 4.2-cm 2 large HVCMOS pixel sensor implemented in a commercial 180-nm process on a lowly doped substrate and its characterization.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

ASDFL: An adaptive super‐pixel discriminative feature‐selective learning for vehicle matching

Abstract There are a large number of cameras in modern transportation system that capture numerous vehicle images continuously. Therefore, automatic analysis of these vehicle images is helpful for traffic flow management, criminal investigations and vehicle inspections. Vehicle matching, which aims to determine whether two input images depict an identical vehicle, is one of the core tasks in vehicle analysis. Recent relevant studies have focused on local feature extraction instead of global extraction, since local details can provide crucial cues to distinguish between cars. However, these methods do not select local features; that is, they do not assign weights to local features. Therefore, in this research, we systematically study the vehicle matching task, and present a novel annotation‐free local‐based deep learning method called Adaptive super‐pixel discriminative feature‐selective learning (ASDFL) to address this issue. In ASDFL, vehicle images are segmented into clusters of super‐pixels of similar size by considering the location and colour similarities of pixels without using any component‐level annotation. These super‐pixels are deemed to be the virtual components of vehicles. Moreover, a convolutional neural network is used to extract the deep features of these virtual components. Thereafter, an instance‐specific mask generation module driven by the extracted global features is enhanced to produce a mask to select the most distinctive virtual components of each vehicle image pair in the feature space. Finally, the vehicle matching task is accomplished by classifying the selected virtual component features of each imaged vehicle pair. Extensive experiments on two popular vehicle identification benchmarks demonstrate that our method is 1.57% and 0.8% more accurate than the previous baselines in a vehicle matching task on the VeRi and VehicleID datasets, respectively, which demonstrates the effectiveness of our method.

Qin, Rong↗