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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Cryogenic readout integrated circuit with analog pile-up and in-Pixel ADC for high frame rate Skipper CCD-in-CMOS Sensors

The Skipper CCD-in-CMOS Parallel Read-Out Circuit V2 (SPROCKET2) is designed to enable high frame rate readout of Skipper CCD-in-CMOS image sensors. The SPROCKET2 pixel is fabricated in a 65 nm CMOS process and occupies a 60$\mu$m $\times$ 60$\mu$m footprint. SPROCKET2 is intended to be heterogeneously integrated with a pixelated Skipper CCD-in-CMOS sensor, such that one readout pixel is connected to a multiplexed array of 16 active image sensor pixels, to match their spatial geometry. Our design benefits from the Skipper CCD-in-CMOS sensor's non-destructive readout capability to achieve exceptionally low noise through multi-sampling and averaging while optimizing for total power consumption. The pixel readout utilizes correlated double sampling to minimize 1/f noise and includes "pile-up" of ten successive samples in the analog domain before digitizing at a rate of 66.7 ksps. Measurement results of in-pixel serial SAR ADC show DNL and INL of ~0. 44 LSB and 0.58 LBS respectively. A large area array of 20,000 SPROCKET2 ADC pixels (multiplexed 1:16 to 320,000 sensor pixels) is currently under test. By reading out data over a 10 Gbps optical link, this pixel design enables a frame rate of $\sim$ 4 kfps for large sensing areas with minimal sensing deadtime. In the highest gain mode, the pixelated ADC has an input-referred resolution of 10$\mu$V with a simulated power consumption of 50$\mu$W. The pixel operates with constant current draw to minimize power-rail crosstalk.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Fast and Accurate Pixel Calibration of Tof Neutron Diffractometers with Machine Learning

At a spallation neutron source, neutron pulses of varying energies are generated, and the detection of neutrons by instrument detectors is recorded as time-of-flight from the emission of the neutron pulse to its arrival at specific detector pixels with high time resolution. The flight path of neutrons from the moderator to the sample and then to the detector must be precisely calibrated at the detector-pixel level using standard powders, so the neutron events from all pixels can be time-focused to produce high-resolution diffraction patterns. Modern time-of-flight neutron diffractometers at spallation neutron sources are equipped with two-dimensional detectors with millimeter-scale pixelations. The number of pixels in a diffraction instrument can reach millions, which makes a single-pixel-level calibration process time-consuming or even impossible with conventional refinement or fitting approaches. Here we present a machine-learning-aided calibration process using a train-and-predict approach, in which machine learning models are trained on the relationship between an individual pixel time-of-flight diffraction pattern and its diffraction constant. These models use a portion of the available pixels for training, and a good model then predicts the diffraction constants precisely and rapidly for large sets of pixel diffraction patterns.

detector pixel calibration↗
DOE OSTI2025

Detector pixel calibration of time-of-flight neutron diffractometers accelerated by machine learning

Modern time-of-flight neutron diffractometers at spallation neutron source are equipped with two dimensional detectors with fine pixelations. The flight path of neutrons from the moderator to the sample and to the detector needs to be precisely calibrated at detector pixel level using standard powders so the diffraction data from all the detector pixels can be correctly time-focused to produce high resolution diffraction peaks. The number of pixels can reach to millions which makes a single-pixel calibration process time-consuming, or even impossible, with conventional fitting routine. Here we presented a machine learning aided calibration process via a “training and predict” process by training machine learning models with the relations between the individual pixel time-of-flight diffraction pattern and fitted diffraction constant. The training models take a portion of the available pixels to predict the diffraction constants precisely and rapidly for massive pixel diffraction patterns.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

The CMS Phase-1 Pixel Detector Upgrade

The CMS detector at the CERN LHC features a silicon pixel detector as its innermost subdetector. The original CMS pixel detector has been replaced with an upgraded pixel system (CMS Phase-1 pixel detector) in the extended year-end technical stop of the LHC in 2016/2017. The upgraded CMS pixel detector is designed to cope with the higher instantaneous luminosities that have been achieved by the LHC after the upgrades to the accelerator during the first long shutdown in 2013–2014. Compared to the original pixel detector, the upgraded detector has a better tracking performance and lower mass with four barrel layers and three endcap disks on each side to provide hit coverage up to an absolute value of pseudorapidity of 2.5. This paper describes the design and construction of the CMS Phase-1 pixel detector as well as its performance from commissioning to early operation in collision data-taking.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

RD53 pixel readout integrated circuits for ATLAS and CMS HL-LHC upgrades

The RD53 collaboration has since 2013 developed new hybrid pixel detector chips with 50 × 50 μm2 pixels for the HL-LHC upgrades of the ATLAS and CMS experiments at CERN. A common architecture, design and verification framework has been developed to enable final pixel chips of different sizes to be designed, verified and tested to handle extreme hit rates of 3 GHz/cm2 (up to 12 GHz per chip) together with an increased trigger rate of 1 MHz and efficient readout of up to 5.12 Gbits/s per pixel chip. Tolerance to an extremely hostile radiation environment with 1 Grad over 10 years and induced SEU (Single Event Upset) rates of up to 100 upsets per second per chip have been major challenges to make reliable pixel chips. Three generations of pixel chips, and many specific mixed signal building blocks and radiation test chips, have been submitted and extensively tested to get to final production chips. The large, complex and high rate pixel chips have been developed with a strong emphasis on low power consumption together with a concurrent development and qualification of novel serial powering at chip, module and system level, to minimize detector material budget.

Alimonti, G↗
DOE OSTI2024

Radiation-Hard Smart-Pixel Detector ASIC ReadOut with Digital AI in 28nm

Detectors at future high energy colliders will face enormous technical challenges. Disentangling the unprecedented numbers of particles expected in each event will require highly granular silicon pixel detectors with billions of readout channels. With event rates as high as 40 MHz, these detectors will generate petabytes of data per second. To enable discovery within strict bandwidth and latency constraints, future trackers must be capable of fast, power efficient, and radiation hard data-reduction at the source. This effort is pursuing the co-design development of high-performance readout smart pixel ASICs for a future Phase III High Luminosity upgrade of the Large Hadron Collider. A 1.6mm2 ASIC prototype was designed by Fermilab in CMOS 28 nm bulk process and submitted for manufacturing in February 2024. It leverages the analog front-end pixel design of a previous prototype fabricated and tested in 2023, which achieved a simulated detection level of ~400e- with 30fF input capacitance. The ROIC consists of two matrices of 16×16 smart pixels, each 25×25 μm2 in size. Each smart pixel contains a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. There is digital space for the integration of our fully combinatorial AI that performs momentum classification at the bunch crossing rate. The total power consumption is ∼6μW per pixel, which corresponds to ~1mW/cm2. The ASIC incorporates programmable front-end charge injection circuitry to generate pixel cluster charges during characterization. The cluster profile will be generated to duplicate hit characteristics of various momentum (pT). We will present early results from chip testing.

Parpillon, Benjamin↗
DOE OSTI2023

In-pixel AI for lossy data compression at source for X-ray detectors

Integrating neural networks for data compression directly in the Read-Out Integrated Circuits (ROICs), i.e. the pixelated front-end, would result in a significant reduction in off-chip data transfer, overcoming the I/O bottleneck. Our ROIC test chip (AI-In-Pixel-65) is designed in a 65 nm Low Power CMOS process for the readout of pixelated X-ray detectors. Each pixel consists of an analog front-end for signal processing and a 10b analog-to-digital converter operating at 100KSPS. Here, we compare two non-reconfigurable techniques, Principal Component Analysis (PCA) and an AutoEncoder (AE) as lossy data compression engines implemented within the pixelated area. The PCA algorithm achieves 50$×$ compression, adds one clock cycle latency, and results in a 21% increase in the pixel area. The AE achieves 70$×$ compression, adds 30 clock cycle latency, and results in a similar area increase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

RD53A: A large-scale prototype chip for the phase II upgrade in the serially powered HL-LHC pixel detectors

The phase II upgrade of the HL-LHC experiments within the LHC intends to deepen the studies of the Higgs boson and to allow the discovery of further particles by adding an integrated luminosity of about 4000 fb -1 over 10 years of operation. This upgrade would overwhelm the installed pixel detector readout chips with higher hit rates and radiation levels than ever before. To match these extreme requirements the RD53 collaboration, a joint effort between ATLAS and CMS, developed RD53A, a new generation pixel detector readout chip prototype manufactured in a 65 nm CMOS technology. It is half the size of the final pixel chips and designed to meet requirements in the face of 3 GHz/cm 2 hit rate after irradiation to 500 Mrad. The detector is able to use 50×50 μm 2 or 25×100 μm 2 pixels with high readout speed of up to 4 links per chip with 1.28 Gbit/s each. Shunt–LDO regulators integrated on the bottom of the chip provide the required voltages to the two power domains, analog and digital. These regulators enable serial powering of the pixel modules, which is the only feasible, radiation hard scheme to ensure acceptable power cable losses and to stay within the material budget for the future pixel detectors. Finally, an overview of the status and challenges of serial powering and the Shunt–LDO regulator development will be given.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

The development of a 6 Li-based pixelated neutron detector for neutron reflectometry at the Spallation Neutron Source

We present a high-rate 6 Li-based pixelated neutron detector developed for neutron reflectometry instruments at the Spallation Neutron Source (SNS). The neutron detector has a pixelated design: each 6 Li scintillator element has its own photosensor and independent channel readout. This paper focuses on the general overview of the detector design and construction, the characterization of the pixelated detector, and the results of the first neutron reflectivity experiments conducted using the pixelated neutron detector at the SNS Liquid Reflectometer (BL-4B). The pixelated neutron detector demonstrated a global time-average count rate of ≥ 1.8 x 10 6 cps, at least 3 orders of magnitude higher than that of the existing neutron detector ( 3 He-based Multi-Wire Proportional Counter), and a local instantaneous count rate of ≥ 1.73 x 10 6 cps / cm 2 . The maximum counting rate of the detector has not yet been determined as the detector is capable of handling the maximum flux available at the beamline. Furthermore, the outcome of the neutron reflectivity experiments showed that the pixelated neutron detector is a promising candidate for next-generation neutron reflectometry instruments at the SNS.

6Li, silicon photomultiplier↗
DOE OSTI2022

Charge sharing in pixelated semiconductor sensors

The charge sharing between neighboring pixels in pixelated sensors can be used to measure particle or x-ray coordinates with accuracy better than the pixel pitch. The accurate model of the charge distribution shape is essential to achieve ultimate coordinate accuracy. The charge sharing is caused by charge carriers' diffusion on the path from the generation point to pixels. This paper is focused on the diffusion of the initially compact charge cloud in the field free region. The diffusion equation solutions are obtained using separation of variable and Fourier synthesis method for different initial conditions and resulting charge distributions are integrated over pixel areas. In conclusion, the look up table containing pre-calculated values for pixel charge fractions is proposed to speed up numerical calculations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

2D microspatial distribution uniformity of photon detection efficiency and crosstalk probability of multi-pixel photon counters

Two-dimensional (2D) microspatial distribution uniformity of photon detection efficiency (PDE) and optical crosstalk probability P{sub ct} of multi-pixel photon counters (MPPCs) is studied. The experimental results show that the 2D spatial distribution of P{sub ct} is obviously uneven, i.e. P{sub ct} is larger at the corners and edges of a single pixel in MPPCs, which suggest a higher electrical field in the depletion region of the pixel at the corners and edges. The nonuniformity of the 2D spatial distribution of PDE also become evident when the size of the pixels of MPPCs is small, which signifies higher nonuniformity of the electric field distribution in MPPCs with small pixel size. A method is proposed for characterization of the 2D electrical field spatial distribution uniformity in a single pixel of MPPCs, which can be used for guiding the optimisation of the fabrication process of MPPCs and their properties. This promising method can naturally be extended to any Geiger avalanche photodiodes (G-APDs) and their arrays. (laser applications and other topics in quantum electronics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Hyperspectral acquisition with ScanImage at the single pixel level: application to time domain coherent Raman imaging

We present a comprehensive strategy and its practical implementation using the commercial ScanImage software platform to perform hyperspectral point scanning microscopy when a fast time-dependent signal varies at each pixel level. In the proposed acquisition scheme, the scan along the X-axis is slowed down while the data acquisition is maintained at a high pace to enable the rapid acquisition of the time-dependent signal at each pixel level. The ScanImage generated raw 2D images have a very asymmetric aspect ratio between X and Y, the X axis encoding both for space and time acquisition. The results are X-axis macro-pixel where the associated time-dependent signal is sampled to provide hyperspectral information. We exemplified the proposed hyperspectral scheme in the context of time-domain coherent Raman imaging, where a pump pulse impulsively excites molecular vibrations that are subsequently probed by a time-delayed probe pulse. In this case, the time-dependent signal is a fast acousto-optics delay line that can scan a delay of 4.5ps in 25 μ s at each pixel level. With this acquisition scheme, we demonstrate ultra-fast hyperspectral vibrational imaging in the low frequency range [10 cm −1 , 150 cm −1 ] over a 500 μm field of view (64 x 64 pixels) in 130ms (∼ 7.5 frames/s). The proposed acquisition scheme can be readily extended to other applications requiring the acquisition of a fast-evolving signal at each pixel level.

Metais, Samuel↗
DOE OSTI2024

Unsupervised Learning for Improved Gamma-Ray Spectrometry in Pixelated Cadmium Zinc Telluride (CZT) Detectors

Machine learning has been found to be ubiquitously useful across many industries, presenting an opportunity to improve radiation detection performance using data-driven algorithms. Improved detector resolution can aid in the detection, identification, and quantification of radionuclides. Here, in this work, a novel, data-driven, unsupervised learning approach is developed to improve detector spectral characteristics by learning, and subsequently rejecting, poorly performing regions of the pixelated detector. Feature engineering is used to fit individual characteristic photo peaks to a Doniach lineshape with a linear background model. Then, principal component analysis is used to learn a lower-dimension latent space representation of each photo peak where the pixels are clustered, and subsequently ranked, based on the cluster mean distance to an optimal point. Pixels within the worst cluster(s) are rejected to improve the full-width at half-maximum (FWHM) by 10% to 15% (relative to the bulk detector) at 50% net efficiency when applied to training data obtained from measurements of a 100 μCi 154 Eu source using a H3D M400i pixelated cadmium zinc telluride detector. These results compare well with, but do not outperform, a greedy algorithm that accumulates pixels in order of FWHM from lowest to highest used as a benchmark. In the future, this approach can be extended to include the detector energy and angular response. Finally, the model is applied to newly seen natural and enriched uranium spectra relevant for nuclear safeguards applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Sensor response and radiation damage effects for 3D pixels in the ATLAS IBL Detector

Pixel sensors in 3D technology equip the outer ends of the staves of the Insertable B Layer (IBL), the innermost layer of the ATLAS Pixel Detector, which was installed before the start of LHC Run 2 in 2015. 3D pixel sensors are expected to exhibit more tolerance to radiation damage and are the technology of choice for the innermost layer in the ATLAS tracker upgrade for the HL-LHC programme. While the LHC has delivered an integrated luminosity of ≃ 235 fb -1 since the start of Run 2, the 3D sensors have received a non-ionising energy deposition corresponding to a fluence of ≃ 8.5 × 10 14 1 MeV neutron-equivalent cm -2 averaged over the sensor area. This paper presents results of measurements of the 3D pixel sensors' response during Run 2 and the first two years of Run 3, with predictions of its evolution until the end of Run 3 in 2025. Data are compared with radiation damage simulations, based on detailed maps of the electric field in the Si substrate, at various fluence levels and bias voltage values. These results illustrate the potential of 3D technology for pixel applications in high-radiation

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

First constraints on a pixelated universe in light of DESI observations

Pixelated dark energy is a string theory scenario with a quantum mechanically stable cosmological constant. The number of pixels that make up the universe slowly increases, manifesting as a time-dependent source of dark energy. DESI has recently reported evidence for dynamical dark energy that fits within this framework. In light of this, we perform the first cosmological analysis of the pixelated model. We find that the simplest model where the pixel growth rate is constant is able to accommodate the data, providing a marginally better fit than Λ⁢ CDM; and we show that models where the pixel growth rate is increasing and of order the Hubble constant today could provide better fits. Our analysis helps to clarify the features of UV constructions of dark energy necessary to accommodate the data.

dark energy↗
DOE OSTI2022

RiverPIXELS: paired Landsat images and expert-labeled sediment and water pixels for a selection of rivers v1.0

RiverPIXELS contains GeoTIFFs of hand-labeled water and sediment pixels from Landsat images containing rivers. Each of the 104 labeled patches contains 256 x 256 Landsat pixels (30 meter resolution). Our aim in releasing RiverPIXELS is to provide an "off-the-shelf" training and testing dataset for building machine-learned models to automatically identify rivers from multispectral imagery. While a number of trained models and/or surface water products already exist, RiverPIXELS aims for pixel-level accuracy in order to precisely identify river boundaries in particular. Our selection of rivers is heavily Arctic, but we include tropical and temperate rivers as well. Patches are provided for the Colville (7), Indigirka (6), Kolyma (4), Ucayali (54), Waitaki (21), and Yana (12) Rivers. For each patch, all surface water pixels are labeled (1) and all in-channel sediment pixels are labeled (2). Sediments not in-channel are considered part of the land (0) class. RiverPIXELS also includes paired surface water data from the Global Surface Water dataset that may be useful as additional features in machine learning models. Each patch therefore contains four aligned GeoTIFFs: labeled, landsat, gswmo, and gswocc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Equalizing the Pixel Response of the Imaging Photoelectric Polarimeter Onboard the IXPE Mission

The Gas Pixel Detector is a gas detector, sensitive to the polarization of X-rays, currently flying onboard the Imaging X-ray Polarimetry Explorer (IXPE)—the first observatory dedicated to X-ray polarimetry. It detects X-rays and their polarization by imaging the ionization tracks generated by photoelectrons absorbed in the sensitive volume, and then reconstructing the initial direction of the photoelectrons. The primary ionization charge is multiplied and ultimately collected on a finely pixellated ASIC specifically developed for X-ray polarimetry. The signal of individual pixels is processed independently and gain variations can be substantial, of the order of 20%. Such variations need to be equalized to correctly reconstruct the track shape, and therefore its polarization direction. The method to do such equalization is presented here and is based on the comparison between the mean charge of a pixel with respect to the other pixels for equivalent events. The method is shown to finely equalize the response of the detectors onboard IXPE, allowing a better track reconstruction and energy resolution, and can in principle be applied to any imaging detector based on tracks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Characterization of a Pixelated Cadmium Telluride Detector System Using a Polychromatic X-Ray Source and Gold Nanoparticle-Loaded Phantoms for Benchtop X-Ray Fluorescence Imaging

In this paper, the imaging dose and scan time have been considered as the two major constraints for routine benchtop x-ray fluorescence computed tomography (XFCT) imaging. One way to address this issue is to acquire x-ray fluorescence (XRF) signals in parallel through a 2D array of single-crystal detectors or a pixelated detector along with the cone-beam x-ray source. To identify a detector system suitable for this purpose, a commercially available, fully spectroscopic cadmium telluride (CdTe) pixelated detector, HEXITEC (High-Energy X-ray Imaging Technology), was tested under the experimental conditions optimized for benchtop XFCT imaging of gold nanoparticles (GNPs). Specifically, two different parallel-hole stainless steel collimators were fabricated and coupled with the detector for seamless integration into our existing benchtop cone-beam XFCT system. After the detector deployment, this benchtop XFCT system was used to detect XRF photons from GNP-loaded phantoms. A pixel-merging algorithm was introduced to enhance the sensitivity of XRF photon detection thereby minimizing the scan time. The effect of pixel-level charge sharing correction algorithms was investigated within the context of benchtop XFCT imaging. The detector energy resolution, in terms of the full width at half maximum (FWHM) values at different gold K-shell XRF energies, was also determined. Of the two charge sharing correction algorithms examined, the charge sharing addition gave better sensitivity than the charge sharing discrimination (csd). On the other hand, under the current experimental conditions, the energy resolution of the HEXITEC detector was the best with the csd and estimated to be 1.56 keV FWHM at 66-69 keV photon energy. Overall, despite some degradation of the detector energy resolution (compared with typical single crystal CdTe detectors), the HEXITEC detector enabled parallel data acquisition under the experimental conditions typical of benchtop XFCT imaging and operated well within our benchtop XFCT setup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗