Using a pulsed laser beam to investigate the feasibility of sub-pixel position resolution with time-correlated transient signals in 3D pixelated CdZnTe detectors
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Giraldo, L. Ocampo↗
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Study of sub-pixel position resolution with time-correlated transient signals in 3D pixelated CdZnTe detectors with varying pixel sizes
Here, we evaluated the sub-pixel position resolution achievable in large-volume CdZnTe pixelated detectors with conventional pixel patterns and for several different pixel sizes: 2.8 mm, 1.72 mm, 1.4 mm and 0.8 mm. Achieving position resolution below the physical dimensions of pixels (sub-pixel resolution) is a practical path for making high-granularity position-sensitive detectors, <100 μμm, using a limited number of pixels dictated by the mechanical constraints and multi-channel readout electronics. High position sensitivity is important for improving the imaging capability of CZT gamma cameras. It also allows for making more accurate corrections of response non-uniformities caused by crystal defects, thus enabling use of standard-grade (unselected) and less expensive CZT crystals for producing large-volume position-sensitive CZT detectors feasible for many practical applications. We analyzed the digitized charge signals from a representative 9 pixels and the cathode, generated using a pulsed-laser light beam focused down to 10 m (650 nm) to scan over a selected 3×3 pixel area. We applied our digital pulse processing technique to the time-correlated signals captured from adjacent pixels to achieve and evaluate the capability for sub-pixel position resolution. As an example, we also demonstrated an application of 3D corrections to improve the energy resolution and positional information of the events for the tested detectors.
36 MATERIALS SCIENCE↗
In-Pixel Readout IC with compact in-pixel ADC for Pixel detectors at HL LHC
The prototype Smart Pixel concept test chip (SP28), designed in a CMOS 28 nm bulk process, is a proof of concept readout integrated circuit (ROIC) designed for a future Phase III High Luminosity upgrade of the Large Hadron Collider. It employs a synchronous analog to digital converter (ADC) for the front-end design, with signal processing and data conversion within a single bunch crossing of 25 ns. It is therefore capable of accurately detecting hits occurring in consecutive bunch crossings, without off-time registration of events and pileup insensitivity, making it particularly suitable for the inner most layers of the vertex detector. The ROIC consists of a matrix of 32 × 16 pixels, each 25 × 25 µm 2 in size. Each pixel contains a charge sensitive preamplifer with leakage current compensation, three auto-zero comparators for a 2-bit fash-type ADC. The total power consumption is approximately 5 µW per pixel. The measured noise at the output of all the hit comparators across the ROIC is < 90 e- with threshold dispersion < 45 e-RMS, which allows an in-time threshold setting of ≈ 475 e-.
Parpillon, Benjamin↗
An Algorithm of an X-ray Hit Allocation to a Single Pixel in a Cluster and Its Test-Circuit Implementation
An on-chip implementable algorithm for allocation of an X-ray photon imprint, called a hit, to a single pixel in the presence of charge sharing in a highly segmented pixel detector is described. Its proof-of-principle implementation is also given supported by the results of tests using a highly collimated X-ray photon beam from a synchrotron source. The algorithm handles asynchronous arrivals of X-ray photons. Activation of groups of pixels, comparisons of peak amplitudes of pulses within an active neighborhood and finally latching of the results of these comparisons constitute the three procedural steps of the algorithm. A grouping of pixels to one virtual pixel, that recovers composite signals and event driven strobes, to control comparisons of fractional signals between neighboring pixels are the actuators of the algorithm. The circuitry necessary to implement the algorithm requires an extensive inter-pixel connection grid of analog and digital signals, that are exchanged between pixels. A test-circuit implementation of the algorithm was achieved with a small array of 32 × 32 pixels and the device was exposed to an 8 keV highly collimated to a diameter of 3-μm X-ray beam. Furthermore, the results of these tests are given in this paper assessing physical implementation of the algorithm.
47 OTHER INSTRUMENTATION↗
Characterization of an architecture for front-end pixel binning in an integrating pixel array detector
Optimization of an area detector involves compromises between various parameters like frame rate, read noise, dynamic range and pixel size. We have implemented and tested a novel front-end binning design in a photon-integrating hybrid pixel array detector using the MM-PAD- 2.0 pixel architecture. In this architecture, the pixels can be optionally binned in a 2 x 2 pixel configuration using a network of switches to selectively direct the output of 4 sensor pixels to a single amplifier input. Doing this allows a trade-off between frame rate and spatial resolution. Tests show that the binned pixels perform well, but with some degradation on performance as compared to an un-binned pixel. The increased parasitic input capacitance does reduce the signal collected per x-ray as well as increases the noise of the pixel. Here, the increase in noise is, however, less than the factor of 2 increase one would observe for binning in post-processing. Spatial scans across the binned pixels show that no measured signal intensity is lost at the inner binning unit boundaries. In the high flux regime, at a 2 x 2 pixel wide beam spot (FWHM) size, binned mode responds linearly up to a photon flux of 10 7 x-rays/s, and performs comparably with un-binned mode up to a photon flux of 10 8 x-rays/s. While this study demonstrates a proof of concept for front-end binning in integrating detectors, we also identify changes to this early-stage prototype which can further improve the performance of binning pixel structures.
47 OTHER INSTRUMENTATION↗
Urban Image Classification: Per-Pixel Classifiers, Sub-Pixel Analysis, Object-Based Image Analysis, and Geospatial Methods: Chapter - 10
Remote sensing methods used to generate base maps to analyze the urban environment rely predominantly on digital sensor data from space-borne platforms. This is due in part from new sources of high spatial resolution data covering the globe, a variety of multispectral and multitemporal sources, sophisticated statistical and geospatial methods, and compatibility with GIS data sources and methods. The goal of this chapter is to review the four groups of classification methods for digital sensor data from space-borne platforms; per-pixel, sub-pixel, object-based (spatial-based), and geospatial methods. Per-pixel methods are widely used methods that classify pixels into distinct categories based solely on the spectral and ancillary information within that pixel. They are used for simple calculations of environmental indices (e.g., NDVI) to sophisticated expert systems to assign urban land covers. Researchers recognize however, that even with the smallest pixel size the spectral information within a pixel is really a combination of multiple urban surfaces. Sub-pixel classification methods therefore aim to statistically quantify the mixture of surfaces to improve overall classification accuracy. While within pixel variations exist, there is also significant evidence that groups of nearby pixels have similar spectral information and therefore belong to the same classification category. Object-oriented methods have emerged that group pixels prior to classification based on spectral similarity and spatial proximity. Classification accuracy using object-based methods show significant success and promise for numerous urban 3 applications. Like the object-oriented methods that recognize the importance of spatial proximity, geospatial methods for urban mapping also utilize neighboring pixels in the classification process. The primary difference though is that geostatistical methods (e.g., spatial autocorrelation methods) are utilized during both the pre- and post-classification steps. Within this chapter, each of the four approaches is described in terms of scale and accuracy classifying urban land use and urban land cover; and for its range of urban applications. We demonstrate the overview of four main classification groups in Figure 1 while Table 1 details the approaches with respect to classification requirements and procedures (e.g., reflectance conversion, steps before training sample selection, training samples, spatial approaches commonly used, classifiers, primary inputs for classification, output structures, number of output layers, and accuracy assessment). The chapter concludes with a brief summary of the methods reviewed and the challenges that remain in developing new classification methods for improving the efficiency and accuracy of mapping urban areas.
Myint, Soe W.↗
Smart Pixels: In-pixel AI for on-sensor data filtering
We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 µm\textsuperscript{2} in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e\textsuperscript{-} and a total dispersion of $\sim$100e\textsuperscript{-} The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4\% – 75.4\% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm\textsuperscript{2} staying within the experimental constraints.
Parpillon, Benjamin↗
Smart Pixels: In-pixel AI for on-sensor data filtering
We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Evaluation of HPK n + - p planar pixel sensors for the CMS Phase-2 upgrade
To cope with the challenging environment of the planned high luminosity upgrade of the Large Hadron Collider (HL-LHC), scheduled to start operation in 2029, CMS will replace its entire tracking system. The requirements for the tracker are largely determined by the long operation time of 10 years with an instantaneous peak luminosity of up to 7.5 × 10 34 cm –2 s –1 in the ultimate performance scenario. Depending on the radial distance from the interaction point, the silicon sensors will receive a particle fluence corresponding to a non-ionizing energy loss of up to $\Phi_{\text {eq}}$ = 3.5 × 10 16 cm –2 . Here this paper focuses on planar pixel sensor design and qualification up to a fluence of $\Phi_{\text {eq}}$ = 1.4 × 10 16 cm –2 . For the development of appropriate planar pixel sensors an R&D program was initiated, which includes $n^+ -p$ sensors on 150 mm (6”) wafers with an active thickness of 150 μm with pixel sizes of 100 × 25 μm 2 and 50 × 50 μm 2 manufactured by Hamamatsu. Single chip modules with ROC4Sens and RD53A readout chips were made. Irradiation with protons and neutrons, as well was an extensive test beam campaign at DESY were carried out. This paper presents the investigation of various assemblies mainly with ROC4Sens readout chips. It demonstrates that multiple designs fulfill the requirements in terms of breakdown voltage, leakage current and efficiency. The single point resolution for 50 × 50 μm 2 pixels is measured as 4.0 μm for non-irradiated samples, and 6.3 μm after irradiation to $\Phi_{\text {eq}}$ = 7.2 × 10 15 cm –2 .
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Design methodology: edgeless 3D ASICs with complex in-pixel processing for pixel detectors
The design methodology for the development of 3D integrated edgeless pixel detectors with in-pixel processing using Electronic Design Automation (EDA) tools is presented. A large area 3 tier 3D detector with one sensor layer and two ASIC layers containing one analog and one digital tier, is built for x-ray photon time of arrival measurement and imaging. A full custom analog pixel is 65μm x 65μm. It is connected to a sensor pixel of the same size on one side, and on the other side it has approximately 40 connections to the digital pixel. A 32 x 32 edgeless array without any peripheral functional blocks constitutes a sub-chip. The sub-chip is an indivisible unit, which is further arranged in a 6 x 6 array to create the entire 1.248cm x 1.248cm ASIC. Each chip has 720 bump-bond I/O connections, on the back of the digital tier to the ceramic PCB. All the analog tier power and biasing is conveyed through the digital tier from the PCB. The assembly has no peripheral functional blocks, and hence the active area extends to the edge of the detector. This was achieved by using a few flavors of almost identical analog pixels (minimal variation in layout) to allow for peripheral biasing blocks to be placed within pixels. The 1024 pixels within a digital sub-chip array have a variety of full custom, semi-custom and automated timing driven functional blocks placed together. The methodology uses a modified mixed-mode on-top digital implementation flow to not only harness the tool efficiency for timing and floor-planning but also to maintain designer control over compact parasitically aware layout. The methodology uses the Cadence design platform, however it is not limited to this tool.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Spectral Measurement Errors due to CCD Serial Pixel-to-Pixel Readout Interference in the Ocean Color Instrument of the NASA PACE Mission
The Ocean Color Instrument on NASA’s PACE mission is a hyperspectral imager with a spatial resolution of 1km x 1km and spectral resolution of 5nm in 2.5nm steps over 320-890nm. The detection system is based on two Charge-Coupled Devices (CCDs) operating in Time Delay Integration (TDI) mode to achieve high signal-to-noise ratio. The front-end optical imager is a rotating mirror-based system that images the ground-scene onto a slit with a field of view of 16km x 1km. The slit-image is re-imaged and wavelength dispersed on the CCDs. As the ground-scene moves through the slit, it moves along the CCD columns as charge is moved along with it. The accumulated charge at the end of each column is collected in a serial pixel. Each of the 16 CCD outputs read out 32 columns of the same ground scene spaced 0.625nm apart. The 32-pixel serial register is swiftly read out before the next TDI cycle. The telescope is spinning at 5.77Hz to achieve the required spatial resolution. This results in a serial pixel readout speed of 8.5MHz. Each serial read-cycle goes through a reset and video period that are each sampled to create a low-noise correlated double sample value. This only allows 59ns for the reset and video to be asserted and settled before sampling. Due to the short time period, the response of the CCD exhibits serial pixel-to-pixel readout interference as the reset and video signals do not have time to fully settle before sampling. Each serial pixel value therefore has a dependence on the value of the preceding pixel value. This leads to a spectral measurement error of up to 0.3%. We explain the operation of the detection system, the behavior of the interference and the resulting wavelength error with results from ground testing and on-orbit characterization.
Ulrik B Gliese↗
Quality control of silicon pixel wafers for the CMS Phase-1 pixel upgrade
The CMS detector at the CERN Large Hadron Collider features as its innermost component a silicon pixel detector. The original pixel detector was completely replaced during the 2016-2017 winter technical stop. One of the goals of this Phase-1 Upgrade of the pixel detector was to replace the sensors in the original CMS forward pixel detector with new, unirradiated sensors. The new CMS forward pixel detector must survive an integrated luminosity of 300 fb$^{-1}$ before being replaced again prior to the High-Luminosity LHC era. Just as in the original construction, the Phase-1 forward pixel sensors were made of n$^{+}$-in-n Diffusion Oxygenated Float Zone silicon. This note documents the quality spot-checking of the new sensors, comparing our results with those provided by the vendor. In general there was good agreement between the results.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Pixel-to-pixel variation on a calibrated PILATUS3-based multi-energy soft x-ray detector
A multi-energy soft x-ray pin-hole camera based on the PILATUS3 100 K x-ray detector has recently been installed on the Madison Symmetric Torus. This photon-counting detector consists of a two-dimensional array of ∼100 000 pixels for which the photon lower-threshold cutoff energy Ec can be independently set for each pixel. This capability allows the measurement of plasma x-ray emissivity in multiple energy ranges with a unique combination of spatial and spectral resolution and the inference of a variety of important plasma properties (e.g., Te, nZ, Zeff). The energy dependence of each pixel is calibrated for the 1.6–6 keV range by scanning individual trimbit settings, while the detector is exposed to fluorescence emission from Ag, In, Mo, Ti, V, and Zr targets. The resulting data for each line are then fit to a characteristic “S-curve” which determines the mapping between the 64 possible trimbit settings for each pixel. The statistical variation of this calibration from pixel-to-pixel was explored, and it was found that the discreteness of trimbit settings results in an effective threshold resolution of ΔE < 100 eV. A separate calibration was performed for the 4–14 keV range, with a resolution of ΔE < 200 eV.
VanMeter, P. (ORCID:0000000244537948)↗
Performance of ePix10K, a high dynamic range, gain auto-ranging pixel detector for FELs
ePix10K is a hybrid pixel detector developed at SLAC for demanding free-electron laser (FEL) applications, providing an ultrahigh dynamic range (245 eV to 88 MeV) through gain auto-ranging. It has three gain modes (high, medium and low) and two auto-ranging modes (high-to-low and medium-to-low). The first ePix10K cameras are built around modules consisting of a sensor flip-chip bonded to 4 ASICs, resulting in 352 × 384 pixels of 100 µm x 100 µm each. We present results from extensive testing of three ePix10K cameras with FEL beams at LCLS, resulting in a measured noise floor of 245 eV rms, or 67 e - equivalent noise charge (ENC), and a range of 11 000 photons at 8 keV. We demonstrate the linearity of the response in various gain combinations: fixed high, fixed medium, fixed low, auto-ranging high to low, and auto-ranging medium-to-low, while maintaining a low noise (well within the counting statistics), a very low cross-talk, perfect saturation response at fluxes up to 900 times the maximum range, and acquisition rates of up to 480 Hz. Finally, we present examples of high dynamic range x-ray imaging spanning more than 4 orders of magnitude dynamic range (from a single photon to 11 000 photons/pixel/pulse at 8 keV). Achieving this high performance with only one auto-ranging switch leads to relatively simple calibration and reconstruction procedures. The low noise levels allow usage with long integration times at non-FEL sources. ePix10K cameras leverage the advantages of hybrid pixel detectors with high production yield and good availability, minimize development complexity through sharing the hardware, software and DAQ development with all other versions of ePix cameras, while providing an upgrade path to 5 kHz, 25 kHz and 100 kHz in three steps over the next few years, matching the LCLS-II requirements.
47 OTHER INSTRUMENTATION↗
Performance of CMOS pixel sensor prototypes in ams H35 and aH18 technology for the ATLAS ITk upgrade
Pixel sensors based on commercial high-voltage CMOS processes are an exciting technology that is considered as an option for the outer layer of the ATLAS inner tracker upgrade at the High Luminosity LHC. Here, charged particles are detected using deep n-wells as sensor diodes with the depleted region extending into the silicon bulk. Both analog and digital readout electronics can be added to achieve different levels of integration up to a fully monolithic sensor. Small scale prototypes using the ams CMOS technology have previously demonstrated that it can achieve the required radiation tolerance of 10(15) n(eq)/cm(2) and detection efficiencies above 99.5%. Recently, large area prototypes, comparable in size to a full sensor, have been produced that include most features required towards a final design: the H35demo prototype produced in ams H35 technology that supports both external and integrated readout and the monolithic ATLASPix1 pre-production design produced in ams aH18 technology. Both chips are based on large fill-factor pixel designs, but differ in readout structure. Performance results for H35DEMO with capacitively-coupled external readout and first results for the monolithic ATLASPix1 are shown.
ATLAS ITk upgrade↗
Experimental Study of an Easily Controlled Ultra-High-Resolution Pixel-Matched Parallel-Hole Collimator with a Small Cadmium Zinc Telluride Pixelated Gamma Camera System
The aim of this study was to develop an easily controlled, ultra-high-resolution, tungsten parallel-hole collimator based on a small pixelated gamma camera system. A small cadmium zinc telluride (CZT) pixelated semiconductor detector (eValuator-2500 detector [eV product, Saxonburg, PA]) was evaluated. This detector is composed of an array of 51.2 × 0.8 × 3-mm{sup 3} individual CZT crystal elements. The ultra-high-resolution, pixel-matched, parallel-hole collimators consisted of six layers, with the same between the hole and pixel size. The basic characteristics of the imaging system, such as sensitivity and spatial resolution, was measured using a {sup 57}Co point source. The measured averages of sensitivity and spatial resolution varied depending on the septal heights of the ultra-high-resolution parallel-hole collimator and source-to-collimator distances. When the 30-mm septal height was at 1-cm source-to-collimator distance, the spatial resolution was approximately 0.85 mm. Using 5-mm septal height, over 0.3 cps/kBq sensitivity was achieved. One advantage of our system is the use of stacked collimators that can select the best combination of system sensitivity and spatial resolution. Our results demonstrated that the developed CZT–pixelated gamma camera system using an ultra-high-resolution parallel-hole collimator of various collimator geometric designs has potential as an effective instrument.
62 RADIOLOGY AND NUCLEAR MEDICINE↗