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At least 109 records · Page 6

Improved Signal Chains for Readout of CMOS Imagers

An improved generic design has been devised for implementing signal chains involved in readout from complementary metal oxide/semiconductor (CMOS) image sensors and for other readout integrated circuits (ICs) that perform equivalent functions. The design applies to any such IC in which output signal charges from the pixels in a given row are transferred simultaneously into sampling capacitors at the bottoms of the columns, then voltages representing individual pixel charges are read out in sequence by sequentially turning on column-selecting field-effect transistors (FETs) in synchronism with source-follower- or operational-amplifier-based amplifier circuits. The improved design affords the best features of prior source-follower-and operational- amplifier-based designs while overcoming the major limitations of those designs. The limitations can be summarized as follows: a) For a source-follower-based signal chain, the ohmic voltage drop associated with DC bias current flowing through the column-selection FET causes unacceptable voltage offset, nonlinearity, and reduced small-signal gain. b) For an operational-amplifier-based signal chain, the required bias current and the output noise increase superlinearly with size of the pixel array because of a corresponding increase in the effective capacitance of the row bus used to couple the sampled column charges to the operational amplifier. The effect of the bus capacitance is to simultaneously slow down the readout circuit and increase noise through the Miller effect.

Pain, Bedabrata

Design and Fabrication of High-Efficiency CMOS/CCD Imagers

An architecture for back-illuminated complementary metal oxide/semiconductor (CMOS) and charge-coupled-device (CCD) ultraviolet/visible/near infrared- light image sensors, and a method of fabrication to implement the architecture, are undergoing development. The architecture and method are expected to enable realization of the full potential of back-illuminated CMOS/CCD imagers to perform with high efficiency, high sensitivity, excellent angular response, and in-pixel signal processing. The architecture and method are compatible with next-generation CMOS dielectric-forming and metallization techniques, and the process flow of the method is compatible with process flows typical of the manufacture of very-large-scale integrated (VLSI) circuits. The architecture and method overcome all obstacles that have hitherto prevented high-yield, low-cost fabrication of back-illuminated CMOS/CCD imagers by use of standard VLSI fabrication tools and techniques. It is not possible to discuss the obstacles in detail within the space available for this article. Briefly, the obstacles are posed by the problems of generating light-absorbing layers having desired uniform and accurate thicknesses, passivation of surfaces, forming structures for efficient collection of charge carriers, and wafer-scale thinning (in contradistinction to diescale thinning). A basic element of the present architecture and method - the element that, more than any other, makes it possible to overcome the obstacles - is the use of an alternative starting material: Instead of starting with a conventional bulk-CMOS wafer that consists of a p-doped epitaxial silicon layer grown on a heavily-p-doped silicon substrate, one starts with a special silicon-on-insulator (SOI) wafer that consists of a thermal oxide buried between a lightly p- or n-doped, thick silicon layer and a device silicon layer of appropriate thickness and doping. The thick silicon layer is used as a handle: that is, as a mechanical support for the device silicon layer during micro-fabrication.

Pain, Bedabrata

Evaluation of 3D pixel silicon sensors for the CMS Phase-2 Inner Tracker

The high-luminosity upgrade of the CERN LHC requires the replacement of the CMS tracking detector to cope with the increased radiation fluence while maintaining its excellent performance. An extensive R&D program, aiming at using 3D pixel silicon sensors in the innermost barrel layer of the detector, has been carried out by CMS in collaboration with the FBK (Trento, Italy) and CNM (Barcelona, Spain) foundries. The sensors will feature a pixel cell size of 25 × 100 µm 2 , with a centrally located electrode connected to the readout chip. The sensors are read out by the RD53A and CROCv1 chips, developed in 65 nm CMOS technology by the RD53 Collaboration, a joint effort between the ATLAS and CMS groups. This paper reports the results achieved in beam test experiments before and after irradiation, up to a fluence of approximately 2 . 6 × 1 0 16 n eq /cm 2 . Measurements of assemblies irradiated to a fluence of 1 × 10 16 n˙eq/cm 2 show a hit detection efficiency higher than 96% at normal incidence, with fewer than 2% of channels masked, across a bias voltage range greater than 50 V . Even after irradiation to a higher fluence of 1.6 × 10 16 n˙eq/cm 2 , similar performance is maintained over a bias voltage range of 30 V , remaining well within CMS requirements.

3D pixel

The ETROC2 as the Final Version for CMS Endcap Timing Layer (ETL) Upgrade

The ETROC (Endcap Timing Readout Chip) is being developed for the LGAD-based CMS Endcap Timing Layer (ETL) at HL-LHC. The ETL on each side of the interaction region will be instrumented with a two-disk system of MIP-sensitive LGAD (Low Gain Avalanche Diodes) silicon devices, read out by ETROCs for precision timing measurement with down to ~30 ps timing resolution per track. The ETROC is designed to handle a 16 x 16 pixel cell matrix, with each pixel being 1.3 mm x 1.3 mm to match the LGAD sensor pixel size. The front-end design for preamplifier and discriminator has been specifically optimized for the reduced LGAD signals, with enough flexibilities to meet the ETL specific needs for time resolution, power budget and radiation profile. The ETROC chip is implemented in a commercial 65nm CMOS process. Each channel consists of a preamplifier, a discriminator, a TDC used for TOA (Time Of Arrival) and TOT (Time Over Threshold) measurements, and a memory for data storage and readout. An in-pixel auto threshold calibration is included, along with a self-testing pattern generator. The TOT is used for time-walk correction of the TOA measurement. The detailed hit information (TOA and TOT) from each cell will be read out from a local circular buffer after each Level-1 Accept (about 1 MHz). In addition, a charge injection circuit is implemented to allow for testing and calibration. For more detailed monitoring of the signal pulses, waveform sampling circuits are included for one pixel. The clock distribution is based on a 16x16 H-tree design with a shielding structure to alleviate potential interference. The global peripheral circuits include a PLL, a phase shifter, an I2C slave controller, a fast control block, a global readout, and a data driver along with an efuse and temperature sensor. The ETROC builds event data frames for each L1A selected event and is also capable of providing L1 trigger information for user-defined delayed hits. The main design challenge is how to extract precision timing information from the small LGAD signals in the presence of high irradiation fluence, while keeping the power consumption and digital activity low. The ETL design goal for the time resolution of 50 ps per hit is required to achieve a 35 ps arrival time measurement for a MIP particle, which has its track registered in two ETL disk layers. The LGAD contribution is known to be about 30 ps, this means that the jitter from the ETROC has to be kept below 40 ps. The ETROC2 is the first full size full functionality prototype design fully compatible with the final chip specifications for CMS ETL and now becomes the final version. The ETROC2 chips have been extensively tested. We will present here new testing results including the bump bonding yield improvement study, the time walk correction (TWC) generality study with one pixel TWC applying to all pixels, the final SEU testing using both heavy ion and proton beam, more beam test studies including different sensors, and readiness for the ETROC2 production for CMS ETL upgrade.

Liu, Tiehui [Fermilab] (ORCID:0009000765225605)

Embedded FPGA developments in 130 nm and 28 nm CMOS for machine learning in particle detector readout

Embedded field programmable gate array (eFPGA) technology allows the implementation of reconfigurable logic within the design of an application-specific integrated circuit (ASIC). This approach offers the low power and efficiency of an ASIC along with the ease of FPGA configuration, particularly beneficial for the use case of machine learning in the data pipeline of next-generation collider experiments. An open-source framework called "FABulous" was used to design eFPGAs using 130 nm and 28 nm CMOS technology nodes, which were subsequently fabricated and verified through testing. The capability of an eFPGA to act as a front-end readout chip was assessed using simulation of high energy particles passing through a silicon pixel sensor. A machine learning-based classifier, designed for reduction of sensor data at the source, was synthesized and configured onto the eFPGA. A successful proof-of-concept was demonstrated through reproduction of the expected algorithm result on the eFPGA with perfect accuracy. Finally, further development of the eFPGA technology and its application to collider detector readout is discussed.

47 OTHER INSTRUMENTATION

Technical guidance for the development of a solid state image sensor for human low vision image warping

This report surveys different technologies and approaches to realize sensors for image warping. The goal is to study the feasibility, technical aspects, and limitations of making an electronic camera with special geometries which implements certain transformations for image warping. This work was inspired by the research done by Dr. Juday at NASA Johnson Space Center on image warping. The study has looked into different solid-state technologies to fabricate image sensors. It is found that among the available technologies, CMOS is preferred over CCD technology. CMOS provides more flexibility to design different functions into the sensor, is more widely available, and is a lower cost solution. By using an architecture with row and column decoders one has the added flexibility of addressing the pixels at random, or read out only part of the image.

Vanderspiegel, Jan

Precision of FLEET Velocimetry Using High-speed CMOS Camera Systems

Femtosecond laser electronic excitation tagging (FLEET) is an optical measurement technique that permits quantitative velocimetry of unseeded air or nitrogen using a single laser and a single camera. In this paper, we seek to determine the fundamental precision of the FLEET technique using high-speed complementary metal-oxide semiconductor (CMOS) cameras. Also, we compare the performance of several different high-speed CMOS camera systems for acquiring FLEET velocimetry data in air and nitrogen free-jet flows. The precision was defined as the standard deviation of a set of several hundred single-shot velocity measurements. Methods of enhancing the precision of the measurement were explored such as digital binning (similar in concept to on-sensor binning, but done in post-processing), row-wise digital binning of the signal in adjacent pixels and increasing the time delay between successive exposures. These techniques generally improved precision; however, binning provided the greatest improvement to the un-intensified camera systems which had low signal-to-noise ratio. When binning row-wise by 8 pixels (about the thickness of the tagged region) and using an inter-frame delay of 65 micro sec, precisions of 0.5 m/s in air and 0.2 m/s in nitrogen were achieved. The camera comparison included a pco.dimax HD, a LaVision Imager scientific CMOS (sCMOS) and a Photron FASTCAM SA-X2, along with a two-stage LaVision High Speed IRO intensifier. Excluding the LaVision Imager sCMOS, the cameras were tested with and without intensification and with both short and long inter-frame delays. Use of intensification and longer inter-frame delay generally improved precision. Overall, the Photron FASTCAM SA-X2 exhibited the best performance in terms of greatest precision and highest signal-to-noise ratio primarily because it had the largest pixels.

Peters, Christopher J.

Precision of FLEET Velocimetry Using High-Speed CMOS Camera Systems

Femtosecond laser electronic excitation tagging (FLEET) is an optical measurement technique that permits quantitative velocimetry of unseeded air or nitrogen using a single laser and a single camera. In this paper, we seek to determine the fundamental precision of the FLEET technique using high-speed complementary metal-oxide semiconductor (CMOS) cameras. Also, we compare the performance of several different high-speed CMOS camera systems for acquiring FLEET velocimetry data in air and nitrogen free-jet flows. The precision was defined as the standard deviation of a set of several hundred single-shot velocity measurements. Methods of enhancing the precision of the measurement were explored such as digital binning (similar in concept to on-sensor binning, but done in post-processing), row-wise digital binning of the signal in adjacent pixels and increasing the time delay between successive exposures. These techniques generally improved precision; however, binning provided the greatest improvement to the un-intensified camera systems which had low signal-to-noise ratio. When binning row-wise by 8 pixels (about the thickness of the tagged region) and using an inter-frame delay of 65 microseconds, precisions of 0.5 meters per second in air and 0.2 meters per second in nitrogen were achieved. The camera comparison included a pco.dimax HD, a LaVision Imager scientific CMOS (sCMOS) and a Photron FASTCAM SA-X2, along with a two-stage LaVision HighSpeed IRO intensifier. Excluding the LaVision Imager sCMOS, the cameras were tested with and without intensification and with both short and long inter-frame delays. Use of intensification and longer inter-frame delay generally improved precision. Overall, the Photron FASTCAM SA-X2 exhibited the best performance in terms of greatest precision and highest signal-to-noise ratio primarily because it had the largest pixels.

Peters, Christopher J.

A Low-Power High-Speed Smart Sensor Design for Space Exploration Missions

A low-power high-speed smart sensor system based on a large format active pixel sensor (APS) integrated with a programmable neural processor for space exploration missions is presented. The concept of building an advanced smart sensing system is demonstrated by a system-level microchip design that is composed with an APS sensor, a programmable neural processor, and an embedded microprocessor in a SOI CMOS technology. This ultra-fast smart sensor system-on-a-chip design mimics what is inherent in biological vision systems. Moreover, it is programmable and capable of performing ultra-fast machine vision processing in all levels such as image acquisition, image fusion, image analysis, scene interpretation, and control functions. The system provides about one tera-operation-per-second computing power which is a two order-of-magnitude increase over that of state-of-the-art microcomputers. Its high performance is due to massively parallel computing structures, high data throughput rates, fast learning capabilities, and advanced VLSI system-on-a-chip implementation.

Fang, Wai-Chi

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING

Evaluation of an event-driven 3FI ASIC for spectroscopic X-ray detection with synchrotron radiation

The novel design and evaluation on the NSLS-II beamline of the 3FI application-specific integrated circuit (ASIC) bump-bonded to a simple, planar, 2D segmented silicon sensor are presented. The ASIC was developed for full-field fluorescence spectral X-ray imaging (3FI). It is a small-scale prototype that features a square array of 32 × 32 pixels, and the size of the pixels is 100 µm × 100 µm. The ASIC was implemented in a 65 nm CMOS integrated circuit fabrication process. Each pixel incorporates a charge-sensitive amplifier, a shaping filter, a discriminator, a peak detector and a sample-and-hold circuit, allowing detection of events and storage of signal amplitudes. The system operates in a frameless event-driven readout mode, outputting analog values for threshold-triggered events, allowing high-speed multi-element X-ray fluorescence data acquisition. The 3FI ASIC achieves per-channel spectrometric performance at a power consumption of only 200 µW per pixel, with nearly all dissipation confined to the analog front-end. An energy resolution is measured at the level of 308 eV full width at half-maximum (FWHM) at 8.04 keV (Cu Kα), and 138 eV FWHM at 3.69 keV (Ca Kα). This per-pixel capability makes the prototype suitable for in situ trace element microanalysis in biological and environmental studies. Moreover, the frameless architecture of the detector is designed to address limitations of conventional X-ray fluorescence microscopy, which typically requires mechanical scanning, by enabling continuous high-throughput data acquisition in future full-field implementations.

47 OTHER INSTRUMENTATION

Downsampling Photodetector Array with Windowing

In a photon counting detector array, each pixel in the array produces an electrical pulse when an incident photon on that pixel is detected. Detection and demodulation of an optical communication signal that modulated the intensity of the optical signal requires counting the number of photon arrivals over a given interval. As the size of photon counting photodetector arrays increases, parallel processing of all the pixels exceeds the resources available in current application-specific integrated circuit (ASIC) and gate array (GA) technology; the desire for a high fill factor in avalanche photodiode (APD) detector arrays also precludes this. Through the use of downsampling and windowing portions of the detector array, the processing is distributed between the ASIC and GA. This allows demodulation of the optical communication signal incident on a large photon counting detector array, as well as providing architecture amenable to algorithmic changes. The detector array readout ASIC functions as a parallel-to-serial converter, serializing the photodetector array output for subsequent processing. Additional downsampling functionality for each pixel is added to this ASIC. Due to the large number of pixels in the array, the readout time of the entire photodetector is greater than the time between photon arrivals; therefore, a downsampling pre-processing step is done in order to increase the time allowed for the readout to occur. Each pixel drives a small counter that is incremented at every detected photon arrival or, equivalently, the charge in a storage capacitor is incremented. At the end of a user-configurable counting period (calculated independently from the ASIC), the counters are sampled and cleared. This downsampled photon count information is then sent one counter word at a time to the GA. For a large array, processing even the downsampled pixel counts exceeds the capabilities of the GA. Windowing of the array, whereby several subsets of pixels are designated for processing, is used to further reduce the computational requirements. The grouping of the designated pixel frame as the photon count information is sent one word at a time to the GA, the aggregation of the pixels in a window can be achieved by selecting only the designated pixel counts from the serial stream of photon counts, thereby obviating the need to store the entire frame of pixel count in the gate array. The pixel count se quence from each window can then be processed, forming lower-rate pixel statistics for each window. By having this processing occur in the GA rather than in the ASIC, future changes to the processing algorithm can be readily implemented. The high-bandwidth requirements of a photon counting array combined with the properties of the optical modulation being detected by the array present a unique problem that has not been addressed by current CCD or CMOS sensor array solutions.

Patawaran, Ferze D.

Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning

Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced, leading to unprecedented data rates exceeding those foreseen at the High- Luminosity Large Hadron Collider. Signal processing that handles data incoming at a rate of $\mathcal{O}$(40 MHz) and intelligently reduces the data within the pixelated region of the detector at rate will enhance physics performance at high luminosity and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first demonstration, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector's data volume by 57.1%–75.7%. The network is designed and simulated as a custom readout integrated circuit with 28 nm CMOS technology and is expected to operate at less than 300 μW with an area of less than 0.2 mm 2 . The temporal development of charge clusters is investigated to demonstrate possible future performance gains, and there is also a discussion of future algorithmic and technological improvements that could enhance efficiency, data reduction, and power per area.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

In-pixel integration of signal processing and AI/ML based data filtering for particle tracking detectors

We present the first physical realization of in-pixel signal processing with integrated AI-based data filtering for particle tracking detectors. Building on prior work that demonstrated a physics-motivated edge-AI algorithm suitable for ASIC implementation, this work marks a significant milestone toward intelligent silicon trackers. Our prototype readout chip performs real-time data reduction at the sensor level while meeting stringent requirements on power, area, and latency. The chip is taped-out in 28nm TSMC CMOS bulk process, which has been shown to have sufficient radiation hardness for particle experiments. This development represents a key step toward enabling fully on-detector edge AI, with broad implications for data throughput and discovery potential in high-rate, high-radiation environments such as the High-Luminosity LHC.

Parpillon, Benjamin [Fermilab; Illinois U., Chicag

Sparsely-Bonded CMOS Hybrid Imager

A method and device for imaging or detecting electromagnetic radiation is provided. A device structure includes a first chip interconnected with a second chip. The first chip includes a detector array, wherein the detector array comprises a plurality of light sensors and one or more transistors. The second chip includes a Read Out Integrated Circuit (ROIC) that reads out, via the transistors, a signal produced by the light sensors. A number of interconnects between the ROIC and the detector array can be less than one per light sensor or pixel.

Cunningham, Thomas J.

Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

Fang, Wai-Chi

The Effects of Radiation on Imagery Sensors in Space

Recent experience using high definition video on the International Space Station reveals camera pixel degradation due to particle radiation to be a much more significant problem with high definition cameras than with standard definition video. Although it may at first appear that increased pixel density on the imager is the logical explanation for this, the ISS implementations of high definition suggest a more complex causal and mediating factor mix. The degree of damage seems to vary from one type of camera to another, and this variation prompts a reconsideration of the possible factors in pixel loss, such as imager size, number of pixels, pixel aperture ratio, imager type (CCD or CMOS), method of error correction/concealment, and the method of compression used for recording or transmission. The problem of imager pixel loss due to particle radiation is not limited to out-of-atmosphere applications. Since particle radiation increases with altitude, it is not surprising to find anecdotal evidence that video cameras subject to many hours of airline travel show an increased incidence of pixel loss. This is even evident in some standard definition video applications, and pixel loss due to particle radiation only stands to become a more salient issue considering the continued diffusion of high definition video cameras in the marketplace.

Mathis, Dylan