Monday, October 02, 2023

MDPI IISW2023 Special Issue - paper on random telegraph noise

The first article in the Sensors special issue for IISW2023 is now available:

Chao et al. from TSMC in a paper titled "Random Telegraph Noise Degradation Caused by Hot Carrier Injection in a 0.8 μm-Pitch 8.3Mpixel Stacked CMOS Image Sensor" write:

In this work, the degradation of the random telegraph noise (RTN) and the threshold voltage (Vt) shift of an 8.3Mpixel stacked CMOS image sensor (CIS) under hot carrier injection (HCI) stress are investigated. We report for the first time the significant statistical differences between these two device aging phenomena. The Vt shift is relatively uniform among all the devices and gradually evolves over time. By contrast, the RTN degradation is evidently abrupt and random in nature and only happens to a small percentage of devices. The generation of new RTN traps by HCI during times of stress is demonstrated both statistically and on the individual device level. An improved method is developed to identify RTN devices with degenerate amplitude histograms.


Figure 1. Simplified test chip architecture. The device under stress is the source follower (SF) NMOS in the 4 × 2-shared pixels on the top layer. The PD0–7 are the photodiodes, and the TG0–7 are the transfer gates in each 4 × 2-shared pixel. The total number of SF is 628 × 1648 = 1.03 M.

Figure 2. (a) The measured IB of a SF device vs. VD with VG stepping from 1.3 V to 2.8 V; (b) The same data as in (a) but plotted against VDS−VDsat≈VD−VG+Vt with Vt as a fitting parameter; (c) The same data as in (b) plotted against 1/(VDS−VDsat) with P=(P1,P2) as two fitting parameters according to Equation (1).

Figure 3. The bias configuration of the SF under test. The red and blue solid circles symbolize electrons and holes, respectively.

Figure 4. The histograms of the measured VGS of the SF for stress time (t) from 0 to 100 min.

Figure 5. (a) The histograms of the threshold voltage shift (ΔVt) after 10-, 20-, 50-, and 100-min stress; (b) The inverse cumulative distribution function (ICDF) curves of ΔVt; (c) the constant ICDF contours against stress time (t).

Figure 6. (a) The histograms of the random noise changes (ΔRN) after 10, 20, 50, 100 min stress; (b) The inverse cumulative distribution function (ICDF) curves; (c) the constant ICDF contours as functions of stress time (t).

Figure 7. The correlation of the SF threshold voltage shift (ΔVt) after 10 min of HCI stress vs. after (a) 20 min, (b) 50 min, and (c) 100 min of stress, respectively. The linear least-square fit of the x/y ratio (red dash line) shows the continuous increase of the ΔVt as the stress time increases. The ΔVt increases are relatively uniform among all 1M devices, which is quite different from the random noise increases in Figure 8 below. Random colors are assigned to the data points to separate the dots from each other.

Figure 8. The correlation of the random noises (RN) before HCI stress (t = 0) vs. after (a) 10 min, (b) 20 min, and (c) 100 min stress, respectively The RN increases are noticeably nonuniform. The RN along the x = y red dash line remains relatively unchanged. The devices on the lower-right branches show a significant increase in RN. The population of the lower branch increases as stress time increases. Random colors are assigned to the data points to separate the dots from each other.

Figure 9. The 2D histograms of the correlation of the Vt shift and RN degradation shows dramatically different statistical behaviors. (a) The Vt change after 100-min stress versus that after 10-min stress. (b) The RN after 100 min stress versus that before the stress.

Figure 10. Generation of RTN traps during HCI stress. The 5000-frame waveforms before (t = 0) and after the HCI stress (t = 20, 100 min) with the corresponding histograms are shown for three selected examples. (a) Device (296, 137) shows one trap before stress and remains unchanged after stress. (b) Device (202, 1338) shows no trap before stress and one trap generated after 20 min of stress. (c) Device (400, 816) shows no trap before stress; however, one trap is generated after 100 min of stress. The RN unit is mV-rms.

Figure 11. Degeneration of the RTN discrete levels. During HCI stress, the non-RTN noises may be increased significantly such that the discrete RTN levels become indistinguishable. (a) Device (141, 1393) show such degeneration after 100 min of stress. (b) Device (481, 405) show degeneration after 20 min of stress. (c) Device (519, 1638) shows unsymmetric side peaks and unsymmetric degeneration after 20 min and 100 min of stresses. The RN unit is mV-rms.

Figure 12. For devices showing a single histogram peak, if the histogram is significantly different from the Gaussian distribution, they are counted as RTN-like devices. The ratio R expressed in Equation (2) is defined as the red area versus the total area under the black histogram. The R values in examples (a) and (b) are 36% and 28%, respectively. The RN unit is mV-rms.

Figure 13. Devices with amplitude distributions close to Gaussian are considered as non-RTN devices. The deviation ratio R is 7% for device (587, 492) in (a) and 9% for device (124, 1349) in (b). The RN unit is mV-rms.

Figure 14. The RN distribution of the RTN and non-RTN devices, sorted by the improved algorithm: (a) before HCI stress, (b) after 20 min stress, and (c) after 100 min stress. The RTN devices clearly contribute to and dominate the long tails of the RN histograms. The number of RTN devices (Nx) (with the R-threshold set to 15%) increases systematically as the stress time increases.

Figure 15. The count of RTN devices increases consistently as stress time increases. N2 is the number of devices showing two or more peaks in amplitude histograms. Nx is N2 plus the number of RTN-like devices determined by setting the R-threshold to 10%, 15%, and 20%, respectively.

Figure 16. (a) The Vt shift and (b) the RN degradation trends against the effective stress defined in Equation (3), where the effectiveness factors are treated as empirical fitting parameters such that all the constant-ICDF points for different voltages fall onto a family of continuous and smooth curves. The fitting results are listed in Table 1.

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I apologize to those of you who tried to read the Pixim data sheets.  I forgot to set the share flag on the folder.  The files are available for viewing by anyone now.

Job Postings - Week of 1 Oct 2023


CMOS Sensor Product Support

Waterloo, Ontario, Canada


Senior Manager, Digital & Analog Mixed Signal IC Design

Camarillo, California, USA


MBE Growth Production Engineer

(US Citizen)

Camarillo, California, USA


ASIC Design Engineer

(US Citizen or equivalent)

Goleta, California, USA


Director - Market Development

Grenoble, France


Senior Scientist

(US Citizen)

Acton, Massachusetts, USA




Optoelectronics Systems Engineer

Redmond, Washington, USA


Optoelectronics Systems Engineer

Vancouver, British Columbia, Canada


University of Arizona

Optical Sciences

Postdoctoral Research Associate I

Tucson, Arizona, USA



Postdoctoral Research Associate I

Tucson, Arizona, USA


Optical Sciences

Postdoctoral Research Associate

Tucson, Arizona, USA



Sandia National Laboratories

Nanophotonics - Postdoctoral Appointee

Albuquerque, New Mexico, USA



Santa Clara University

Assistant Professor, Electrical and Computer Engineering (Tenure-track)

Santa Clara, California, USA


Conference List - November 2023

Semi MEMS and Sensors Executive Conference - 6-8 Nov 2023 - Phoenix, Arizona, USA - Website

Coordinating Panel for Advanced Detectors Workshop - 7-10 Nov 2023 - Menlo Park, California, USA - Website

Compamed - 13-16 Nov 2023 - Dusseldorf, Germany - Website

RSNA 109th Scientific Assembly and Annual Meeting  - 26-30 Nov 2023 - Chicago, Illinois, USA - Website

Return to Conference List index 

Saturday, September 30, 2023

Pixim Documentation

Since someone just pointed out that the Pixim weblink in the ISW vendor list was dead, I decided to put up Pixim datasheets next.  These are different from most because Pixim sold a chipset that included the sensor and a matching processor to turn the chip outputs (basically timing data) into digital image data.  Pixim also made several demonstration cameras. Sony bought Pixim in 2012 and stopped making Pixim-type chips a couple of years later because they felt they had a better way to do HDR imaging. The debate continues.

Link to the Pixim folder

Return to the Documentation List

Friday, September 29, 2023

Omnivision announces new sensor for security and surveillance applications

OMNIVISION Announces New Low-power, Enhanced-performance 2MP Image Sensor for Security Surveillance Cameras
The OS02N features a 2.5-micron enhanced-performance FSI pixel with on-sensor DPC for higher sensitivity, performance and reliability while remaining cost-effective
SANTA CLARA, Calif. – September 27, 2023 – OMNIVISION, a leading global developer of semiconductor solutions, including advanced digital imaging, analog, and touch & display technology, today announced the new OS02N, a 2-megapixel (MP) frontside illumination (FSI) image sensor with optimized defective pixel correction (DPC) algorithm for higher sensitivity, improved performance and increased reliability for IP and HD analog security cameras, including professional surveillance and outdoor home security cameras. The OS02N supports always-on with its low-power capability.
“Customers need high-performing security cameras that produce sharp, high-resolution images with low power consumption for extended battery life. The OS02N meets these requirements and is also a cost-effective solution,” said Cheney Zhang, senior marketing manager, OMNIVISION. “The OS02N uses FSI technology, which has a large pixel size for better quantum efficiency and excellent signal-to-noise ratio, resulting in high sensitivity in low-light conditions and dramatically improved image quality and performance. It has a 1/3.27-inch optical format and is designed to be pin-to-pin compatible with our OS04L and OS04D image sensors.”
The OS02N features a 2.5-micron pixel based on OMNIVISION’s OmniPixel®3-HS technology. This enhanced-performance, cost-effective solution uses FSI technology for true-to-life color reproduction in both bright and dark conditions. Optimized DPC algorithm improves sensor quality and reliability above and beyond standard devices by providing real-time correction of defective pixels that can result throughout the sensor’s life cycle, especially in harsh operating conditions. The OS02N features 1920x1080 resolution at 30 frames per second (FPS).
The OS02N supports MIPI and DVP interfaces. It is sampling now and will be in mass production in Q1 2024. For more information, contact your OMNIVISION sales representative:


Thursday, September 28, 2023

Sheba Microsystems MEMS-based lens athermalization solution

Sheba Microsystems Launches Revolutionary MEMS Autofocus Actuator for Active Athermalization in Embedded Vision Cameras

Breakthrough µPistons™ technology uniquely solves decades-long embedded vision camera industry’s problem of lens thermal expansion. Novel product unlocks unparalleled resolution and consistent high-quality imaging performance for automotive, action, drone, mobile robotics, security and surveillance, and machine vision cameras.

TORONTO--(BUSINESS WIRE)--Sheba Microsystems Inc., a global leader in MEMS technologies, today announced the launch of its revolutionary new product, the MEMS Autofocus Actuator for Active Athermalization in Embedded Vision Cameras used in automotive, action, drones, machine vision, security and surveillance, and mobile robotics.

The first-of-its-kind solution tackles the long-standing industry problem of embedded vision cameras’ inability to maintain image quality and focus stability during temperature fluctuations as optics undergo thermal expansion.

While smartphones use autofocus actuators and electromagnetic actuators including voice coil motors (VCMs), these actuators are unreliable for achieving active athermalization in embedded vision cameras due to extreme environmental conditions. Embedded vision camera optics are also 30 times larger than smartphone optics. Other autofocus systems in-market such as tunable lenses lack thermal stability and compromise optical quality.

“MEMS actuators are fast, precise, and small in size, and are actually uniquely suited to solve thermal expansion issues, because they are thermally stable and maintain consistent performance regardless of temperature changes,” said CEO and co-founder Dr. Faez Ba-Tis, PhD. “Because of these known advantages, there have been previous industry attempts at incorporating MEMS actuators into cameras, but because they failed drop tests they were quickly abandoned. Sheba’s new design solves for all of these previous blockers, which opens up limitless possibilities for embedded vision camera innovation.”

Sheba’s proprietary technology compensates for thermal expansion by uniquely moving the lightweight sensor, instead of moving the lenses. The silicon-based MEMS actuator platform actuates the image sensor along the optical axis to compensate for thermal expansion in the optics. The weight of the image sensor represents only 2-3 % of the optical lens weight, which makes it easier to handle, enabling ultra-fast and precise autofocus performance even when temperatures fluctuate.

Sheba’s novel piston-tube electrode configuration takes advantage of a larger capacitive area, allowing for substantial stroke and increased force. In contrast to traditional MEMS comb-drive electrode configuration, Sheba’s µPistons™ design makes the MEMS actuators uniquely resilient against severe shocks, since the electrodes are well-supported and interconnected with each other.

Sheba’s new MEMS actuator has successfully passed drop tests as well as other reliability tests, including thermal shock, thermal cycling, vibration, mechanical shock, drop, tumble, and microdrop tests. It is also highly rugged, which helps maintain image focus during high shocks in action cameras or machine vision environments.

“Digital camera technologies are increasingly used in almost every aspect of our lives,” said Ba-Tis. “From sharing photos of our travels in social media, to experiencing new artificial intelligence innovations powered by machine vision, and accelerating the deployment of autonomous vehicles in our communities, high quality images are imperative to not only capture our most memorable events, but to also keep us safe. In situations where split-second decisions are critical, image quality becomes paramount.”

Sheba’s MEMS actuator offers lens design flexibility and is suitable for near and far-field imaging. It is easily integrated into existing systems and scaled up on mass production tools for automotive, action, drone, mobile robotics, security and surveillance, and machine vision cameras.
Sheba is offering evaluation kits to interested customers, so they can test and evaluate the new product in their own labs to ensure the reliability of the technology. The kit includes camera samples, a daughter board with the MEMS driver, interposer, and camera test jig to perform mechanical reliability tests, software, and user manual.

To learn more about Sheba Microsystems or to order an evaluation kit for your organization, visit


Wednesday, September 27, 2023

EETimes article on PixArt Imaging's "smart pixel" sensor


Smart Pixel Optical Sensing – Exerting AI in Pixels Level

The PAC9001LU Smart Pixel Optical Sensing Chip is a Computer Vision ASIC that fits as an always-on motion sensor by leveraging the novel AI-driven pixel architecture into the sensor array design. Based on a CMOS Image Sensor rolling shutter structural design with an array of 36 x 16 pixels, it can support a high frame rate of up to 1000Hz to facilitate image capturing of fast-moving object applications. The design of AI in pixels integrates a frame comparing circuit with AI-powered algorithms to compute differences in pixel luminosity within a configurable image area. It directly provides analog frame differences and event info in Pixel Differences Mode and supports Smart Motion Detection Mode to eliminate the complex image signal processing in the processor. The partial array sensing, such as configurable ROI region, provides supple custom scene capturing for the needs of AIoT edge applications.

 PAC9001LU directly handles the digital conversion of raw image signals. It computes the image subtraction difference between two frames internally in the chip to provide the difference of each pixel in an 8-bit data format. This 8-bit data size is relatively small compared to the raw image data of a whole pixel array, which can effectively reduce data transmission bandwidth and latency issues.

The PAC9001LU chip is in a W2.5 x L2.6 x H0.43 mm3 CSP package body (excluding solder balls). A recommended matching lens set, LST0-2621 is also available to form a complete module when assembled with the PAC9001LU chip and comes in a size of W3.79 x L3.63 x H1.67 mm3 (height is including guide pin).

  • The low-power consumption during the Smart Motion Detection Mode that comes with intelligent informative is the most remarkable building block worthwhile in enabling AI applications. As compare to PIR or CMOS Image Sensor (CIS), higher power consumption is required for further data processing in system level.
  •  The high report rate, which can go up to 1000Hz can achieve motion detection with fast-moving objects, which outperforms the PIR or conventional CIS.
  •  The PAC9001LU is more robust with reliable performance. It has fewer false alarms detecting motion and higher immunity to temperature interference. The external environment factors, such as bright and hot sunlight from outdoors, the indoors thermal noise from heated devices are not affecting its sensing performance. The built-in algorithms can eliminate interferences like background noise too.
  •  The small form factor of the complete PAC9001LU sensor module, including the lens set, can nicely fit into the slim bezel ID design.
  •  The traditional PIR sensors are usually required not to be shielded by plastics or glass front-facing cover, which may impact the detection of thermal IR radiation. Whereas the PAC9001LU solution does not have the restraint of having a front cover of any materials and still can keep the motion sensing quality, even placing the motion sensing device indoors looking out from the glass window is possible. With the cover protection, the PAC9001LU is less prone to external damage.

PAC9001LU sensor can support low-light sensing in low or no-light conditions, which is very suitable for use in a dark environment, such as a basement.

The PAC9001LU can cater to the need for in-chip high-speed motion detection, eliminating the external controller processing.


In addition to motion sensing, the PAC9001LU sensor can provide the coordinate information of a targeted moving object that is in sync with each pixel differences image data. 

The PAC9001KE Evaluation Kit is available for evaluation and design research purposes.

Sunday, September 24, 2023

Job Postings - Week of 24 Sep 2023

To start the revised posting scheme,here are recently posted jobs from Apple and onsemi:


Image Sensor Validation Engineer

Cupertino, California, USA


Sensor Process Engineer - 

Camera Hardware

Cupertino, California, USA


Image Sensor Validation Engineer

Grenoble, Isere, France


Sensor Process Engineer

Kanagawa, Kanagawa-ken, Japan


Sensor Process Engineer

Cupertino, California, USA


Pixel Development Engineer

Pasadena, California, USA


Technical Program Manager (TPM), 

Image Sensor

Tokyo, Tokyo-to, Japan



Strategic Platform Architect –

Image Sensors

San Jose, California, USA


Technical Project Manager –

Image and Depth Sensors

Haifa, Israel


Sr Director Bracknell Design Center 

Bracknell, Berkshire, UK


Summer 2024 Analog/Digital Verification Intern 

San Jose, California, USA


Process Design Kit Development Staff Engineer 

Scottsdale, Arizona, USA


Let us know if you would like us to check out a specific company or if you know of jobs we should post.

Job Posting Update

In order to eliminate the delays involved in reproducing jobs listings in detail, the method of reporting is changing. Starting today, this Jobs Update will be a report on job listings rather than the listings themselves.  Even in the apparent slowdown in the job market, the number of listings is still quite large and the backlog of listings that might be of interest is much larger.

To manage this situation, we will proceeds as follows: for the next few weeks, the posting will focus each week on a small number of employers with multiple openings. Relevant job titles with their locations and original listing links will be posted. The job descriptions will no be included simply because they are all so long - click the links to see the details. Please note that we will attempt always to link to the original listing on the employer website, not to job boards.

Weekly job lists in ISW will continue to have individual links for four weeks but since many jobs remain unfilled longer than that, the older postings will be held in an archive for a year. The link to the archive is positioned below the four week links.

Initially, some of the postings may be several months old but, at some point, our listings will catch up with the backlog and each weekly posting will include only recent additions.