2024 SEMI MEMS and Imaging Summit program announced

SEMI MEMS & Imaging Sensors Summit 2024 will take place November 14-15 at the International Conference Center Munich (ICM), Messe Münich in Germany.

Thursday, 14^th November 2024 

Session 1: Market Dynamics: Landscape and Growth Strategies

09:00  Welcome Remarks
Laith Altimime, President, SEMI Europe

09:20  Opening Remarks by MEMS and Imaging Committee Chair
Philippe Monnoyer, VTT Technical Research Center of Finland Ltd

09:25  Keynote: Smart Sensors for Smart Life – How Advanced Sensor Technologies Enable Life-Changing Use Cases
Stefan Finkbeiner, General Manager, Bosch Sensortec

09:45  Keynote: Sensing the World: Innovating for a More Sustainable Future
Simone Ferri, APMS Group Vice President, MEMS sub-group General Manager, STMicroelectronics

10:05  Reserved for Yole Development

10:25  Key Takeaways by MEMS and Imaging Committee Chair
Philippe Monnoyer, VTT Technical Research Center of Finland Ltd

10:30  Networking Coffee Break

Session 2: Sustainable Supply Chain Capabilities

11:10  Opening Remarks by Session Chair
Pawel Malinowski, Program Manager and Researcher, imec

11:15  A Paradigm Shift From Imaging to Vision: Oculi Enables 600x Reduction in Latency-Energy Factor for Visual Edge Applications
Charbel Rizk, Founder & CEO, Oculi

11:35  Reserved for Comet Yxlon

11:55  Key Takeaways by Session Chair
Pawel Malinowski, Program Manager and Researcher, imec

12:00  Networking Lunch

Session 3: MEMS - Exploring Future Trends for Technologies and Device Manufacturing

13:20  Opening Remarks by Session Chair
Pierre Damien Berger, MEMS Industrial Partnerships Manager, CEA LETI

13:25  Unlocking Novel Opportunities: How 300mm-capable MEMS Foundries Will Change the Game
Jessica Gomez, CEO, Rogue Valley Microdevices

13:45  Trends in Emerging MEMS
Alissa Fitzgerald, CEO, A.M. Fitzgerald & Associates, LLC

14:05  The Most Common Antistiction Films are PFAS, Now What?
David Springer, Product Manager, MVD and Release Etch Products, KLA Corporation

14:25  Reserved for Infineon

14:45  Latest Innovations in MEMS Wafer Bonding
Thomas Uhrmann, Director of Business Development, EV Group

15:05  Key Takeaways by Session Chair
Pierre Damien Berger, MEMS Industrial Partnerships Manager, CEA LETI

Session 4: Imaging - Exploring Future Trends for Technologies and Device Manufacturing

15:10  Opening Remarks by Session Chair
Stefano Guerrieri, Engineering Fellow and Key Expert Imager & Sensor Components, ams OSRAM

15:15  Topic Coming Soon
Avi Bakal, CEO & Co-founder, TriEye

15:35  Active Hyperspectral Imaging Using Extremely Fast Tunable SWIR Light Source
Jussi Soukkamaki, Lead, Hyperspectral & Imaging Technologies, VTT Technical Research Centre of Finland Ltd

15:55  Networking Coffee Break

16:40  Reserved

17:00  Reserved for CEA-Leti

17:20  Reserved for STMicroelectronics

17:40  Key Takeaways by Session Chair
Stefano Guerrieri, Engineering Fellow and Key Expert Imager & Sensor Components, ams OSRAM

Friday, 15th November 2024 

Session 5: MEMS and Imaging Young Talent

09:00  Opening Remarks by Session Chair
Dimitrios Damianos, Project Manager, Yole Group

09:05  Unlocking Infrared Multispectral Imaging with Pixelated Metasurface Technology
Charles Altuzarra, Chief Executive Officer & Co-founder, Metahelios

09:10  Electrically Tunable Dual-Band VIS/SWIR Imaging and Sensing
Andrea Ballabio, CEO, EYE4NIR

09:15  FMCW Chip-Scale LiDARs Scale Up for Large Volume Markets Thanks to Silicon Photonics Technology
Simoens François, CEO, SteerLight

09:20  ShadowChrome: A Novel Approach to an Old Problem
Geoff Rhoads, Chief Technology Officer, Transformative Optics Corporation

09:25  Feasibility Investigation of Spherically Bent Image Sensors
Amit Pandey, PhD Student, Technische Hochschule Ingolstadt

09:30  Intelligence Through Vision
Stijn Goossens, CTO, Qurv

09:35  Next Generation Quantum Dot SWIR Sensors
Artem Shulga, CEO & Founder, QDI Systems

09:40  Closing Remarks by Session Chair
Dimitrios Damianos, Project Manager, Yole Group

09:45  Networking Coffee Break

Session 6: Innovations for Next-Gen Applications: Smart Mobility

10:35  Opening Remarks by Session Chair
Bernd Dielacher, Business Development Manager MEMS, EVG

10:40  Reserved

11:00  New Topology for MEMS Advances Performance and Speeds Manufacturing
Eric Aguilar, CEO, Omnitron Sensors, Inc.

11:20  Key Takeaways by Session Chair
Bernd Dielacher, Business Development Manager MEMS, EVG

Session 7: Innovations for Next-Gen Applications: Health

11:25  Opening Remarks by Session Chair
Ran Ruby YAN, Director of HMI & HealthTech Business Line, GLOBALFOUNDRIES

11:30  Reserved

11:50  Sensors for Monitoring Vital Signs in Wearable Devices
Markus Arzberger, Senior Director, ams-OSRAM International GmbH

12:10  Pioneering Non-Invasive Wearable MIR Spectrometry for Key Health Biomarkers Analysis
Jan F. Kischkat, CEO, Quantune Technologies GmbH

12:30  Key Takeaways by Session Chair
Ran Ruby YAN, Director of HMI & HealthTech Business Line, GLOBALFOUNDRIES

12:35  End of Conference Reflections by MEMS and Imaging Committee Chair
Philippe Monnoyer, VTT Technical Research Center of Finland Ltd

12:45  Closing Remarks
Laith Altimime, President, SEMI Europe

12:50  Networking Lunch

IEEE SENSORS 2024 --- image sensor topics announced

The list of topics and the authors for the following two events related to image sensor technology have been finalized for the IEEE SENSORS 2024 Conference. The conference will be held in Kobe, Japan, from 20-23 October 2024. It will provide the opportunity to hear world class speakers in the field of image sensors and to sample the sensor ecosystem that extends beyond to see how imaging fits in.

Workshop: “From Imaging to Sensing: Latest and Future Trends of CMOS Image Sensors” [Sunday, 20 October]

Organizers: Sozo Yokogawa (Sony Semiconductor Solutions corp.) • Erez Tadmor (onsemi)

“Trends and Developments in State-of-the-Art CMOS Image Sensors”, Daniel McGrath, TechInsights
“CMOS Image Sensor Technology: what we have solved, what are to be solved”, Eiichi Funatsu, OMNIVISION
“Automotive Imaging: Beyond human Vision”, Vladi Korobov, onsemi
“Recent Evolution of CMOS Image Sensor Pixel Technology”, Bumsuk Kim et al., Samsung Electronics
“High precision ToF image sensor and system for 3D scanning application”, Keita Yasutomi, Shizuoka University
“High-definition SPAD image sensors for computer vision applications”, Kazuhiro Morimoto, Canon Inc.
“Single Photon Avalanche Diode Sensor Technologies for Pixel Size Shrinkage, Photon Detection Efficiency Enhancement and 3.36-pm-pitch Photon-counting Architecture”, Jun Ogi, Sony Semiconductor Solutions Corp.
“SWIR Single-Photon Detection with Ge-on-Si Technology”, Neil Na, Artilux Inc.
“From SPADs to smart sensors: ToF system innovation and AI enable endless application”, Laurent Plaza & Olivier Lemarchand, STMicroelectronics
“Depth Sensing Technologies, Cameras and Sensors for VR and AR”, Harish Venkataraman, Meta Inc.
 
Focus session: Overview of The Focus Sensor on Stacking in Image Sensor, [Monday, 21 October]

Orgainizer: S-G. Wu, Brillnics

Co-chairs: DN Yaung, TSMC; John McCarten, L3 Harris

Over the past decade, 3-dimensional (3D) wafer level stacked backside Illuminated (BSI) CMOS image sensors (CIS) have achieved the rapid progress in mass production. This focus session on stacking in image sensors will have 4 invited papers to explore the sensor stack technology evolution from process development, circuit architecture to AI/edge computing in system integration.

“The Productization of Stacking in Image Sensors”, Daniel McGrath, TechInsights
“Evolution of Image Sensing and Computing Architectures with Stacking Device Technologies”, BC Hseih, Qualcomm
“Event-based vision sensor”, Christoph Posch, Prophesee
“Evolution of digital pixel sensor (DPS) and advancement by stacking technologies”, Ikeno Rimon, Brillnics

Galaxycore educational videos

 

Are you curious about how CMOS image sensors capture such clear and vivid images? Start your journey with the first episode of "CIS Explained". In this episode, we dive deep into the workings of these sophisticated sensors, from the basics of pixel arrays to the intricacies of signal conversion.
This episode serves as your gateway to understanding CMOS image sensors.

In this video, we're breaking down Quantum Efficiency (QE) and its crucial role in CIS. QE is a critical measure of how efficiently our sensors convert incoming light into electrical signals, directly affecting image accuracy and quality. This video will guide you through what QE means for CIS, its impact on your images, and how we're improving QE for better, more reliable imaging.

GalaxyCore DAG HDR Technology Film

Exploring GalaxyCore's Sensor-Shift Optical Image Stabilization (OIS) in under Two Minutes

GalaxyCore's COM packaging technology—a breakthrough in CIS packaging. This video explains how placing two suspended gold wires on the image sensor and bonding it to an IR base can enhance the durability and clarity of image sensors, prevent contamination, and ensure optimal optical alignment.

Avoiding information loss in the photon transfer method

In a recent paper titled "PCH-EM: A Solution to Information Loss in the Photon Transfer Method" in IEEE Trans. on Electron Devices, Aaron Hendrickson et al. propose a new statistical technique to estimate CIS parameters such as conversion gain and read noise.

Abstract: Working from a Poisson-Gaussian noise model, a multisample extension of the photon counting histogram expectation-maximization (PCH-EM) algorithm is derived as a general-purpose alternative to the photon transfer (PT) method. This algorithm is derived from the same model, requires the same experimental data, and estimates the same sensor performance parameters as the time-tested PT method, all while obtaining lower uncertainty estimates. It is shown that as read noise becomes large, multiple data samples are necessary to capture enough information about the parameters of a device under test, justifying the need for a multisample extension. An estimation procedure is devised consisting of initial PT characterization followed by repeated iteration of PCH-EM to demonstrate the improvement in estimating uncertainty achievable with PCH-EM, particularly in the regime of deep subelectron read noise (DSERN). A statistical argument based on the information theoretic concept of sufficiency is formulated to explain how PT data reduction procedures discard information contained in raw sensor data, thus explaining why the proposed algorithm is able to obtain lower uncertainty estimates of key sensor performance parameters, such as read noise and conversion gain. Experimental data captured from a CMOS quanta image sensor with DSERN are then used to demonstrate the algorithm’s usage and validate the underlying theory and statistical model. In support of the reproducible research effort, the code associated with this work can be obtained on the MathWorks file exchange (FEX) (Hendrickson et al., 2024).

 

RRMSE versus read noise for parameter estimates computed using constant flux implementation of PT and PCH-EM. RRMSE curves for PT μ~ and σ~ grow large near σread=0 and were clipped from the plot window.

Open access paper link: https://ieeexplore.ieee.org/document/10570238

Job Postings - Week of 18 August 2024

Omnivision Principal Image Sensor Technology Engineer	Santa Clara, California, USA	Link
Teledyne Product Assurance Engineer	Chelmsford, England, UK	Link
Tokyo Electron Labs Heterogenous Integration Process Engineer I	Albany, New York, USA	Link
Fraunhofer IMS Doktorand*in Optische Detektoren mit integrierten 2D-Materialien	Duisburg, Germany	Link
AMETEK Forza Silicon Principal Mixed Signal Design Engineer	Pasadena, CA, USA	Link
University of Birmingham Professor of Silicon Detector Instrumentation for Particle Physics	Birmingham, England, UK	Link
Ouster Sensor Package Design Engineer	San Francisco, California, USA	Link
Beijing Institute of High Energy Physics CEPC Overseas High-Level Young Talents	Beijing, China	Link
Thermo Fisher Scientific Sr. Staff Product Engineer	Waltham, Massachusetts, USA (Remote)	Link

Harvest Imaging Forum 2024 registration open

The Harvest Imaging forum tradition continues, a next and tenth one will be organized on November 7 & 8, 2024, in Delft, the Netherlands. The basic intention of the Harvest Imaging forum is to have a scientific and technical in-depth discussion on one particular topic that is of great importance and value to digital imaging. The forum 2024 will be an in-person event.

The 2024 Harvest Imaging forum will deal with a single topic from the field of solid-state imaging world and will have only one world-level expert as the speaker:

"AI and VISION : A shallow dive into deep learning"

Prof. dr. Jan van Gemert (Delft Univ. of Technology, Nl)

Abstract: Artificial Intelligence is taking the world by storm! The AI engine is powered by “Deep Learning”. Deep learning differs from normal computer programming in that it allows computers to learn tasks from large, labelled, datasets. In this Harvest Imaging Forum we will go through all fundamentals of Deep Learning: Multi-layer perceptrons, Back-propagation, Optimization, Convolutional neural networks, Recurrent neural networks, un-/self-supervised learning and transformers and self-attention (GPT).

Bio: Jan van Gemert received a PhD degree from the University of Amsterdam in 2010. There he was a post-doctoral fellow as well as at École Normale Supérieure in Paris. Currently he leads the Computer Vision lab at Delft University of Technology. He teaches the Deep learning and Computer Vision MSc courses. His research focuses on visual inductive priors for deep learning for automatic image and video understanding. He has published over 100 peer-reviewed papers with more than 7,500 citations. See his Google scholar profile for his publications: https://scholar.google.com/citations?hl=en&user=JUdMRGcAAAAJ

Registration: The registration fee for this 2-days forum is set to 1295 Euro for an in-person attendance. Next to the cost of attending the forum, this fee for the in-person attendance does include:

•  Coffee breaks in the mornings and afternoons,
•  Lunch on both forum days,
•  Dinner on the first forum day,
•  Soft and hard copy of the presented material.

If you are interested to attend this forum, please fill out the registration form here: https://harvestimaging.com/forum_registration_2024.php

PhD thesis on a low power "time-to-first-spike" event sensor

Title: Event-based Image Sensor for low-power

Author: Mohamed AKRARAI (Universite Grenoble Alpes)

Abstract: In the framework of the OCEAN 12 European project, this PhD achieved the design, the implementation, the testing of an event based image sensor, and the publication of several scientific papers in international conferences, including renowned ones like the International Symposium on Asynchronous Circuits and Systems (ASYNC). The design of event-based image sensors, which are frameless, require a dedicated architecture and an asynchronous logic reacting to events. First, this PhD gives an overview of architectures based on a hybrid pixel matrix including TFS and DVS pixels. Indeed, this two kind of pixels are able to manage the spatial redundancy and the temporal redundancy respectively. One of the main achievement of this work is to take advantage of having both pixels inside an imager in order to reduce its output bitstream and its power consumption. Then, the design of the pixels and readout in FDSOI 28 nm technology from STMicroelectronics is detailed. Finally, two image sensors have been implemented in a testchip and tested.

Link: https://theses.hal.science/tel-04213080v1/file/AKRARAI_2023_archivage.pdf

 

EETimes article on imec

Full article: https://www.eetimes.eu/imec-getting-high-precision-sensors-to-market/

Imec: Getting High-Precision Sensors to Market

At the recent ITF World 2024, EE Times Europe talked with imec researchers to catch up on what they’re doing with high-precision sensors—and more importantly, how they make sure their innovations get into the hands of industrial players.

Imec develops sensors for cameras and displays, and it works with both light and ultrasound—for medical applications, for example. But the Leuven, Belgium–based research institute never takes technology to market itself. It either finds industrial partners—or when conditions are right, imec creates a spinoff. One way to understand how imec takes an idea from lab to fab and finds a way to get it to market is to zoom in on its approach with image sensors for cameras.

“We make image sensors that are at the beating heart of incredible cameras around the world,” said Paul Heremans, vice president of future CMOS devices and senior fellow at imec. “Our research starts with material selection and an overall new concept for sensors and goes all the way to development, engineering and low-volume manufacturing within imec’s pilot line.”

A good example is the Pharsighted E9-100S ultra-high-speed video camera, developed by Pharsighted LLC and marketed by Photron. The camera reaches 326,000 frames per second (full frame: 640 × 480 pixels) and up to 2,720,000 frames per second at a lower frame size (640 × 32 pixels), thanks to a high-speed image sensor developed and manufactured by imec.

Another example is an electron imager used in a cryo-transmission electron microscope (cryo-TEM) marketed by a U.S. company called Thermo Fisher. The instrument produces atomic resolution pictures of DNA strands and other complex molecules. These images help in the drug-discovery process by allowing researchers to understand the structure of the molecules they need to target.
Thermo Fisher uses direct electron detection imagers, developed by imec and built into the company’s Falcon direct electron detection imagers, each composed of 4K × 4K pixels. The pixels are very large to get to the ultimate sensitivity. Consequently, the chip is so large (5.7 × 5.7 cm) that only four fit on a 200-mm wafer.

A third example is hyperspectral imagers, with very special filters that detect many more colors than just red, green and blue (RGB). Hyperspectral imagers pick up tens or hundreds of spectral bands. They can achieve this level of performance because imec implements processing filters on each pixel.

“We can do that on almost any commercial imager and turn it into a hyperspectral camera,” Heremans said. “Our technology is used by plenty of customers with a range of applications—from surveillance to satellite-based Earth observation, from medical to agriculture and more.”

Spectricity

To bring some of its work on hyperspectral imagers to market, imec created a startup called Spectricity. “The whole idea is to bring this field of multispectral imaging or spectroscopy into cellphones or other high-volume products,” said Glenn Vandevoorde, CEO of Spectricity. “Our imagers can see things that are not visible to the human eye. Instead of just processing RGB data, which a traditional camera does, we take a complete spectral image, where each pixel contains 16 different color points—including near-infrared. And with that, you can detect different materials that look alike but are actually very different. Or you can do color correction on smartphones. Sometimes people look very different, depending on the ambient light. We can detect what kind of light is shining—and based on that, adjust the color.”
The first use case for cellphones is auto white balancing. When a picture is taken with a cellphone, sometimes the colors show up very differently from reality, because the camera doesn’t have an accurate white point, which is the set of values that make up the color white in an image. These values change under different conditions, which means they need to be calibrated often. All other colors are then adjusted based on the white point reference.

Traditional smartphone cameras cannot determine the ambient light accurately, so they cannot find the white point to serve as a viable reference. But the multispectral imager obtains the full spectral information of the ambient light and applies advanced AI algorithms to detect the white point, which leads to accurate auto white balancing and true color correction.

Spectricity said its sensor is being evaluated by seven out of the top eight smartphone manufacturers in the world for integration into phones. “By the end of this year, you will see several smartphone vendors launching the first phones with multispectral imagers inside,” Vandevoorde said.

While smartphones are the ultimate target for high volume, they are also very cost-competitive—and it takes a long time to introduce a new feature in a smartphone. Spectricity is targeting other smartphone applications but also applications for webcams, security cameras and in-cabin video cameras for cars. One category of use cases takes advantage of the ability of multispectral images to detect health conditions.

 

 

Spectricity’s spectral image sensor technology extends the paradigm of RGB color image sensors. Instead of red, green and blue filters on the pixels, many different spectral filters are deposited on the pixels, using wafer-scale, high-volume fabrication techniques. (Source: Spectricity)

 

Spectricity’s miniaturized spectral camera module, optimized for mobile devices.

“For example, you can accurately monitor how a person’s skin tone develops every day,” Vandevoorde said. “We can monitor blood flow in the skin, we can monitor moisture in the skin, we can detect melanoma and so on. These and many other things can be detected with these multispectral imagers.”
Spectricity has raised €28 million in funding since it was founded in 2018—and the startup has its own mass-production line at X-Fab, one of the company’s investors. “We have our machinery and our process installed there,” Vandevoorde said. “It’s now going through qualification—and by the end of the year, we’ll be ready for mass production to start shipping large volume to customers.” 

How imec finds the right trends to target
Spectricity is a good example of how imec spots a need and develops technology to meet that need. Spectroscopy, of course, is not new. It’s been around for decades, and researchers use it in labs to detect different materials and different gases. What’s new is that imec integrated spectroscopy onto CMOS technology and developed processes to produce it in high volumes for just a couple of dollars. Researchers worked on the idea for about 10 years—and once it was running on imec’s pilot line, the institute set up Spectricity to take it into mass production and develop applications around it. 

“We sniff around different trends,” said Xavier Rottenberg, scientific director and group leader of wave-based sensors and actuators at imec. “We’re in contact with a lot of players in the industry to get exposed to plenty of problems. Based on that, we develop a gut feeling. But gut feelings are dangerous, because it might be that you’re just hungry. However, with an educated gut feeling, sometimes your intuition is right.”

Once imec develops an idea in the lab, it takes the technology to its pilot line to develop a demonstrator. “We do proofs of concept to see how a device performs,” Rottenberg said. “Then we set up contacts in the ecosystem to form partnerships to bring the platform to a level where it can be mass-produced in an industrial fab.”

In some cases, an idea is too far out for partners to pick up for near-term profit. That’s when imec ventures out with a spinoff company, as it did with Spectricity.