Friday, November 24, 2017

Curved Origami Image Sensor

University of Wisconsin-Madison reports that its researchers were able to make a curved image sensor:

A flat silicon sensor "just can’t process images captured by a curved camera lens as well as the similarly curved image sensor — otherwise known as the retina — in a human eye.

Zhenqiang (Jack) Ma has devised a method for making curved digital image sensors in shapes that mimic the convex features of an insect’s compound eye and a mammal’s concave “pinhole” eye.

To create the curved photodetector, Ma and his students formed pixels by mapping repeating geometric shapes — somewhat like a soccer ball — onto a thin, flat flexible sheet of silicon called a nanomembrane, which sits on a flexible substrate. Then, they used a laser to cut away some of those pixels so the remaining silicon formed perfect, gapless seams when they placed it atop a dome shape (for a convex detector) or into a bowl shape (for a concave detector).

“We can first divide it into a hexagon and pentagon structure, and each of those can be further divided,” says Ma. “You can forever divide them, in theory, so that means the pixels can be really, really dense, and there are no empty areas. This is really scalable, and we can bend it into whatever shape we want.”

Pixel density is a boon for photographers, as a camera’s ability to take high-resolution photos is determined, in megapixels, by the amount of information its sensor can capture.

This image shows how the researchers mapped pixels
onto the silicon, then cut some sections away so
the resulting silicon drapes over a dome shape, with
no wrinkles or gaps at the seams.

The open-access paper has been publishes in Nature Communications: "Origami silicon optoelectronics for hemispherical electronic eye systems" by Kan Zhang, Yei Hwan Jung, Solomon Mikael, Jung-Hun Seo, Munho Kim, Hongyi Mi, Han Zhou, Zhenyang Xia, Weidong Zhou, Shaoqin Gong & Zhenqiang Ma

A concave version of the digital image sensor (left)
bends inward for creating a hemispherical focal plane
array. A convex version (right) bends like a soccer
ball for mimicking an insect’s compound eye.
A silicon nanomembrane-based photodiode used for the
electronic eyes. An array of such photodiodes were
printed and fabricated on a pre-cut flexible polyimide

Cambridge Mechatronics Wins Company of 2017 Award, vivaMOS Wins Emerging Technology Company of the Year Award at TechWorks

The UK TechWorks names Cambridge Mechatronics the Company of the Year. The company is a world-leader and pioneer in shape memory alloys, which it uses to create single-piece motors the size of a human hair and controlled to a precision of the wavelength of light. Its technology is being designed into a huge array of products: AF and OIS for smartphones cameras and drones and devices to improve the accuracy of 3D-sensing, among many other things.

BBC’s head of technology Rory Cellan-Jones said of Cambridge Mechatronics: "The company has successfully qualified their actuators of use in one of the world’s top three smartphone brands."

The large-area X-Ray CMOS image sensors company vivaMOS wins the Emerging Company of the Year award. vivaMOS was founded in July 2015 as a technology spin-out from the CMOS image sensor group at Rutherford Appleton Laboratory (RAL) in the Science & Technology Facilities Council (STFC).

Thursday, November 23, 2017

NHK on 8K Image Sensor Development

IEEE Broadcast Symposium publishes NHK Hiroshi Shimamoto video presentation "Development of 8K UHDTV Cameras and Image Sensors:"

Wednesday, November 22, 2017

Image Sensors at ISSCC 2018

ISSCC 2018 publishes its Advance Program. There is a lot of interesting image sensor papers in the Image Sensors session:

5.1 A Back-Illuminated Global-Shutter CMOS Image Sensor with Pixel-Parallel 14b Subthreshold ADC
M. Sakakibara, K. Ogawa, S. Sakai, Y. Tochigi, K. Honda, H. Kikuchi, T. Wada, Y. Kamikubo, T. Miura, M. Nakamizo, N. Jyo, R. Hayashibara, Y. Furukawa, S. Miyata, S. Yamamoto, Y. Ota, H. Takahashi, T. Taura, Y. Oike, K. Tatani, T. Nagano, T. Ezaki, T. Hirayama,
Sony, Japan

5.2 An 8K4K-Resolution 60fps 450ke- -Saturation-Signal Organic-Photoconductive-Film Global Shutter CMOS Image Sensor with In-Pixel Noise Canceller
K. Nishimura, S. Shishido, Y. Miyake, M. Yanagida, Y. Satou, M. Shouho, H. Kanehara, R. Sakaida, Y. Sato, J. Hirase, Y. Tomekawa, Y. Abe, H. Fujinaka, Y. Matsunaga, M. Murakami, M. Harada, Y. Inoue,
Panasonic, Japan

5.3 A 1/2.8-inch 24Mpixel CMOS Image Sensor with 0.9μm Unit Pixels Separated by Full-Depth Deep-Trench Isolation
Y. Kim, W. Choi, D. Park, H. Jeoung, B. Kim, Y. Oh, S. Oh, B. Park, E. Kim, Y. Lee, T. Jung, Y. Kim, S. Yoon, S. Hong, J. Lee, S. Jung, C-R. Moon, Y. Park, D. Lee, D. Chang, Samsung Electronics, Hwaseong, Korea

5.4 A 1/4-inch 3.9Mpixel Low-Power Event-Driven Back-Illuminated Stacked CMOS Image Sensor
O. Kumagai, A. Niwa, K. Hanzawa, H. Kato, S. Futami, T. Ohyama, T. Imoto, M. Nakamizo, H. Murakami, T. Nishino, A. Bostamam, T. Iinuma, N. Kuzuya, K. Hatsukawa, B. Frederick, B. William, T. Wakano, T. Nagano, H. Wakabayashi, Y. Nitta
Sony Japan and USA

5.5 A 1.1μm-Pitch 13.5Mpixel 3D-Stacked CMOS Image Sensor Featuring 230fps Full-High Definition and 514fps High-Definition Videos by Reading 2 or 3 Rows Simultaneously Using a Column-Switching Matrix
P-S. Chou, C-H. Chang, M. M. Mhala, C-M. Liu, C-P. Chao, C-Y. Huang, H. Tu, T. Wu, S-F. Yeh, S. Takahashi, Y. Huang,
TSMC, Hsinchu, Taiwan

5.6 A 2.1μm 33Mpixel CMOS Imager with Multi-Functional 3-Stage Pipeline ADC for 480fps High Speed Mode and 120fps Low-Noise Mode
T. Yasue, K. Tomioka, R. Funatsu, T. Nakamura, T. Yamasaki, H. Shimamoto, T. Kosugi, J. Sungwook, T. Watanabe, M. Nagase, T. Kitajima, S. Aoyama, S. Kawahito
NHK Science & Technology Research Laboratories, Tokyo, Japan;
Brookman Technology, Hamamatsu, Japan;
Shizuoka University, Hamamatsu, Japan

5.7 A 20ch TDC/ADC Hybrid SoC for 240×96-Pixel 10%-Reflection less than 0.125%-Precision 200m-Range Imaging LiDAR with Smart Accumulation Technique
K. Yoshioka, H. Kubota, T. Fukushima, S. Kondo, T. T. Ta, H. Okuni, K. Watanabe, Y. Ojima, K. Kimura, S. Hosoda, Y. Oota, T. Koizumi, N. Kawabe, Y. Ishii, Y. Iwagami, S. Yagi, I. Fujisawa, N. Kano, T. Sugimoto, D. Kurose, N. Waki, Y. Higashi, T. Nakamura, Y. Nagashima, H. Ishii, A. Sai, N. Matsumoto
Toshiba, Kawasaki, Japan; 2
Toshiba Memory, Kawasaki, Japan

5.8 1Mpixel 65nm BSI 320MHz Demodulated TOF Image Sensor with 3.5μm Global Shutter Pixels and Analog Binning
C. S. Bamji, S. Mehta, B. Thompson, T. Elkhatib, S. Wurster, O. Akkaya, A. Payne, J. Godbaz, M. Fenton, V. Rajasekaran, L. Prather, S. Nagaraja, V. Mogallapu, D. Snow, R. McCauley, M. Mukadam, I. Agi, S. McCarthy, Z. Xu, T. Perry, W. Qian, V-H. Chan, P. Adepu, G. Ali, M. Ahmed, A. Mukherjee, S. Nayak, D. Gampell, S. Acharya, L. Kordus, P. O'Connor
Microsoft, Mountain View, CA

5.9 A 256×256 45/65nm 3D-Stacked SPAD-Based Direct TOF Image Sensor for LiDAR Applications with Optical Polar Modulation for up to 18.6dB Interference Suppression
A. Ronchini Ximenes, P. Padmanabhan, M-J. Lee, Y. Yamashita, D. N. Yaung, E. Charbon
Delft University of Technology, Delft, The Netherlands;
EPFL, Neuchatel, Switzerland;
TSMC, Hsinchu, Taiwan

5.10 A 32×32-Pixel Time-Resolved Single-Photon Image Sensor with 44.64μm Pitch and 19.48% Fill-Factor with On-Chip Row/Frame Skipping Features Reaching 800kHz Observation Rate for Quantum Physics Applications
L. Gasparini, M. Zarghami, H. Xu, L. Parmesan, M. Moreno Garcia, M. Unternährer, B. Bessire, A. Stefanov, D. Stoppa, M. Perenzoni,
Fondazione Bruno Kessler (FBK), Trento, Italy;
University of Bern, Bern, Switzerland;

There is also a tutorial:

T6 Single-Photon Detection in CMOS
Matteo Perenzoni, Fondazione Bruno Kessler, Trento, Italy
Every single photon carries information in position, time, etc. Single-photon devices are now demonstrated and available in several CMOS technologies, but the needed circuits and architectures are completely different from conventional visible light sensors.

This tutorial starts from the description of structure and operation of a single-photon detector, and it continues on the definition of circuits for the front-end electronics needed to efficiently manage the extracted information, addressing challenges and requirements. Then, it concludes with an overview of the different architectures that are specific for each application field, with examples in the biomedical, consumer, and space domain.

One of the forums has Sony presentation on compressive sensing:

Compressive Imaging for CMOS Image Sensors
Yusuke Oike, Sony Semiconductor Solutions, Atsugi, Japan

KB Securities: High-End Smartphone Camera ASP to Rise to $60-90

BusinessKorea says that the next generation Samsung Galaxy S9 smartphone will feature a "3-stack layer" image sensor capable of 1,000 fps speed. The newspaper says it will have a dual camera on the rear. It's not clear whether the both sensors would be that fast or just one of them.

Korea-based KB Securities analyst Kim Dong-won believes that "When Samsung Electronics applies 3-stack layer laminated image sensors to smartphone cameras next year, the ASP of camera modules will double or triple to US$ 60 to US$ 90 due to the installation of super high-priced image sensors, camera module parts and design changes among others."

Soitec on SOI-based Imagers

EETimes' Junko Yoshida publishes an interview with Soitec CEO Paul Boudre. The company now offers SOI wafers for imaging, in addition to its more traditional applications:

"Soitec sees a growing opportunity for its Imager-SOI. Without naming any customers, Soitec listed a number of advantages of Imager-SOI. These include the ability to lower NIR illuminator power consumption, better performance through increased signal to noise ratio, and keeping cost down — because of its “lower die size” compared to bulk for the same resolution."

One should note that the first reports about Soitec plans to make on imaging-optimized wafers appeared in 2013.

EEJournal publishes an article on Soitec wafer types and their differences:

Tuesday, November 21, 2017

Automotive Imaging Technologies Compared

BrightWay Vision publishes a Youtube video comparing Velodyne lidar, Autliv-FLIR thermal camera, RGB camera, and BrightWay gated imaging system in bad weather conditions: at night, 50mm per hour rain, and fog with 60m visibility:

Monday, November 20, 2017

ams Partners with Sunny Optical on 3D Camera Solutions

ams and Ningbo Sunny Opotech, a subsidiary of Sunny Optical Technology, announce a collaboration to develop and market 3D sensing camera solutions for mobile device and automotive applications to OEMs in China and the rest of the world.

Alexander Everke, CEO of ams, commented, “We are very excited about this collaboration which brings together ams’ leadership in optical sensing with Sunny Optical’s leading position in optical components and module manufacturing. Teaming up with Sunny Opotech, we are accelerating the time-to-market and availability of high quality 3D sensing solutions for smartphones and mobile devices where efficient module integration is key to enable 3D sensing for smartphone OEMs. At the same time, this collaboration allows us to pursue emerging 3D sensing opportunities in the automotive world.

David Wang, CEO of Ningbo Sunny Opotech Co., Ltd., added, “Sunny Opotech believes that ams is the industry’s leading 3D sensing technology provider with a complete portfolio of key components and technologies enhanced by a unique patent portfolio. Combining this with Sunny Opotech’s advanced semiconductor packaging technology, optical system design, mass production abilities as well as precise active alignment and optical calibration technologies will enable us to bring Chinese OEMs and global customers optimized and comprehensive 3D sensing solutions. Sunny Opotech is very much looking forward to create substantial value for both partners through the collaboration with ams.

Saturday, November 18, 2017

New Omnivision CEO Opens Patent War in China

Omnivision board of directors appointed a new CEO - Yu Renrong. Yu Renrong was born in 1966, has Chinese Nationality, no permanent residence abroad, Bachelor’s degree. Yu has graduated in 1990 from the Department of Radio, Tsinghua University, Beijing and has been involved into management of various companies since 1998.

Omnivision and Spreadtrum co-founder Datong (David) Chen has been appointed Chairman of the Board. The company's former CEO and Chairman Shaw Hong now becomes Chairman Emeritus and Chairman of OVT Strategic Development Committee.

IFNews, EEWorld, asmag, IPR: The company files two lawsuits against SmartSens claiming that its security-aimed SC5035 image sensor infringes on Omnivision's Chinese patent ZL200510052302.4.

According to iKnow site, the ZL200510052302.4 is actually a patent family:

Similarly to Omnivision's Nyxel announcement, StartSens too says it has improved IR sensitivity in its SC5035 sensor, but has announced this 6 months earlier, on April 18, 2017:

"SmartSens Technology's near-infrared enhancement is due to its new pixel structure. In the new structure, the electron capture region of each pixel is extended to more fully capture the electrons generated by the near-infrared band photons. This special pixel structure makes the photoelectric conversion efficiency of the near infrared band more than doubled compared with the original technology. At the same time, the new structure of the adjacent photodiode do a deep isolation, reducing the crosstalk between pixels, improve image clarity.

The 5-megapixel SC5035 is the first device in the SmartSens Technology CMOS image sensor lineup with the new technology, and its near-infrared (NIR) band is twice as susceptible to existing products. In the current security monitoring, machine vision and intelligent transportation systems and other applications, the night infrared fill light wavelengths concentrated in the 850nm ~ 940nm near infrared band. So the sensitivity of the near infrared band to enhance, can greatly enhance the product's night vision effect.

SmartSens graph shows 940nm QE of ~30% in 2um pixel, while Omnivision Nixel achieves 40% QE in 2.8um pixel:

SC5035 flyer is available on-line:

Other than SC5035, SmartSens has quite a broad lineup of sensors for security and surveillance applications:

Friday, November 17, 2017

SystemPlus Reveals that iPhone X IR Imager is SOI-based

EETimes publishes Junko Yoshida's article based on Yole Developpement and SystemPlus Consulting analysis of Apple iPhone X TrueDepth design. The biggest surprise is that ST IR imager is using SOI process, said to be the first such sensor in mass production:

SystemPlus and Yole "deduced that silicon-on-insulator (SOI) wafers are being used in near-infrared (NIR) imaging sensors. They noted that SOI has played a key role in improving the sensitivity of NIR sensors — developed by STMicroelectronics — to meet Apple’s stringent demands.

Pierre Cambou, activity leader for imaging and sensors at Yole Développement, called the SOI-based NIR image sensors “a very interesting milestone for SOI.”

Apple’s adoption of ST’s NIR sensors marks the debut of SOI in mass production for image sensors, noted Cambou. “Image sensors are characterized by large surface due to the physical size of light. Therefore, this is a great market to be in for a substrate supplier” like Soitec, he added.

Yole and System Plus Consulting found inside ST’s NIR sensor “the use of silicon-on-insulator (SOI) on top of deep-trench isolation (DTI).” DTI is deployed to prevent leakage between photodiodes. Apple reportedly etched literal trenches between each one, then filled the trenches with insulating material that stops electric current.

Optically speaking, Cambou explained that SOI wafers are advantageous because the insulator layer functions like a mirror. “Infrared light penetrates deeper, and it reflects back to the active layer,” he noted. Electrically speaking, Cambou noted, SOI improves NIR’s sensitivity largely because it’s good at minimizing leakage within the pixel. The improved sensitivity provides good image contrast.

Asked if ST’s NIR sensors are using FD-SOI or SOI wafers, Cambou said that the research firms couldn’t tell.

Asked about surprises unearthed by the teardown, Cambou cited the size of ST’s NIR sensor chip. It measures 25mm2, and has only 1.4 megapixels due to the large 2.8-μm pixel size.