CMOS image sensor technology advances for mobile devices

Gove, Robert John

doi:10.1016/b978-0-08-102434-8.00007-6

Cited by 20 publications

(14 citation statements)

References 15 publications

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“…The high-performance complementary metal-oxide-semiconductor (CMOS) color image sensor technology is critical to the continued development of mobile devices such as smartphones and tablet PCs, automotive image sensors, and medical imaging cameras. − CMOS color image sensors typically employ two-dimensional (2D) color filter arrays consisting of a mosaic of red (R), green (G), and blue (B) filters, that is, the Bayer filter arrangement, in which the active areas of the G filters are twice as those of the R and B filters, on top of the Si photodetector . With the miniaturization of the sensors in recent years, the pixel size has been significantly decreased to afford a high-resolution image.…”

Section: Introductionmentioning

confidence: 99%

Green-Light-Selective Organic Photodiodes with High Detectivity for CMOS Color Image Sensors

Lim

Yun

Minami

et al. 2020

ACS Appl. Mater. Interfaces

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Stacked structures employing wavelength-selective organic photodiodes (OPDs) have been studied as promising alternatives to the conventional Si-based image sensors because of their color constancy. Herein, novel donor (D)−π–acceptor (A) molecules are designed, synthesized, and characterized as green-light-selective absorbers for application in organic-on-Si hybrid complementary metal-oxide-semiconductor (CMOS) color image sensors. The p-type molecules, combined with two fused-type heterocyclic donors and an electron-accepting unit, exhibit cyanine-like properties that are characterized by intense and sharp absorption. This molecular design leads to improved absorption properties, thermal stability, and higher photoelectric conversion compared to those of a molecular design based on a nonfused ring. A maximum external quantum efficiency of 66% (λmax = 550 nm) and high specific detectivity (D*) of 8 × 1013 cm Hz1/2/W are achieved in an OPD consisting of a bulk heterojunction blend with two transparent electrodes on both sides. Finally, the green-light-detection capability of the narrow-band green-selective OPD is demonstrated by the optical simulation of an organic-on-Si hybrid, stacked-type, full-color photodetector comprising the green-light-selective OPD and a bottom Si photodiode with only blue and red color filters. Based on this molecular design, further optimization of the OPDs can allow the development of various optoelectronic sensors including 3D-stacked image sensors with enhanced sensitivities to replace the conventional Si-based CMOS image sensors.

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Section: Introductionmentioning

confidence: 99%

Green-Light-Selective Organic Photodiodes with High Detectivity for CMOS Color Image Sensors

Lim

Yun

Minami

et al. 2020

ACS Appl. Mater. Interfaces

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“…The need for image sensor technology is quickly extending beyond smartphones, which presently have the highest market share, and includes internet security cameras, computer vision systems used in industrial automation, and cameras for automatic vehicle driving. The roadmap of CCD and CMOS image sensors from past technologies toward better future resolution with megapixel cameras having 3D stacked sensors for improved image sensing is shown in Figure , showing that the pixel size of the imaging devices is continuing to decrease with the passing years while the 3D stacking of materials is proposed for future innovations …”

Section: Technological Evolution Of Image Sensing: An Overview On Cur...mentioning

confidence: 99%

Technological Evolution of Image Sensing Designed by Nanostructured Materials

Iqbal

Malik

et al. 2023

ACS Materials Lett.

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Imaging sensing holds a remarkable place in modern electronics and optoelectronics for the complementary metal-oxide-semiconductor integration of highspeed optical communications and photodetection with the merits of high-speed operation, cost-effectiveness, and noncomplex fabrication. The optimum quality of image sensing relies on noise, sensitivity, power consumption, voltage operation, and speed imaging to access and compete with the state-of-the-art image sensing devices in the industry. Many studies have been conducted to address these issues; however, performance has not yet been optimized and solutions are still in the works. In this review, we briefly provide information on recent advances in image sensing using nanostructured emerging materials through nanofabrication integration including the technology evolution on traditional and modern technology platforms, general mechanisms, classification, and actual applications as well as existing limitations. Finally, new challenges and perspectives for the future trends of image sensing and their possible solutions are also discussed.

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“…Image sensors consist of devices that capture an image for purposes of display or storage. Current cell phones typically incorporate these image sensors, usually based on CMOS (Complementary Metal Oxide Semiconductor) technology, which enable high quality images [3]. A CMOS in mobile phones is used for digital image sensing.…”

Section: Introductionmentioning

confidence: 99%

Introducing m-learning in the classroom: a proposal for diffraction and image processing training

Calvo¹

2022

AJP

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Dedicated to Prof Maria J YzuelWe present results obtained with teaching and learning technique, the so called m-Learning (or mobile-Learning). This is a proposal with the aim to introduce an easy procedure to teach how to treat acquired images digitally, and to be detected and analyzed by undergraduate students, of the branch of physics and optics. The results indicated that m-learning could be compatible with diffraction phenomena training in the classroom.

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CMOS image sensor technology advances for mobile devices

Cited by 20 publications

References 15 publications

Green-Light-Selective Organic Photodiodes with High Detectivity for CMOS Color Image Sensors

Green-Light-Selective Organic Photodiodes with High Detectivity for CMOS Color Image Sensors

Technological Evolution of Image Sensing Designed by Nanostructured Materials

Introducing m-learning in the classroom: a proposal for diffraction and image processing training

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