Si CMOS Image-Sensors Designed With Hydrogen-Ion Implantation Induced Nanocavities for Enhancing Output Voltage Sensing Margin via Proximity Gettering

Kim, Il-Hwan; Park, Junseong; Shim, Tae‐Hun; Park, Jea‐Gun

doi:10.1109/ted.2017.2677948

Cited by 6 publications

(3 citation statements)

References 21 publications

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“…Other approaches giving good results are based on the use of p/p ++ epitaxial wafers and relaxation gettering‐based hydrogen‐ion‐induced nanocavities created in the substrate underneath the depletion region of the photodiodes . Some results are shown in Figure , giving for Fe, Cu, Ni, and Co the change in dark photocurrent

V_{dark - photo} (%) = \frac{V_{normaldark - photo false(metal contamination false)}}{V_{normaldark - photo false(no contamination false)}}

for two different substrates, i.e., p‐substrates with and without H + implantation (6 × 10 16 cm −2 at 26 keV + 3 μm epitaxial layer) and p/p ++ epitaxial wafers.…”

Section: Cmos Image Sensorsmentioning

confidence: 99%

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Device Performance as a Metrology Tool to Detect Metals in Silicon

Claeys

Simoen

2019

Physica Status Solidi (a)

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Herein, the impact of transition metals (TMs) on the electrical device performance, i.e., carrier lifetime, leakage current, low‐frequency noise, photocurrent, and solar cell efficiency is reviewed. Defect information is obtained by using either simple device structures such as metal‐oxide‐semiconductor (MOS) capacitors and pn‐diodes or transistors. The impact of metals on complementary MOS (CMOS) image sensors (CIS) and solar cells is also briefly addressed. Scaled devices are a power tool to detect small‐sized defect clusters or even single metal atoms. Examples are given for a variety of both slow‐ and fast‐diffusing metals. The final section outlines the power of density functional theory (DFT) ab initio calculations to support the experimental observations and to get a deeper physical insight into the defect structure.

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V_{dark - photo} (%) = \frac{V_{normaldark - photo false(metal contamination false)}}{V_{normaldark - photo false(no contamination false)}}

for two different substrates, i.e., p‐substrates with and without H + implantation (6 × 10 16 cm −2 at 26 keV + 3 μm epitaxial layer) and p/p ++ epitaxial wafers.…”

Section: Cmos Image Sensorsmentioning

confidence: 99%

“…Figure 11. Change in dark photocurrent before and after contamination with a) Fe, b) Cu, c) Ni, and d) Co for different substrates and with or without hydrogen implantation (after Kim et al[26] ).…”

mentioning

confidence: 99%

Device Performance as a Metrology Tool to Detect Metals in Silicon

Claeys

Simoen

2019

Physica Status Solidi (a)

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“…In addition, the scaling down of the pixel size has been limited by the diffraction limit of the optical system. Thus, research on enhancing the efficiency of absorbing photo light with the Si photodiodes of conventional CISs has been intensively conducted to achieve extremely high pixel resolution; this includes structural changes in the CIS from frontside illumination (FSI) to backside illumination (BSI) [7][8][9][10][11] and research on the structure and process of doped silicon photodiodes [12,13]. These studies showcase the ongoing efforts to improve the diffraction limit and SNR by increasing the size of the photodiode and the number of electrons that can be generated by light for the same pixel size.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Organic–Si C-MOSFET Image Sensor Designed with Blue-, Green-, and Red-Sensitive Organic Photodiodes on Si C-MOSFET-Based Photo Signal Sensor Circuit

Jeong,

Park,

Choi

et al. 2024

Nanomaterials

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The resolution of Si complementary metal–oxide–semiconductor field-effect transistor (C-MOSFET) image sensors (CISs) has been intensively enhanced to follow the technological revolution of smartphones, AI devices, autonomous cars, robots, and drones, approaching the physical and material limits of a resolution increase in conventional Si CISs because of the low quantum efficiency (i.e., ~40%) and aperture ratio (i.e., ~60%). As a novel solution, a hybrid organic–Si image sensor was developed by implementing B, G, and R organic photodiodes on four n-MOSFETs for photocurrent sensing. Photosensitive organic donor and acceptor materials were designed with cost-effective small molecules, i.e., the B, G, and R donor and acceptor small molecules were Coumarin6 and C_60, DMQA and MePTC, and ZnPc and TiOPc, respectively. The output voltage sensing margins (i.e., photocurrent signal difference) of the hybrid organic–Si B, G, and R image sensor pixels presented results 17, 11, and 37% higher than those of conventional Si CISs. In addition, the hybrid organic–Si B, G, and R image sensor pixels could achieve an ideal aperture ratio (i.e., ~100%) compared with a Si CIS pixel using the backside illumination process (i.e., ~60%). Moreover, they may display a lower fabrication cost than image sensors because of the simple image sensor structure (i.e., hybrid organic–Si photodiode with four n-MOSFETs).

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Impact of Metals on Silicon Devices and Circuits

Claeys

Simoen²

2018

Springer Series in Materials Science

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Si CMOS Image-Sensors Designed With Hydrogen-Ion Implantation Induced Nanocavities for Enhancing Output Voltage Sensing Margin via Proximity Gettering

Cited by 6 publications

References 21 publications

Device Performance as a Metrology Tool to Detect Metals in Silicon

Device Performance as a Metrology Tool to Detect Metals in Silicon

Hybrid Organic–Si C-MOSFET Image Sensor Designed with Blue-, Green-, and Red-Sensitive Organic Photodiodes on Si C-MOSFET-Based Photo Signal Sensor Circuit

Impact of Metals on Silicon Devices and Circuits

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