Emitter-Receiver Photodetector Module on Silicon for Longer-Wave Detection
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Solution Overview
Problem
CMOS image sensors have limitations in the detectable wavelength range and suffer from poor sensitivity at longer wavelengths, necessitating the development of improved sensing devices.
Innovation Solution
The use of heteroepitaxy to deposit compound semiconductor materials on silicon substrates, enabling the fabrication of photodetector modules with enhanced detectable wavelength range and sensitivity, suitable for applications like LIDAR and image sensing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CMOS image sensors are used for manufacturing, then high-volume manufacturing capability and mature process technology are achieved, but the detectable wavelength range is limited and sensitivity at longer wavelengths is poor
Solution Approach 1:
The patent employs a heteroepitaxial structure combining compound semiconductor materials (InP, InGaAs) with silicon substrate. This composite material approach enables the photodetector to detect longer wavelengths (up to 1.7 micrometers) while maintaining compatibility with existing silicon-based manufacturing processes, thus resolving the contradiction between extended wavelength range and manufacturing ease
Solution Approach 2:
The invention introduces a buffer layer structure with graded composition (InP/InGaAs/InAlAs) between the silicon substrate and the active photodetector region. This local quality variation allows the structure to maintain mechanical compatibility with silicon while providing the optical properties needed for extended wavelength detection, balancing manufacturing compatibility with improved detection capability
2Reliability
If heteroepitaxy of compound semiconductor materials on silicon is used, then detectable wavelength range and sensitivity are improved, but manufacturing complexity increases
Solution Approach 1:
The patent utilizes parameter changes in the buffer layer composition (gradual transition from InP to InGaAs to InAlAs) to manage lattice mismatch and thermal expansion differences between silicon and compound semiconductors. This parameter adjustment approach enables successful heteroepitaxial growth with reduced defect density, improving sensitivity while controlling manufacturing complexity through systematic material design
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for the large-volume manufacturing of optoelectronic devices with improved performance metrics, including extended wavelength range and higher sensitivity, facilitating their integration into various electronic devices and systems.
Implementation Method 1
The laser device can be a VCSEL (vertical cavity surface emitting laser) array device
Implementation Method 2
The image sensor can be spatially disposed to include an aperture configured on the sensing portion of the exterior region of the housing
Implementation Method 3
The use of heteroepitaxy to deposit compound semiconductor materials on silicon substrates
Data Source
AI summary
Techniques for realizing compound semiconductor (CS) optoelectronic devices on silicon (Si) substrates are disclosed. The integration platform is based on heteroepitaxy of CS materials and device structures on Si by direct heteroepitaxy on planar Si substrates or by selective area heteroepitaxy on dielectric patterned Si substrates. Following deposition of the CS device structures, device fabrication steps can be carried out using Si complimentary metal-oxide semiconductor (CMOS) fabrication techniques to enable large-volume manufacturing. The integration platform can enable manufacturing of optoelectronic module devices including photodetector arrays for image sensors and vertical cavity surface emitting laser arrays. Such module devices can be used in various applications including light detection and ranging (LIDAR) systems for automotive and robotic vehicles as well as mobile devices such as smart phones and tablets, and for other perception applications such as industrial vision, artificial intelligence (AI), augmented reality (AR) and virtual reality (VR).