Advances in a CMOS Image Sensor based miniature fluorescence Detection System for Biosensing applications

1. Advances in a CMOS Image Sensor based miniature fluorescence Detection System for Biosensing applications Orly Yadid-Pecht Integrated Sensors, Intelligent Systems, iCORE Professor University of Calgary

2. Outline • Wide Dynamic range sensors – extension on the high side • Individual Pixel Reset • Dual Sampling • Automatic WDR Sensor • Low Power Global Shutter WDR sensor • Memory based WDR Sensor • Low Light Level Imager for Bio-medical Applications • ACS and AR • Our Low Light Level Imager • Further optical filtering to improve the sensitivity for fluorescence applications

3. Some PR… The first book on CMOS Image Sensors (Kluwer, 2004) *****

4. Some background… Prof. Orly Yadid-Pecht • Headed the VLSI systems center at BGU • National Research Council (US) Fellow at the Jet Propulsion Laboratory (JPL)/ California Institute of Technology (Caltech), in the area of smart CMOS Active Pixel Sensors (APS) • iCORE associate chair between 2003-2005. • IEEE Fellow for contributions to “the Design and Modeling of CMOS Image sensors” (2007) • More than 100 journal papers and conference papers, more than a dozen patents and 7 book chapters • More than a dozen projects with industry and government successfully accomplished • Director on the board of two companies • iCORE Professor of Integrated Sensors and Intelligent Systems (program launched end of Sep 2009)

5. Acknowledgements • Terence Tam • Alex Fish • Marianna Biederman • Mihir Maik • Yonatan Dattner

6. Why CMOS image sensors? Today Once… An image A camera A computer

7. Exposure control Timing control Auto focus “CMOS Camera-on-a-chip” CMOS Enables Integration! • Data compression • Color processing • Image enhancement • Uniformity correction • Edge/motion detection • Digital watermarking • Object tracking • Windows definition • Others… • Multiple chip imaging function • 100's of mW power dissipation • Multiple power supply • Single-chip image sensor • Lower power dissipation (10 - 100mW) • Single-power supply

8. My motivation in the 90’s… O. Yadid‑Pecht et al. "A Random Access Photodiode Array for Intelligent Image Capture" Bio-Inspired vision: Published in the IEEE Transactions on Electronic Devices (IEEE TED, 1991)

9. Additional Functionality – “Smart sensor” example: Wide Dynamic Range Sensors Published in the IEEE Journal of Solid State Circuits (IEEE JSSC, 1997)

10. Early example – Individual Pixel Reset (from my JPL/ Caltech work, 1996)

11. Another example – Dual Sampling (from my JPL/ Caltech work, 1997)

12. Newer WDR Sensors (2003, 2007 & 2009) (a) (b) • AWARDII Wide Dynamic Range CMOS Image Sensor • Full coverage of wide dynamic range illumination levels • Floating point representation • Real time operation • Minimal effect on spatial and temporal resolution • Scene observed with a traditional CMOS APS sensor • Scene observed with the in-pixel auto-exposure CMOS APS sensor.

13. LP WDR Snapshot APS (Fish, Belenky & Yadid-Pecht, 2005, 2009) • Global shuttering is the ideal solution for capturing objects moving at high speed • The challenge is to implement the processing circuitry within the pixel while achieving acceptable pixel size • For LP – For good output swing and reasonable DR – technology scaling and aggressive supply voltage reduction – not the best solution! A.Fish , A. Belenky, O. Yadid-Pecht, “Wide dynamic range snapshot APS for ultra-low power applications”, IEEE Transaction on Circuits and Systems II, V.52 n.11, pp.729-733, Nov. 2005

14. Low Power WDR snapshot sensor - pixel description • Photodiode (Pd) • Simple analog comparator • Digital low-power multiplexer (can be implemented using Pass-Transistor Logic technique) • Conventional analog output chain (can be implemented by a source follower amplifier), • Reset transistor (M1), • Control of comparator input (transistors M2, M3, M5), • Shutter switch (transistor M6), • Reset of the analog/digital storage (transistor M4)

15. Results

16. LP WDR Sensor - Results • (a) 32x32 scene observed at room light illumination conditions, • (b) 32x32 scene observed at room light conditions with a laser light on the object without WDR expansion, • (c) 32x32 scene observed at room light conditions with a laser light on the object with 1-bit WDR expansion, • (d) 32x32 scene observed at room light conditions with a laser light on the object with 2-bit WDR expansion.

17. In-pixel memory snapshot WDR (Belenky, Fish, Spivak & Yadid-Pecht, 2007) • The proposed imager is based on the multi-reset WDR approach and it allows an efficient global shutter pixel • The proposed imager provides wide DR by applying adaptive exposure time to each pixel, according to the local illumination intensity level

18. Schematic of single pixel and corresponding processing circuitry and digital memory.

19. My current motivation- Applications. Main areas: Biomedical and Security

20. Low Light Level Imager - Motivation Miniature, low cost and low light level detection ability (for florescence)

21. Low Light Level Imager • Application: Lab-on-a-chip for Biomedical Research • Challenges: • Low noise imager design • Special Filter design for Florescence Imaging • System Integration • Our focus here is on the low noise imager design

22. Noise in CMOS APS Imaging Under uniform, flat-field illumination noise is categorized as Temporal Noise or Spatial Noise ( ) Pixel Level Column Level CMOS APS FPN + = + + = • Temporal Noise: Variations in pixel output value from frame to frame, visible as pixel “flickering” • Largely due to reset or KT/C noise • Spatial Noise : Variations in pixel output value across an array, fixed from frame to frame, also known as Fixed Pattern Noise (FPN) • Largely due to source follower non-linearity and offset 22

23. Existing Noise Suppression Techniques Active Reset Active Column Sensor Readout Suppression of pixel response non-uniformity, through unity gain readout Suppression of temporal reset noise through negative-feedback reset 23

24. Implemented Design Unity Gain Sampling Mode Active Reset Mode 24

25. Sensor Array Two 128x128 CMOS image sensor arrays were fabricated. The first sensor array was divided into two vertical sub-arrays to compare the proposed technique with a conventional ACS. Each sub-array was also divided into three groups, each group employing a different pixel structure to test dark current. The second sensor array was designed to accommodate the best pixel structure with the modified AR and ACS methods. ACS Proposed Technique 25

26. Implemented Pixel Structure • Three different types of nwell /psub photodiodes were implemented. • Different n+ areas were utilized per each photodiode, to produce STI area variations. Examples of layout and a pixel structure of two different pixels. 26

27. Measurements Results (1) An improvement of 45% in pixel FPN (from FPN of 0.29% to 0.16%) was achieved compared to the conventional ACS. An improvement of up to 19% in dark current among the different pixels was found. SNR of 15dB at illumination level as low as 4nW/mm² was measured. 27

28. Measurements Results (2) Image captured by the designed imagers First imager Second imager 28

29. (Interim) Summary FPN can be improved (modified ACS technique proven effective). Reset noise can be lower (modified AR technique proven effective). Some Dark current reduction – possible (changes to the active region pushed out the STI, and showed up to 19% in dark current between the best and the worst pixel designs). 29

30. Optical Filter – First type - Results First filter (Sudan II Blue Lysochrome dye ) has a rejection of -26 dB at excitation light of 340nm and -3 dB transmission (~50%) of emission light at 450nm (Figure a) Imager with filter - improvement of 17 times is achieved (Figure b) (a) (b)

31. First Fluorescence System Measurements • 2µm-diameter polystyrene microbeads were used • Fluorescence microbeads were placed on the emission filter in clusters and exposed to UV light with the maximum at 350nm • Image of the microbeads from (a) chip micrograph, and (b) sensor array after contrast adjustment (b) (a) 31/26

32. Future Research • Sensor improvement - Widening the dynamic range both for high and low light levels is possible – our current research aim • Optical filtering improvement - Necessary for the our specific Bio-Medical application (neural growth monitoring via fluorescence) and others