CMOS APS for X-ray, Photon and Astronomy based applications Andy Blue

Outline I will attempt to outline what are seen to be the main developments and topics of interests in CMOS APS devices for photon, X-ray and astronomy applications I will do this by Showing the progress made since ~2005 Where we are now What’s changed (and why) Disclaimer: this will be more ideas based than detailed engineering explanations 4T, 5T etc. models are available.. Also will try to cover as much as possible in allocated time

MI 3 = Multi-dimensional Integrated Intelligent Imaging Main goals were: To significantly extend the effective spectral response of APS’s from high- energy gammas and ionising particles to the infra-red (including the increasingly important soft X-ray/EUV regions) To develop on-chip "intelligence" down to the pixel level, through adaptive signal processing/pattern recognition, to extent the limits of detectability and applicability, and mitigate the problems of data overload. To provide a continuing responsive export core to meet the future imaging challenge within the UK science base; to ensure through building upon existing links with industry the future availability and exploitation of APS devices and systems. M-I 3 was supported by an RC-UK Basic Technology Programme 4-year £4.4 (€6.5)M grant. 2005

University of Sheffield STFC RAL (CMOS Imaging) University of Liverpool (Environmental Gene Regulation & Semiconductor Centre) University of Glasgow (PPE) University College London (Radiation Physics) Brunel University (Imaging for Space and Terrestrial Applications) University of York (Electron Optics, Applied Electromagnetics and Electron Optics) Cambridge (MRC Laboratory for Molecular Biology) University of Surrey (Centre for Vision, Speech and Signal Processing, ) Institute of Cancer Research N Allinson, P Allport, T Anaxagoras, J Aveyard, C Arvanitis, R Bates, A Blue, S Bohndiek, J Cabello, L Chen, S Chen, A Clark, C Clayton, E Cook, A Cossins, J Crooks, M El-Gomati, PM Evans, W Faruqi, M French, J Gow, T Greenshaw, T Greig, EJ Harris, R Henderson, A Holland, G Jeyasundra, D Karadaglic, M Key-Charriere, T Konstantinidis, HX Liang, S Maini, G McMullen, A Olivo, V O'Shea, J Osmond, RJ Ott, M Prydderch, L Qiang, G Riley, G Royle, G Segneri, R Speller, JRN Symonds-Tayler, R Turchetta, C Venanzi, K Wells, H Zin Collaborators

CMOS APS in 2004 CCD’s still dominated the market Low noise CMOS APS were cheap – Most commonly used in webcams and cheap camera applications – They made up a very small %age of high end camera devices Few foundries were open to R+D Hard(er) to work with compared to present day No access to layout stacks No idea where epi was (backside etching was ‘non trivial’) Inaccurate CMOS simulation processes No real desire to go to thicker epi-layers Was told by a designer the only reason companies wanted low noise APS was so people could take pictures in nightclubs with their camera phones. High Rate readout was an issue Small pixels fine Reading 10k small pixels was not (at decent frame rate)

2015 The latest IC Insights report talks about CMOS sensor market status: IC Insights report CMOS image sensors were [one of the] fastest growing product category in 2012 with sales rising 22% to a new record-high $7.1 billion previous peak of $5.8 billion set in Since the 2009 downturn year, CMOS image sensor sales have climbed 85% due to the strong growth of embedded cameras used in smartphones and portable computers (including tablets) and the expansion of digital imaging into more systems applications CMOS designs are now grabbing large chunks of marketshare from CCD image sensors, which are forecast to see revenues decline by a CAGR of 2.4% between 2012 and Sales of CMOS imaging devices are projected to grow by a CAGR of about 12.0% in the forecast period and account for 85% of the total image sensor market versus 15% for CCDs in This compares to a 60/40 split in 2009."

Applications in Medicine The specification for detectors to fulfil numerous imaging tasks have not changed since 2005 Large area coverage for full field radiography (mammography and chest imaging) 50um pixel pitch or less for high spatial resolution Low noise and good QE to allow single X-ray detection High Dynamic Range (12 bits) No image lag and ghosting High frame rate for image acquisitions with sub-second timing resolution Good spectral matching with high light yield CsI:Tl phosphors Radiation hardness (particular for radiation therapy guidance and for prolonged life span of diagnostic sensors)

LAS – Large Area Sensor (8” wafer) 40µm x 40µm Pixel 1350 x 1350 Pixels 54mm x 54mm Sensing Area Stitched process (next slide) 10 Analogue outputs 20 Frames/Second Seamless array Multiple resets for high dynamic range Large Area Coverage

Optical reticle divided into 4 main areas for each chip Sensor is constructed by repeating the blocks N times to create larger device A BD C Stitching 1

A A BD C C ‘Stitching’ B D AAAAAAAA BB BBB CCCC C D D D Top sections contain pixel reset control circuits Bottom sections contain column addressing and analogue readout circuits 2 outputs per section Left Edge contains row addressing and reset control circuits Stitching 2

Why <50um? Reducing pixels size increases spatial frequency Reducing gap between scintillator and DUT increases spatial frequency

Linearity and QE 11 Epi-layer Differences in Stacks 550nm = Emission wavelength of CSi:Tl photon

Gain of CMOS APS 200e/DN indicates ability to detect single X-rays (20KeV)

X-ray Diffraction Imaging Increasing integration time Example application: X-Ray diffraction of breast issue samples Large area required Large area sensor Multiple integration time Combined transmission and diffraction image Characterization and Testing of LAS: A Prototype 'Large Area Sensor' With Performance Characteristics Suitable for Medical Imaging Applications. SE. Bohndiek,, A. Blue et al. IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 56 (5)

Without Multiple Regions of Reset Image of a laser point

With Multiple Regions of Reset Image of a laser point

Where are we today? ‘Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging’ M Esposito et al. Phys. Med. Biol.59 (2014) 3533–3554

UV applications Why UV? Multitude of applications Temperature of arc welds Tuning of jet engine plume Circular dichroism measurements UV light deposits it’s energy in a very short range of silicon Won’t pass though bulk SI or electronics to reach epi-layer However APS can be post processed Back substrate is removed (plasma/laser) Opening in the passivation of the electronics (plasma etching)

Backthinned v Regular QE Improved in the low visible and UV “bump” at 230nm is actually beginning of absorption of UV in air Optical and electrical characterization of a back-thinned CMOS active pixel sensor. A Blue et al NIM A Volume 604, Issues 1–2, (2009_ # Pixels

Andrew Blue PSD9 14/9/11 19 Experiment performed at Diamond Light Source, Beamline I06. A permalloy sample was used to create a diffraction pattern Permalloy is a Nickel-Iron alloy, used here as a representative test sample. Soft X-rays (700 eV) diffracted. Sensor was back-illuminated and kept in a vacuum. CCD kept at -55°C, Vanilla cooled from 20°C to -20°C. Detector Beamline Permalloy Sample Diffraction Experiment Soft X-rays detection

Andrew Blue PSD9 14/9/ s Integration Time Low Noise Mode, -55°C Dashed line is where the line profile is taken from. Solid square indicates the area the vanilla sensor covered. 300s integration time shows some blooming in saturated pixels. Ratio of peak height to inter-peak average give a Peak-to-Trough value. CCD Diffraction Pattern

Andrew Blue PSD9 14/9/11 21 Vanilla CMOS Diffraction Digital Mode, -10°C 0.05s Integration Time Longest integration time shows no blooming when saturated. Shortest integration time can still identify all peaks. Relative peak heights the same regardless of frame rate UV applications APS Diffraction Pattern

Andrew Blue PSD9 14/9/11 22 Signal to Noise ratio calculated based on the charge collected from an unsaturated spot. Signal to Noise ratio increases linearly with integration time Princeton CCD maintained at a temperature of -55°C. S/N ratios calculated then averaged for different modes. Vanilla CMOS APS S/N calculated at -10°C in Digital mode. Signal to Noise Active Pixel Sensors for Direct Detection of Soft X-rays. A Blue et al Journal of Instrumentation 6: 12. (2011)

Where are we today? Samsung introduces its new 28 megapixel (MP) APS-C* CMOS image sensor for digital cameras, which offers superior light absorption thanks to the back-side illuminated (BSI) pixel technology and 65- nanometer (nm) low-power copper process. Samsung Launches Industry’s First 28-Megapixel APS-C CMOS Image Sensor for Digital Cameras Utilizes advanced back-side illuminated (BSI) pixel technology and 65- nanometer (nm) copper process technology to offer outstanding image quality and energy efficiency What came from the UV R&D over the last 10 years soon transformed into BSI - Backside illumination For conventional CMOS imagers, we desire a smaller pixel size ~2.2um is smallest photochemical chain in conventional film Smaller pixel size Increase resolution Reduced FWC (Full well capacity) Increased using Back Side Illumination Sep 2014

Space Applications CMOS image sensors are playing a growing role in space applications due to the inherent advantages offered by CMOS technology. CMOS APS feature low power consumption ~ 10’s of mW compared ~ 100’s of mW for a CCD with an equivalent format Ability to read out regions of interest (sub windows) Ideal for user in star trackers Desire to readout multiple windows to track a number of objects 520x520 – 4fps 200x200 – 28fps50x50 – 432fps

Space Applications “Cypress also announced commercial availability of the HAS2 image sensor, the latest development in the Cypress STAR family of radiation-tolerant image sensors. “ The device has an array of 1024 x 1024 active pixels (18 µm) supports on-chip Non-Destructive Readout multiple windowing The prime sensor selected for JANUS camera system is a CIS115 Developed by e2v technologies CMOS image sensor with 4 pixel design with 7 μ m pitch Image area is divided into 4 section, each with its own analogue output, capable of a readout rate of up to 10 MPixels-1 Thinned to approximately 9 μ m 2014 Soman, M. et al ‘Non-linear responsivity characterisation of a CMOS Active Pixel Sensor for high resolution imaging of the Jovian system. Journal ofI nstrumentation, 10(2), article no. C02012

Summary CCD’s v CMOS APS market has changed significantly 85% of the total image sensor market ( by 2017) More foundries share more information We can simulate CMOS APS to a better level We can get thicker epi-layers Back side illumination is an industry standard IPhone etc. Issues Need smart ideas on high density (fast) readout Data sparsification Ideas on ‘On the fly’ image processing (FPGAs ‘Upstream’) My experience of MI3 was that an increase in the KE between the application users and the engineers/physicists made a huge difference to our productivity

Backup

Photon to Voltage conversion done within pixel Integrated electronics in circuit to suit applications (eg discriminator, flags) Low mass, low power cameras. Smaller pixel size. Shorter optics / smaller instrument. Charge sensed inside pixel... No charge transfer. Greater radiation tolerance. Active Pixel Sensors

Startracker – Test Device OPIC - On Pixel Intelligent CMOS HDR – High Dynamic Range Vanilla – ROI, Flushed Reset, A/D readout LAS – Large Area Sensor eLeNa - Low Noise Sensor MI3 Sensors Mi3 sensors