Wednesday, November 23, 2016 — 9:30 AM EST

Candidate

Mostafa Azizi

Title

CMOS-MEMS Scanning Microwave Microscopy

Supervisor

Raafat Mansour

Abstract

This thesis presents the design, fabrication and experimental validation of an integrated dual-mode scanning microwave microscopy (SMM)/Atomic Force Microscopy (AFM) system that does not require the use of a conventional laser-based AFM or external scanners. Microfabricated SMM probes are collocated with strain-based piezoresistive AFM probes in a CMOS-MEMS process, and are actuated by integrated electrothermal scanners. Integration of AFM enables dual-mode imaging (topography and electrical properties); it also enables control over tip-sample distance, which is crucial for accurate SMM imaging. The SMM (also known as Scanning Near-field Microwave Microscope and Scanning Evanescent Microwave Microscope) is the most well-known type of Scanning Probe Microscopes (SPM) that can quantify local dielectric and conductivity of materials. It has emerged as the most promising means for the fast, non-contact, and non-destructive study of materials and semiconductor devices.

The CMOS-MEMS SMM devices are fabricated by using a standard foundry CMOS process, followed by an in-house mask-less post-processing technique to release them. Single-chip SMM/AFM devices with integrated 1-D and 3-D actuation are introduced. The CMOS-MEMS fabrication process allows external bulky scanners to be replaced with integrated MEMS actuators that are small and immune to vibration and drift. In this work, electrothermal MEMS actuators are utilized to scan the tip over the sample in 3 degrees of freedom, over a 13 µm x 13 µm x 10 µm scan range in the x, y, and z directions, respectively. Furthermore, the availability of polysilicon layers on the CMOS processes allows for on-chip integrated piezoresistive position sensing that obviates the need for the laser system. Vertical tip-sample distance control of a few nanometers is achieved with the integrated piezoresistive position sensors. These devices are used to modulate the tip-sample separation to underlying samples with a periodic signal, improving immunity to long-term system drifts.

To improve the sensitivity of the CMOS-MEMS SMM, different types of matching networks for SMMs are thoroughly analyzed and closed form formulas are presented for each type. Based on the analysis, the stub matching method is selected to match the high tip-to-sample impedance to the 50 ohm characteristic impedance of the system. After that, with the help of lumped models and EM simulations, different sections of the CMOS-MEMS SMM system are analyzed and suggestions for selecting the best micro-transmission line and bonding-pad transmission lines are given. A measurement circuit for SMM is then presented and explained, showing how this measurement system can improve the output-signal-to-noise ratio and hence the sensitivity of microwave imaging. Calculations for the entire SMM system indicate that sub-attofarad tip-sample impedance can be measured. It is noteworthy that most of the analyses and suggestions given in this thesis can be applied to any Scanning Microwave Microscopes or, even more generally, to any microwave system that needs to sense a small signal.

Finally, the measurement results for the fabricated CMOS-MEMS SMM are presented to verify the proposed methods. Several samples with sub-micron and nanometer feature sizes are imaged. A special test sample with no topography but with buried dielectric materials in grid and stripes is also designed and measured.

Location 
EIT - Centre for Environmental and Information Technology
Room 3142
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

S M T W T F S
28
29
30
31
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
  1. 2019 (194)
    1. December (1)
    2. November (1)
    3. October (1)
    4. September (1)
    5. August (26)
    6. July (40)
    7. June (24)
    8. May (23)
    9. April (35)
    10. March (25)
    11. February (9)
    12. January (10)
  2. 2018 (150)
    1. December (13)
    2. November (25)
    3. October (12)
    4. September (13)
    5. August (7)
    6. July (23)
    7. June (9)
    8. May (6)
    9. April (9)
    10. March (16)
    11. February (10)
    12. January (7)
  3. 2017 (212)
  4. 2016 (242)
  5. 2015 (242)
  6. 2014 (268)
  7. 2013 (192)
  8. 2012 (31)