Zhuo Li PhD student, Dept. of ECE, USU. zhuo.li@aggiemail.usu.edu

1. Paper review:Fractional Order Plasma Position Control of the STOR-1M TokamakOutlook of FOC in Plasma Etching:Challenges and Opportunities Zhuo Li PhD student, Dept. of ECE, USU. zhuo.li@aggiemail.usu.edu

2. References • [1]. ShayokMukhopadhyay, YangQuanChen, Ajay Singh and Farrell Edwards, “Fractional Order Plasma Position Control of the STOR-1M Tokamak”, 48th IEEE CDC, Dec, 2009, pp.422-427. • [2]. Mukhopadhyay,Shayok, "Fractional Order Modeling and Control: Development of Analog Strategies for Plasma Position Control of the Stor-1M Tokamak" (2009). All Graduate Theses and Dissertations. Paper 460. [online available], http://digitalcommons.usu.edu/etd/460 • [3]. M. Emaami-Khonsari, “Modelling and Control of Plasma Position in the STOR-M Tokamak,” Ph.D., University of Saskatchewan, Saskatoon, April 1990. • [4]. Shane Lynn, “Virtual Metrology for Plasma Etch Processes”, PhD thesis, Electronic Engineering Department, National Univ. of Ireland. • [5] John V. Ringwood,Shane Lynn, Giorgio Bacelli, BeibeiMa, EmanueleRagnoli, and Sean McLoone, “Estimation and Control in Semiconductor Etch: Practice and Possibilities”, IEEE TRANS ON SEMICONDUCTOR MANUFACTURING, VOL. 23, NO. 1, FEBRUARY 2010 • [6]. Lynn Fuller, “Plasma Etching”, [lecture slides], Microelectronic Engineering, Rochester Institute of Technology. • [7]. Henri Janseny, Han Gardeniers, Meint de Boer, Miko Elwenspoek and Jan Fluitman, “A survey on the reactive ion etching of silicon in micro-technology”, J. Micromech. Microeng. 6 (1996), 14–28. • [8]. Lab modules, webpage, [online], http://matec.org/ps/library3/secure/modules/047/, [Mar.16.2012]

3. The Physical System • Tokamak: is a device using a magnetic field to confine a plasma in the shape of a “doughnut”. [Wikipedia.org] Fig3-1. The schematic of Tokamakas a transformer.[1] Fig3-2. The STOR-1M Tokamak in USU. [1]

4. Bank Current Waveforms • BT - Toroidalfield bank • IOh - Ohmic heating bank • IVe - Vertical equilibrium bank • IHc- Horizontal compensation bank • IVc - Vertical compensation bank Fig4. The bank current waveforms of STOR-1M. [1]

5. Measurement Mechanism • Plasma position estimation mechanism [3] • Four magnetic “pickup” coils measure the magnetic field produced by the toroidal plasma current. • By comparing the strengths of this measured magnetic field one can estimate the position of the current. • Proposed technique in the paper • Ratio of the voltages • E.g. Fig5-1. The Plasma position estimation system.[3] Fig5-2. Proposed position estimation approach. [3]

6. Plasma Position Modeling • The transfer function • First order plus delay model approximation

7. Fractional Order Controller • Controller parameters • Results and comparison (on emulator) Table: CONTROLLER PARAMETERS FOR THE STOR-1M TOKAMAK Fig8-1. Position control results. [3] Fig8-2. Position control results. [3]

8. Conclusion • FO-PI controller is better than the ZN-PID controller in terms of response time, control effort and steady state error.

9. Outlook-challenges • Plasma etching process in semiconductor manufacturing • Etching variables hard to measure • Real-time control hard to achieve • Measurement technology in the literature [5] • Virtual metrology [4] • Optical emission spectroscopy (OES) • Mass spectrometry • Plasma impedance monitoring • Etc. Fig9. OES. [4]

10. Plasma Etching - Intro • Etching outcome and profile • Isotropic (non-directional removal of material from a substrate) • Anisotropic (directional) Ideal etch Poor etch Fig10-2. One-run multi-step RIE process. Top left: after anisotropic etching the top Si of an SOI wafer. Top right: after etching the insulator and sidewall passivation. Middle left: during isotropic etching of the base Si. Middle right: after isotropic etching the base Si. Bottom: typical finished MEMS products. [7] Fig10-1. No process is ideal, some anisotropic plasma etches are close. [6]

11. The Plasma Etching Chamber Fig11-1: Typical parallel-plate RIE system. [*] Fig11-2. RIE Process Chamber. [8] Fig11-4. Physical etch process chamber. [8] Fig11-3: Typical RF sputtering system. [*] * MEMSnet®, https://www.memsnet.org/mems/beginner/etch.html

12. Controls in the Literature Fig12. Etch tool control possibilities with information flow. [4]

13. Controls in the Literature • Run-to-Run (R2R) Control [a],[b],[c]. • Predictive functional control [4]. • Neural network control • Etc. [a], M. Hankinson, T. Vincent, K.B. Irani, and P.P. Khargonekar. Integrated real-time and run-to-run control of etch depth in reactive ion etching. IEEE T. Semiconduct. M., 10(1):121-130, Feb. 1997. [b]. X.A. Wang and R.L. Mahajan. Articial neural network model-based run-to-run process controller. IEEE Trans. Components, Packaging, and Manufacturing Technology, Part C., 19(1):19-26, Jan. 1996. [c]. J.P. Card, M. Naimo, and W. Ziminsky. Run-to-run process control of a plasma etch process with neural network modelling. Qual. Reliab. Eng. Int., 14(4):247-260, 1998.

14. Outlook-Opportunities • Data Go fractional ?! Fig10. Endpoint mono-chromtoroutput over four preventative maintenance (PM) cycles. [4]

15. Outlook-Opportunities • Other efficient “learning machines” • RVM • Other fitting methods • TLS fitting for “data boxes” (not point) • Interval computation tools (IntLab) • Dynamic VM – R2R VM • Fractional Order ANN based VM • Neuronal dynamics is inherently “fractional order” • Fractional order iterative learning control • Cognitive process control Slide from Dr.Chen’s Lam Research Talk

16. Outlook-Opportunities • Dynamic Virtual Metrology in Semiconductor Manufacturing Slide from Dr.Chen’s Lam Research Talk http://bcam.berkeley.edu/research/new_researchframes.html

17. Thank you!Q&A