SOI based micromachining SOI-MUMPS
Based on SOI (Silicon-onInsulator) wafer
Device thickness ranges
from nanometers to 100s
microns
Structural material is
Single crystal Silicon
Better mechanical properties
Ready to use for many
applications: first sacrif
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Homework Assignment 4
1. 1 pt. Assume you are having problems with PR adhesion to your sample, what three things
could you do to improve PR adhesion (assume nothing was being done before)?
2. 3 pt. Draw the PR side profiles for the following three c
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Homework Assignment 5
1.
(6 pts) Assume a 500W RF plasma etcher (@ 13.56 MHz), VDC = 300 V, and the plasma
potential is measured to reach a maximum of 40.0 V. i) What is VP? ii) What is the
approximate time varying cathode voltage (in the form Vc(t)
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Homework Assignment 6
1.
(1 pt) If a silicon nitride coated wafer is 475 microns thick and has a 6.00 mm diameter
opening in the nitride layer on one side, what will be the size and shape of the membrane
formed on the other side?
2. (1 pt) Using a c
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Final Exam (due 23:55 pm on May 8)
1. True or False questions (1 point each, total 20)
1).
A NFPA health rating of 4 means that the chemical is designated as may be
harmfully if inhaled or absorbed.
2).
A dehydration bake is used to remove solvents
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Homework Assignment 1
1. (1 pts) (T/F) The scaling law provides good extrapolation of classical laws down to
nanometer regime.
False, nano regime is different (such as quantum effect)
2. (8 pts) Fill in all the blanks for Scaling:
Characteristic
Mas
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Homework Assignment 4
1. 1 pt. Assume you are having problems with PR adhesion to your sample, what three things
could you do to improve PR adhesion (assume nothing was being done before)?
1. Prime wafer by dehydration bake
2. Adhesion promoter
3. P
Name:
Homework Assignment 2
1. (3 pts) A cantilever beam is made from silicon. The size is 500 micron in length, 20
micron in width and 2 micron in thickness. If you use this cantilever to detect force, what
is the sensitivity? (Youngs modulus of silicon
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Homework Assignment 3
1. (2 pts) Search web for NFPA rating of Potassium Hydroxide Solution (30%). What is its
NFPA rating and what does it mean?
3-0-1, the mean can be find in the slides
2. 1pt. Is the NFPA rating for common chemicals different dep
9/7/16
Class 6: Markov Chains I
What is stochastic?
Random or probabilistic but with some
direction.
W.B.Langdon@cs.bham.ac.uk
ISE 560: Stochastic Models in IE
1
9/7/16
A stochastic process is a series of random
numerical observations over time.
Two Coord
10/24/16
Class 12: Exponential & Poisson Distributions
Exponential Distribution:
Time/interval between successive arrivals/ events
of interest is usually exponentially distributed
Examples:
Time to arrival of next customer
Time until failure of a semicond
8/29/16
ISE/OR 560: Stochastic Models in IE
Class 4 & 5: Combinations of RVs, Conditional
Probability & Conditional Expectation
Joint Distribution Functions: CDF, pmf, pdf
Covariance
Independence
Expectation for a function of a random
variables.
ISE/OR 56
9/21/16
Class 8: Markov Chains III
Markov Property says: Future is independent of past
given the present
The Markov Property becomes
PX n 1 j X n i, X n 1 in 1 , X 0 i0
PX n 1 j X n i
Let Pij = Pcfw_Xn+1 = j| Xn = i: the probability that the
process wil
11/30/16
Class 16: M/M/s Queues &
Exponential Queues in Series
j for j 0,1,2,.
j for j 1,2,.
j
1 0 0 j j 0 j 0 j 2,3,.
traffic intensity 0 1
0 1
j j 1
ISE/OR 560: Stochastic Models in IE
1
11/30/16
Assuming steady state has been reached, average
n
10/17/16
ISE/OR 560: Stochastic Models in IE
Class 11: MDPs II
1. What are the actions we can take? What constitutes an
action? Action Space A
As
sS
2. When can actions be selected? (Time and event)
Decision Epochs: T[0,)
3. What kind of information will
8/24/16
Value of Information
We introduced how to handle decision
problems using only the information that is
currently available about the problem
We presented concepts of the general theory for
making decisions that explicitly accounts for the
gains or
10/12/16
ISE/OR 560: Stochastic Models in IE
Class 10:
Markov Decision Processes (MDPs) I
Discrete Time Markov Chain (DTMC)
ISE/OR 560: Stochastic Models in IE
1
10/12/16
Markov Decision Process Overview
MDP Model Formulation
State Space
Action Space
Rewa
11/2/16
Class 14: Continuous Time Markov Processes
Future depends on current state of the process
rather than probabilistically restarting
Definition: A Markov process is a stochastic
process cfw_X(t), t T such that for all t1 < t2<
t3<tn+1 T,
PX t n 1 x
9/28/16
Class 9: Markov Chains IV
Markov Chain Passage Times
Absorbing State Markov Chains
ISE/OR 560: Stochastic Models in IE
1
9/28/16
First Passage Time: Nij
The number of time steps necessary to reach state j
for the first time, starting from state i
11/28/16
ISE/OR 560: Stochastic Models in IE
Class 15: Queueing I
Suppose we have a continuous-time stochastic
process cfw_X(t), t0 taking on values in the set
of nonnegative integers.
The process cfw_X(t), t0 is a continuous time
Markov chain if for all