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Beam Electron Induced Deposition of Platinum Contacts Daniel Chang, Matthew Ervin, John Barry, Barbara Nichols, John Melngailis, Alma Wickenden Nanoscale Material Integration The integration of non-conventional materials such as polymer fibers into integrated circuits of the future could greatly improve performance and functionality. Electron beam induced deposition (EBID) is being investigated as an approach for achieving such integration. Accomplishment 1: Aura Mechanism Below: Monte Carlo simulations of electron scattering suggest aura sizes should differ in different substrates. Energy dispersive x-ray analysis reveals trend of decreasing Phosphorous content following anneal: Process Theory and Implementation Precursor Flux Electron Beam Volatile By-Products Deposit Substrate Absorbed Molecules Hypothesis tested by comparing theoretical vs. experimental aura diameter ratios on SiO2 and GaAs. Theoretical ratios were derived from substrate stopping powers (SPs), which are used as proxies for aura diameters. Results suggest annealing expels P from Pt deposits, thus raising density and possibly improving contact quality. Challenge 3: Integrating Carbon Nanotube Incorporating a CNT onto a circuit defined by two Au contacts would strongly demonstrate EBID s integrative capabilities. A precursor gas is directed onto the substrate surface. Interaction between the electron beam, substrate, and absorbed precursor molecules deposits metal. EBID does not damage substrate or implant it with ions. Accomplishment 3: Integrative Capabilities A carbon nanotube was transplanted onto two Au EBID contacts. provided mechanical and electrical Pt contacts. Novel Precursor Gas Organic (carbon-containing) precursors deposit large amounts of carbon which degrades contact quality. A novel inorganic precursor, Pt(PF3)4, minimizes carbon contamination in deposits for resistivities of ~3 times pure Pt. Experimental ratios match theoretical SP trend, suggesting secondary emission is the aura formation mechanism. Possible solutions: low beam energies and thin substrates. Challenges and Accomplishments Challenge 1: Aura Formation Undesired auras form around EBID-formed Pt deposits. Challenge 2: Effects of Annealing Previous experiments indicated that annealing contacts may improve metal quality. The cause of improvement is tested here on Pt deposits made with EBID. Above Right: CNT breaks following resistance measurements, indicating successful passing of current through circuit. 100 C anneal improved circuit resistance from ~520 Kohm to ~290 Kohm. This confirms EBID s integrative capability as well the benefits of low-temperature annealing on Pt contacts. Accomplishment 2: Anneal Effects Analyzed Conclusion EBID, used in conjunction with Pt(PF3)4, has shown much potential as a means of integrating nanoscale materials into circuits. By understanding the aura mechanism and the effects of annealing, contacts may further be improved to provide greater deposition precision and contact quality. This allows for a reliable, high-quality process of device integration. ~ 16% reduction in deposit height following 100o C anneal. Hypothesis: secondary emission of electrons causes auras.
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Maryland >> ECE >> 2006 (Fall, 2008)
...
Maryland >> ECE >> 2006 (Fall, 2008)
Integration of Functional Nano-Technology Materials on a Single Chip Ratanak Heng, Dr. Stephen Kilpatrick, Dr. Alma Wickenden, Dr. RD Vispute, Dr. Shiva Hullavarad, Dr. T. Venkatesan Minimizing Size, Maximizing Functionality Thin Film Structures Z...
Maryland >> ECE >> 2006 (Fall, 2008)
Introduction and Overview Motivation and Objective The purpose of this project is to study novel carbon nanotube-embedded chemical sensors that can detect environmentally toxic microscopic agents. Carbon nanotubes (CNTs) are rolled sheets of carbon...
Maryland >> ECE >> 2006 (Fall, 2008)
Detection of Humans Carrying Concealed Objects Jeremy Webb, Yang Ran, and Dr. Rama Chellappa Problem: Detect concealed objects on the ankle and around the midsection by looking at gait changes using computer vision techniques Detect deviations to the...
Maryland >> ECE >> 2006 (Fall, 2008)
SPEAKER RECOGNITION AND VOICE MINING Olakunle Ogunsuyi, Dr. Carol Y. Espy-Wilson, Sandeep Manocha and Srikanth Vishnubhotla INTRODUCTION This work investigated issues related to speaker recognition, with emphasis on speech detection in multi-speaker...
Maryland >> ECE >> 2006 (Fall, 2008)
Recognition of Nasalized & Non-nasalized Vowels Bilal A. Raja, Carol Y. Espy-Wilson, and Tarun Pruthi Speech Communication Lab, ECE Dept and Inst. Of Systems Research, University of Maryland, College Park, MD 20742 Introduction The presence of nasal...
Maryland >> ECE >> 2006 (Fall, 2008)
Nonlinear MZI as a DPSK Regenerator Chad Ropp and Dr. Julius Goldhar Transmitter Receiver Introduction Fiber optic technology is fundamental for modern high speed long distance communication. Up until now commercial communication systems utilized si...
Maryland >> CSCAMM >> 08 (Fall, 2008)
A Dielectric Invisibility Carpet Jensen Li Prof. Xiang Zhangs Research Group Nanoscale Science and Engineering Center (NSEC) University of California at Berkeley, USA Theory developed with Sir John Pendry, Imperial College London, UK CLK08 - 09/22/2...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #1 Question 1 Why does redistribution cause e ciency losses? Why might society choose to redistribute resources from one group to another when doing so...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #2 Question 1 Andrew, Beth and Cathy live in Lindhville. Andrew demand for bike paths, a public good, is given by s Q = 12 2P . Beth demand is Q = 18 P...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #3 Question 1 Seven in ten students attending publicly funded universities leave the state after graduation, indicating that a very larger fraction of ...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #4 Question 1 For each of the Social Security reforms listed below, brie discuss the pros and cons of the reform, paying y attention in particular to e...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #5 Question 1 Suppose a nation has a tax rate of 10% on the rst $20,000 of taxable income, then 25% on the next $30,000, then 50% on all taxable income...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #6 Question 1 For which group of workers is the substitution eect associated with a tax increase more likely to outweigh the income eect: primary earne...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Empirical Research Paper The due date for this assignment is May 10th. This project counts for 15% of your course grade. Point of the Empirical Paper I have ass...
Maryland >> ECON >> 422 (Fall, 2008)
Econ 422, Spring 2007 Problem Set #1 Question 1 Prove that V (a + bX) = b2 V (X), where X is a random variable. Question 2 Show that if X and Y are independent random variables, then cov(X; Y ) = 0 Question 3 If fx1 ; x2 ; :x25 g is a random sample...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #2 Question 1 Let kids denote the number of children ever born to a woman, and let educ denote years of education for the woman. A simple model relat...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #3 Question 1 Suppose the following equation is estimated using data on 4,137 college students colgpa colgpa hsperc sat = = = = 1:392 0:0135hsperc + ...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #4 Question 1 Which of the following can cause the usual OLS t-statistics to be invalid (that is, not to have t-distributions under Ho )? (i) Heteros...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #5 Question 1 The following equation was estimated, where sleep is the total minutes per week spent sleeping at night, totwrk is total weekly minutes...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Quiz #1 (30) Question 1 Let Y1 ; Y2 ; Y3 be independent, identically distributed random variables from a population with mean variance 2 . Let Y = 1 (Y1 + Y2 + Y...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Quiz #2 (20) Question 1 (10) (10) 1. Write the expression for the variance of c . 1 2. How in practice would you estimate the variance of c when you can directl...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Quiz #3 (20) Question 1 For each of the following points, determine whether or not they will cause the usual OLS t-statistics to be invalid. Explain why you came...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Quiz #4 (25) Question 1 Suppose that you wished to estimate the eect of education on earnings (ie the returns to education) using data for a cross-section of wor...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Computer Problem Set #1: Getting familiar with STATA The due date for this assignment is March 8th. Instructions. STATA commands are included within the descripti...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Computer Problem Set #2: Hypothesis Testing and Comparison of Models The due date for this assignment is April 24th. Instructions. STATA commands are included wit...
Maryland >> ECON >> 422 (Fall, 2008)
-log: C:\\Documents and Settings\\Jessica Hennessey\\My Documents\\Jess\\Teach\\422 Spring 07\\Computer\\PS2.txt log type: text opened on: 8 Apr 2007, 14:14:25 . set mem 100m (102400k) . set matsize 800 . set more off . use \"data\\malaria\" . describe Contains...
Maryland >> ECON >> 422 (Fall, 2008)
ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Midterm Exam (8) Question 1: Variance (6) (a) Prove that V (a + bX) = b2 V (X), where X is a random variable. (2) (b) Explain in words why a does not factor into...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #1 Question 1 Why does redistribution cause e ciency losses? Why might society choose to redistribute resources from one group to another when doing ...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #2 Question 1 Can an activity generate both positive and negative externalities at the same time? Explain your answer. Question 2 Suppose that deman...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #3 Question 1 Seven in ten students attending publicly funded universities leave the state after graduation, indicating that a very larger fraction o...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #4 Question 1 In his research, the author of your textbook found evidence that the elasticity of labor supply with respect to disability insurance be...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #5 Question 1 Suppose a nation has a tax rate of 10% on the rst $20,000 of taxable income, then 25% on the next $30,000, then 50% on all taxable inco...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Midterm Exam (10) Question 1 Does taxing the wealthy to give benets to the poor increase social welfare? Explain. (20) Question 2 Suppose that the demand for a...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Final Exam (20) Question 1: Tax Incidence Let say that College Park decided that it would impose a tax on every cup of coee that Starbucks sold. s Assume that th...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Spring 2009 Department of Economics, University of Maryland Jessica Hennessey Problem Set #1 Question 1 Why does redistribution cause e ciency losses? Why might society choose to redistribute resources from one group to another when doing ...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #1 Question 1 Why does redistribution cause e ciency losses? Why might society choose to redistribute resources from one group to another when doing so...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #2 Question 1 Your utility function is U = ln(2C) where C is the amount of consumption you have in any given period. Your income is $40,000 per year an...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #3 Question 1 Matt is an employee at a large university, where he pays $120 a month in insurance premiums and his employer pays $300 per month. He nds ...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #4 Question 1 Suppose a nation has a tax rate of 10% on the rst $20,000 of taxable income, then 25% on the next $30,000, then 50% on all taxable income...
Maryland >> ECON >> 454 (Fall, 2008)
ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #5 Question 1 Andrew, Beth and Cathy live in Lindhville. Andrew demand for bike paths, a public good, is given by s Q = 12 2P . Beth demand is Q = 18 P...
Maryland >> ECON >> 454 (Fall, 2008)
Lecture 1 Introduction to Public Finance Why study Public Finance? Understand the role of the government in the economy Three Perspectives Understand why and when governments get involved Understand why and what services are provided Unders...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 1 Introduction to Econometrics What is Econometrics? From Tintner, A Definition of Econometrics, Econometrica (1953) An econometrician is An economist, who needs to utilize correct economic theory A mathematician, who needs to use appropria...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 2 Review of Probability and Statistics Random Variables Probability Distributions Discrete Variable Continuous Variable x Important distinction of mean: population versus sample What is a mean? Population mean: weighted average of poss...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 3 February 1, 2007 Review of Probability and Statistics Quick review of last class Sample versus Population Random variables and sampling distribution Known parameters (,2) Unbiased estimator E ( ) = Consistency Definition: An estimator...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 3 February 1, 2007 Review of Probability and Statistics Quick review of last class Sample versus Population Random variables and sampling distribution Known parameters (,2) Unbiased estimator E ( ) = Consistency Definition: ...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 4 February 6, 2007 Review of Probability and Statistics Quick review of last class Consistency Normal Distribution Any linear combination of normally distributed variables yields a normally distributed variable Confidence Interval It is a r...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 4 February 6, 2007 Review of Probability and Statistics Quick review of last class Consistency Normal Distribution Any linear combination of normally distributed variables yields a normally distributed variable It is a random interval [...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 5 February 8, 2007 Review of Probability and Statistics 2 random variables: Joint Distribution Joint probability density function Marginal probability density function Independence Why important? Definition of independence: Useful conclus...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 5 February 8, 2007 Review of Probability and Statistics 2 random variables: Joint Distribution Joint probability density function Marginal probability density function Independence Why important? Definition of independence: Useful...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 6 February 13, 2007 Simple Linear Regression Lets think about our problem Simple equation y = 0 + 1x + u Fitted line Residual Concept of Regression Function We started with the inherent relationship: y = 0 + 1x + u The expected valu...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 6 February 13, 2007 Simple Linear Regression Lets think about our problem Simple equation y = 0 + 1x + u Fitted line Residual Concept of Regression Function We started with the inherent relationship: y = 0 + 1x + u The exp...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 7 February 22, 2007 Simple Linear Regression What do the OLS Estimators tell us? Sample covariance between x and y Sample variance of x The slope coefficient is of primary interest, as: y = 0 + 1x dy = 1 dx Mathpnl.dta When will th...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 7 February 22, 2007 Simple Linear Regression What do the OLS Estimators tell us? Sample covariance between x and y Sample variance of x The slope coefficient is of primary interest, as: y = 0 + 1x dy = 1 dx Mathpnl.dta When will th...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 8 February 27, 2007 Simple Linear Regression Quick review of last class How to interpret OLS coefficients Goodness of Fit: R-Squared Assumptions of OLS: SLR1-SLR4 Use these four assumptions to prove unbiasedness of OLS Assumption concerning...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 8 February 27, 2007 Simple Linear Regression Quick review of last class How to interpret OLS coefficients of Fit: R-Squared of OLS: SLR1-SLR4 Goodness Assumptions Use these four assumptions to prove unbiasedness of OLS Assumption co...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 9 March 1, 2007 Multiple Linear Regression Quick review of last class SLR5: Homoskedasticity Allows us to say OLS is BLUE Units of Measurement Functional form: how to interpret Working with more than one independent variable We want to be ...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 9 March 1, 2007 Multiple Linear Regression Quick review of last class SLR5: Homoskedasticity Allows us to say OLS is BLUE Units of Measurement form: how to interpret Functional Working with more than one independent variable We w...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 10 March 6, 2007 Multiple Linear Regression Estimating the Variance Our variance formula is 2 Var ( j ) = SST j (1 R 2 ) j We need an unbiased estimate of 2 2 = Var (u ) = E (u 2 ) = ui2 n Want to replace error with residual, but need...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 10 March 6, 2007 Multiple Linear Regression Estimating the Variance Our variance formula is 2 Var ( j ) = SST j (1 R 2 ) j We need an unbiased estimate of 2 2 = Var (u ) = E (u 2 ) = ui2 n Want to replace error with residual, b...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 11 March 8, 2007 Multiple Linear Regression Think Conceptually Variation in Y that can be explained by X Y X X Think Conceptually The larger the blue area, the more information is used to form the estimate; the more precise we can get it ...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 11 March 8, 2007 Multiple Linear Regression Think Conceptually Variation in Y that can be explained by X Y X X Think Conceptually The larger the blue area, the more information is used to form the estimate; the more precise we can get it ...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 12 March 13, 2007 Review for Midterm Inference Midterm Review Review of Probability and Statistics Wooldridge Appendix B & C Problem Set 1 Quiz 1 Simple Linear Regression Wooldridge Chapter 2 Problem Set 2 Quiz 2 Multiple Linear Regression...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 12 March 13, 2007 Review for Midterm Inference Midterm Review Review of Probability and Statistics Wooldridge Appendix B & C Problem Set 1 Quiz 1 Simple Linear Regression Wooldridge Chapter 2 Problem Set 2 Quiz 2 Multiple L...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 13 March 27, 2007 Inference Review from last class MLR6: The population error u is independent of the explanatory variables x1, x2, xk and is normally distributed with zero mean and variance 2: u~N(0, 2). CLM Assumptions: j ~ N ( j , va...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 13 March 27, 2007 Inference Review from last class MLR6: The population error u is independent of the explanatory variables x1, x2, xk and is normally distributed with zero mean and variance 2: u~N(0, 2). CLM Assumptions: j ~ N ( j ...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 14 March 29, 2007 Inference Review from last class All about testing one restriction H0 : j = c Everything uses the same test statistic j j se( j ) ~ t n k 1 Difference is between two and one sided hypotheses and how you look up the c...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 14 March 29, 2007 Inference Review from last class All about testing one restriction H0 : j = c Everything uses the same test statistic j j j ~ t n k 1 se( ) Difference is between two and one sided hypotheses and how you look up...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 15 April 3, 2007 Further Issues Review from last class F-test Testing null hypothesis which involves restrictions on multiple coefficients Compare two different models: the unrestricted versus the restricted model F-statistic F= ( SSRR SS...
Maryland >> ECON >> 422 (Fall, 2008)
Lecture 15 April 3, 2007 Further Issues Review from last class F-test Testing null hypothesis which involves restrictions on multiple coefficients Compare two different models: the unrestricted versus the restricted model F-statistic ( SSRR ...
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