ECE606: Solid State Devices Lecture 11 Interface States Recombination Carrier Transport

Size: px
Start display at page:

Download "ECE606: Solid State Devices Lecture 11 Interface States Recombination Carrier Transport"

Transcription

1 C606: Sold State eves Leture Iterfae States Reombato Carrer Trasport Gerhard Klmek Outle ) SRH formula adapted to terfae states ) Surfae reombato depleto rego 3) Coluso

2 Surfae Reombato Curret R For sgle level bulk traps. bulk p = ( + ) + ( p + p ) pn T N T = ( p ) p N ( + ) + ( p + p ) T For sgle level terfae trap at R ( s ps ) T = ps d ( + ) + ( p + p ) s s s s s R C = V R d 3 Case : Morty Carrer Reombato R ( ) ( + )( p + ) s0 s0 s0 ps0 = IT d = ps s0 ( + + ) + ( p + p + p ) s0 s0 s s0 s0 s s s0 ps0it d s p + + s ps ps s0 s s0 p d ps s0 IT = s ps ps + + s0 s s0 oor doped s0 + s0 p s0 + p s0 4

3 Cosder the eomator p = + + = + + N s ps s s ps s s0 s s0 s p N ( ) β e = + + ( F ) β e = + + e ( ) β ps ( F ) β s e ( ) β ps ( ) β F F e e s x x = + e + ae x β F s0 + s0 p s0 + p s0 5 Cosder the eomator ( ) β ( ) β e ps e = + + N N = + e + s ( ) β ps ( ) β F F s e F ' F ps At = = + + N N s ps At = F >, x = 0 = + + small At = ' <, = + small + = F s F F ' 6

4 Approxmate the eomator ( ) β ( ) β e ps e = + + N N s F ' F ' for F F otherwse F F ' 7 Itegrated Reombato C R = R = C ps s0 IT p d p + + s ps s V V s0 s s0 F ' F ps s0 p d F F ' 8

5 Surfae Reombato Veloty F F ps s0 IT R p d ' 0 = p = s p g ps IT F F s s0 Surfae reombato veloty 9 Outle ) Nature of terfae states ) SRH formula adapted to terfae states 3) Surfae reombato depleto rego 4) Coluso 0

6 Case : Reombato epleto ( s ps ) IT ( ) R = s ps = β e e + = d ( + ) + ( p + p ) sit s s s s s β IT ps ps e ( ) β e s ( ) β d + d s ~0 p s ~0 R = s IT V ( ) β C e s e ps ( ) β + d Case : Reombato epleto R = = C s IT V s IT ( ) β + e s e ps ( ) s ps e e ( ) ( ) β β d d β + + s ~0 = φ s IT + ps dx s x + 0 P s ~0 = π β s ps IT

7 R Why do doors/aeptors ot at as R-G Ceters? p d ps s0 = s ps ps + + s0 s s0 p N s ps 0 = 0 R A p d ps s0 = s ps ps + + s0 s s0 p N s ps 0 A = A 0 F F ' 3 Summary π R = s ps IT β ' R = p ps IT F F s Iterfae (depleto) Iterfae (morty) R = N p p T Bulk (morty) 4

8 C606: Sold State eves Leture Carrer Trasport Gerhard Klmek Outle ) Overvew ) rft Curret 3) Physs of Moblty 4) Hgh feld effets 5) Coluso RF: Advaed eve Fudmetals, Pages

9 Curret Flow Through Semodutors epeds o hemal omposto, rystal struture, temperature, dopg, et. V I I = G V = q v A Carrer esty veloty Quatum Mehas + qulbrum Statstal Mehas apsulated to oepts of effetve masses ad oupato fators (Ch. -4) Trasport wth satterg, o-equlbrum Statstal Mehas apsulated to drft-dffuso equato wth reombato-geerato (Ch. 5 & 6) 7 No-equlbrum Systems Chapter 5 Chapter 6 vs. I V

10 Summary of Trasport quatos + ( A ) = q p + N N = J r + g t q p = r + g t q J N N N J = qµ + q N N N J P P P = qpµ q p P P P V I 9 Outle ) Overvew ) rft Curret 3) Physs of Moblty 4) Hgh feld effets 5) Coluso 0

11 Meag of ffetve Mass m 0 ħ d + U ψ = ψ rys x + U ext x m0 dx m ħ d + U φ = φ ext x m0 dx rft by letr feld. J = qµ d( m υ) m υ = q dt τ t qτ τ υ( t) = e m x x x x

12 rft by letr feld. qτ υ ( t) = e m t τ x x x x J qτ = ( t, - ps) m µ = qµ (Theory vald oe t > - ps) υ tme frto υ ( ) υ 3 Outle ) Overvew ) rft Curret 3) Physs of Moblty 4) Hgh feld effets 5) Coluso 4

13 Moblty ad Physs of Satterg Tme x x x x µ = qτ m m 0 m Ferm s Golde rule π τ ψ ( x) U ( x) ψ ( x) dx ħ 5 Phoo ad Iozed Impurty Satterg Iozed mpurty T τ ~ N 3 m 0 Hgher temperature, more phoo satterg m τ ~ T 3 6

14 Multple Satterg vets Iozed mpurty Phoo satterg others. µ = µ + µ ph ph II µ phµ II µ = µ + µ µ µ phµ II m m ph µ µ = + µ + II µ 0 = µ m + + ( NI N0 ) α II m = τ τ τ τ II ph s m = µ qτ Matthesso Rule. 7 Model for Iozed mpurty Satterg µ + µ N N α 0, = µ,m + ( I 0, ) m µ,m 8

15 Temperature-depedet Moblty 3 ~ T µ τ 9 Outle ) Overvew ) rft Curret 3) Physs of Moblty 4) Hgh Feld ffets 5) Coluso 30

16 Moblty at Hgh Felds? υ x x x x qτ υ = µ µ + C N 0 N m N What auses veloty saturato at hgh felds? Where does all the moblty formula deve smulator ome from? 3 Veloty Saturato S/Ge = 0 J = J + J = 0 J = J J > J + J = > 3 J + J J J = J J J

17 Veloty Overshoot & Iter-valley Trasfer Larger m Smaller m What type of satterg would you eed for ter-valley trasfer? 33 opg depedet Resstvty J = ρj J = q( µ + µ p p) ρ = q( µ + µ p) = for -type qµ N = for p-type qµ N p V A p 34

18 Coluso ) Posso ad drft-dffuso equatos form a omplete sem-lassal trasport model that a expla wde varety of deve pheomea. ) rft urret results from respose of eletros/holes to eletr feld. The physs of moblty s omplex ad materal depedet. 3) Costay of low-feld moblty a be heked by expermets. 35

Lecture 8: Electrons and hole currents, IC Resistors. Announcements

Lecture 8: Electrons and hole currents, IC Resistors. Announcements EECS 15 Sprg 4, Leture 8 Leture 8: Eletros a hole urrets, IC Resstors EECS 15 Sprg 4, Leture 8 Aouemets The mterm s sheule for Marh 1, 6-8 pm, Sbley Autorum The thr homework s ue Weesay /11 1 EECS 15 Sprg

More information

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical ECE66: Sold State Devces Lecture 13 Solutos of the Cotuty Eqs. Aalytcal & Numercal Gerhard Klmeck gekco@purdue.edu Outle Aalytcal Solutos to the Cotuty Equatos 1) Example problems ) Summary Numercal Solutos

More information

Space charge. Lecture 8 09/11/2011. p-n junction with gradient. p-n junction with gradient. V. p-n junction. Space charge

Space charge. Lecture 8 09/11/2011. p-n junction with gradient. p-n junction with gradient. V. p-n junction. Space charge ecture 8 09/11/011 Sace charge. - jucto Sace charge th a gradet Out of equlbrum Sace charge -tye ad -tye regos Usually N >>N A thus q N x = N A /(N +N A x = N /(N +N A A ad x = The sace charge exteds towards

More information

Solid State Device Fundamentals

Solid State Device Fundamentals Sold State Devce Fudametals 9 polar jucto trasstor Sold State Devce Fudametals 9. polar Jucto Trasstor NS 345 Lecture ourse by Alexader M. Zatsev alexader.zatsev@cs.cuy.edu Tel: 718 98 81 4N101b Departmet

More information

EE105 - Fall 2006 Microelectronic Devices and Circuits. Your EECS105 Week

EE105 - Fall 2006 Microelectronic Devices and Circuits. Your EECS105 Week EE15 - Fall 6 Mcroelectroc Devces a Crcuts Prof. Ja M. Rabaey (ja@eecs) Lecture : Semcouctor Bascs Your EECS15 Week Mo Tu We Th Fr 9am 1am Lab 353 Cory Lab 353 Cory Lab 353 Cory 11am Dscusso 93 Cory 1pm

More information

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013 ECE 595, Secto 0 Numercal Smulatos Lecture 9: FEM for Electroc Trasport Prof. Peter Bermel February, 03 Outle Recap from Wedesday Physcs-based devce modelg Electroc trasport theory FEM electroc trasport

More information

UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES. Midterm I

UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES. Midterm I UNIVERSITY OF CALIFORNIA, BERKELEY EPARTMENT OF ELECTRICAL ENGINEERING AN COMPUTER SCIENCES EECS 130 Professor Chemg Hu Fall 009 Mdterm I Name: Closed book. Oe sheet of otes s allowed. There are 8 pages

More information

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon EE105 - Srg 007 Mcroelectroc Devces ad Crcuts Perodc Table of Elemets Lecture Semcoductor Bascs Electroc Proertes of Slco Slco s Grou IV (atomc umber 14) Atom electroc structure: 1s s 6 3s 3 Crystal electroc

More information

Semiconductor Device Physics

Semiconductor Device Physics 1 Semcoductor evce Physcs Lecture 7 htt://ztomul.wordress.com 0 1 3 Semcoductor evce Physcs Chater 6 Jucto odes: I-V Characterstcs 3 Chater 6 Jucto odes: I-V Characterstcs Qualtatve ervato Majorty carrers

More information

6.4.5 MOS capacitance-voltage analysis

6.4.5 MOS capacitance-voltage analysis 6.4.5 MOS capactace-voltage aalyss arous parameters of a MOS devce ca be determed from the - characterstcs.. Type of substrate dopg. Isulator capactace = /d sulator thckess d 3. The mmum depleto capactace

More information

Diode DC Non-ideal Characteristics

Diode DC Non-ideal Characteristics Dode DC No-deal Characterstcs - e qv/kt V reverse curret ot saturated (geerato the deleto rego) dode breakdow 2 3 recombato the deleto rego l( ) 5 hgh-level jecto of morty carrers l( ) sloeq/ηkt V η η2

More information

Lecture #13. Diode Current due to Generation

Lecture #13. Diode Current due to Generation Lecture #13 Juctos OUTLINE reverse bas curret devatos from deal behavor small-sgal model Readg: Chaters 6. & 7 EE13 Lecture 13, Slde 1 Dode Curret due to Geerato If a electro-hole ar s geerated (e.g. by

More information

Modeling of dark characteristics for longwavelength

Modeling of dark characteristics for longwavelength Modelg of dark haratersts for logwaelegth HgCdTe photodode Z. J. Qua, X. S. Che, W. Lu atoal Laboratory for Ifrared Physs Shagha Isttute of Tehal Physs Chese Aademy of Sees Outle Itroduto Carrer desty

More information

Carrier Action under Perturbation

Carrier Action under Perturbation Carrer Acto uder Perturbato Eulbrum: o curret ad o formato ca be represeted. Ferm-level s flat! Perturbato s ecessary to artfcally ecode formato perturbed states: electrc feld (drft), cocetrato gradet

More information

ECSE-6300 IC Fabrication Laboratory Lecture 6 Diffusion in Silicon. Lecture Outline

ECSE-6300 IC Fabrication Laboratory Lecture 6 Diffusion in Silicon. Lecture Outline ECSE-6300 IC Fabrcato Laboratory Lecture 6 ffuso Slco Prof. Resselaer Polytechc Isttute Troy, NY 1180 Offce: CII-69 Tel.: (518) 76-909 e-mals: luj@rp.edu http://www.ecse.rp.edu/courses/s16/ecse 6300/dex.html

More information

Transport Equation. For constant ε, the force per unit fluid volume due to electric field becomes,

Transport Equation. For constant ε, the force per unit fluid volume due to electric field becomes, Trasport Eqato For ostat ε, the fore per t fld volme de to eletr feld beomes, - ρ f E N/m 3 or ρ f ψ Mometm Eq. (trodg the eletr fore term as body fore term) ρ + ρ = p + µ d t Steady state, reep flow d

More information

Homework #2 Solutions, EE/MSE 486, Spring 2017 Problem 1:

Homework #2 Solutions, EE/MSE 486, Spring 2017 Problem 1: Homework # Solutos, EE/MSE 486, Sprg 017 Problem 1: P o p N N A ( N N A) Here / for type dopg; 4 p p N A N ( N A N) / for p type dog. 4 At 1000C, 3.1*10 16 3/ From the table the otes, we have T 0.603eV

More information

Chapter 2 Motion and Recombination of Electrons and Holes

Chapter 2 Motion and Recombination of Electrons and Holes Chapter 2 Motio ad Recombiatio of Electros ad Holes 2.1 Thermal Eergy ad Thermal Velocity Average electro or hole kietic eergy 3 2 kt 1 2 2 mv th v th 3kT m eff 3 23 1.38 10 JK 0.26 9.1 10 1 31 300 kg

More information

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law Module : The equato of cotuty Lecture 5: Coservato of Mass for each speces & Fck s Law NPTEL, IIT Kharagpur, Prof. Sakat Chakraborty, Departmet of Chemcal Egeerg 2 Basc Deftos I Mass Trasfer, we usually

More information

1. MOS: Device Operation and Large Signal Model

1. MOS: Device Operation and Large Signal Model 1. MOS: ece Oerato ad arge Sgal Model Readg: Sedra & Smth Sec. 5.1-5.3 (S&S 5 th Ed: Sec. 4.1-4.3) ECE 10, Fall 011, F. Najmabad Oeratoal Bass of a Feld-Effect Trasstor (1) Cosder the hyothetcal semcoductor

More information

The E vs k diagrams are in general a function of the k -space direction in a crystal

The E vs k diagrams are in general a function of the k -space direction in a crystal vs dagram p m m he parameter s called the crystal mometum ad s a parameter that results from applyg Schrödger wave equato to a sgle-crystal lattce. lectros travelg dfferet drectos ecouter dfferet potetal

More information

EP2200 Queueing theory and teletraffic systems. Queueing networks. Viktoria Fodor KTH EES/LCN KTH EES/LCN

EP2200 Queueing theory and teletraffic systems. Queueing networks. Viktoria Fodor KTH EES/LCN KTH EES/LCN EP2200 Queueg theory ad teletraffc systems Queueg etworks Vktora Fodor Ope ad closed queug etworks Queug etwork: etwork of queug systems E.g. data packets traversg the etwork from router to router Ope

More information

Ellipsometry Overview

Ellipsometry Overview llpsometry Overvew ~ R Δ p ρ = ta( Ψ) e = ~ Rs ñ(λ) = (λ) + k(λ) ε = ñ 2 p-plae s-plae p-plae plae of cdece s-plae llpsometry buldg-blocks Lght ad Polarzato Materals / Optcal Costats Iteracto of Lght wth

More information

( ) Thermal noise ktb (T is absolute temperature in kelvin, B is bandwidth, k is Boltzamann s constant) Shot noise

( ) Thermal noise ktb (T is absolute temperature in kelvin, B is bandwidth, k is Boltzamann s constant) Shot noise OISE Thermal oe ktb (T abolute temperature kelv, B badwdth, k Boltzama cotat) 3 k.38 0 joule / kelv ( joule /ecod watt) ( ) v ( freq) 4kTB Thermal oe refer to the ketc eergy of a body of partcle a a reult

More information

1. Overview of basic probability

1. Overview of basic probability 13.42 Desg Prcples for Ocea Vehcles Prof. A.H. Techet Sprg 2005 1. Overvew of basc probablty Emprcally, probablty ca be defed as the umber of favorable outcomes dvded by the total umber of outcomes, other

More information

Random Variate Generation ENM 307 SIMULATION. Anadolu Üniversitesi, Endüstri Mühendisliği Bölümü. Yrd. Doç. Dr. Gürkan ÖZTÜRK.

Random Variate Generation ENM 307 SIMULATION. Anadolu Üniversitesi, Endüstri Mühendisliği Bölümü. Yrd. Doç. Dr. Gürkan ÖZTÜRK. adom Varate Geerato ENM 307 SIMULATION Aadolu Üverstes, Edüstr Mühedslğ Bölümü Yrd. Doç. Dr. Gürka ÖZTÜK 0 adom Varate Geerato adom varate geerato s about procedures for samplg from a varety of wdely-used

More information

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin Learzato of the Swg Equato We wll cover sectos.5.-.6 ad begg of Secto 3.3 these otes. 1. Sgle mache-fte bus case Cosder a sgle mache coected to a fte bus, as show Fg. 1 below. E y1 V=1./_ Fg. 1 The admttace

More information

d b c d a c a a a c d b

d b c d a c a a a c d b Beha Uverty Faculty of Egeerg Shoubra Electrcal Egeerg eartmet Frt Year commucato. t emeter Eam ate: 3 0 ECE: Electroc Egeerg fudametal urato : 3 hour K=.38 3 J/K h=6.64 34 J. q=.6 9 C m o =9. 3 Kg [S]

More information

The BTE with a B-field: Simple Approach

The BTE with a B-field: Simple Approach ECE 656: Electronic Transport in Semiconductors Fall 017 The BTE with a B-field: Simple Approach Mark Lundstrom Electrical and Computer Engineering Purdue University West Lafayette, IN USA 10/11/17 Introduction

More information

Section 3. Measurement Errors

Section 3. Measurement Errors eto 3 Measuremet Errors Egeerg Measuremets 3 Types of Errors Itrs errors develops durg the data aqusto proess. Extrs errors foud durg data trasfer ad storage ad are due to the orrupto of the sgal y ose.

More information

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits Block-Based Compact hermal Modelg of Semcoductor Itegrated Crcuts Master s hess Defese Caddate: Jg Ba Commttee Members: Dr. Mg-Cheg Cheg Dr. Daqg Hou Dr. Robert Schllg July 27, 2009 Outle Itroducto Backgroud

More information

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA THE ROYAL STATISTICAL SOCIETY 3 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA PAPER I STATISTICAL THEORY & METHODS The Socety provdes these solutos to assst caddates preparg for the examatos future years ad

More information

Special Instructions / Useful Data

Special Instructions / Useful Data JAM 6 Set of all real umbers P A..d. B, p Posso Specal Istructos / Useful Data x,, :,,, x x Probablty of a evet A Idepedetly ad detcally dstrbuted Bomal dstrbuto wth parameters ad p Posso dstrbuto wth

More information

Overcoming Limitations of Sampling for Aggregation Queries

Overcoming Limitations of Sampling for Aggregation Queries CIS 6930 Approxmate Quer Processg Paper Presetato Sprg 2004 - Istructor: Dr Al Dobra Overcomg Lmtatos of Samplg for Aggregato Queres Authors: Surajt Chaudhur, Gautam Das, Maur Datar, Rajeev Motwa, ad Vvek

More information

Analysis of System Performance IN2072 Chapter 5 Analysis of Non Markov Systems

Analysis of System Performance IN2072 Chapter 5 Analysis of Non Markov Systems Char for Network Archtectures ad Servces Prof. Carle Departmet of Computer Scece U Müche Aalyss of System Performace IN2072 Chapter 5 Aalyss of No Markov Systems Dr. Alexader Kle Prof. Dr.-Ig. Georg Carle

More information

ELG4179: Wireless Communication Fundamentals S.Loyka. Frequency-Selective and Time-Varying Channels

ELG4179: Wireless Communication Fundamentals S.Loyka. Frequency-Selective and Time-Varying Channels Frequeny-Seletve and Tme-Varyng Channels Ampltude flutuatons are not the only effet. Wreless hannel an be frequeny seletve (.e. not flat) and tmevaryng. Frequeny flat/frequeny-seletve hannels Frequeny

More information

SOLUTIONS: ECE 606 Homework Week 7 Mark Lundstrom Purdue University (revised 3/27/13) e E i E T

SOLUTIONS: ECE 606 Homework Week 7 Mark Lundstrom Purdue University (revised 3/27/13) e E i E T SOUIONS: ECE 606 Homework Week 7 Mark udstrom Purdue Uiversity (revised 3/27/13) 1) Cosider a - type semicoductor for which the oly states i the badgap are door levels (i.e. ( E = E D ). Begi with the

More information

Lecture 07: Poles and Zeros

Lecture 07: Poles and Zeros Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto

More information

Uniform magnetic susceptibilities

Uniform magnetic susceptibilities Uform magetc susceptbltes Typcal behavors ad measuremet techques SUSCPTIILIT UNIFORM & MAGNTOMTRIS page 1 - M ICFP- lectroc propertes of solds (Fabrce ert Varous behavors of M(H magetzato M Lear respose

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Postpoed exam: ECON430 Statstcs Date of exam: Jauary 0, 0 Tme for exam: 09:00 a.m. :00 oo The problem set covers 5 pages Resources allowed: All wrtte ad prted

More information

Probability and. Lecture 13: and Correlation

Probability and. Lecture 13: and Correlation 933 Probablty ad Statstcs for Software ad Kowledge Egeers Lecture 3: Smple Lear Regresso ad Correlato Mocha Soptkamo, Ph.D. Outle The Smple Lear Regresso Model (.) Fttg the Regresso Le (.) The Aalyss of

More information

ENGI 3423 Simple Linear Regression Page 12-01

ENGI 3423 Simple Linear Regression Page 12-01 ENGI 343 mple Lear Regresso Page - mple Lear Regresso ometmes a expermet s set up where the expermeter has cotrol over the values of oe or more varables X ad measures the resultg values of aother varable

More information

Intrinsic Carrier Concentration

Intrinsic Carrier Concentration Itrisic Carrier Cocetratio I. Defiitio Itrisic semicoductor: A semicoductor material with o dopats. It electrical characteristics such as cocetratio of charge carriers, deped oly o pure crystal. II. To

More information

X-ray vortices from nonlinear inverse Thomson scattering

X-ray vortices from nonlinear inverse Thomson scattering JLab semar 8/7/6 X-ray vortces from olear verse Thomso scatterg Yoshtaka Tara Natoal Isttute of Advaced Idustral Scece ad Techology (AIST) Vstg scetst: Msssspp State Uversty ad Jefferso Lab. Optcal vortex

More information

L5 Polynomial / Spline Curves

L5 Polynomial / Spline Curves L5 Polyomal / Sple Curves Cotets Coc sectos Polyomal Curves Hermte Curves Bezer Curves B-Sples No-Uform Ratoal B-Sples (NURBS) Mapulato ad Represetato of Curves Types of Curve Equatos Implct: Descrbe a

More information

Section 7.2 Two-way ANOVA with random effect(s)

Section 7.2 Two-way ANOVA with random effect(s) Secto 7. Two-wy ANOVA wth rdom effect(s) 1 1. Model wth Two Rdom ffects The fctors hgher-wy ANOVAs c g e cosdered fxed or rdom depedg o the cotext of the study. or ech fctor: Are the levels of tht fctor

More information

A practical threshold estimation for jump processes

A practical threshold estimation for jump processes A practcal threshold estmato for jump processes Yasutaka Shmzu (Osaka Uversty, Japa) WORKSHOP o Face ad Related Mathematcal ad Statstcal Issues @ Kyoto, JAPAN, 3 6 Sept., 2008. Itroducto O (Ω, F,P; {F

More information

Channel model. Free space propagation

Channel model. Free space propagation //06 Channel model Free spae rado propagaton Terrestral propagaton - refleton, dffraton, satterng arge-sale fadng Empral models Small-sale fadng Nose and nterferene Wreless Systems 06 Free spae propagaton

More information

Lecture 10: Condensed matter systems

Lecture 10: Condensed matter systems Lectue 0: Codesed matte systems Itoducg matte ts codesed state.! Ams: " Idstgushable patcles ad the quatum atue of matte: # Cosequeces # Revew of deal gas etopy # Femos ad Bosos " Quatum statstcs. # Occupato

More information

Towards developing a reacting- DNS code Design and numerical issues

Towards developing a reacting- DNS code Design and numerical issues Towards developg a reactg- DNS code Desg ad umercal ssues Rx Yu 20-03-09 20-03-09 FM teral semar Motvatos Why we eed a Reactg DNS code No model for both flow (turbulece) ad combusto Study applcatos of

More information

Dopant Compensation. Lecture 2. Carrier Drift. Types of Charge in a Semiconductor

Dopant Compensation. Lecture 2. Carrier Drift. Types of Charge in a Semiconductor Lecture OUTLIE Bc Semcoductor Phycs (cot d) rrer d uo P ucto odes Electrosttcs ctce ot omesto tye semcoductor c be coverted to P tye mterl by couter dog t wth ccetors such tht >. comested semcoductor mterl

More information

Lecture 1: Semiconductor Physics I. Fermi surface of a cubic semiconductor

Lecture 1: Semiconductor Physics I. Fermi surface of a cubic semiconductor Leture 1: Semiodutor Physis I Fermi surfae of a ubi semiodutor 1 Leture 1: Semiodutor Physis I Cotet: Eergy bads, Fermi-Dira distributio, Desity of States, Dopig Readig guide: 1.1 1.5 Ludstrom 3D Eergy

More information

Lecture 7: Properties of Materials for Integrated Circuits Context

Lecture 7: Properties of Materials for Integrated Circuits Context Lecture 7: Propertes of Materals for Itegrate Crcuts Cotext Over the last two weeks, we revewe: Basc passve compoets Capactors Resstors Iuctors Lear crcut moels Phasor otato Trasfer fuctos Boe plots 1

More information

ECE 6340 Intermediate EM Waves. Fall Prof. David R. Jackson Dept. of ECE. Notes 3

ECE 6340 Intermediate EM Waves. Fall Prof. David R. Jackson Dept. of ECE. Notes 3 C 634 Intermedate M Waves Fall 216 Prof. Davd R. akson Dept. of C Notes 3 1 Types of Current ρ v Note: The free-harge densty ρ v refers to those harge arrers (ether postve or negatve) that are free to

More information

Solid State Device Fundamentals

Solid State Device Fundamentals Solid State Device Fudametals ENS 345 Lecture Course by Alexader M. Zaitsev alexader.zaitsev@csi.cuy.edu Tel: 718 982 2812 4N101b 1 Thermal motio of electros Average kietic eergy of electro or hole (thermal

More information

Lecture 3 Semiconductor Physics (II) Carrier Transport

Lecture 3 Semiconductor Physics (II) Carrier Transport Lecture 3 Semiconductor Physics (II) Carrier Transport Thermal Motion Carrier Drift Carrier Diffusion Outline Reading Assignment: Howe and Sodini; Chapter 2, Sect. 2.4-2.6 6.012 Spring 2009 Lecture 3 1

More information

INTRODUCTION TO INERTIAL CONFINEMENT FUSION

INTRODUCTION TO INERTIAL CONFINEMENT FUSION INRODUCION O INERIAL CONFINEMEN FUSION R. Bett Lecture 1 Formula or hot pot temperature Reved dyamc model ad gto codto Etropy he ormula below wa derved Lecture 9. It repreet the maxmum value o the cetral

More information

IS 709/809: Computational Methods in IS Research. Simple Markovian Queueing Model

IS 709/809: Computational Methods in IS Research. Simple Markovian Queueing Model IS 79/89: Comutatoal Methods IS Research Smle Marova Queueg Model Nrmalya Roy Deartmet of Iformato Systems Uversty of Marylad Baltmore Couty www.umbc.edu Queueg Theory Software QtsPlus software The software

More information

Introduction to Econometrics (3 rd Updated Edition, Global Edition) Solutions to Odd-Numbered End-of-Chapter Exercises: Chapter 9

Introduction to Econometrics (3 rd Updated Edition, Global Edition) Solutions to Odd-Numbered End-of-Chapter Exercises: Chapter 9 Itroducto to Ecoometrcs (3 rd Udated Edto, Global Edto) by James H. Stock ad Mark W. Watso Solutos to Odd-Numbered Ed-of-Chater Exercses: Chater 9 (Ths verso August 7, 04) 05 Pearso Educato, Ltd. Stock/Watso

More information

Multiple Choice Test. Chapter Adequacy of Models for Regression

Multiple Choice Test. Chapter Adequacy of Models for Regression Multple Choce Test Chapter 06.0 Adequac of Models for Regresso. For a lear regresso model to be cosdered adequate, the percetage of scaled resduals that eed to be the rage [-,] s greater tha or equal to

More information

Wireless Link Properties

Wireless Link Properties Opportustc Ecrypto for Robust Wreless Securty R. Chadramoul ( Moul ) moul@steves.edu Multmeda System, Networkg, ad Commucatos (MSyNC) Laboratory, Departmet of Electrcal ad Computer Egeerg, Steves Isttute

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

Cross-plane Seebeck coefficient and Lorenz number in superlattices

Cross-plane Seebeck coefficient and Lorenz number in superlattices PHYSICAL REVIEW B 76, 25311 27 Cross-plae Seebeck coeffcet ad Lorez umber superlattces Z. Ba, M. Zebarjad, R. Sgh, Y. Ezzahr, ad A. Shakour Electrcal Egeerg Departmet, Uversty of Calfora, Sata Cruz, Calfora

More information

Midterm Exam 1, section 2 (Solution) Thursday, February hour, 15 minutes

Midterm Exam 1, section 2 (Solution) Thursday, February hour, 15 minutes coometrcs, CON Sa Fracsco State Uverst Mchael Bar Sprg 5 Mdterm xam, secto Soluto Thursda, Februar 6 hour, 5 mutes Name: Istructos. Ths s closed book, closed otes exam.. No calculators of a kd are allowed..

More information

16 Homework lecture 16

16 Homework lecture 16 Quees College, CUNY, Departmet of Computer Scece Numercal Methods CSCI 361 / 761 Fall 2018 Istructor: Dr. Sateesh Mae c Sateesh R. Mae 2018 16 Homework lecture 16 Please emal your soluto, as a fle attachmet,

More information

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg

More information

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements Aoucemets No-Parametrc Desty Estmato Techques HW assged Most of ths lecture was o the blacboard. These sldes cover the same materal as preseted DHS Bometrcs CSE 90-a Lecture 7 CSE90a Fall 06 CSE90a Fall

More information

Integral Equation Methods. Jacob White. Thanks to Deepak Ramaswamy, Michal Rewienski, Xin Wang and Karen Veroy

Integral Equation Methods. Jacob White. Thanks to Deepak Ramaswamy, Michal Rewienski, Xin Wang and Karen Veroy Itroducto to Smulato - Lecture 22 Itegral Equato ethods Jacob Whte Thaks to Deepak Ramaswamy, chal Rewesk, X Wag ad Kare Veroy Outle Itegral Equato ethods Exteror versus teror problems Start wth usg pot

More information

Initial-Value Problems for ODEs. numerical errors (round-off and truncation errors) Consider a perturbed system: dz dt

Initial-Value Problems for ODEs. numerical errors (round-off and truncation errors) Consider a perturbed system: dz dt Ital-Value Problems or ODEs d GIVEN: t t,, a FIND: t or atb umercal errors (roud-o ad trucato errors) Cosder a perturbed sstem: dz t, z t, at b z a a Does z(t) (t)? () (uqueess) a uque soluto (t) exsts

More information

Introduction. Free Electron Fermi Gas. Energy Levels in One Dimension

Introduction. Free Electron Fermi Gas. Energy Levels in One Dimension ree Electro er Gas Eergy Levels Oe Deso Effect of eperature o the er-drac Dstrbuto ree Electro Gas hree Desos Heat Capacty of the Electro Gas Electrcal Coductvty ad Oh s Law Moto Magetc elds heral Coductvty

More information

External Electric Field Influence on Charge Carriers and Electrical Parameters of Polycrystalline Silicon Solar Cell

External Electric Field Influence on Charge Carriers and Electrical Parameters of Polycrystalline Silicon Solar Cell Research Joural of Appled ceces, Egeerg ad Techology 4(17: 967-97, 1 IN: 4-7467 Maxwell cetfc Orgazato, 1 ubmtted: ecember, 11 Accepted: Jauary 1, 1 Publshed: eptember 1, 1 Exteral Electrc Feld Ifluece

More information

Signal,autocorrelation -0.6

Signal,autocorrelation -0.6 Sgal,autocorrelato Phase ose p/.9.3.7. -.5 5 5 5 Tme Sgal,autocorrelato Phase ose p/.5..7.3 -. -.5 5 5 5 Tme Sgal,autocorrelato. Phase ose p/.9.3.7. -.5 5 5 5 Tme Sgal,autocorrelato. Phase ose p/.8..6.

More information

[ L] υ = (3) [ L] n. Q: What are the units of K in Eq. (3)? (Why is units placed in quotations.) What is the relationship to K in Eq. (1)?

[ L] υ = (3) [ L] n. Q: What are the units of K in Eq. (3)? (Why is units placed in quotations.) What is the relationship to K in Eq. (1)? Chem 78 Spr. M. Wes Bdg Polyomals Bdg Polyomals We ve looked at three cases of lgad bdg so far: The sgle set of depedet stes (ss[]s [ ] [ ] Multple sets of depedet stes (ms[]s, or m[]ss All or oe, or two-state

More information

III-16 G. Brief Review of Grand Orthogonality Theorem and impact on Representations (Γ i ) l i = h n = number of irreducible representations.

III-16 G. Brief Review of Grand Orthogonality Theorem and impact on Representations (Γ i ) l i = h n = number of irreducible representations. III- G. Bref evew of Grad Orthogoalty Theorem ad mpact o epresetatos ( ) GOT: h [ () m ] [ () m ] δδ δmm ll GOT puts great restrcto o form of rreducble represetato also o umber: l h umber of rreducble

More information

Objectives of Multiple Regression

Objectives of Multiple Regression Obectves of Multple Regresso Establsh the lear equato that best predcts values of a depedet varable Y usg more tha oe eplaator varable from a large set of potetal predctors {,,... k }. Fd that subset of

More information

MONOPOLISTIC COMPETITION MODEL

MONOPOLISTIC COMPETITION MODEL MONOPOLISTIC COMPETITION MODEL Key gredets Cosumer utlty: log (/ ) log (taste for varety of dfferetated goods) Produto of dfferetated produts: y (/ b) max[ f, ] (reasg returs/fxed osts) Assume that good,

More information

Time Domain Method of Moments

Time Domain Method of Moments Time Domain Method of Moments Massahusetts Institute of Tehnology 6.635 leture notes 1 Introdution The Method of Moments (MoM) introdued in the previous leture is widely used for solving integral equations

More information

Lecture 10 - Carrier Flow (cont.) February 28, 2007

Lecture 10 - Carrier Flow (cont.) February 28, 2007 6.720J/3.43J Integrated Microelectronic Devices - Spring 2007 Lecture 10-1 Lecture 10 - Carrier Flow (cont.) February 28, 2007 Contents: 1. Minority-carrier type situations Reading assignment: del Alamo,

More information

Chapter 5 Carrier transport phenomena

Chapter 5 Carrier transport phenomena Chater 5 Carrier trasort heomea W.K. Che lectrohysics, NCTU Trasort The et flow of electros a holes i material is calle trasort Two basic trasort mechaisms Drift: movemet of charge ue to electric fiels

More information

Statistics: Unlocking the Power of Data Lock 5

Statistics: Unlocking the Power of Data Lock 5 STAT 0 Dr. Kar Lock Morga Exam 2 Grades: I- Class Multple Regresso SECTIONS 9.2, 0., 0.2 Multple explaatory varables (0.) Parttog varablty R 2, ANOVA (9.2) Codtos resdual plot (0.2) Exam 2 Re- grades Re-

More information

Introduction to Molecular Spectroscopy

Introduction to Molecular Spectroscopy Chem 5.6, Fall 004 Leture #36 Page Introduton to Moleular Spetrosopy QM s essental for understandng moleular spetra and spetrosopy. In ths leture we delneate some features of NMR as an ntrodutory example

More information

ECON 482 / WH Hong The Simple Regression Model 1. Definition of the Simple Regression Model

ECON 482 / WH Hong The Simple Regression Model 1. Definition of the Simple Regression Model ECON 48 / WH Hog The Smple Regresso Model. Defto of the Smple Regresso Model Smple Regresso Model Expla varable y terms of varable x y = β + β x+ u y : depedet varable, explaed varable, respose varable,

More information

16.512, Rocket Propulsion Prof. Manuel Martinez-Sanchez Lecture 10: Ablative Cooling, Film Cooling

16.512, Rocket Propulsion Prof. Manuel Martinez-Sanchez Lecture 10: Ablative Cooling, Film Cooling 6.5, Roet Propulso Prof. Mauel Martez-Sahez Leture 0: Ablatve Coolg, l Coolg Traset Heatg of a Slab Typal proble: Uooled throat of a sold propellat roet Ier layer retards heat flux to the heat s. Heat

More information

Lecture #11. A Note of Caution

Lecture #11. A Note of Caution ctur #11 OUTE uctos rvrs brakdow dal dod aalyss» currt flow (qualtatv)» morty carrr dstrbutos Radg: Chatr 6 Srg 003 EE130 ctur 11, Sld 1 ot of Cauto Tycally, juctos C dvcs ar formd by coutr-dog. Th quatos

More information

Physics 2102 Spring 2007 Lecture 10 Current and Resistance

Physics 2102 Spring 2007 Lecture 10 Current and Resistance esstance Is Futle! Physcs 0 Sprng 007 Jonathan Dowlng Physcs 0 Sprng 007 Lecture 0 Current and esstance Georg Smon Ohm (789-854) What are we gong to learn? A road map lectrc charge lectrc force on other

More information

Coupled Quantum - Scattering Modeling of Thermoelectric Properties of Si/Ge/Si Quantum Well Superlattice

Coupled Quantum - Scattering Modeling of Thermoelectric Properties of Si/Ge/Si Quantum Well Superlattice Proceedgs of IMECE 6 26 ASME Iteratoal Mechacal Egeerg Cogress Chcago, Illos, November 5-1, 26 Coupled Quatum - Scatterg Modelg of Thermoelectrc Propertes of S/Ge/S Quatum Well Superlattce A. Bulusu Graduate

More information

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The

More information

THE ACOUSTIC WAVE PROPAGATION EQUATION IN A TURBULENT COMBUSTING FLOW

THE ACOUSTIC WAVE PROPAGATION EQUATION IN A TURBULENT COMBUSTING FLOW ICSV14 Cars Australa 9-1 July, 7 THE ACOUSTIC WAVE PROPAGATION EQUATION IN A TURBULENT COMBUSTING FLOW Jm B.W. Kok ad Bram de Jager Uversty of Twete Dept. of Meh Eg. PO Box 17, 75 AE Eshede The Netherlads.b.w.kok@utwete.l

More information

University of California at Berkeley College of Engineering Dept. of Electrical Engineering and Computer Sciences.

University of California at Berkeley College of Engineering Dept. of Electrical Engineering and Computer Sciences. Uversty of Clfor t Berkeley College of Egeerg et. of Electrcl Egeerg Comuter Sceces EE 5 Mterm I Srg 6 Prof. Mg C. u Feb. 3, 6 Gueles Close book otes. Oe-ge formto sheet llowe. There re some useful formuls

More information

Uniform excitation: applied field and optical generation. Non-uniform doping/excitation: diffusion, continuity

Uniform excitation: applied field and optical generation. Non-uniform doping/excitation: diffusion, continuity 6.012 - Electronic Devices and Circuits Lecture 2 - Uniform Excitation; Non-uniform conditions Announcements Review Carrier concentrations in TE given the doping level What happens above and below room

More information

Mark Lundstrom Spring SOLUTIONS: ECE 305 Homework: Week 5. Mark Lundstrom Purdue University

Mark Lundstrom Spring SOLUTIONS: ECE 305 Homework: Week 5. Mark Lundstrom Purdue University Mark udstrom Sprig 2015 SOUTIONS: ECE 305 Homework: Week 5 Mark udstrom Purdue Uiversity The followig problems cocer the Miority Carrier Diffusio Equatio (MCDE) for electros: Δ t = D Δ + G For all the

More information

Electrical Resistance

Electrical Resistance Electrical Resistace I + V _ W Material with resistivity ρ t L Resistace R V I = L ρ Wt (Uit: ohms) where ρ is the electrical resistivity Addig parts/billio to parts/thousad of dopats to pure Si ca chage

More information

Evolution Operators and Boundary Conditions for Propagation and Reflection Methods

Evolution Operators and Boundary Conditions for Propagation and Reflection Methods voluto Operators ad for Propagato ad Reflecto Methods Davd Yevck Departmet of Physcs Uversty of Waterloo Physcs 5/3/9 Collaborators Frak Schmdt ZIB Tlma Frese ZIB Uversty of Waterloo] atem l-refae Nortel

More information

AN EULER-MC LAURIN FORMULA FOR INFINITE DIMENSIONAL SPACES

AN EULER-MC LAURIN FORMULA FOR INFINITE DIMENSIONAL SPACES AN EULER-MC LAURIN FORMULA FOR INFINITE DIMENSIONAL SPACES Jose Javer Garca Moreta Graduate Studet of Physcs ( Sold State ) at UPV/EHU Address: P.O 6 890 Portugalete, Vzcaya (Spa) Phoe: (00) 3 685 77 16

More information

Lecture 14. P-N Junction Diodes: Part 3 Quantitative Analysis (Math, math and more math) Reading: Pierret 6.1

Lecture 14. P-N Junction Diodes: Part 3 Quantitative Analysis (Math, math and more math) Reading: Pierret 6.1 Lctur 4 - ucto ods art 3 Quattatv alyss Math, math ad mor math Radg rrt 6. Gorga Tch ECE 3040 - r. la oolttl Quattatv - od Soluto ssumtos stady stat codtos o- dgrat dog 3 o- dmsoal aalyss 4 low- lvl jcto

More information

9.1 Introduction to the probit and logit models

9.1 Introduction to the probit and logit models EC3000 Ecoometrcs Lecture 9 Probt & Logt Aalss 9. Itroducto to the probt ad logt models 9. The logt model 9.3 The probt model Appedx 9. Itroducto to the probt ad logt models These models are used regressos

More information

ECE606: Solid State Devices Lecture 7

ECE606: Solid State Devices Lecture 7 C606: Sold Stat vcs Lctur 7 Grhard Klmck gkco@purdu.du Rfrc: Vol. 6, Ch. 3 & 4 Prstato Outl Itrsc carrr coctrato Pottal, fld, ad charg -k dagram vs. bad-dagram Basc cocpts of doors ad accptors Law of mass-acto

More information

A Method for Damping Estimation Based On Least Square Fit

A Method for Damping Estimation Based On Least Square Fit Amerca Joural of Egeerg Research (AJER) 5 Amerca Joural of Egeerg Research (AJER) e-issn: 3-847 p-issn : 3-936 Volume-4, Issue-7, pp-5-9 www.ajer.org Research Paper Ope Access A Method for Dampg Estmato

More information

Hard Core Predicates: How to encrypt? Recap

Hard Core Predicates: How to encrypt? Recap Hard Core Predcates: How to ecrypt? Debdeep Mukhopadhyay IIT Kharagpur Recap A ecrypto scheme s secured f for every probablstc adversary A carryg out some specfed kd of attack ad for every polyomal p(.),

More information