Organic Electronic Devices
|
|
- Andrew Crawford
- 5 years ago
- Views:
Transcription
1 Orgai letroi Devies Week 3: Charge rasport Leture 3.3: Multiple rap ad Release MR Model Brya W. Boudouris Chemial gieerig Purdue Uiversity
2 Leture Overview ad Learig Objetives Coepts to be Covered i this Leture Segmet Itrodutio to rap States withi the Badgap o Semiodutig Materials xplaatio o the Physial Ratioale Behid the Multiple rap ad hermal Release MR Model Quatiiatio o the Mobility o a Semiodutor usig the MR Model ad Materials ad Devie Properties Learig Objetives By the Colusio o this Presetatio, You Should be Able to:. xplai how the trap eergy levels ad the desity o traps aet the trasport o a harge aordig to the MR model. 2. Deie the terms eetive mobility, eetive desity o states or traps ad the eetive desity o states at the odutio bad edge. 3. Derive a ressio or the eetive mobility o a semiodutor based o the MR model.
3 Itrodutio to the Multiple rap ad hermal Release MR Model he key dieree betwee bad trasport i traditioal solid state physis ad orgai eletroi devies is the LARG AMOU O DISORDR i most orgai eletroi systems relative to iorgai semiodutors. I some orgai materials, trasport is limited by loalized states idued by deets ad uwated impurities. hese deets ad impurities are reerred to by the athall term o traps. Imagie a rasport Bad with Impurity States C ergy,,2,3 Loalized states with trap eergies at 3 distit eergy levels here is a iite probability that the arrier will be trapped i ad that the arrier will be released rom oe o the lower eergy trap states available due to the deets ad impurities.
4 Assumptios ad Deiitios o the MR Model. he trap states are highly loalized ad arriers trapped i these states aot move easily rom these loatios i the eergy badgap. 2. Charge arriers arrivig at the trap site are aptured istataeously ad with a probability o lose to. 3. he release o the trapped arriers is otrolled by a thermally-ativated proess. 4. We will talk about two types o traps. a Shallow traps are withi 2-3 k o the bad edge ad arriers stuk withi these traps have a harateristi time o release. b Deep traps are > 2-3 k rom the bad edge ad arriers loalized i these traps have a very diiult time beig removed without a exteral stimulus. 5. wo key parameters will gover the slowig o the harges as they move through the semiodutor: the eergy levels o the traps ad 2 the umber o traps.
5 Desribig Charge rasport with a etive Mobility A eetive mobility e or the harge arriers a be writte as: α k Bad rasport Mobility or the Mobility i e the Absee o raps ergy Level o the rap α Measure o the rap Desity ote that this is i terms o a sigle trap eergy level, but it a be geeralized to model traps with a variety o eergy levels. How a the α term be quatiied i a more rigorous maer based o ressios we have derived i the past? Deie:. etive Desity o States or the rap Sites 2. C etive Desity o States at the Codutio dge
6 Desribig Charge rasport with a etive Mobility Part II ow, we see that the total arrier oetratio O must either be i the ree or trapped state. So: Reall that we a write the oetratio o ree arriers as the ollowig O + k k I a similar maer, we a write a aalogous equatio or the oetratio o trapped arriers k k
7 Desribig Charge rasport with a etive Mobility Part III he ratio o ree harge arriers θ a the be ressed as ollows Substitutig i the deiitios o the previous slide yields the ollowig O + θ his redues to: + k k k θ + k θ
8 Desribig Charge rasport with a etive Mobility Part I I the limit that: he the equatio o the previous slide redues to: But, reall the iitial deiitio o the eetive mobility >> k k k θ k e α
9 Desribig Charge rasport with a etive Mobility Part hereore, we a rewrite the eetive mobility as: e θ α his tells us that as the desity o states i the odutio bad grows relative to the desity o states o the trap levels, the mobility should irease. I real systems, the trap desity will be distributed with respet to eergy. A simple model assumes a oetial distributio with a harateristi temperature. D ad see that ; where : > k k I we assume a step-utio or the ermi-dira distributio, the the itegratio to determie the umber o trapped harges beomes: k
10 Deiig the hreshold oltage I order to overome this oetratio o trap states, oe a apply a voltage as the exteral stimuli. his applied voltage a be related to the threshold voltage, whih is a measure o the umber o trapped harges i the semiodutor, aordig to the ollowig equatio. C q C q Capaitae o the ide separatig the metal otat rom the orgai semiodutor udametal Charge he, we a say that: k C q Solvig or the ermi eergy yields: C l k q
11 Deiig the hreshold oltage Part II Isertig this ito the deiitio o the ree harge arriers gives the ollowig Ivokig the deiitio o the eetive mobility used earlier yields: + q C d k D 2 θ + + e e q C q C q C ypial values ~45 K, ~ 2 2 m -3
12 Summary ad Preview o the ext Leture ergy e + C q C q he multiple trap ad release MR model is a useul desriptio or the trasport o harges i a somewhat disordered semiodutor. hat is, whe there are deet sites or impurities that have eergy levels that are withi the badgap o the semiodutig material, oe a aout or these i the orgai material still has a somewhat well deied bad struture. Geerally, the parameters or this model a be haraterized by perormig temperature-depedet trasport erimets. + C By usig a ombiatio o ew theory related to the MR model ad the stadard theory assoiated with bad trasport, we were able to derive a equatio or the ressio o the eetive mobility relative to the bad trasport mobility. ext ime: rasport i Highly Disordered Orgai Semiodutors q 2
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 informationChapter MOSFET
Chapter 17-1. MOFET MOFET-based ICs have beome domiat teholog i the semiodutor idustr. We will stud the followig i this hapter: - Qualitative theor of operatio - Quatitative I D -versus-v D harateristis
More informationCHAPTER 6d. NUMERICAL INTERPOLATION
CHAPER 6d. NUMERICAL INERPOLAION A. J. Clark School o Egieerig Departmet o Civil ad Evirometal Egieerig by Dr. Ibrahim A. Assakka Sprig ENCE - Computatio Methods i Civil Egieerig II Departmet o Civil ad
More information(8) 1f = f. can be viewed as a real vector space where addition is defined by ( a1+ bi
Geeral Liear Spaes (Vetor Spaes) ad Solutios o ODEs Deiitio: A vetor spae V is a set, with additio ad salig o elemet deied or all elemets o the set, that is losed uder additio ad salig, otais a zero elemet
More informationChemistry 2. Assumed knowledge. Learning outcomes. The particle on a ring j = 3. Lecture 4. Cyclic π Systems
Chemistry Leture QuatitativeMO Theoryfor Begiers: Cyli Systems Assumed kowledge Be able to predit the umber of eletros ad the presee of ougatio i a rig otaiig arbo ad/or heteroatoms suh as itroge ad oxyge.
More informationSome pictures are taken from the UvA-VU Master Course: Advanced Solid State Physics by Anne de Visser (University of Amsterdam), Solid State Course
Some pitures are take rom the UA-VU Master Course: Adaed Solid State Physis by Ae de Visser (Uiersity o Amsterdam), Solid State Course by Mark arrel (Ciiati Uiersity), rom Ibah ad Lüth, rom Ashrot ad Mermi
More informationREPRESENTING MARKOV CHAINS WITH TRANSITION DIAGRAMS
Joural o Mathematics ad Statistics, 9 (3): 49-54, 3 ISSN 549-36 3 Sciece Publicatios doi:.38/jmssp.3.49.54 Published Olie 9 (3) 3 (http://www.thescipub.com/jmss.toc) REPRESENTING MARKOV CHAINS WITH TRANSITION
More informationPrinciple Of Superposition
ecture 5: PREIMINRY CONCEP O RUCUR NYI Priciple Of uperpositio Mathematically, the priciple of superpositio is stated as ( a ) G( a ) G( ) G a a or for a liear structural system, the respose at a give
More informationCHAPTER 6c. NUMERICAL INTERPOLATION
CHAPTER 6c. NUMERICAL INTERPOLATION A. J. Clark School o Egieerig Departmet o Civil ad Evirometal Egieerig y Dr. Irahim A. Assakka Sprig ENCE - Computatio Methods i Civil Egieerig II Departmet o Civil
More informationCS537. Numerical Analysis and Computing
CS57 Numerical Aalysis ad Computig Lecture Locatig Roots o Equatios Proessor Ju Zhag Departmet o Computer Sciece Uiversity o Ketucky Leigto KY 456-6 Jauary 9 9 What is the Root May physical system ca be
More informationCS321. Numerical Analysis and Computing
CS Numerical Aalysis ad Computig Lecture Locatig Roots o Equatios Proessor Ju Zhag Departmet o Computer Sciece Uiversity o Ketucky Leigto KY 456-6 September 8 5 What is the Root May physical system ca
More informationAnother face of DIRECT
Aother ae o DIEC Lakhdar Chiter Departmet o Mathematis, Seti Uiversity, Seti 19000, Algeria E-mail address: hiterl@yahoo.r Abstrat It is show that, otrary to a laim o [D. E. Fikel, C.. Kelley, Additive
More informationMass Transfer Chapter 3. Diffusion in Concentrated Solutions
Mass Trasfer Chapter 3 Diffusio i Coetrated Solutios. Otober 07 3. DIFFUSION IN CONCENTRATED SOLUTIONS 3. Theor Diffusio auses ovetio i fluids Covetive flow ours beause of pressure gradiets (most ommo)
More informationEECS 455 Solutions to Problem Set 8
. Problem 7.55 o text EECS 455 Solutios to Problem Set 8 a) For repeaters i asade, the probability o i out o repeaters to produe a error is give by the biomial distributio P i p i p i However, there is
More informationSolid State Device Fundamentals
Solid State Device Fudametals ES 345 Lecture ourse by Alexader M. Zaitsev alexader.zaitsev@csi.cuy.edu Tel: 718 98 81 4101b ollege of State Islad / UY Dopig semicoductors Doped semicoductors are semicoductors,
More informationPrinciples of Communications Lecture 12: Noise in Modulation Systems. Chih-Wei Liu 劉志尉 National Chiao Tung University
Priiples of Commuiatios Leture 1: Noise i Modulatio Systems Chih-Wei Liu 劉志尉 Natioal Chiao ug Uiversity wliu@twis.ee.tu.edu.tw Outlies Sigal-to-Noise Ratio Noise ad Phase Errors i Coheret Systems Noise
More informationREQUIREMENTS FOR EFFICIENT TRANSISTOR OPERATION I B. Icn. I cp
RQURMNS FOR FFCN RANSSOR OPRAON r 1. AN so that the fudametal basis of trasistor atio, that of a urret otrolled by a small voltage flowig aross a large resistor to geerate a large voltage is maitaied.
More informationComputational Methods CMSC/AMSC/MAPL 460. Quadrature: Integration
Computatioal Metods CMSC/AMSC/MAPL 6 Quadrature: Itegratio Ramai Duraiswami, Dept. o Computer Siee Some material adapted rom te olie slides o Eri Sadt ad Diae O Leary Numerial Itegratio Idea is to do itegral
More informationANOTHER PROOF FOR FERMAT S LAST THEOREM 1. INTRODUCTION
ANOTHER PROOF FOR FERMAT S LAST THEOREM Mugur B. RĂUŢ Correspodig author: Mugur B. RĂUŢ, E-mail: m_b_raut@yahoo.om Abstrat I this paper we propose aother proof for Fermat s Last Theorem (FLT). We foud
More informationTopic 9 - Taylor and MacLaurin Series
Topic 9 - Taylor ad MacLauri Series A. Taylors Theorem. The use o power series is very commo i uctioal aalysis i act may useul ad commoly used uctios ca be writte as a power series ad this remarkable result
More informationObserver Design with Reduced Measurement Information
Observer Desig with Redued Measuremet Iformatio I pratie all the states aot be measured so that SVF aot be used Istead oly a redued set of measuremets give by y = x + Du p is available where y( R We assume
More informationCS284A: Representations and Algorithms in Molecular Biology
CS284A: Represetatios ad Algorithms i Molecular Biology Scribe Notes o Lectures 3 & 4: Motif Discovery via Eumeratio & Motif Represetatio Usig Positio Weight Matrix Joshua Gervi Based o presetatios by
More informationLecture 8. Dirac and Weierstrass
Leture 8. Dira ad Weierstrass Audrey Terras May 5, 9 A New Kid of Produt of Futios You are familiar with the poitwise produt of futios de ed by f g(x) f(x) g(x): You just tae the produt of the real umbers
More informationMost text will write ordinary derivatives using either Leibniz notation 2 3. y + 5y= e and y y. xx tt t
Itroductio to Differetial Equatios Defiitios ad Termiolog Differetial Equatio: A equatio cotaiig the derivatives of oe or more depedet variables, with respect to oe or more idepedet variables, is said
More information5. Fast NLMS-OCF Algorithm
5. Fast LMS-OCF Algorithm The LMS-OCF algorithm preseted i Chapter, which relies o Gram-Schmidt orthogoalizatio, has a compleity O ( M ). The square-law depedece o computatioal requiremets o the umber
More informationClass #25 Wednesday, April 19, 2018
Cla # Wedesday, April 9, 8 PDE: More Heat Equatio with Derivative Boudary Coditios Let s do aother heat equatio problem similar to the previous oe. For this oe, I ll use a square plate (N = ), but I m
More informationNUMERICAL METHODS FOR SOLVING EQUATIONS
Mathematics Revisio Guides Numerical Methods for Solvig Equatios Page 1 of 11 M.K. HOME TUITION Mathematics Revisio Guides Level: GCSE Higher Tier NUMERICAL METHODS FOR SOLVING EQUATIONS Versio:. Date:
More informationSemiconductor Statistical Mechanics (Read Kittel Ch. 8)
EE30 - Solid State Electroics Semicoductor Statistical Mechaics (Read Kittel Ch. 8) Coductio bad occupatio desity: f( E)gE ( ) de f(e) - occupatio probability - Fermi-Dirac fuctio: g(e) - desity of states
More informationPhys. 201 Mathematical Physics 1 Dr. Nidal M. Ershaidat Doc. 12
Physics Departmet, Yarmouk Uiversity, Irbid Jorda Phys. Mathematical Physics Dr. Nidal M. Ershaidat Doc. Fourier Series Deiitio A Fourier series is a expasio o a periodic uctio (x) i terms o a iiite sum
More informationLecture 2: Monte Carlo Simulation
STAT/Q SCI 43: Itroductio to Resamplig ethods Sprig 27 Istructor: Ye-Chi Che Lecture 2: ote Carlo Simulatio 2 ote Carlo Itegratio Assume we wat to evaluate the followig itegratio: e x3 dx What ca we do?
More information16th International Symposium on Ballistics San Francisco, CA, September 1996
16th Iteratioal Symposium o Ballistis Sa Fraiso, CA, 3-8 September 1996 GURNEY FORULAS FOR EXPLOSIVE CHARGES SURROUNDING RIGID CORES William J. Flis, Dya East Corporatio, 36 Horizo Drive, Kig of Prussia,
More informationFluids Lecture 2 Notes
Fluids Leture Notes. Airfoil orte Sheet Models. Thi-Airfoil Aalysis Problem Readig: Aderso.,.7 Airfoil orte Sheet Models Surfae orte Sheet Model A aurate meas of represetig the flow about a airfoil i a
More informationNumerical Integration Formulas
Numerical Itegratio Formulas Berli Che Departmet o Computer Sciece & Iormatio Egieerig Natioal Taiwa Normal Uiversity Reerece: 1. Applied Numerical Methods with MATLAB or Egieers, Chapter 19 & Teachig
More informationChemical Engineering 160/260 Polymer Science and Engineering. Model for Polymer Solutions February 5, 2001
Chemical Egieerig 60/60 Polymer Sciece ad Egieerig Lecture 9 - Flory-Huggis Model for Polymer Solutios February 5, 00 Read Sperlig, Chapter 4 Objectives! To develop the classical Flory-Huggis theory for
More informationAfter the completion of this section the student. V.4.2. Power Series Solution. V.4.3. The Method of Frobenius. V.4.4. Taylor Series Solution
Chapter V ODE V.4 Power Series Solutio Otober, 8 385 V.4 Power Series Solutio Objetives: After the ompletio of this setio the studet - should reall the power series solutio of a liear ODE with variable
More informationHypothesis Testing. Evaluation of Performance of Learned h. Issues. Trade-off Between Bias and Variance
Hypothesis Testig Empirically evaluatig accuracy of hypotheses: importat activity i ML. Three questios: Give observed accuracy over a sample set, how well does this estimate apply over additioal samples?
More informationSNAP Centre Workshop. Basic Algebraic Manipulation
SNAP Cetre Workshop Basic Algebraic Maipulatio 8 Simplifyig Algebraic Expressios Whe a expressio is writte i the most compact maer possible, it is cosidered to be simplified. Not Simplified: x(x + 4x)
More informationBasic Waves and Optics
Lasers ad appliatios APPENDIX Basi Waves ad Optis. Eletromageti Waves The eletromageti wave osists of osillatig eletri ( E ) ad mageti ( B ) fields. The eletromageti spetrum is formed by the various possible
More informationCHAPTER 10 INFINITE SEQUENCES AND SERIES
CHAPTER 10 INFINITE SEQUENCES AND SERIES 10.1 Sequeces 10.2 Ifiite Series 10.3 The Itegral Tests 10.4 Compariso Tests 10.5 The Ratio ad Root Tests 10.6 Alteratig Series: Absolute ad Coditioal Covergece
More informationN A N A ( ) We re-arrange and collapse the random variables into a set corresponding to the weighted
7- trodutio Note that rom 08bx0v3.do (p6) while rom page 7, ad Title Bo Xu Y = μ T B E N N ( Y ) = ( ) UV N μ Commet: Bo, Write a brie itrodutio explaiig what this doumet will do. You a opy parts rom the
More informationMCT242: Electronic Instrumentation Lecture 2: Instrumentation Definitions
Faculty of Egieerig MCT242: Electroic Istrumetatio Lecture 2: Istrumetatio Defiitios Overview Measuremet Error Accuracy Precisio ad Mea Resolutio Mea Variace ad Stadard deviatio Fiesse Sesitivity Rage
More informationMixtures of Gaussians and the EM Algorithm
Mixtures of Gaussias ad the EM Algorithm CSE 6363 Machie Learig Vassilis Athitsos Computer Sciece ad Egieerig Departmet Uiversity of Texas at Arligto 1 Gaussias A popular way to estimate probability desity
More informationPolynomial Generalizations and Combinatorial Interpretations for Sequences Including the Fibonacci and Pell Numbers
Ope Joural o Discrete Mathematics,,, - http://dxdoiorg/46/odm6 Published Olie Jauary (http://wwwscirporg/oural/odm) Polyomial Geeralizatios ad Combiatorial Iterpretatios or Seueces Icludig the Fiboacci
More informationSequences, Mathematical Induction, and Recursion. CSE 2353 Discrete Computational Structures Spring 2018
CSE 353 Discrete Computatioal Structures Sprig 08 Sequeces, Mathematical Iductio, ad Recursio (Chapter 5, Epp) Note: some course slides adopted from publisher-provided material Overview May mathematical
More informationLinear Regression Models
Liear Regressio Models Dr. Joh Mellor-Crummey Departmet of Computer Sciece Rice Uiversity johmc@cs.rice.edu COMP 528 Lecture 9 15 February 2005 Goals for Today Uderstad how to Use scatter diagrams to ispect
More informationBasic Probability/Statistical Theory I
Basi Probability/Statistial Theory I Epetatio The epetatio or epeted values of a disrete radom variable X is the arithmeti mea of the radom variable s distributio. E[ X ] p( X ) all Epetatio by oditioig
More informationRecurrences: Methods and Examples
Reurrees: Methods ad Examples CSE 30 Algorithms ad Data Strutures Alexadra Stefa Uiversity of exas at Arligto Updated: 308 Summatios Review Review slides o Summatios Reurrees Reursive algorithms It may
More informationNonstandard Lorentz-Einstein transformations
Nostadard Loretz-istei trasformatios Berhard Rothestei 1 ad Stefa Popesu 1) Politehia Uiversity of Timisoara, Physis Departmet, Timisoara, Romaia brothestei@gmail.om ) Siemes AG, rlage, Germay stefa.popesu@siemes.om
More informationCountry Waste Profile Report for Kuwait Reporting year: 2000
Coutry Waste Profile Report for Kuwait Reportig year: 2000 This is a sub-doumet from the report Radioative Waste Maagemet Profiles No 4 a ompilatio of data from the Net Eabled Waste Maagemet Database,
More informationThe Discrete-Time Fourier Transform (DTFT)
EEL: Discrete-Time Sigals ad Systems The Discrete-Time Fourier Trasorm (DTFT) The Discrete-Time Fourier Trasorm (DTFT). Itroductio I these otes, we itroduce the discrete-time Fourier trasorm (DTFT) ad
More informationUnderstanding Samples
1 Will Moroe CS 109 Samplig ad Bootstrappig Lecture Notes #17 August 2, 2017 Based o a hadout by Chris Piech I this chapter we are goig to talk about statistics calculated o samples from a populatio. We
More informationTaylor Polynomials and Approximations - Classwork
Taylor Polyomials ad Approimatios - Classwork Suppose you were asked to id si 37 o. You have o calculator other tha oe that ca do simple additio, subtractio, multiplicatio, or divisio. Fareched\ Not really.
More informationTIME-PERIODIC SOLUTIONS OF A PROBLEM OF PHASE TRANSITIONS
Far East Joural o Mathematical Scieces (FJMS) 6 Pushpa Publishig House, Allahabad, Idia Published Olie: Jue 6 http://dx.doi.org/.7654/ms99947 Volume 99, umber, 6, Pages 947-953 ISS: 97-87 Proceedigs o
More informationPhysics 324, Fall Dirac Notation. These notes were produced by David Kaplan for Phys. 324 in Autumn 2001.
Physics 324, Fall 2002 Dirac Notatio These otes were produced by David Kapla for Phys. 324 i Autum 2001. 1 Vectors 1.1 Ier product Recall from liear algebra: we ca represet a vector V as a colum vector;
More informationChapter 4: Angle Modulation
57 Chapter 4: Agle Modulatio 4.1 Itrodutio to Agle Modulatio This hapter desribes frequey odulatio (FM) ad phase odulatio (PM), whih are both fors of agle odulatio. Agle odulatio has several advatages
More informationName Solutions to Test 2 October 14, 2015
Name Solutios to Test October 4, 05 This test cosists of three parts. Please ote that i parts II ad III, you ca skip oe questio of those offered. The equatios below may be helpful with some problems. Costats
More informationChapter 13, Part A Analysis of Variance and Experimental Design
Slides Prepared by JOHN S. LOUCKS St. Edward s Uiversity Slide 1 Chapter 13, Part A Aalysis of Variace ad Eperimetal Desig Itroductio to Aalysis of Variace Aalysis of Variace: Testig for the Equality of
More informationMOST PEOPLE WOULD RATHER LIVE WITH A PROBLEM THEY CAN'T SOLVE, THAN ACCEPT A SOLUTION THEY CAN'T UNDERSTAND.
XI-1 (1074) MOST PEOPLE WOULD RATHER LIVE WITH A PROBLEM THEY CAN'T SOLVE, THAN ACCEPT A SOLUTION THEY CAN'T UNDERSTAND. R. E. D. WOOLSEY AND H. S. SWANSON XI-2 (1075) STATISTICAL DECISION MAKING Advaced
More informationADVANCED SOFTWARE ENGINEERING
ADVANCED SOFTWARE ENGINEERING COMP 3705 Exercise Usage-based Testig ad Reliability Versio 1.0-040406 Departmet of Computer Ssciece Sada Narayaappa, Aeliese Adrews Versio 1.1-050405 Departmet of Commuicatio
More informationLecture 11: A Fourier Transform Primer
PHYS 34 Fall 1 ecture 11: A Fourier Trasform Primer Ro Reifeberger Birck aotechology Ceter Purdue Uiversity ecture 11 1 f() I may edeavors, we ecouter sigals that eriodically reeat f(t) T t Such reeatig
More informationAnalytic Theory of Probabilities
Aalytic Theory of Probabilities PS Laplace Book II Chapter II, 4 pp 94 03 4 A lottery beig composed of umbered tickets of which r exit at each drawig, oe requires the probability that after i drawigs all
More informationAnalog Filter Synthesis
6 Aalog Filter Sythesis Nam Pham Aubur Uiversity Bogda M. Wilamowsi Aubur Uiversity 6. Itrodutio...6-6. Methods to Sythesize Low-Pass Filter...6- Butterworth Low-Pass Filter Chebyshev Low-Pass Filter Iverse
More informationThe Relative Angle Distribution Function in the Langevin Theory of Dilute Dipoles. Robert D. Nielsen
The Relative Agle Distributio Fuctio i the agevi Theory of Dilute Dipoles Robert D. Nielse ExxoMobil Research ad Egieerig Co., Clito Towship, 545 Route East, Aadale, NJ 0880 robert.ielse@exxomobil.com
More informationIntroduction to Signals and Systems, Part V: Lecture Summary
EEL33: Discrete-Time Sigals ad Systems Itroductio to Sigals ad Systems, Part V: Lecture Summary Itroductio to Sigals ad Systems, Part V: Lecture Summary So far we have oly looked at examples of o-recursive
More informationLinear Associator Linear Layer
Hebbia Learig opic 6 Note: lecture otes by Michael Negevitsky (uiversity of asmaia) Bob Keller (Harvey Mudd College CA) ad Marti Haga (Uiversity of Colorado) are used Mai idea: learig based o associatio
More informationSECTION 2 Electrostatics
SECTION Electrostatics This sectio, based o Chapter of Griffiths, covers effects of electric fields ad forces i static (timeidepedet) situatios. The topics are: Electric field Gauss s Law Electric potetial
More informationTemperature dependence of dark current in a CCD
Portlad State Uiversity PDXSholar Physis Faulty Publiatios ad Presetatios Physis 4-1- Temperature depedee of dark urret i a CCD Ralf Widehor Portlad State Uiversity Morley M. Blouke Portlad State Uiversity
More informationg () n = g () n () f, f n = f () n () x ( n =1,2,3, ) j 1 + j 2 + +nj n = n +2j j n = r & j 1 j 1, j 2, j 3, j 4 = ( 4, 0, 0, 0) f 4 f 3 3!
Higher Derivative o Compositio. Formulas o Higher Derivative o Compositio.. Faà di Bruo's Formula About the ormula o the higher derivative o compositio, the oe by a mathematicia Faà di Bruo i Italy o about
More informationMath 10A final exam, December 16, 2016
Please put away all books, calculators, cell phoes ad other devices. You may cosult a sigle two-sided sheet of otes. Please write carefully ad clearly, USING WORDS (ot just symbols). Remember that the
More informationFourier Series and the Wave Equation
Fourier Series ad the Wave Equatio We start with the oe-dimesioal wave equatio u u =, x u(, t) = u(, t) =, ux (,) = f( x), u ( x,) = This represets a vibratig strig, where u is the displacemet of the strig
More informationZeros of Polynomials
Math 160 www.timetodare.com 4.5 4.6 Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered with fidig the solutios of polyomial equatios of ay degree
More information2.1 (a) The mean free time between collisions using Equation (2.2.4b) is. The distance traveled by drift between collisions is
Chater Mobility (a) The mea ree time betwee ollisios usig Euatio (4b) is m m m m 850 3 se where is gie to be 500 m /Vse (= 005 m /Vse), a m is assume to be m 0 (b) We ee to i the rit eloity irst: 50000m
More informationChE 471 Lecture 10 Fall 2005 SAFE OPERATION OF TUBULAR (PFR) ADIABATIC REACTORS
SAFE OPERATION OF TUBULAR (PFR) ADIABATIC REACTORS I a exothermic reactio the temperature will cotiue to rise as oe moves alog a plug flow reactor util all of the limitig reactat is exhausted. Schematically
More informationFIR Filter Design: Part I
EEL3: Discrete-Time Sigals ad Systems FIR Filter Desig: Part I. Itroductio FIR Filter Desig: Part I I this set o otes, we cotiue our exploratio o the requecy respose o FIR ilters. First, we cosider some
More informationTMA4245 Statistics. Corrected 30 May and 4 June Norwegian University of Science and Technology Department of Mathematical Sciences.
Norwegia Uiversity of Sciece ad Techology Departmet of Mathematical Scieces Corrected 3 May ad 4 Jue Solutios TMA445 Statistics Saturday 6 May 9: 3: Problem Sow desity a The probability is.9.5 6x x dx
More information( ) = p and P( i = b) = q.
MATH 540 Radom Walks Part 1 A radom walk X is special stochastic process that measures the height (or value) of a particle that radomly moves upward or dowward certai fixed amouts o each uit icremet of
More informationB. Maddah ENMG 622 ENMG /20/09
B. Maddah ENMG 6 ENMG 5 5//9 Queueig Theory () Distributio of waitig time i M/M/ Let T q be the waitig time i queue of a ustomer. The it a be show that, ( ) t { q > } =. T t e Let T be the total time of
More informationFrom deterministic regular waves to a random field. From a determinstic regular wave to a deterministic irregular solution
Classiicatio: Iteral Status: Drat z ξ(x,y, w& x w u u& h Particle ositio From determiistic regular waves to a radom ield Sverre Haver, StatoilHydro, Jauary 8 From a determistic regular wave to a determiistic
More informationTrue Nature of Potential Energy of a Hydrogen Atom
True Nature of Potetial Eergy of a Hydroge Atom Koshu Suto Key words: Bohr Radius, Potetial Eergy, Rest Mass Eergy, Classical Electro Radius PACS codes: 365Sq, 365-w, 33+p Abstract I cosiderig the potetial
More informationNonequilibrium Excess Carriers in Semiconductors
Lecture 8 Semicoductor Physics VI Noequilibrium Excess Carriers i Semicoductors Noequilibrium coditios. Excess electros i the coductio bad ad excess holes i the valece bad Ambiolar trasort : Excess electros
More informationln(i G ) 26.1 Review 26.2 Statistics of multiple breakdowns M Rows HBD SBD N Atoms Time
EE650R: Reliability Physics of Naoelectroic Devices Lecture 26: TDDB: Statistics of Multiple Breadows Date: Nov 17, 2006 ClassNotes: Jaydeep P. Kulari Review: Pradeep R. Nair 26.1 Review I the last class
More informationStanding Waves Worksheet
Name Date Period Stadig Waes Worksheet Show your work clearly o a separate page i ecessary. Make a sketch o the problem. Start each solutio with a udametal cocept equatio writte i symbolic ariables. Sole
More informationTopic 9: Sampling Distributions of Estimators
Topic 9: Samplig Distributios of Estimators Course 003, 2018 Page 0 Samplig distributios of estimators Sice our estimators are statistics (particular fuctios of radom variables), their distributio ca be
More informationLecture 1 Probability and Statistics
Wikipedia: Lecture 1 Probability ad Statistics Bejami Disraeli, British statesma ad literary figure (1804 1881): There are three kids of lies: lies, damed lies, ad statistics. popularized i US by Mark
More informationLecture 9: Independent Groups & Repeated Measures t-test
Brittay s ote 4/6/207 Lecture 9: Idepedet s & Repeated Measures t-test Review: Sigle Sample z-test Populatio (o-treatmet) Sample (treatmet) Need to kow mea ad stadard deviatio Problem with this? Sigle
More informationME203 Section 4.1 Forced Vibration Response of Linear System Nov 4, 2002 (1) kx c x& m mg
ME3 Setio 4.1 Fored Vibratio Respose of Liear Syste Nov 4, Whe a liear ehaial syste is exited by a exteral fore, its respose will deped o the for of the exitatio fore F(t) ad the aout of dapig whih is
More informationThe McClelland approximation and the distribution of -electron molecular orbital energy levels
J. Serb. Chem. Soc. 7 (10) 967 973 (007) UDC 54 74+537.87:53.74+539.194 JSCS 369 Origial scietific paper The McClellad approximatio ad the distributio of -electro molecular orbital eergy levels IVAN GUTMAN*
More informationThe Phi Power Series
The Phi Power Series I did this work i about 0 years while poderig the relatioship betwee the golde mea ad the Madelbrot set. I have fially decided to make it available from my blog at http://semresearch.wordpress.com/.
More informationSolutions 3.2-Page 215
Solutios.-Page Problem Fid the geeral solutios i powers of of the differetial equatios. State the reurree relatios ad the guarateed radius of overgee i eah ase. ) Substitutig,, ad ito the differetial equatio
More informationParallel Programming: Speedups and Amdahl s law
Parallel Programmig: Seedus ad Amdahl s law Mike Bailey mjb@cs.oregostate.edu Orego State Uiversity Orego State Uiversity Comuter Grahics seedus.ad.amdahls.law.tx Defiitio of Seedu 2 If you are usig rocessors,
More informationWe are mainly going to be concerned with power series in x, such as. (x)} converges - that is, lims N n
Review of Power Series, Power Series Solutios A power series i x - a is a ifiite series of the form c (x a) =c +c (x a)+(x a) +... We also call this a power series cetered at a. Ex. (x+) is cetered at
More informationRandomized Algorithms I, Spring 2018, Department of Computer Science, University of Helsinki Homework 1: Solutions (Discussed January 25, 2018)
Radomized Algorithms I, Sprig 08, Departmet of Computer Sciece, Uiversity of Helsiki Homework : Solutios Discussed Jauary 5, 08). Exercise.: Cosider the followig balls-ad-bi game. We start with oe black
More informationENGI 4430 Advanced Calculus for Engineering Faculty of Engineering and Applied Science Problem Set 4 Solutions [Numerical Methods]
ENGI 3 Advaced Calculus or Egieerig Facult o Egieerig ad Applied Sciece Problem Set Solutios [Numerical Methods]. Use Simpso s rule with our itervals to estimate I si d a, b, h a si si.889 si 3 si.889
More informationU8L1: Sec Equations of Lines in R 2
MCVU U8L: Sec. 8.9. Equatios of Lies i R Review of Equatios of a Straight Lie (-D) Cosider the lie passig through A (-,) with slope, as show i the diagram below. I poit slope form, the equatio of the lie
More informationLecture 6. Semiconductor physics IV. The Semiconductor in Equilibrium
Lecture 6 Semicoductor physics IV The Semicoductor i Equilibrium Equilibrium, or thermal equilibrium No exteral forces such as voltages, electric fields. Magetic fields, or temperature gradiets are actig
More informationREVERSIBLE NON-FLOW PROCESS CONSTANT VOLUME PROCESS (ISOCHORIC PROCESS) In a constant volume process, he working substance is contained in a rigid
REVERSIBLE NON-FLOW PROCESS CONSTANT VOLUME PROCESS (ISOCHORIC PROCESS) I a ostat olume roess, he workig substae is otaied i a rigid essel, hee the boudaries of the system are immoable, so work aot be
More informationNonlinear regression
oliear regressio How to aalyse data? How to aalyse data? Plot! How to aalyse data? Plot! Huma brai is oe the most powerfull computatioall tools Works differetly tha a computer What if data have o liear
More informationUsing the IML Procedure to Examine the Efficacy of a New Control Charting Technique
Paper 2894-2018 Usig the IML Procedure to Examie the Efficacy of a New Cotrol Chartig Techique Austi Brow, M.S., Uiversity of Norther Colorado; Bryce Whitehead, M.S., Uiversity of Norther Colorado ABSTRACT
More informationPRACTICE PROBLEMS FOR THE FINAL
PRACTICE PROBLEMS FOR THE FINAL Math 36Q Fall 25 Professor Hoh Below is a list of practice questios for the Fial Exam. I would suggest also goig over the practice problems ad exams for Exam ad Exam 2 to
More informationIntroduction to Astrophysics Tutorial 2: Polytropic Models
Itroductio to Astrophysics Tutorial : Polytropic Models Iair Arcavi 1 Summary of the Equatios of Stellar Structure We have arrived at a set of dieretial equatios which ca be used to describe the structure
More information