Aug 25, 2009

NanoTechnology - Video Tutorial and Useful Links

Topics
  1. An Introduction to BioMEMS and Bionanotechnology
  2. Fundamentals of Nanoelectronics
  3. Computational NanoElectronics
  4. Nanoscale Transistors
  5. Nanophotonics
  6. Nanomaterials
  7. Concepts of Quantum Transport
  8. Nanotechnology and the Study of Human Diseases
  9. Fascinating Nanotechnology



An Introduction to BioMEMS and Bionanotechnology
BioMEMS and Bionanotechnology have the potential to make significant impact in a wide range of fields and applications. This lecture series introduces the basic concepts and topics underlying the interdisciplinary areas of BioMEMS and Bionanotechnology. Advances in this field require the knowledge of polymer processing and soft lithography in addition to silicon-inspired fabrication. Since the primary aim of many of these devices and systems is to form sensors for biological and chemical entities, an introduction to DNA, proteins, and microbiology is also essential. These devices and systems are designed to handle fluids at these small scale and hence the basic concepts of microfluidics need to be reviewed. Means to transport fluids and biological entities in these devices are necessary for the proper functioning and design of integrated devices, that can perform complete analysis on biological and chemical samples. These key topics are reviewed in this lecture series to equip the listener to get engaged deeper in these exciting areas of research.


Fundamentals of Nanoelectronics

Lectures contain:
Lecture 1: Energy Level Diagram; Lecture 2: What Makes Electrons Flow?; Lecture 3: Quantum of Conductance; Lecture 4: Charging Effects 1; Lecture 5: Charging Effects 2; Lecture 6: Charging Effect, Towards Ohm's Law; Lecture 7: Hydrogen Atom; Lecture 8: Schrödinger Equation 1; Lecture 9: Schrödinger Equation 2; Lecture 10: Finite Difference Method 1; Lecture 11: Finite Difference Method 2; Lecture 12: Separation of Variables; Lecture 13: Atomic Energy Levels; Lecture 14: Covalent Bonds; Lecture 15a: Basis Functions 1; Lecture 15b: Basis Functions 2; Lecture 15c: Basis Functions 3; Lecture 16: Bandstructure 1; Lecture 17: Bandstructure 2; Lecture 18: Bandstructure 3; Lecture 19: Bandstructure 4; Lecture 20: Reciprocal Lattice; Lecture 21: Graphene Bandstructure; Lecture 22: Carbon Nanotubes; Lecture 23: Subbands; Lecture 24: Density of States; Lecture 25: Density of States: General Approach; Lecture 26: Density of States in Nanostructures; Lecture 27: Minimum Resistance of a Wire 1; Lecture 28: Minimum Resistance of a Wire 2; Lecture 29: Effective Mass Equation; Lecture 30: Quantum Capacitance; Lecture 31: Broadening; Lecture 32: Broadening and Lifetime; Lecture 33: Local Density of States; Lecture 34: Current/Voltage Characteristics; Lecture 35: Transmission; Lecture 36: Coherent Transport; Lecture 37: Wavefunction versus Green's Function; Lecture 38: Ohm's Law; Lecture 39: Coulomb Blockade

Abstract:
The development of "nanotechnology" has made it possible to engineer material and devices on a length scale as small as several nanometers (atomic distances are ~ 0.1 nm). The properties of such "nanostructures" cannot be described in terms of macroscopic parameters like mobility or diffusion coefficient and a microscopic or atomistic viewpoint is called for. The purpose of this course is to convey the conceptual framework that underlies this microscopic viewpoint using examples related to the emerging field of nanoelectronics.


Computational NanoElectronics

Lectures contain:

Introduction to Computational Electronics; Simplified Band-Structure Model; Empirical Pseudopotential Method Description; Choice of the Distribution Function; Relaxation-Time Approximation; Scattering Mechanisms; Numerical Analysis; Drift-Diffusion Model, Part A: Introduction; Drift-Diffusion Model, Part B: Solution Details; Drift-Diffusion Model, Part C: Sharfetter-Gummel, Time-Dependent Simulations; Drift-Diffusion Model, Mobility Modeling; Introduction to DD Modeling with PADRE; Introduction to Silvaco Simulation Software; MOS Capacitors: Description and Semiclassical Simulation With PADRE; What is CMOS Technology Facing?

Abstract:
Scaling of CMOS devices into the nanometer regime leads to increased processing cost. In this regard, the field of Computational Electronics is becoming more and more important because device simulation offers unique possibility to test hypothetical devices which have not been fabricated yet and it also gives unique insight into the device behavior by allowing the observation of phenomena that can not be measured on real devices. The of this class is to introduce the students to all semi-classical semiconductor device modeling techniques that are implemented in either commercial or publicly available software. As such, it should help students to understand when one can use drift-diffusion model and when it is necessary to use hydrodynamic, lattice heating, and even particle-based simulations. A short tutorial on using the Silvaco/PADRE simulation software is included and its purpose is to make users familiar with the syntax used in almost all commercial device simulation software.


Nanoscale Transistors

Lectures contain:

Introductory Lecture (Fall 06); Lecture 1: MOSFET Review; Lecture 2: Introduction to Device Simulation; Lecture 3: 1D MOS Electrostatics; Lecture 4: MOS Capacitors; Lecture 5: Poly Si Gate MOS Capacitors; Lecture 6: Quantum Mechanical Effects; Lecture 7: MOSFET IV, Part I; Lecture 8: MOSFET IV, Part II; Lecture 9: MOSFET IV, Part III; Lecture 10: The Ballistic MOSFET; Lecture 11: The Quasi-ballistic MOSFET; Lecture 12: Subthreshold Conduction; Lecture 13: Threshold Voltage and MOSFET Capacitances; Lecture 14: Effective Mobility; Lecture 15: 2D Electrostatics, Part I; Lecture 16: 2D Electrostatics, Part II; The Limits of CMOS Scaling from a Power-Constrained Technology Optimization Perspective; Lecture 17: Device Scaling; Lecture 18: VT Engineering; Lecture 19: Series Resistance; Lecture 20: MOSFET Leakage; Lecture 21: Gate resistance and Interconnects; Lecture 22: CMOS Process Steps; Lecture 23: CMOS Process Flow; Lecture 24: CMOS Circuits, Part I; Lecture 25: CMOS Circuits, Part I I; Lecture 26: CMOS Limits; Lecture 27: RF CMOS; Lecture 28: Overview of SOI Technology; Lecture 29: SOI Electrostatics; Lecture 30: UTB SOI Electrostatics; Lecture 31: Heterostructure Fundamentals; Lecture 32: Heterojunction Diodes; Lecture 33: Heterojunction Bipolar Transistors; Lecture 34: Heterostructure FETs.

Abstract:
This course examines the device physics of advanced transistors and the process, device, circuit, and systems considerations that enter into the development of new integrated circuit technologies. The course consists of three parts. Part 1 treats MOS and MOSFET fundamentals as well as second order effects such as gate leakage and quantum mechanical effects. Short channel effects, device scaling, and circuit and system considerations are the subject of Part 2. In Part 3, we examine new transistor materials and device structures. The use of computer simulation to examine device issues is an integral part of the course.


Nanophotonics

Lectures contain:
Introductory Lecture; s Lecture 1: Light Interaction with Matter-Review of Maxwell's Equations; s Lecture 2: Dispersion in Materials; s Lecture 3: Optical Properties of Insulators, Semiconductors and Metals; s Lecture 4: Electromagnetic Properties of Molecules, Nano- and Microscopic Particles; s Lecture 5: Photonic Crystals - Introduction; s Lecture 6: Basic Properties of Electromagnetic Effects in Periodic Media; s Lecture 7: Photonic Crystal Waveguides; s Lecture 8: Photonic Crystals Fibers; s Lecture 9: Introduction to Metal Optics; s Lecture 10: Surface Plasmon Excitation; s Lecture 11: Guiding Light Along Nanoparticle Arrays; Nano Scale Optics with Nearfield Scanning Optical Microscopy (NSOM); s Lecture 14: Metamaterials: Giving Light the Second Hand, Part 1; s Lecture 15: Metamaterials: Giving Light the Second Hand, Part 2.

Abstract:
The course covers nanoscale processes and devices and their applications for manipulating light on the nanoscale. The following topics will be covered: Fundamentals, Maxwell’s equations, light-matter interaction, dispersion, EM properties of nanostructures, etc. Photonic crystals, Photonic crystal fibers, Photonic nanocircuits, Metal optics, Manipulating light with plasmonic nanostructures, Plasmonic nano-sensors, Near-field optics, Metamaterials, negative refractive index and super-resolution.


Nanomaterials

Lectures contain:
Lecture 1: Film Deposition Methods; Lecture 2: Lithography; Lecture 3: Advanced Lithography; Lecture 4: Atom Optics; Lecture 5: Chemical Synthesis; Lecture 6: Carbon Nanomaterials, part 1; Lecture 7: Carbon Nanomaterials, part 2; Lecture 8: Carbon Nanomaterials, part 3; Lecture 9: SPM Lithography, part 1; Lecture 10: SPM Lithography, part 2; Lecture 11: SPM Lithography, part 3; Lecture 12: Nanoscale CMOS, part 1; Lecture 13: Nanoscale CMOS, part 2; Lecture 14: Nanoscale Alternatives; Lecture 15: Nanomagnetism, part 1; Lecture 16: Nanomagnetism, part 2; Lecture 17: Nanoscale Thermal Properties; Lecture 18: Nanoelectromechanical Systems, part 1; Lecture 19: Nanoelectromechanical Systems, part 2.

Abstract:
"Nanomaterials," is an interdisciplinary introduction to processing, structure, and properties of materials at the nanometer length scale. The course will cover recent breakthroughs and assess the impact of this burgeoning field. Specific nanofabrication topics include epitaxy, beam lithographies, self- assembly, biocatalytic synthesis, atom optics, and scanning probe lithography. The unique size- dependent properties (mechanical, thermal, chemical, optical, electronic, and magnetic) that result from nanoscale structure will be explored in the context of technological applications including computation, magnetic storage, sensors, and actuators.


Concepts of Quantum Transport

Lectures contain:
Introduction; Lecture 1: Nanodevices and Maxwell's Demon; Lecture 2: Electrical Resistance - A Simple Model; Lecture 3: Probabilities, Wavefunctions and Green Functions; Lecture 4: Coulomb blockade and Fock space; McCoy Lecture: Nanodevices and Maxwell's Demon; PASI Lecture: Nanodevices and Maxwell's Demon, Part 1; PASI Lecture: Nanodevices and Maxwell's Demon, Part 2

Abstract:
How does the resistance of a conductor change as we shrink its length all the way down to a few atoms? This is a question that has intrigued scientists for a long time, but it is only during the last twenty years that it has become possible for experimentalists to provide clear answers, leading to enormous progress in our understanding. There is also great applied interest in this question at this time, since every computer we buy has about a billion transistors that rely on controlling the flow of electrons through a conductor a few hundred atoms in length.

In this series of four lectures (total length ~ 5-6 hours) Datta attempts to convey the physics of current flow in nanodevices in simple physical terms, stressing clearly what is understood and what is not. In Lecture 1, "Nanodevices and Maxwell's demon", Datta attempts to convey the subtle interplay of dynamics and thermodynamics that is the hallmark of transport physics using an electronic device reminiscent of the demon imagined by Maxwell in the nineteenth century to illustrate the limitations of the second law of thermodynamics. Lecture 2 ("Electrical Resistance: A simple model") explains many important concepts like the quantum of conductance using a simple model that Datta uses routinely to teach an undergraduate class on Nanoelectronics. Lecture 3 ("Probabilities, wavefunctions and Green's functions) describes the full quantum transport model touching on some of the most advanced concepts of non-equilibrium statistical mechanics including the Boltzmann equation and the non-equilibrium Green function (NEGF) formalism and yet keeping the discussion accessible to advanced undergraduates. Finally in Lecture 4 ("Coulomb blockade and Fock space") Datta explains the limitations of the current models and speculates on possible directions in which the field might evolve.

Overall the objective is to convey an appreciation for state-of-the-art quantum transport models far from equilibrium, assuming no significant background in quantum mechanics or statistical mechanics.



Quantum Transport: Atom to Transistor

Lectures contain:
Lecture 1: Energy Level Diagram; Lecture 2: What Makes Electrons Flow?; Lecture 3: The Quantum of Conductance; Lecture 4: Charging/Coulomb Blockade; Lecture 5: Summary/Towards Ohm's Law; Lecture 6: Schrodinger Equation: Basic Concepts; Lecture 7: Schrodinger Equation: Method of Finite Differences; Lecture 8: Schrodinger Equation: Examples; Lecture 9: Self Consistent Field: Basic Concept; Lecture 10: Self Consistent Field: Relation to the Multi-Electron Picture; Lecture 11: Self Consistent Field: Bonding; Lecture 12: Basis Functions: As a Computatinal Tool; Lecture 13: Basis Functions: As a Conceptual Tool; Lecture 14: Basis Functions: Density Matrix I; Lecture 15: Basis Functions: Density Matrix II; Lecture 16: Band Structure: Toy Examples; Lecture 17: Band Structure: Beyond 1-D; Lecture 18: Band Structure: 3-D Solids; Lecture 19: Band Structure: Prelude to Sub-Bands; Lecture 20: Subbands: Quantum Wells, Wires, Dots and Nano-Tubes; Lecture 21: Subbands: Density of States; Lecture 22: Subbands: Minimum Resistance of a Wire; Lecture 23: Capacitance: Model Hamiltonian; Lecture 24: Capacitance: Electron Density; Lecture 25: Capacitance: Quantum vs. Electrostatic Capacitance; Lecture 26: Level Broadening: Open Systems and Local Density of States; Lecture 27: Level Broadening: Self Energy; Lecture 28: Level Broadening: Lifetime; Lecture 29: Level Broadening: Irreversibility; Lecture 30: Coherent Transport: Overview; Lecture 31: Coherent Transport: Transmission and Examples; Lecture 32: Coherent Transport: Non-Equilibrium Density Matrix; Lecture 33: Coherent Transport: Inflow/Outflow; Lecture 34: Non-Coherent Transport: Why does an Atom Emit Light?; Lecture 35: Non-Coherent Transport: Radiative Lifetime; Lecture 36: Non-Coherent Transport: Radiative Transitions; Lecture 37: Non-Coherent Transport: Phonons, Emission and Absorption; Lecture 38: Non-Coherent Transport: Inflow/Outflow; Lecture 39: Atom to Transistor: "Physics" of Ohm's Law; Lecture 40: Self Consistent Field Method and Its Limitations; Lecture 41: Coulomb Blockade; Lecture 41a: Coulomb Blockade; Lecture 42: Spin

Abstract:
The development of "nanotechnology" has made it possible to engineer materials and devices on a length scale as small as several nanometers (atomic distances are ~ 0.1 nm). The properties of such "nanostructures" cannot be described in terms of macroscopic parameters like mobility and diffusion coefficient and a microscopic or atomistic viewpoint is called for. The purpose of this course is to convey the conceptual framework that underlies this microscopic theory of matter which developed in course of the 20th century following the advent of quantum mechanics. However, this requires us to discuss a lot more than just quantum mechanics - it requires an appreciation of some of the most advanced concepts of non-equilibrium statistical mechanics. Traditionally these topics are spread out over many physics/ chemistry courses that take many semesters to cover. Our aim is to condense the essential concepts into a one semester course using electrical engineering related examples. The only background we assume is matrix algebra including familiarity with MATLAB (or an equivalent mathematical software package). We use MATLAB-based numerical examples to provide concrete illustrations and we strongly recommend that the students set up their own computer program on a PC to reproduce the results. This hands-on experience is needed to grasp such deep and diverse concepts in so short a time.


These lectures were found via NanoHub website which is a web-based resource for research, education, and collaboration in nanotechnology, is an initiative of the NSF-funded Network for Computational Nanotechnology (NCN).
They have many more video lectures, seminar videos teaching materials, just visit their website!


And here are some MIT World's nanotechnology video courses/lectures:

Taking Nanotechnology from the Laboratory to the Soldier

About the lecture:
A U.S. Army soldier carries more than 100 pounds of gear into battle. What can be done to lighten the load, while still providing maximum protection? Edwin Thomas, Director of MIT’s new Institute for Soldier Nanotechnologies, describes an alternative to the past practice of “dressing up a soldier like a Christmas tree”. He describes instead, a dynamic battle suit that wards off bullets and biochemical threats while providing real-time data on the soldier’s medical condition. Thomas, who spent time training for this project at Fort Polk, explains how interdisciplinary teams are exploring nanomaterial designs that could also benefit civilian emergency responders.



Nanotechnology and the Study of Human Diseases

About the lecture:

Subra Suresh fleshes out the promise of nanotechnology, at least in regard to our understanding of disease. His talk, which focuses on malaria and its impact on red blood cells, demonstrates how the fields of engineering, biology and medicine are converging.

To function properly, he explains, a red blood cell -- eight micrometers in diameter or 1/10th the thickness of a human hair -- must be able to squeeze through three micrometer openings in blood vessels. Working with a “laser tweezer” and two tiny (nano-sized) glass beads, Suresh can apply pressure to stretch single cells so that they become thin enough to fit through small openings. He uses a computer to simulate in three dimensions how red blood cells might fold and lengthen under normal conditions in the human body.



Google's Video has the following lectures on nanotechnology:

Nanowires and Nanocrystals for Nanotechnology
Lecture description:
Nanowires and nanocrystals represent important nanomaterials with one-dimensional and zero-dimensional morphology, respectively. Here I will give an overview on the research about how these nanomaterials impact the critical applications in faster transistors, smaller nonvolatile memory devices, efficient solar energy conversion, high-energy battery and nanobiotechnology.


Nanotechnology: Past, Present and Future
Lecture description:
Nanotechnology is little-known to the general public, but in the science and policy community its promise is exciting. What are the promises and pitfalls of this new field? How is it going to help the field of medicine? What are the implications for our economy? Join us as leaders in the field discuss the very real hopes and concerns for nanotechnology applied to aging-related research.


Fascinating Nanotechnology

And finally BBC's Audio Lectures "The Triumph of Technology"


NanoTechnology - Video Tutorial and Useful Links

Topics
  1. An Introduction to BioMEMS and Bionanotechnology
  2. Fundamentals of Nanoelectronics
  3. Computational NanoElectronics
  4. Nanoscale Transistors
  5. Nanophotonics
  6. Nanomaterials
  7. Concepts of Quantum Transport
  8. Nanotechnology and the Study of Human Diseases
  9. Fascinating Nanotechnology



An Introduction to BioMEMS and Bionanotechnology
BioMEMS and Bionanotechnology have the potential to make significant impact in a wide range of fields and applications. This lecture series introduces the basic concepts and topics underlying the interdisciplinary areas of BioMEMS and Bionanotechnology. Advances in this field require the knowledge of polymer processing and soft lithography in addition to silicon-inspired fabrication. Since the primary aim of many of these devices and systems is to form sensors for biological and chemical entities, an introduction to DNA, proteins, and microbiology is also essential. These devices and systems are designed to handle fluids at these small scale and hence the basic concepts of microfluidics need to be reviewed. Means to transport fluids and biological entities in these devices are necessary for the proper functioning and design of integrated devices, that can perform complete analysis on biological and chemical samples. These key topics are reviewed in this lecture series to equip the listener to get engaged deeper in these exciting areas of research.


Fundamentals of Nanoelectronics

Lectures contain:
Lecture 1: Energy Level Diagram; Lecture 2: What Makes Electrons Flow?; Lecture 3: Quantum of Conductance; Lecture 4: Charging Effects 1; Lecture 5: Charging Effects 2; Lecture 6: Charging Effect, Towards Ohm's Law; Lecture 7: Hydrogen Atom; Lecture 8: Schrödinger Equation 1; Lecture 9: Schrödinger Equation 2; Lecture 10: Finite Difference Method 1; Lecture 11: Finite Difference Method 2; Lecture 12: Separation of Variables; Lecture 13: Atomic Energy Levels; Lecture 14: Covalent Bonds; Lecture 15a: Basis Functions 1; Lecture 15b: Basis Functions 2; Lecture 15c: Basis Functions 3; Lecture 16: Bandstructure 1; Lecture 17: Bandstructure 2; Lecture 18: Bandstructure 3; Lecture 19: Bandstructure 4; Lecture 20: Reciprocal Lattice; Lecture 21: Graphene Bandstructure; Lecture 22: Carbon Nanotubes; Lecture 23: Subbands; Lecture 24: Density of States; Lecture 25: Density of States: General Approach; Lecture 26: Density of States in Nanostructures; Lecture 27: Minimum Resistance of a Wire 1; Lecture 28: Minimum Resistance of a Wire 2; Lecture 29: Effective Mass Equation; Lecture 30: Quantum Capacitance; Lecture 31: Broadening; Lecture 32: Broadening and Lifetime; Lecture 33: Local Density of States; Lecture 34: Current/Voltage Characteristics; Lecture 35: Transmission; Lecture 36: Coherent Transport; Lecture 37: Wavefunction versus Green's Function; Lecture 38: Ohm's Law; Lecture 39: Coulomb Blockade

Abstract:
The development of "nanotechnology" has made it possible to engineer material and devices on a length scale as small as several nanometers (atomic distances are ~ 0.1 nm). The properties of such "nanostructures" cannot be described in terms of macroscopic parameters like mobility or diffusion coefficient and a microscopic or atomistic viewpoint is called for. The purpose of this course is to convey the conceptual framework that underlies this microscopic viewpoint using examples related to the emerging field of nanoelectronics.


Computational NanoElectronics

Lectures contain:

Introduction to Computational Electronics; Simplified Band-Structure Model; Empirical Pseudopotential Method Description; Choice of the Distribution Function; Relaxation-Time Approximation; Scattering Mechanisms; Numerical Analysis; Drift-Diffusion Model, Part A: Introduction; Drift-Diffusion Model, Part B: Solution Details; Drift-Diffusion Model, Part C: Sharfetter-Gummel, Time-Dependent Simulations; Drift-Diffusion Model, Mobility Modeling; Introduction to DD Modeling with PADRE; Introduction to Silvaco Simulation Software; MOS Capacitors: Description and Semiclassical Simulation With PADRE; What is CMOS Technology Facing?

Abstract:
Scaling of CMOS devices into the nanometer regime leads to increased processing cost. In this regard, the field of Computational Electronics is becoming more and more important because device simulation offers unique possibility to test hypothetical devices which have not been fabricated yet and it also gives unique insight into the device behavior by allowing the observation of phenomena that can not be measured on real devices. The of this class is to introduce the students to all semi-classical semiconductor device modeling techniques that are implemented in either commercial or publicly available software. As such, it should help students to understand when one can use drift-diffusion model and when it is necessary to use hydrodynamic, lattice heating, and even particle-based simulations. A short tutorial on using the Silvaco/PADRE simulation software is included and its purpose is to make users familiar with the syntax used in almost all commercial device simulation software.


Nanoscale Transistors

Lectures contain:

Introductory Lecture (Fall 06); Lecture 1: MOSFET Review; Lecture 2: Introduction to Device Simulation; Lecture 3: 1D MOS Electrostatics; Lecture 4: MOS Capacitors; Lecture 5: Poly Si Gate MOS Capacitors; Lecture 6: Quantum Mechanical Effects; Lecture 7: MOSFET IV, Part I; Lecture 8: MOSFET IV, Part II; Lecture 9: MOSFET IV, Part III; Lecture 10: The Ballistic MOSFET; Lecture 11: The Quasi-ballistic MOSFET; Lecture 12: Subthreshold Conduction; Lecture 13: Threshold Voltage and MOSFET Capacitances; Lecture 14: Effective Mobility; Lecture 15: 2D Electrostatics, Part I; Lecture 16: 2D Electrostatics, Part II; The Limits of CMOS Scaling from a Power-Constrained Technology Optimization Perspective; Lecture 17: Device Scaling; Lecture 18: VT Engineering; Lecture 19: Series Resistance; Lecture 20: MOSFET Leakage; Lecture 21: Gate resistance and Interconnects; Lecture 22: CMOS Process Steps; Lecture 23: CMOS Process Flow; Lecture 24: CMOS Circuits, Part I; Lecture 25: CMOS Circuits, Part I I; Lecture 26: CMOS Limits; Lecture 27: RF CMOS; Lecture 28: Overview of SOI Technology; Lecture 29: SOI Electrostatics; Lecture 30: UTB SOI Electrostatics; Lecture 31: Heterostructure Fundamentals; Lecture 32: Heterojunction Diodes; Lecture 33: Heterojunction Bipolar Transistors; Lecture 34: Heterostructure FETs.

Abstract:
This course examines the device physics of advanced transistors and the process, device, circuit, and systems considerations that enter into the development of new integrated circuit technologies. The course consists of three parts. Part 1 treats MOS and MOSFET fundamentals as well as second order effects such as gate leakage and quantum mechanical effects. Short channel effects, device scaling, and circuit and system considerations are the subject of Part 2. In Part 3, we examine new transistor materials and device structures. The use of computer simulation to examine device issues is an integral part of the course.


Nanophotonics

Lectures contain:
Introductory Lecture; s Lecture 1: Light Interaction with Matter-Review of Maxwell's Equations; s Lecture 2: Dispersion in Materials; s Lecture 3: Optical Properties of Insulators, Semiconductors and Metals; s Lecture 4: Electromagnetic Properties of Molecules, Nano- and Microscopic Particles; s Lecture 5: Photonic Crystals - Introduction; s Lecture 6: Basic Properties of Electromagnetic Effects in Periodic Media; s Lecture 7: Photonic Crystal Waveguides; s Lecture 8: Photonic Crystals Fibers; s Lecture 9: Introduction to Metal Optics; s Lecture 10: Surface Plasmon Excitation; s Lecture 11: Guiding Light Along Nanoparticle Arrays; Nano Scale Optics with Nearfield Scanning Optical Microscopy (NSOM); s Lecture 14: Metamaterials: Giving Light the Second Hand, Part 1; s Lecture 15: Metamaterials: Giving Light the Second Hand, Part 2.

Abstract:
The course covers nanoscale processes and devices and their applications for manipulating light on the nanoscale. The following topics will be covered: Fundamentals, Maxwell’s equations, light-matter interaction, dispersion, EM properties of nanostructures, etc. Photonic crystals, Photonic crystal fibers, Photonic nanocircuits, Metal optics, Manipulating light with plasmonic nanostructures, Plasmonic nano-sensors, Near-field optics, Metamaterials, negative refractive index and super-resolution.


Nanomaterials

Lectures contain:
Lecture 1: Film Deposition Methods; Lecture 2: Lithography; Lecture 3: Advanced Lithography; Lecture 4: Atom Optics; Lecture 5: Chemical Synthesis; Lecture 6: Carbon Nanomaterials, part 1; Lecture 7: Carbon Nanomaterials, part 2; Lecture 8: Carbon Nanomaterials, part 3; Lecture 9: SPM Lithography, part 1; Lecture 10: SPM Lithography, part 2; Lecture 11: SPM Lithography, part 3; Lecture 12: Nanoscale CMOS, part 1; Lecture 13: Nanoscale CMOS, part 2; Lecture 14: Nanoscale Alternatives; Lecture 15: Nanomagnetism, part 1; Lecture 16: Nanomagnetism, part 2; Lecture 17: Nanoscale Thermal Properties; Lecture 18: Nanoelectromechanical Systems, part 1; Lecture 19: Nanoelectromechanical Systems, part 2.

Abstract:
"Nanomaterials," is an interdisciplinary introduction to processing, structure, and properties of materials at the nanometer length scale. The course will cover recent breakthroughs and assess the impact of this burgeoning field. Specific nanofabrication topics include epitaxy, beam lithographies, self- assembly, biocatalytic synthesis, atom optics, and scanning probe lithography. The unique size- dependent properties (mechanical, thermal, chemical, optical, electronic, and magnetic) that result from nanoscale structure will be explored in the context of technological applications including computation, magnetic storage, sensors, and actuators.


Concepts of Quantum Transport

Lectures contain:
Introduction; Lecture 1: Nanodevices and Maxwell's Demon; Lecture 2: Electrical Resistance - A Simple Model; Lecture 3: Probabilities, Wavefunctions and Green Functions; Lecture 4: Coulomb blockade and Fock space; McCoy Lecture: Nanodevices and Maxwell's Demon; PASI Lecture: Nanodevices and Maxwell's Demon, Part 1; PASI Lecture: Nanodevices and Maxwell's Demon, Part 2

Abstract:
How does the resistance of a conductor change as we shrink its length all the way down to a few atoms? This is a question that has intrigued scientists for a long time, but it is only during the last twenty years that it has become possible for experimentalists to provide clear answers, leading to enormous progress in our understanding. There is also great applied interest in this question at this time, since every computer we buy has about a billion transistors that rely on controlling the flow of electrons through a conductor a few hundred atoms in length.

In this series of four lectures (total length ~ 5-6 hours) Datta attempts to convey the physics of current flow in nanodevices in simple physical terms, stressing clearly what is understood and what is not. In Lecture 1, "Nanodevices and Maxwell's demon", Datta attempts to convey the subtle interplay of dynamics and thermodynamics that is the hallmark of transport physics using an electronic device reminiscent of the demon imagined by Maxwell in the nineteenth century to illustrate the limitations of the second law of thermodynamics. Lecture 2 ("Electrical Resistance: A simple model") explains many important concepts like the quantum of conductance using a simple model that Datta uses routinely to teach an undergraduate class on Nanoelectronics. Lecture 3 ("Probabilities, wavefunctions and Green's functions) describes the full quantum transport model touching on some of the most advanced concepts of non-equilibrium statistical mechanics including the Boltzmann equation and the non-equilibrium Green function (NEGF) formalism and yet keeping the discussion accessible to advanced undergraduates. Finally in Lecture 4 ("Coulomb blockade and Fock space") Datta explains the limitations of the current models and speculates on possible directions in which the field might evolve.

Overall the objective is to convey an appreciation for state-of-the-art quantum transport models far from equilibrium, assuming no significant background in quantum mechanics or statistical mechanics.



Quantum Transport: Atom to Transistor

Lectures contain:
Lecture 1: Energy Level Diagram; Lecture 2: What Makes Electrons Flow?; Lecture 3: The Quantum of Conductance; Lecture 4: Charging/Coulomb Blockade; Lecture 5: Summary/Towards Ohm's Law; Lecture 6: Schrodinger Equation: Basic Concepts; Lecture 7: Schrodinger Equation: Method of Finite Differences; Lecture 8: Schrodinger Equation: Examples; Lecture 9: Self Consistent Field: Basic Concept; Lecture 10: Self Consistent Field: Relation to the Multi-Electron Picture; Lecture 11: Self Consistent Field: Bonding; Lecture 12: Basis Functions: As a Computatinal Tool; Lecture 13: Basis Functions: As a Conceptual Tool; Lecture 14: Basis Functions: Density Matrix I; Lecture 15: Basis Functions: Density Matrix II; Lecture 16: Band Structure: Toy Examples; Lecture 17: Band Structure: Beyond 1-D; Lecture 18: Band Structure: 3-D Solids; Lecture 19: Band Structure: Prelude to Sub-Bands; Lecture 20: Subbands: Quantum Wells, Wires, Dots and Nano-Tubes; Lecture 21: Subbands: Density of States; Lecture 22: Subbands: Minimum Resistance of a Wire; Lecture 23: Capacitance: Model Hamiltonian; Lecture 24: Capacitance: Electron Density; Lecture 25: Capacitance: Quantum vs. Electrostatic Capacitance; Lecture 26: Level Broadening: Open Systems and Local Density of States; Lecture 27: Level Broadening: Self Energy; Lecture 28: Level Broadening: Lifetime; Lecture 29: Level Broadening: Irreversibility; Lecture 30: Coherent Transport: Overview; Lecture 31: Coherent Transport: Transmission and Examples; Lecture 32: Coherent Transport: Non-Equilibrium Density Matrix; Lecture 33: Coherent Transport: Inflow/Outflow; Lecture 34: Non-Coherent Transport: Why does an Atom Emit Light?; Lecture 35: Non-Coherent Transport: Radiative Lifetime; Lecture 36: Non-Coherent Transport: Radiative Transitions; Lecture 37: Non-Coherent Transport: Phonons, Emission and Absorption; Lecture 38: Non-Coherent Transport: Inflow/Outflow; Lecture 39: Atom to Transistor: "Physics" of Ohm's Law; Lecture 40: Self Consistent Field Method and Its Limitations; Lecture 41: Coulomb Blockade; Lecture 41a: Coulomb Blockade; Lecture 42: Spin

Abstract:
The development of "nanotechnology" has made it possible to engineer materials and devices on a length scale as small as several nanometers (atomic distances are ~ 0.1 nm). The properties of such "nanostructures" cannot be described in terms of macroscopic parameters like mobility and diffusion coefficient and a microscopic or atomistic viewpoint is called for. The purpose of this course is to convey the conceptual framework that underlies this microscopic theory of matter which developed in course of the 20th century following the advent of quantum mechanics. However, this requires us to discuss a lot more than just quantum mechanics - it requires an appreciation of some of the most advanced concepts of non-equilibrium statistical mechanics. Traditionally these topics are spread out over many physics/ chemistry courses that take many semesters to cover. Our aim is to condense the essential concepts into a one semester course using electrical engineering related examples. The only background we assume is matrix algebra including familiarity with MATLAB (or an equivalent mathematical software package). We use MATLAB-based numerical examples to provide concrete illustrations and we strongly recommend that the students set up their own computer program on a PC to reproduce the results. This hands-on experience is needed to grasp such deep and diverse concepts in so short a time.


These lectures were found via NanoHub website which is a web-based resource for research, education, and collaboration in nanotechnology, is an initiative of the NSF-funded Network for Computational Nanotechnology (NCN).
They have many more video lectures, seminar videos teaching materials, just visit their website!


And here are some MIT World's nanotechnology video courses/lectures:

Taking Nanotechnology from the Laboratory to the Soldier

About the lecture:
A U.S. Army soldier carries more than 100 pounds of gear into battle. What can be done to lighten the load, while still providing maximum protection? Edwin Thomas, Director of MIT’s new Institute for Soldier Nanotechnologies, describes an alternative to the past practice of “dressing up a soldier like a Christmas tree”. He describes instead, a dynamic battle suit that wards off bullets and biochemical threats while providing real-time data on the soldier’s medical condition. Thomas, who spent time training for this project at Fort Polk, explains how interdisciplinary teams are exploring nanomaterial designs that could also benefit civilian emergency responders.



Nanotechnology and the Study of Human Diseases

About the lecture:

Subra Suresh fleshes out the promise of nanotechnology, at least in regard to our understanding of disease. His talk, which focuses on malaria and its impact on red blood cells, demonstrates how the fields of engineering, biology and medicine are converging.

To function properly, he explains, a red blood cell -- eight micrometers in diameter or 1/10th the thickness of a human hair -- must be able to squeeze through three micrometer openings in blood vessels. Working with a “laser tweezer” and two tiny (nano-sized) glass beads, Suresh can apply pressure to stretch single cells so that they become thin enough to fit through small openings. He uses a computer to simulate in three dimensions how red blood cells might fold and lengthen under normal conditions in the human body.



Google's Video has the following lectures on nanotechnology:

Nanowires and Nanocrystals for Nanotechnology
Lecture description:
Nanowires and nanocrystals represent important nanomaterials with one-dimensional and zero-dimensional morphology, respectively. Here I will give an overview on the research about how these nanomaterials impact the critical applications in faster transistors, smaller nonvolatile memory devices, efficient solar energy conversion, high-energy battery and nanobiotechnology.


Nanotechnology: Past, Present and Future
Lecture description:
Nanotechnology is little-known to the general public, but in the science and policy community its promise is exciting. What are the promises and pitfalls of this new field? How is it going to help the field of medicine? What are the implications for our economy? Join us as leaders in the field discuss the very real hopes and concerns for nanotechnology applied to aging-related research.


Fascinating Nanotechnology

And finally BBC's Audio Lectures "The Triumph of Technology"


Computer Science - Video Lectures and Full Video Courses

Computer Science : Topics
  • C Programming
  • Essential Concepts of Computer Science
  • Principles of Computing
  • Introduction to Web Design
  • Client Side Web Programming
  • Server-Side Web Development
  • Visual Basic .NET
  • ASP.NET
  • ASP.Net Video Course
  • Advanced Programming
  • Programming Concepts and Data
  • Data Analysis Using Spread Sheets
  • XML with Java
  • Algorithms for Nearest Neighbor Search
  • Similarity Search: A Web Perspective
  • Functional Programming Seminar
  • Design Patterns as Higher-Order Datatype Generic Programs



C Programming (N305, Indiana and Purdue Universities)

Course topics:
Introduction to Computers: Hardware and Languages. Programming: First C Program. Mixing Data Types. Basic IO: printf() and scanf(). Variable Declarations, Data Types, Expressions: Variables and Operators. Assignments. Algorithms. Standard C Statements. Functions: Declarations. Information Representation: Positive Integers, Negative Integer Representation, Floating Point Representation, Characters and Images, Machine Instructions. Arrays: Strings and Multidimensional Arrays. Literals and Variables.



Essential Concepts of Computer Science (N301, Indiana and Purdue Universities)


Course topics:
History of Computing. Analog and Digital Representation. Binary Notation. Extending Binary. Two's Complement Notation. Floating Point Notation. Basic Logic Gates. Building a Half Adder. Building a Full Adder. Building a Subtracter. Building an ALU. Von Neumann Architectue. The Fetch-Execute Cycle. Basic Machine Language. Repetition in Machine Language. Beginning Algorithms. Branching Mechanisms. Looping. Complexity in Algorithms. Measuring Complexity. Encapsulation. Software Engineering. Software Engineering Models.



Principles of Computing (N100, Indiana and Purdue Universities)


Course topics:
Basic problem-solving with STAIR (Stating the problem, Tools, Algorithms, Implementation, Refinement). The universal information manipulator. Lights, Legos, and Numbers. Converting from binary to and from base 10. Basic logic gates. Storing data in ABNIAC. ASCII representation in ABNIAC. Addition and looping in ABNIAC.



Introduction to Web Design (N241, Indiana and Purdue Universities)


Course topics:
Basic HTML. Validation. CSS. Fonts and Colors in CSS. Binary, Decimal, Octal, Hex. Internet Addressing. Linux. Overview of Unix. Basic Unix Commands. Permissions. Colors and Images. Science of Colors. GIF. Learning Emacs. XHTML Images, Links, and Lists. Layout with CSS. Buttons in CSS. CSS Layout with Float. Tables. Cross-Browser CSS. Adding Audio. Multimedia With Flash. Multimedia with Wax. Basic Image Swapping. Rollover Buttons. Extending HTML.



Client Side Web Programming (N341, Indiana and Purdue Universities)


Course topics:
Program Development. Documenting Your Code. Introducing Programming. Object Oriented Concepts. Working with Variables. Dialogue Windows. String Objects. Number and Math Objects. If-Then-Else Structures. Switch Statements. Complex Conditions. Conditional Loops. Introducing Arrays. Multidimensional Arrays. JavaScript Modularity. Browser Objects. Introducing DOM. Regular Expressions. JavaScript and Forms. Form Validation. Window Object. Document Object. Cascading Style Sheets. Styles with JavaScript. Cookies.



Server-Side Web Development (N342, Indiana and Purdue Universities)


Course topics:
Intro to Server-Side Programming. Programming on the Web Server. Installing Apache on Windows. Installing PHP in Windows. Configuring PHP. Installing an IDE. Creating your 1st PHP Program. Preparing your Code. Using Variables. Complex String Variables. Responding to HTML Forms. Responding to Complex Forms. Creating Random Numbers. If Statement. Functions. Function Parameters. Variable Scope. Persistence. For and While Loops. Basic Arrays. Responding to Checkboxes. Associative Arrays. Multidimensional Arrays. Multi-Array. String Manipulation. Saving and Loading Files. Files. Directories. Mail. Using Regular Expressions. Introducing MySQL. Tables. Queries. Connecting to a Database within PHP. Examining Entities and Relationships. Joins. Innerjoins. Many to Many Joins.



Visual Basic .NET (N331, Indiana and Purdue Universities)


Course topics:
Inside Visual Studio. Buttons. Labels. Text Boxes. Check Boxes. List Boxes. Combo Boxes. Five Programming Steps. Variables. Branching. If. Then. Else. Looping. Do. While. For. Next. Arrays. Menus.



ASP.NET (N431, Indiana and Purdue Universities)


Course topics:
.NET Intro. Web Controls. Form Validation. Required Field Validator. Specialized Validators. Text Files vs Databases. Database Introduction. SQL Introduction. Insert. Update. Data Binding. Data List. Data Grid. Data Set Sorting. Tracking User Sessions. Session States. Caching. Error Handling. Forms-Based Authentication. Security. Local Encryption. Sending Mail.



Advanced Programming (N335, Indiana and Purdue Universities)


Course topics:
What is .NET. Programming Intro. Object Orientation. .Net Namespaces. Data Type. Strings. Dates. Creating a Class. Polymorphism. Inheritance. Creating Folders. Multithreading. SQL Overview. Data Wizards. Data Sets.



Programming Concepts and Data (N201, Indiana and Purdue Universities)


Course topics:
Problem Solving. Background, History, and Fundamentals of Computing. Working With HTML. History of Programming Languages. Machine Language. Miracle. Conditions. Using Loops. Javascript. Functions. Working with Arrays. Introduction to Databases.



Data Analysis Using Spread Sheets (N207, Indiana and Purdue Universities)


Course topics:
Introduction to STAIR. Computer Hardware. Binary, Hexidecimal, and ASCII. Computer Software. Computer Security. Webpages, Websites, and E-Commerce. Databases. Introduction to Spreadsheets. Charts. Univariate Data Analysis. Multivariate Data Analysis. Regression.



XML with Java (E-259, Harvard University)


Course description:
This course introduces XML as a key enabling technology in Java-based applications. Students learn the fundamentals of XML and its derivatives, including DTD, SVG, XML Schema, XPath, XQuery, XSL-FO, and XSLT. Students also gain experience with programmatic interfaces to XML like SAX and DOM, standard APIs like JAXP and TrAX, and industry-standard software like Ant, Tomcat, Xerces, and Xalan. The course acquaints students with J2EE, including JavaServer Pages (JSP) and Java Servlet, and also explores HTTP, SOAP, web services, and WSDL. The course's projects focus on the implementation and deployment of these technologies.

Course topics:
XML 1.1 and SAX 2.0.2. DOM Level 3, XPath 1.0 (and 2.0) and XSLT 1.0 (and 2.0). Namespaces in XML 1.1 (Second Edition), SVG 1.1, and XSL (XSL-FO) 1.1. HTTP 1.1, JavaServer Pages 2.1, and Java Servlet 2.5. XQuery 1.0 and DTD. XML Schema (Second Edition). Web Services, SOAP 1.2, and WSDL 1.1. Ajax.


Algorithms for Nearest Neighbor Search (by Yury Lifshits)



Similarity Search: A Web Perspective (by Yuri Lifshits)


Lecture description:
Similarity search is the problem of preprocessing a database of N objects in such a way that given a query object, one can effectively determine its nearest neighbors in database. "Geometric near-neighbor access tree" data structure, an early work (1995) by Sergey Brin, is one of the most known solutions to this problem.

Similarity search is closely connected to many algorithmic problems in the web. Similarity search is an abstraction of many algorithmic problems we face in data management. In this talk we will focus on:

- Personalized news aggregation: Searching for news articles that are most similar to the user's profile of interests.
- Behavioral targeting: Searching for the most relevant advertisement for displaying to a given user.
- Social network analysis: Suggesting new friends.
- Computing co-occurrence similarities.
- "Best match search": Searching resumes, jobs, boyfriends, girlfriends, cars, apartments.

The lecture describes features that make web applications somewhat different from previously studied models. Thus the lecturer re-examine the formalization and the classical algorithms for similarity search. This leads us to new algorithms (Yuri present two of them) and numerous open problems in the field.



Functional Programming Seminar

Simon Peyton-Jones: "Taming Effects - The Next Big Challenge"

Satnam Singh: "Declarative Programming Techniques for Many-Core Architectures"

John Hughes: "Testing with QuickCheck"

Simon Peyton-Jones: "Composing Contracts - An Adventure in Financial Engineering"


John Launchbury: "High-Assurance Software"

Nested Data Parallelism in Haskell (by Simon Peyton-Jones)


Design Patterns as Higher-Order Datatype Generic Programs

Lecture by Dr Jeremy Gibbons of Oxford Computing Lab.



Games in Haskell (by Matthew Sackman)


XMonad - A Haskell Success Story


After all these mind boggling functional programming video lectures, here is a video for relaxation about Claude Shannon, founder of the field of information theory.


Claude Shannon - Father of the Information Age


Video contents:
Considered the founding father of the electronic communication age, Claude Shannon's work ushered in the Digital Revolution. This fascinating program explores his life and the major influence his work had on today's digital world through interviews with his friends and colleagues.

Computer Science - Video Lectures and Full Video Courses

Computer Science : Topics
  • C Programming
  • Essential Concepts of Computer Science
  • Principles of Computing
  • Introduction to Web Design
  • Client Side Web Programming
  • Server-Side Web Development
  • Visual Basic .NET
  • ASP.NET
  • ASP.Net Video Course
  • Advanced Programming
  • Programming Concepts and Data
  • Data Analysis Using Spread Sheets
  • XML with Java
  • Algorithms for Nearest Neighbor Search
  • Similarity Search: A Web Perspective
  • Functional Programming Seminar
  • Design Patterns as Higher-Order Datatype Generic Programs



C Programming (N305, Indiana and Purdue Universities)

Course topics:
Introduction to Computers: Hardware and Languages. Programming: First C Program. Mixing Data Types. Basic IO: printf() and scanf(). Variable Declarations, Data Types, Expressions: Variables and Operators. Assignments. Algorithms. Standard C Statements. Functions: Declarations. Information Representation: Positive Integers, Negative Integer Representation, Floating Point Representation, Characters and Images, Machine Instructions. Arrays: Strings and Multidimensional Arrays. Literals and Variables.



Essential Concepts of Computer Science (N301, Indiana and Purdue Universities)


Course topics:
History of Computing. Analog and Digital Representation. Binary Notation. Extending Binary. Two's Complement Notation. Floating Point Notation. Basic Logic Gates. Building a Half Adder. Building a Full Adder. Building a Subtracter. Building an ALU. Von Neumann Architectue. The Fetch-Execute Cycle. Basic Machine Language. Repetition in Machine Language. Beginning Algorithms. Branching Mechanisms. Looping. Complexity in Algorithms. Measuring Complexity. Encapsulation. Software Engineering. Software Engineering Models.



Principles of Computing (N100, Indiana and Purdue Universities)


Course topics:
Basic problem-solving with STAIR (Stating the problem, Tools, Algorithms, Implementation, Refinement). The universal information manipulator. Lights, Legos, and Numbers. Converting from binary to and from base 10. Basic logic gates. Storing data in ABNIAC. ASCII representation in ABNIAC. Addition and looping in ABNIAC.



Introduction to Web Design (N241, Indiana and Purdue Universities)


Course topics:
Basic HTML. Validation. CSS. Fonts and Colors in CSS. Binary, Decimal, Octal, Hex. Internet Addressing. Linux. Overview of Unix. Basic Unix Commands. Permissions. Colors and Images. Science of Colors. GIF. Learning Emacs. XHTML Images, Links, and Lists. Layout with CSS. Buttons in CSS. CSS Layout with Float. Tables. Cross-Browser CSS. Adding Audio. Multimedia With Flash. Multimedia with Wax. Basic Image Swapping. Rollover Buttons. Extending HTML.



Client Side Web Programming (N341, Indiana and Purdue Universities)


Course topics:
Program Development. Documenting Your Code. Introducing Programming. Object Oriented Concepts. Working with Variables. Dialogue Windows. String Objects. Number and Math Objects. If-Then-Else Structures. Switch Statements. Complex Conditions. Conditional Loops. Introducing Arrays. Multidimensional Arrays. JavaScript Modularity. Browser Objects. Introducing DOM. Regular Expressions. JavaScript and Forms. Form Validation. Window Object. Document Object. Cascading Style Sheets. Styles with JavaScript. Cookies.



Server-Side Web Development (N342, Indiana and Purdue Universities)


Course topics:
Intro to Server-Side Programming. Programming on the Web Server. Installing Apache on Windows. Installing PHP in Windows. Configuring PHP. Installing an IDE. Creating your 1st PHP Program. Preparing your Code. Using Variables. Complex String Variables. Responding to HTML Forms. Responding to Complex Forms. Creating Random Numbers. If Statement. Functions. Function Parameters. Variable Scope. Persistence. For and While Loops. Basic Arrays. Responding to Checkboxes. Associative Arrays. Multidimensional Arrays. Multi-Array. String Manipulation. Saving and Loading Files. Files. Directories. Mail. Using Regular Expressions. Introducing MySQL. Tables. Queries. Connecting to a Database within PHP. Examining Entities and Relationships. Joins. Innerjoins. Many to Many Joins.



Visual Basic .NET (N331, Indiana and Purdue Universities)


Course topics:
Inside Visual Studio. Buttons. Labels. Text Boxes. Check Boxes. List Boxes. Combo Boxes. Five Programming Steps. Variables. Branching. If. Then. Else. Looping. Do. While. For. Next. Arrays. Menus.



ASP.NET (N431, Indiana and Purdue Universities)


Course topics:
.NET Intro. Web Controls. Form Validation. Required Field Validator. Specialized Validators. Text Files vs Databases. Database Introduction. SQL Introduction. Insert. Update. Data Binding. Data List. Data Grid. Data Set Sorting. Tracking User Sessions. Session States. Caching. Error Handling. Forms-Based Authentication. Security. Local Encryption. Sending Mail.



Advanced Programming (N335, Indiana and Purdue Universities)


Course topics:
What is .NET. Programming Intro. Object Orientation. .Net Namespaces. Data Type. Strings. Dates. Creating a Class. Polymorphism. Inheritance. Creating Folders. Multithreading. SQL Overview. Data Wizards. Data Sets.



Programming Concepts and Data (N201, Indiana and Purdue Universities)


Course topics:
Problem Solving. Background, History, and Fundamentals of Computing. Working With HTML. History of Programming Languages. Machine Language. Miracle. Conditions. Using Loops. Javascript. Functions. Working with Arrays. Introduction to Databases.



Data Analysis Using Spread Sheets (N207, Indiana and Purdue Universities)


Course topics:
Introduction to STAIR. Computer Hardware. Binary, Hexidecimal, and ASCII. Computer Software. Computer Security. Webpages, Websites, and E-Commerce. Databases. Introduction to Spreadsheets. Charts. Univariate Data Analysis. Multivariate Data Analysis. Regression.



XML with Java (E-259, Harvard University)


Course description:
This course introduces XML as a key enabling technology in Java-based applications. Students learn the fundamentals of XML and its derivatives, including DTD, SVG, XML Schema, XPath, XQuery, XSL-FO, and XSLT. Students also gain experience with programmatic interfaces to XML like SAX and DOM, standard APIs like JAXP and TrAX, and industry-standard software like Ant, Tomcat, Xerces, and Xalan. The course acquaints students with J2EE, including JavaServer Pages (JSP) and Java Servlet, and also explores HTTP, SOAP, web services, and WSDL. The course's projects focus on the implementation and deployment of these technologies.

Course topics:
XML 1.1 and SAX 2.0.2. DOM Level 3, XPath 1.0 (and 2.0) and XSLT 1.0 (and 2.0). Namespaces in XML 1.1 (Second Edition), SVG 1.1, and XSL (XSL-FO) 1.1. HTTP 1.1, JavaServer Pages 2.1, and Java Servlet 2.5. XQuery 1.0 and DTD. XML Schema (Second Edition). Web Services, SOAP 1.2, and WSDL 1.1. Ajax.


Algorithms for Nearest Neighbor Search (by Yury Lifshits)



Similarity Search: A Web Perspective (by Yuri Lifshits)


Lecture description:
Similarity search is the problem of preprocessing a database of N objects in such a way that given a query object, one can effectively determine its nearest neighbors in database. "Geometric near-neighbor access tree" data structure, an early work (1995) by Sergey Brin, is one of the most known solutions to this problem.

Similarity search is closely connected to many algorithmic problems in the web. Similarity search is an abstraction of many algorithmic problems we face in data management. In this talk we will focus on:

- Personalized news aggregation: Searching for news articles that are most similar to the user's profile of interests.
- Behavioral targeting: Searching for the most relevant advertisement for displaying to a given user.
- Social network analysis: Suggesting new friends.
- Computing co-occurrence similarities.
- "Best match search": Searching resumes, jobs, boyfriends, girlfriends, cars, apartments.

The lecture describes features that make web applications somewhat different from previously studied models. Thus the lecturer re-examine the formalization and the classical algorithms for similarity search. This leads us to new algorithms (Yuri present two of them) and numerous open problems in the field.



Functional Programming Seminar

Simon Peyton-Jones: "Taming Effects - The Next Big Challenge"

Satnam Singh: "Declarative Programming Techniques for Many-Core Architectures"

John Hughes: "Testing with QuickCheck"

Simon Peyton-Jones: "Composing Contracts - An Adventure in Financial Engineering"


John Launchbury: "High-Assurance Software"

Nested Data Parallelism in Haskell (by Simon Peyton-Jones)


Design Patterns as Higher-Order Datatype Generic Programs

Lecture by Dr Jeremy Gibbons of Oxford Computing Lab.



Games in Haskell (by Matthew Sackman)


XMonad - A Haskell Success Story


After all these mind boggling functional programming video lectures, here is a video for relaxation about Claude Shannon, founder of the field of information theory.


Claude Shannon - Father of the Information Age


Video contents:
Considered the founding father of the electronic communication age, Claude Shannon's work ushered in the Digital Revolution. This fascinating program explores his life and the major influence his work had on today's digital world through interviews with his friends and colleagues.

Mathematic Books and Video Lectures - Useful Links

List of Topics

  • Intermediate Algebra
  • Elementary Statistics
  • Applied Probability
  • Finite Mathematics with Applications
  • Trigonometry for Calculus
  • Introduction to Mathematical Computation
  • Pre-Calculus and Introduction to Analytic Geometry
  • First Year Calculus (Calculus I)
  • Business Calculus
  • Mathematical Writing
  • Mathematics and Computer Science Problem Seminar
  • Dynamical Systems and Chaos
  • Computer Musings Lecture Series



Algebra Review
  • Video Lectures: Math 160 (University of Idaho)
Course covers: factoring, interval notation, definition of function, functions, piece-wise defined functions, function composition, quadratic functions, solving quadratic functions. Slope of the line, equation of the line, parallel and perpendicular lines. Law of exponents, properties of logarithms. Applications to exponential function, exponential growth and decay. Solving systems of equations by substitution and elimination.


Intermediate AlgebraThe primary purpose of Intermediate Algebra is to improve your skills and competency in algebra so that you will be successful in calculus, the other math courses required for your major, and in the courses that use mathematics. Another goal is to help you develop your mathematical learning skills so that you will be more confident in future mathematical courses.

Course covers: the real numbers, linear equations, linear inequalities and absolute value, linear equations and inequalities in two variables, systems of linear equations, exponents, polynomials and polynomial functions, factoring, rational expressions, roots and radicals, quadratic equations and inequalities.



Elementary Statistics
Elementary Statistics is an introduction to data analysis course that makes use of graphical and numerical techniques to study patterns and departures from patterns. The student studies randomness with emphasis on understanding variation, collects information in the face of uncertainty, checks distributional assumptions, tests hypotheses, uses probability as a tool for anticipating what the distribution of data may look like under a set of assumptions, and uses appropriate statistical models to draw conclusions from data.

The course introduces the student to applications in engineering, business, economics, medicine, education, the sciences, and other related fields. The use of technology (computers or graphing calculators) will be required in certain applications.

Course covers: Sampling and data. Statistical graphs, quartiles and percentiles, mean, median, mode, variance and standard deviation. Basic probability, independent and dependent events, addition and multiplication rules. Discrete random variables, discrete probability distribution functions, expected value, binomial probability distribution function. Continuous random variables, continuous probability distribution functions, uniform probability distribution, exponential probability distribution. The normal probability distribution function, standard normal probability density function. Central limit theorem for averages and sums. Confidence intervals. Hypothesis testing. The Chi-Square distribution function. Linear regression and correlation.



Applied Probability (5 lectures)
Focuses on modeling, quantification, and analysis of uncertainty by teaching random variables, simple random processes and their probability distributions, Markov processes, limit theorems, elements of statistical inference, and decision making under uncertainty. This course extends the discrete probability learned in the discrete math class. It focuses on actual applications, and places little emphasis on proofs. A problem set based on identifying tumors using MRI (Magnetic Resonance Imaging) is done using Matlab.


Finite Mathematics with Applications
  • Video Lectures: Math 1313 (University of Houston)
Course covers slopes, equations and graphing of lines, linear depreciation, cost, revenue and profit functions, intersection of lines, break-even analysis, the method of least squares, graphing linear inequalities, graphing systems of linear inequalities, linear programming problems, graphical solution of linear problems, simple interest, future value, present value, and effect rate, annuities, amortization and sinking funds. Set notation and terminology, set operations, Venn diagrams, number of elements in a set, the multiplication rule, permutations and combinations. Experiments, events and sample spaces, definition of probability, rules of probability, use of counting technique, conditional probability, independent events, Bayes' theorem, distributions of random variables, expected value, odds, variance and standard deviation, Chebyshev's inequality, the binomial distribution, the normal distribution, applications of the normal distribution.


Trigonometry for Calculus
The goal of this course is to prepare you for the trigonometry that you will encounter in calculus. During this one credit course in trigonometry, you will learn how to evaluate trigonometric functions, sketch the graphs of the sine, cosine and tangent functions, study the inverse trigonometric functions and much more.

Course covers the Cartesian coordinate system, functions, angle and radian measure, special right triangles, the unit circle, the trigonometric ratios, graphs of trig. ratios, periodic functions, fundamental trigonometric identities and inverse trigonometric functions.



Introduction to Mathematical Computation
Throughout the course we will illustrate application of software in typical undergraduate mathematical subjects such as calculus, probability, linear algebra, and number theory. Further, we will move to structural programming. We conclude the course by illustrating elements of contemporary platform independent language, java. No programming experience required

Course covers: Basic commands in Mathematica, Mathematica in Calculus, Mathematica in Probability, Mathematica and Linear Algebra, Mathematica and Number Theory, Mathematica and structural programming, Introduction to Java.


Note: Links to lectures 6 - 17 are missing. You can access them by changing the last number of the link to the first 5 lectures. Example: to access lecture 12 use address http://130.212.40.150:8080/ramgen/mathematica/lecture12.rm, etc.


Pre-Calculus and Introduction to Analytic Geometry
The primary purpose of Pre-Calculus and Analytic Geometry is to improve your skills and competency in algebra so that you will be successful in calculus, the other math courses required for your major, and in the courses that use mathematics. Another goal is to help you develop your mathematical learning skills so that you will be more confident in future mathematical courses.

Course covers: equations and identities, graphs, functions and their graphs, polynomial and rational functions, exponential and logarithmic functions, analytic geometry.



First Year Calculus (Calculus I)
The central object of the study in calculus is the concept of a function. Functions are used to describe the real world around us. Calculus introduces two fundamental concepts which enable us to describe and investigate functions. These are: the derivative and the integral. The derivative describes the behavior of a function at a particular time. The integral carries information about the history of a function.

Course covers: limits, limit laws, continuity, limits involving infinity, rates of change, derivatives, differentiation rules, product and quotient rules, rates of change in science, derivatives of trigonometric functions, the chain rule, implicit differentiation, logarithmic differentiation, maxima and minima, mean value theorem, L'Hospital's rule, optimization problems, areas and distances, definite integral, fundamental theorem of calculus.



Business Calculus
  • Video Lectures: Math 1314 (University of Houston)

Course covers limits, one-sided limits and continuity, the derivative, basic rules of differentiation, the product and quotient rules, the chain rule, higher order derivatives, basic applications of derivative, marginal functions in economics, applications of the first derivative, applications of the second derivative, curve sketching, absolute extrema, optimization, applications with exponential functions, antiderivatives, integration by substitution, area under the curve - Riemann Sums, the fundamental theorem of calculus, evaluation of definite integral, area between two curves, functions of several variables, partial derivatives, relative extrema.


Mathematical Writing (by Donald E. Knuth!)
Issues of technical writing and the effective presentation of mathematics and computer science. Preparation of theses, papers, books, and "literate" computer programs.

"I also gave a class called Mathematical Writing, just for one quarter," says Knuth. "The lectures are still of special interest because they feature quite a few important guest lecturers." This collection contains thirty-one tapes.



Mathematics and Computer Science Problem Seminar (by Donald E. Knuth!)
During the course students with Professor Knuth solve 5 problems which have not been solved.
According to D. E. Knuth course is given only once in two years because it takes him two years to think of good enough problems. The goal of the course it to understand problem solving in general and not just to solve those 5 problems and to get into as many of the different areas of computer science research as possible.

"This was an experimental project where we'd have three or four cameras in a basement studio and we would film classes of about an hour," says Knuth. "We got a bunch of our brightest students and gave them extremely difficult problems. You could literally see the Aha taking place. People can watch the problem-solving process as it occurred." Over 25 hours of these sessions are available for viewing.



Dynamical Systems and Chaos
The course will provide quick introduction to Dynamical Systems, Ergodic Theory and Chaos. We will start with examples of dynamical systems, with basic notions such as orbits, periodic points, phase portraits, attraction and repulsion, calculus of fixed points, invariant measures, Bernoulli shifts and ergodic theorems of various types.
Then we will study bifurcations on the example of dynamics of quadratic maps. The quadratic family will be used to demonstrate the transition to chaos and the main features of chaotic behaviour. We will touch Sarkovsii's Theorem and Newton's Method.

Elements of Symbolic Dynamics and subshifts of finite type will be considered. Then we will move to fractals and discuss fractal dimension and related topics. After that we will introduce Holomorphic Dynamics and the main objects such as Julia sets and the Mandelbrot set. Time permitting, we will consider some rational maps in dimension two and higher. Henon map will be considered, as well as some maps arising in the theory of fractal groups, and the Smale horse shoe map. We will consider also spectra and spectral measures related to such groups and to fractal sets like Sierpinski gasket or Cantor set.



Computer Musings Lecture Series (by Donald E. Knuth)

?These lectures I'?ve given have been inspired and shaped by the questions and responses of the audiences to whom I spoke, and I want to keep them alive,prof. D.E.Knuth explains. We'?ve got these tapes and the world is going digital; Stanford Centre for Professional Development has the talent and expertise to convert them. I feel that archiving is important. I'?ve learned from archived lectures and classes myself, so I think others can learn from these.

A sampling of musings includes:
  • Dancing Links
  • Fast Input/Output with Many Disks, Using a Magic Trick
  • MMIX: A RISC Computer for the New Millennium
  • The Joy of Asymptotics
  • Bubblesort at random (one-dimensional particle physics)
  • Trees, Forests, and Polyominoes
  • Finding all spanning trees


"Other" Donald E. Knuth Lectures

Also available are two five-session short courses about TeX (1981); twelve lectures about the implementation of TeX (1982); video recordings of eight history sessions about Computer Science at Stanford, taped in 1987 and featuring many alumni of our department; and some reminiscences by Professors Feigenbaum, Floyd, Golub, Herriot, Knuth, McCarthy, Miller, and Wiederhold about the founding of Stanford's Computer Science Department, The Living Legends (1997).

Questions from audience and students are important to the learning process, according to Knuth. Sometimes the expression of a more mature idea isn't the most interesting or effective way to learn you may learn more from how a professor reacts to an idea or a question. He pauses, and then adds, People might learn a lot from watching me fumble around to answer a question.

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