This module gives a brief overview of computational chemistry, a branch of chemistry concerned with theoretically determining properties of molecules. The fundamentals of how to conduct a computational project are discussed as well as the variety of different models that can be used. Because of the difficulty of dealing with nanosized materials, computational modeling has become an important characterization tool in nanotechnology.
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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.
This course will cover the basic concepts of design of integrated nanomedical systems for diagnostics and therapeutics. Topics to be covered include: why nanomedical approaches are needed, cell targeting strategies, choice of core nanomaterials, technologies for testing composition and structure of multilayered nanomedical systems, optimizing zeta potentials, design and testing of cell and intracellular targeting systems, in-vivo issues, drug delivery and proper dosing, assessing efficacy of drug/gene delivery, nanotoxicity, animal testing, and regulatory issues. In addition to attending lectures and participating in classroom discussions, students will write and present an original research nanomedical system design project. This course will serve as an interdisciplinary training for doctoral students in Biomedical Engineering and other fields for a basic understanding of the principles and challenges of nanomedicine.
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 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. The objectives of the course are to convey the basic concepts of nanoelectronics to electrical engineering students with no background in quantum mechanics and statistical mechanics.
While the Greek root nano just means dwarf, the nanoscale has become a giant focus of contemporary science and technology. We will examine the fundamental issues underlying the excitement involved in nanoscale research - what, why and how. Specific topics include assembly, properties, applications and societal issues.
This collection of homeworks is used in ECE 255 "Introduction to Electronic Analysis and Design" (Purdue University). Students do their work, or sometimes check their work, by using the Spice 3F4 simulator on nanoHUB.org.
This homework assignment is part of ECE 606 "Solid State Devices" (Purdue University). It contains 5 problems which lead students through a comparison of the depletion approximation and an exact solution of PN junction diodes. Students compute the exact solution by using the PN Junction Lab available on nanoHUB.org.
This homework assignment was created for EE 218 "Introduction to Nanoelectronics and Nanotechnology" (Stanford University). It includes a couple of simple "warm up" exercises and two design problems, intended to teach students the electronic properties of resonant tunneling diodes and carbon nanotubes, and how they can be used as components in real circuits. Students do their work via the Resonant Tunneling Diode Simulator and the MSL Simulator, which are both available online through NanoHub.org
The Interdisciplinary Journal of Problem-based Learning (IJPBL) publishes relevant, interesting, and challenging articles of research, analysis, or promising practice related to all aspects of implementing problem-based learning (PBL) in K–12 and post-secondary classrooms.
This seminar will provide an introductory overview for non-experts of the emerging field of nanometer scale science and technology. The following topics will be emphasized: (1) Historical background and motivation for the study of nanometer scale phenomena; (2) Strategies for controlling the structure of matter with nanometer scale precision; (3) Size-dependent properties (e.g., electrical, optical, and magnetic) that emerge at the nanometer scale; (4) Real-world applications that utilize nanometer scale devices. If time permits, the seminar will also describe the unique challenges that educators face when teaching an interdisciplinary and constantly evolving field such as nanometer scale science and technology. Specific classroom experiences from a nanomaterials undergraduate course at Northwestern University will be shared.
In 1965, Gordon Moore observed that the number of transistors on a silicon chip doubled every technology generation (12 months at that time, currently 18-24 months). He predicted that this trend would continue for a while. Forty years later, Moore's Law continues to hold. Since the number of transistors in a circuit is a measure of the circuit's computational power, the doubling of transistor counts compounded over a 40 year period has led to an enormous increase in the performance of electronic devices and a corresponding decrease in their cost per function. The result has shaped our modern world by making computers, personal computers, cell phones, portable music players, personal digital assistants, etc. pervasive. This talk is an overview of a technology that shaped the 20th Century and that may have a similarly profound impact on the 21st Century. I'll explain how engineers double the number of transistors per chip, the challenges they face as they strive to continue Moore's Law, and take a brief look at some new technologies that researchers are examining.
These are companion exercises for two lectures offering practical guides to the use of a general device simulator (PROPHET) available on nanoHUB.org. PROPHET is a partial differential equation (PDE) solver that offers users the flexibility of integrating new models and equations for their nano-device simulations. The first lecture covers the basics of PROPHET, including the set-up of simulation structures and parameters based on pre-defined PDE systems. The second lecture uses examples to illustrate how to build user-defined PDE systems in PROPHET. Exercise problems: 1-D Poisson Equation and 2-D Poisson Equation
Semiconductor device technology has transformed our world by making possible supercomputers, personal computers, cell phones, ipods, and much more that we now take for granted. Moore's Law observes that the number of transistors (the basic building blocks of electronic systems) per electronic chip doubles each technology generation. This doubling of transistor density each technology generation has continued since Gordon Moore, one of the co-founders of Intel, made his observation in 1965. It has led to an exponential growth in the capability of electronic systems and an exponential decrease in their cost. The microelectronic technology of the 1960's has evolved into today's nanoelectronics technology. This talk gives a brief overview of the history of electronics, a look at where it stands today, and some thoughts about where electronics is heading.
The purpose of this series of lectures is to introduce the "bottom-up" approach to nanoelectronics using concrete examples. No prior knowledge of quantum mechanics or statistical mechanics is assumed; however, familiarity with matrix algebra will be helpful for some topics.
This presentation will discuss light concentration and enhancement in nanometer-scale ridge aperture antennas. Resent research, including numerical simulations and near field optical measurements has demonstrated that nanoscale ridge antenna apertures can concentrate light into nanometer domain. More importantly, these ridge antenna apertures also provide enhanced optical transmission several orders of magnitude higher than regularly shaped nano-apertures. We will discuss fundamental theories of ridge antenna apertures, finite-difference time-domain (FDTD) calculations for optimizing the design of these antenna apertures, and near field scanning optical microscope (NSOM) measurements of the near field intensity distribution of the light transmitted through these apertures. It is shown that the nanoscale antenna apertures can produce a concentrated light spot beyond the diffraction limit with enhanced transmission. Potential applications of these nanoscale aperture antennas include nano-lithography and nano-imaging.
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.
Welcome to the Nanotechnology 501, a series of lectures designed to provide an introduction to nanotechnology.
What is a nanowire? What is a nanotube? Why are they interesting and what are their potential applications? How are they made? This presentation is intended to begin to answer these questions while introducing some fundamental concepts such as wave-particle duality, quantum confinement, the electronic structure of solids, and the relationship between size and properties in nanomaterials.
This course will provide students with the fundamentals of computational problem-solving techniques that are used to understand and predict properties of nanoscale systems. Emphasis will be placed on how to use simulations effectively, intelligently, and cohesively to predict properties that occur at the nanoscale for real systems. The course is designed to present a broad overview of computational nanoscience and is therefore suitable for both experimental and theoretical researchers. While some aspects of the simulation methods such as numerical algorithms will be presented, there will be little if any programming required. Rather, we will emphasize the intelligent application (as opposed to “black box” use) of codes and methods, and the connection between the computer results and the physical properties of the problem.