Homework_4_S17_NME_220.pdf - NME 220 Introduction to...

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NME 220: Introduction to molecular and nanoscale principles (S17) Prof. James M. Carothers Homework #4, Due electronically Wednesday, April 26, 2017 at 12:30pm Objective: This is a short problem set because of Engineering Discovery Days. The section 1 problems are included here to emphasize important fundamental concepts (these are similar to questions answered on Problem Set #3 and we worked several in class). Section 2 is provides a ‘soft start’ for using Tellurium and simulation analysis for your design projects. Section 1. 1.1 Blood gets its red color from hemoglobin. Hemoglobin is red because the protein absorbs yellow and green light (500-600 nm) very strongly and blue light (400-450 nm), leaving only red light transmitted. What is the energy of a quantum of yellow light absorbed by hemoglobin at 550 nm? 1.2 a) What is the de Broglie wavelength associated with a tennis ball of mass 50 g served at 90 miles per hour? b) Does the tennis ball exhibit wavelike-characteristics? If not, why not? 1.3 Electrons with wavelengths 0.1 Å are often used in diffraction experiments. To generate these, electrons from a hot filament are accelerated by a large potential difference Δ Φ to a velocity corresponding to the targeted wavelength. What is Δ Φ for a de Broglie wavelength of 0.1 Å? 1.4 Begin with Newton's equation ( F = ma ) for motion of orbiting electron Coulombic force = mass x centripetal acceleration Insert the condition for quantization of angular momentum to obtain Bohr's equation for E (kinetic + potential) of an electron in a hydrogen atom of nuclear charge + e . Hints: Centripetal acceleration is given by ω 2 r . According to Coulomb's law: electrostatic attraction between + e and – e is given by - e 2 / r 2
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Section 2. Aptamer biosensor project work. (SEE SECTION 3, below, for PHOTODETECTORS PROJECT WORK). 2.1 For this assignment, we will use Tellurium, which is a python environment for modeling and simulating biochemical systems. You can use this environment to simulate the outputs of complex biochemical systems formulating them as sets of chemical reactions (a numerical solver evaluates the chemical reaction network as a set of ordinary differential equations, ODEs).
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