ComputationalEngineering (Matlab codes)

Particle Wavelengths Generate a plot estimating wavelength (in nm) vs. energy (in meV) for electrons, phonons, and photons in the 0 – 200 meV energy range. The equations for particle wavelength (λ) are below where h is Plank’s constant, m* is the effective mass, vs is velocity, E is energy, and c is the speed of light. For Silicon m*=0.26 mo, vs = 8433 m/s, and the Debeye temperature is ΘD=645K. This implies a phonon cutoff at 55 meV, i.e. phonons at wavelengths with E>55 meV are not allowed. Comment on which particles are Fermions, Bosons, and Boltzons, along with which heat transfer mechanism is associated with each particle. Electrons: λ = h ; Phonons: λ = hvs ; Photons: λ = hc 2 m e* E E E Power Dissipation in CPUs A 1 cm × 1 cm computer processor has 1×109 transistors on it. Each transistor occupies an area 0.1μm2. The processor is in contact with an environment that has an effective thermal conductivity of 10W/m-K, and heat must travel a distance of 1mm before it is completely removed from the processor. Plot the temperature of the processor as a function of the power dissipated by the transistors from 1nW to 100 nW. Comment on the energy challenges associated with cloud computing and data centers. Thermal Conductivity of Metals Create a table of electrical conductivity (S/m) and thermal conductivity (W/m-K) for Mo, Fe, W, Ti, Cr, Co, Ni, Cu, Ag, Al, Au. Create a plot of thermal conductivity vs. electrical conductivity at T=300 K. Using the “polyfit” and “polyval” commands perform a linear fit to the data. Plot the data as scatter points and overlay your linear fit. Comment on the slope and the particles carrying the heat in metals. Also, comment on how you may reduce the thermal conductivity of a metal.