# EEGR 215 LUM Electrical Engineering Materials and Devices Python Exercise

User Generated

zbunzznqnyunwev

Engineering

EEGR 215

Loyola University Maryland

EEGR

## Description

It has to be your own work please, This is a project assignment in Material and devices subject.
i'll attach the file.

Also you have to work on Python.

so please read the project and you'll understand how it works. thanks.

### Unformatted Attachment Preview

Project #2: Carrier Statistics Error Analysis using Python EEGR 215, Summer 2020 Project Goal: The purpose of this project is to calculate when exactly the equations used for assumption regarding band analysis are no longer valid. Specifically we want plot a 3D contour showing how doping and temperature can affect the error of the calculated measurements. Case Study (Read Carefully): Assume you have a typical piece of Silicon Wafer, it is doped by N-type carriers (electrons) and it operated at an elevated temperature. Assume, NA = 1e8 cm-3. We will use Short-hand (assumption) approach to calculate the n, p, and EF-Ei then use recalculate using first principal equation while making minimal assumptions. We want to know the range in which the Short-hand approach gives the same answer as the first principal approach. Part 1, Short-Hand Approach: • Assume: ni = 1e10cm-3, Eg = 1.1eV, n ≈ ND • For N-Type: o EF-Ei = kTln(n/ni) o np = ni2 Output: 3 Contour Plots, Solve for n and Δ = EF-Ei o Z/Color Axis #1: n = electron concentration o Z/Color Axis #2: Δ = Fermi Level o Z/Color Axis #3: Degeneracy = 1 (degenerate) or 0 (non-degenerate) o X-axis: Temperature (range = 250K – 1200K) o Y-axis: N-type Doping (range = 1e8 – 1e20 [cm-3]) • Part 2, First Principal Approach: Find the effective mass for electrons and holes for Silicon and solve for n using first principals. Note that every parameters is a function of temperature. Solve for n and Δ = EF-Ei Output: 3 Contour Plots, Solve for n and Δ = EF-Ei • • • • • Z/Color Axis #1: n = electron concentration Z/Color Axis #2: Δ = Fermi Level Z/Color Axis #3: Degeneracy = 1 (degenerate) or 0 (non-degenerate) X-axis: Temperature (range = 250K – 1200K) Y-axis: N-type Doping (range = 1e8 – 1e20 [cm-3]) Part 3, Error Analysis: For the final analysis, compare your results for the Short-Hand approach in part 1 to the First Principals approach in part 2. For this we want to create a contour plot showing the percent error between the two approaches. Plot the error for n = electron concentration, and Δ = Fermi Level as a function of doping and temperature. • • • • • Error = |Approx – Exact|/Exact Value Z/Color Axis #1: Error for n = electron concentration Z/Color Axis #2: Error for Δ = Fermi Level X-axis: Temperature (range = 250K – 1200K) Y-axis: N-type Doping (range = 1e8 – 1e20 [cm-3]) Turn-in Items: • • • • • • 3 Contour Plots for part 1 3 Contour Plots for part 2 2 Contour Plots for part 3 Cover Page .ipynb file for Python Code Write up with embedded Contour figures with captions and labels
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### Review

Anonymous
Just what I was looking for! Super helpful.

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