weisscharlesj / ProgrammingInChem

Jupyter notebooks and data for incorporating programming into chemistry courses

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Introducing Students to Scientific Computing in the Laboratory Through Python and Jupyter Notebooks

The below materials are for introducing students to scientific computing in the laboratory through python and jupyter notebooks and are released under the CC BY-NC-SA 4.0 licence. These materials were created by Andrew Klose and Charles Weiss of Augustana University in support of the chapter Introducing Students to Scientific Computing in the Laboratory through Python and Jupyter Notebooks in the American Chemical Society published book Teaching Programming across the Chemistry Curriculum. Instructors interested in copies of completed Jupyter notebooks (i.e., the answer keys) are welcome to contact the authors directly. These activities do not require students to have had any previous training in computer programming and involve varying degrees of coding required of chemistry students to help introduce students to scientific computing, the Python programing language, and Jupyter notebooks. An overview of the activities are provided below.

  1. Stochastic Radiation Simulation - This activity uses a pseudorandom number generator to simulate first-order radioactive decay behavior. The Jupyter notebook provides pre-written code and only requires students to follow along in the Jupyter notebook, run the code, and make small modifications to the code as a means to providing a first introduction to using Jupyter notebooks and giving students a sense of the utility of computer programming in science. This activity has been employed in a General Chemistry course as part of a radiation laboratory activity.
  2. Entropy Calculation - The goal of this activity is to calculate the entropy of a substance using specific heat data and enthalpy of phase change data. Students are required to write all the code for this activity following prompts and instructions provided in the Jupyter notebook markdown cells. No coding background is assumed of students, and this Jupyter notebook can also provide students a first introduction to Jupyter notebooks and Python. This activity has been employed in an intermediate-level chemistry course.
  3. Real Gases - This activity involves students curve fitting real gas data to derive constants and involves students running pre-written code and writting some of their own. This activity has been employed as part of a advanced-level Physical Chemistry course.

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Jupyter notebooks and data for incorporating programming into chemistry courses


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