❓ 🔬 Materials Design: Lists and Tuples

# You must make sure to run all cells in sequence using shift + enter or you might encounter errors
from pykubegrader.initialize import initialize_assignment

responses = initialize_assignment("8_lists_and_tuples_q", "week_2", "readings", assignment_points = 11.0, assignment_tag = 'week2-readings')

# Initialize Otter
import otter
grader = otter.Notebook("8_lists_and_tuples_q.ipynb")

❓ 🔬 Materials Design: Lists and Tuples#

[Unk23]

# Run this block of code by pressing Shift + Enter to display the question
from questions._8_lists_and_tuples_q import Question1
Question1().show()

# Run this block of code by pressing Shift + Enter to display the question
from questions._8_lists_and_tuples_q import Question2
Question2().show()

# Run this block of code by pressing Shift + Enter to display the question
from questions._8_lists_and_tuples_q import Question3
Question3().show()

Materials Processing Sequence 🏭#

Instructions:#

  1. Create the following variables:

    • element_properties: A tuple storing properties of titanium (“Ti”, 22, 47.87)

    • processing_steps: A list storing heat treatment steps [“Solution Treatment”, “Quenching”, “Aging”]

    • temperatures: A list of processing temperatures [955, 25, 540]

    • times: A list of processing times in hours [1.0, 0.1, 24.0]

    • total_time: Use sum() to calculate total processing time

    • max_temp: Use max() to find the highest temperature

    • num_steps: Calculate the number of processing steps using len()

    • process_complete: A boolean indicating if all steps are completed (True)

  2. Print a descriptive message that incorporates all the above variables, formatted like this:

    Processing Ti (Atomic number: 22, Mass: 47.87) using 3 steps:
Solution Treatment at 955°C for 1.0 hours
Quenching at 25°C for 0.1 hours
Aging at 540°C for 24.0 hours
Total processing time: 25.1 hours
Maximum temperature: 955°C
Process completion status: True

def materials_processing():
    # Define the variables
    element_properties = ...
    processing_steps = ...
    temperatures = ...
    times = ...
    total_time = ...
    max_temp = ...
    num_steps = ...
    process_complete = ...

    return (
        element_properties,
        processing_steps,
        temperatures,
        times,
        total_time,
        max_temp,
        num_steps,
        process_complete,
    )

# This code is provided for you to test the function to ensure it is correct
# please do not modify the provided code
# Get all variables
(
    element_properties,
    processing_steps,
    temperatures,
    times,
    total_time,
    max_temp,
    num_steps,
    process_complete,
) = materials_processing()

# Print the descriptive message
print(f"Processing {element_properties[0]} (Atomic number: {element_properties[1]}, Mass: {element_properties[2]}) using {num_steps} steps:")
for step, temp, time in zip(processing_steps, temperatures, times):
    print(f"{step} at {temp}°C for {time} hours")
print(f"Total processing time: {total_time} hours")
print(f"Maximum temperature: {max_temp}°C")
print(f"Process completion status: {process_complete}")

grader.check("question-Materials-Processing-Sequence")

References#

[Unk23]

Data-driven automated synthesis. https://www.nature.com/collections/ddbfdfhfbh, 8 June 2023. Accessed: 2024-12-23.

[HCS+16]

Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Bengio. Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1. ArXiv, 2016. URL: http://papers.neurips.cc/paper/6573-binarized-neural-networks.pdf.

Submitting Assignment#

Please run the following block of code using shift + enter to submit your assignment, you should see your score.

from pykubegrader.submit.submit_assignment import submit_assignment

submit_assignment("week2-readings", "8_lists_and_tuples_q")