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\nML: Li-ion 🔋 Crystal Structure\n

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\n\nPublisher:\n\nAPMonitor\n\n\n
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\nPhysical and chemical properties of the Lithium-ion silicate cathodes are used to predict the crystal structure of a Lithium-ion battery material as monoclinic, orthorhombic and triclinic. This case study demonstrates how feature...\nPhysical and chemical properties of the Lithium-ion silicate cathodes are used to predict the crystal structure of a Lithium-ion battery material as monoclinic, orthorhombic and triclinic. This case study demonstrates how feature engineering improves the classification results.

Objective
Predict the crystal structure type (monoclinic, orthorhombic, triclinic) from Lithium-ion physical and chemical compound information.

Background
Lithium-ion batteries are commonly used for portable electronics, electric vehicles, and aerospace applications. During discharge, Lithium ions move from the negative electrode through an electrolyte to the positive electrode to create a voltage and current. During recharging, the ions migrate back to the negative electrode. The crystal structure (monoclinic, orthorhombic, triclinic) is available for 339 different chemicals that contain lithium.\n
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Resource Details

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Curator Rating
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Educator Rating
Not yet Rated
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Media Length
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25:23
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Grade
10th - Higher Ed
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Subjects
STEM
3 more...
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Media Type
Instructional Videos
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Source:
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\nAPMonitor.com\n\n
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Date
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2022
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Language
English
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Audiences
For Teacher Use
2 more...
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Usage Permissions
Fine Print: Educational Use
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Concepts

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crystal structure, data, energy
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Additional Tags

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apmonitor, machine learning, materials, chemparse, python, feature engineering, space group, negative electrode, clear output, label encoder, feature hasher, confusion matrix, feature hashing, crystal system, band structure, hasband structure, hot encoding, chemical formula, ordinal encoding, fit transform, data frame, numerical features, categorical features, multilabel problem, data types, test data, case study, monoclinic orthorhombic, features, monoclinic
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Classroom Considerations

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Best For: Explaining a topic
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