Experimental Chemistry
1. Experimental Design
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πΉ Designing Experiments:
πΉ Plan investigations with clear objectives to study chemical phenomena systematically.
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πΉ Key Variables:
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πΉ Independent Variable:
πΉ The variable that is deliberately changed.
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πΉ Dependent Variable:
πΉ The variable that is measured or observed.
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πΉ Control Variables:
πΉ Variables that are kept constant to ensure a fair test.
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πΉ Independent Variable:
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πΉ Procedures:
πΉ Write clear, step-by-step instructions including materials, methods, and conditions for reproducibility.
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πΉ Risks and Precautions:
πΉ Identify hazards and apply safety measures such as protective equipments, proper handling, and emergency plans.
2. Methods of Purification and Analysis
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πΉ Purification Techniques:
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πΉ Filtration:
πΉ Separates solids from liquids by passing mixture through filter paper.
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πΉ Distillation:
πΉ Separates liquids based on different boiling points.
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πΉ Chromatography:
πΉ Separates mixture components based on movement through a stationary phase.
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πΉ Locating Agents:
πΉ Used in chromatography to reveal colorless compounds, e.g., iodine vapour, UV light.
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πΉ Filtration:
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πΉ Identity and Purity:
πΉ Melting and boiling points indicate purityβpure substances have sharp points matching known values; impurities cause changes.
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πΉ Importance of Purity:
πΉ Ensures safety and quality in food, drugs, and everyday products by removing harmful impurities.
- β οΈ Control variables can be changed during an experiment; they must be kept constant.
- β οΈ Filtration can separate dissolved substances; it only separates solids from liquids.
- β οΈ Chromatography always produces colored spots; locating agents may be needed for colorless substances.
- β οΈ Impurities always raise melting points; they usually lower and broaden melting ranges.
- π Clearly identify and label independent, dependent, and control variables in experiment design questions.
- π Describe purification techniques with appropriate diagrams where possible.
- π Explain how melting and boiling points reflect purity.
- π Highlight safety measures when designing experimental procedures.