1. What is a Calibration Curve?

A calibration curve is a method used in analytical chemistry to determine the concentration of a substance in an unknown sample by comparing it to a set of standard samples of known concentration. The curve is typically linear and follows the equation y = mx + b.

2. How Does the Calculator Work?

The calculator uses the linear calibration curve equation:

Where:

• \( y \) — Response signal (e.g., absorbance, peak area)
• \( m \) — Slope of the calibration curve
• \( x \) — Concentration of the analyte
• \( b \) — Y-intercept of the calibration curve

Explanation: The equation describes the linear relationship between the instrument response and the analyte concentration.

3. Importance of Calibration Curves

Details: Calibration curves are essential for quantitative analysis in various fields including chemistry, biochemistry, and environmental science. They allow for the conversion of instrument signals into meaningful concentration values.

4. Using the Calculator

Tips: Enter the slope and intercept values from your calibration curve, along with the x value (concentration) you want to calculate the response for. All values can be positive or negative decimals.

5. Frequently Asked Questions (FAQ)

Q1: How do I determine the slope and intercept?
A: These are typically calculated using linear regression analysis of your standard curve data points.

Q2: What is the R² value in calibration curves?
A: R² (coefficient of determination) measures how well the regression line approximates the real data points (1 = perfect fit).

Q3: When should a calibration curve be performed?
A: Before each analytical run, or whenever there are changes in instrumentation, reagents, or analytical conditions.

Q4: How many points should a calibration curve have?
A: Typically 5-8 concentration points, evenly spaced across the expected concentration range.

Q5: What if my data isn't linear?
A: Non-linear regression or transformation of data may be needed for non-linear relationships.