Calibration Curve Calculator
Calculate unknown concentrations using linear calibration curves and the standard addition method. Perfect for analytical chemistry, spectroscopy, and chromatography applications.
Calculate with Linear Equation
Calibration Equation
y = x
Solving for x: x = (y - 0) / 1 = 0.000000
Analysis
Common Applications
- •UV-Vis spectroscopy analysis
- •HPLC peak area correlation
- •Mass spectrometry quantitation
- •Clinical chemistry analysis
- •Environmental testing
Standard Addition Method
y = a·x + b
Linear calibration equation
- y: Instrumental signal
- x: Concentration
- a: Sensitivity (slope)
- b: Background (intercept)
Example Calculation
UV-Vis Spectroscopy Analysis
Method: Standard addition method
Calibration equation: y = 0.5x + 0.1
Sensitivity (a): 0.5 (slope)
Background (b): 0.1 (intercept)
Measured signal: 2.1
Step-by-Step Calculation
1. Apply formula: x = (y - b) / a
2. Substitute values: x = (2.1 - 0.1) / 0.5
3. Calculate: x = 2.0 / 0.5
4. Result: x = 4.0 concentration units
Understanding Calibration Curves
Linear Calibration Theory
Calibration curves establish the relationship between instrument response and analyte concentration. The linear equation y = ax + b is fundamental to quantitative analysis.
- •Provides traceability to certified materials
- •Enables accurate quantification
- •Compensates for matrix effects
Quality Assessment
The correlation coefficient (R²) indicates how well the linear model fits the data.
R² ≥ 0.995: Excellent
Suitable for all applications
R² ≥ 0.99: Very Good
Acceptable for most methods
R² ≥ 0.95: Good
May require optimization
Applications in Analytical Chemistry
Spectroscopy
UV-Vis, IR, and atomic absorption spectroscopy rely on calibration curves following Beer-Lambert law.
Chromatography
HPLC, GC, and ion chromatography use calibration curves to relate peak area to concentration.
Mass Spectrometry
Quantitative MS analysis requires calibration curves to correlate ion abundance with concentration.