Calibration Methods and Techniques Flashcards
What is the purpose of calibrations in analytical chemistry?
To convert instrument signals into concentrations.
In a calibration curve, what does the x-axis represent?
Concentration.
In a externalcalibration curve, what does the y-axis represent?
The instrument signal.
What should ideally form when plotting data on a calibration curve?
A straight line.
What is a residual in the context of calibration curves?
The difference between the measured value and the expected value from the calibration curve.
What causes residuals in calibration curves?
Indeterminate error.
What happens to calibration curves at high concentrations?
They deviate from linearity due to chemical effects.
What must the sample being analyzed be within?
The working range of the standard.
What is a key limitation of calibration curves?
Limited to the linear (dynamic) range of the curve.
What is the detection limit?
The lowest detectable amount of analyte.
Define baseline noise.
Random, unwanted signal fluctuations.
What is the limit of quantification (LOQ)?
The smallest concentration that can be reliably quantified.
What is the limit of detection (LOD)?
The smallest detectable signal.
What are calibration blanks used for?
To measure background noise.
What do calibration blanks contain?
No analyte.
What is the equation for LOD?
Standard + 3(Std. dev).
What is the equation for LOQ?
Standard + 10(Std. dev).
How does the slope of the calibration curve relate to sensitivity?
A steeper slope indicates higher sensitivity and lower LOD.
True or False: Higher sensitivity is always preferable in analytical methods.
False.
What is the dilution formula used in the preparation of standards?
C1V1 = C2V2.
What is the first step in the process of preparing standards?
A stock solution is prepared.
Define matrix in the context of sample analysis.
Everything in the sample except the analyte.
What is the matrix effect?
Other components enhance or suppress the analytical signal.
What is the purpose of using internal standards?
When the sample volume is small and errors are more likely.
