Exam 1 Flashcards
What is Spectrometry
The reactions and measurements of Radiation Intensity
Assumptions of External Calibration
1.) There is no error in the [conc] of standards - careful prep of samples is required
2.) No errors in measurement - careful observation and measurement required
3.) Signal response is the same for standards and samples - done by instrument or blank measurement
OVERALL no CORRECTIONS
Assumes matrix effect are absent or have little impact in the analytical (use of certified pure substances)
Systematic Errors
from inaccurate gravimetric and volumetric measurements
Matrix Effect
Species not within blank, present in sample, will cause samples/standards different responses.
Differences in experimental variables at the time of measurement of blanks, standards and samples
Precision
Reproducibility of results from a measurement.
Represented as stdev, relative stdev,
standard error of mean, coefficient of variant and variance
Bias
A measure of the systematic error of an analytical method, technique, equipment or calibration. Proper instrument calibration and use blanks to reduce bias
Sensitivity
The ability to discriminate between small differences in analyte [conc] limited by the slope of the calibration curve and precision of the measurement.
Detection Limit
The minimum concentration or mass of an analyte that can be detected (Sm = signal(blank) + k * blank(stdev)
Dynamic Range
Concentration over which measurement is reliable
Selectivity
Freedom from interferences
What is more sensitive?
a.) slope= 3.0 E3 ; R^2 = 0.9393
b.) slope= 3.0 E4 ; R^2 = 0.8326
B.) - When talking about sensitivity, the slope express the sensitivity. Not the R^2
Standard Addition Method
Used to eliminate matrix in samples by spiking the sample with known aliquots of a standard
Must use if standard and unk. have drastically different solution environments
Standard add. Method: How does it work?
Constant is added to remove proportionality ( i.e. we are changing from proportionality to equaling)
Internal Standard Method (Quality Control Method)
I.S. should have similar properties to the test samples and standards; producing a distinct signal from both sample/standards
Added in constant amount
or present in excess, assumed to be constant
Corrects both measurement and instrument error.
Using a ratio of both sample/standard provides a better R^2
Signal
The measurement that contains the information of the analyte
Noise
Contains no information regarding the analyte and overall decrease accuracy and precision - overall limiting the amount of analyte that can be detected
Signal-to-Noise Ratio (S/N)
Best describes the quality of an analytical measurement of an analytical method or the performance of an instrument and is defined as the stdev of the measurement of the signal
Sources of Instrumental error
Faulty calibrations
Calibration errors in meters
Weights
volumetric glassware
Chemical Noise
Variations in experimental onditions cause a change in the chemistry of the analyte
Instrumental Noise
This is associated with components of the instrument
Thermal Noise / Johnson Noise
Caused by electron or charge agitation which leads to fluctuations
Measure results of signal changes in temp
Voltage Measurement
Bandwidth dependent
Shot Noise
Fluctuations of electrons in semiconductors
Dependent on Bandwidth
Hardware - Signal to noise enhancement
1.) Grounding/Shielding
2.) Electronic filtering
3.) Modulation
Grounding/Shielding
Surrounding critical instrument components with a conducting material attached to the ground to remove noise and electromagnetic radiation from the environment
Electronic Filtering
Removes frequencies that are different from the signal frequency (use low or high pass filter to reduce noise)
Modulation
Move signal to quieter region of the spectrum
Software - signal to noise enhancement
Ensemble Averaging
Smoothing
Digital filtering
Ensemble Averaging
Noise is often random, signal is not. By recording repetitive signals, random noise can be reduced
Entirely dependent on times measured (n)
Provides stronger signals
Smoothing
Averaging successive points from rough data - the more successive points, increases smooth character of line
Digital Filtering
Mathematically remove selected fragments
Signal is low so use a low pass filter to reduce background - converts from signal domain to frequency domain