Sample Analysis Design Element2 - Basic Software Concepts (cont d)
Samples per Peak In order to establish a minimum level of precision, the ion signal (peak) must be measured several times during the scan
Samples per Peak Recommended values for Samples per Peak as a function of the mode of resolution: -10 samples for low resolution measurements - 20 samples for medium resolution measurements - 30 samples for high resolution measurements
Detection Modes
Detector Modes Counting Mode: is a digital measurement (counting) and counts events instead of ion signal height it is therefore very sensitive and useful especially for the detection of low signals (concentrations). during acquisition, the number of occurrences is used to generate the intensity information that is stored in a data file this mode of operation can be used in the detection range from 0 to 5 x 10 6 counts per second (cps)
Detection Modes Analog Mode: is a standard detection mode each time an ion signal exceeds a certain threshold, the height above the threshold delivers the intensity information (that is stored in a data file) the detection range is between 10 4 and 10 8 cps
Detection Modes Both Mode: the analog and the counting signals are monitored by the hardware continuously should the ion signal exceed the security threshold ( trip ) of the ion counter (5 x 10 6 cps), then the protection device disables the counting part until the intensities are below the trip level (if applicable) Note a cross calibration between modes is done automatically
Element2 Software Concepts MASS CALIBRATION
Mass Calibration The expectation of an ICP-MS user is to see the exact information about peaks, mass numbers, etc. when looking at the computer screen Unfortunately, the computer hardware has no idea about mass and intensity of ions or peaks in a mass spectra
Mass Calibration The computer knows DAC (Digital-to-Analog Converter) steps for setting the magnetic field of the instrument and the ADC steps (Analog-to- Digital Converter) for a received intensity The Mass Calibration program translates and adjusts the information available by the computer hardware into the information an ICP- MS user really needs; i.e. mass numbers and intensities for single ions and isotopic patterns
Mass Calibration The computer translates DAC values into mass numbers. The DAC values are used for setting the strength of the magnetic field, which modifies the direction of the ions. The hardware is referred to as Magnet DAC or MDAC The actual translation table, the Mass Calibration Table, is stored on the computer s disk in the data directory as <name>.mcl
Mass Calibration
Mass Calibration
Mass Calibration
The big questions are: - What value best represents a set of measurements and how reliable is it?
An ICP analysis yields LOTS of data typically, 9 individual measurements for each analyte for each sample (3 replicates * 3 runs) the report sequence or ASCII data file gives you the mean (average) of the replicates and the standard deviation of the replicates What does that REALLY mean?
Assuming a normal (gaussian) distribution of the data: 1st question - what is the most probable value for the population? 1st approach - take the mean (average) 2nd approach - take the median useful if there are few measurements and asymmetry is involved
Mean: x = Ʃ(x i ) / n Median = the value of the middle item, or the mean of the values of the two middle items, when the data are arranged in an increasing or decreasing order of magnitude
E.g. 42, 39, 31, 35, and 38 Median = 38
Generally speaking, the median of a set of n items, where n is odd, is the value of the (n +1) / 2 th largest item E.g. The median of 25 numbers is the value of the (25 +1) /2 = 13 th largest number
By definition, the mean is heavily influenced by extreme values while the median is not Outliers strongly effect the mean value, but show little to no effect on median E.g.: xi = 4, 4, 4, 5, 5, 6, 6, 6, 6, 7, 7, 8, 9, 9, 17 Median = 6 Mean = 6.867
Dispersion of a population Ok, you ve decided to take the mean - How reliable is it? Two measures to judge reliability of the mean: - Range and Standard Deviation
Range: R = x max x min strongly influenced by extreme values with n being sufficiently large (> 9), you can use quantiles to buffer the range against outliers n = 10, cast out high and low. Left with n = 8, the range of which is called the 10-90% range if n is large enough, can bracket the data in the 17-83% range (will bound ~2/3 of all data)
Taking the mean (or median) of the bounded range should provide a good estimate of the true value Why 17 th and 83 rd quantiles? Encompasses ~2/3 of the data points, which is very close the interval of the mean +/- 1 standard deviation (SD)
The Standard Deviation most common measure of dispersion robust statistic - will provide meaningful data even if the population does not strictly meet the definition of the normal population
Relative standard deviation (or coefficient of variation c.o.v.) RSD (%) = 100*sx / mean
Predominant sources of error in ICP-MS analysis: weighing/volume error error in standard concentration instrument error
How does one evaluate the true error or uncertainty associated with an ICP-MS analysis? Sample preparation errors are probably greater than instrument error
SO...strictly speaking, replicates should be conducted by preparing multiple aliquots of the same sample and running them multiple times However, this is generally impractical to do for all samples A better idea is to do this for maybe one or two samples
Reproducibility and Repeatability Reproducibility = standard deviation of a method over a long time frame Repeatability = standard deviation of a method over a short time frame (with all controllable conditions being the same)
Reporting ICP Data due to systematic and random errors, ICP data should rarely, if ever, be reported to greater than 3 or 4 significant digits