Vocabulary of Anal Chem (Cont.)

8/13/2019 Vocabulary of Anal Chem (Cont.)

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The Vocabulary

of AnalyticalChemistry (cont.)


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Developing the procedure

Compensating for interferences

Calibration

Sampling

Validation


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A methods accuracy depends on its selectivity for the

analyte.

Potential interferents may be present in the sampleitself or

in the reagentsused during the analysis.

how to m inim ize these two sou rces of inter ference ???

Stotal= SA+ Sreag= knA+ SreagStotal= SA+ Sreag= kCA+ Sreag

measu re the signal for amethod blank

1) When the sample is free of interferent

the total signal, Stotal

the signal due to the analyte, SAthe signal due to interferents in the reagents, Sreag


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Method blank:

A sample that contains all components of the matrix

except the analyte. A method blank also is known as a reagent blank.

When the sample is a liquid, or is in solution, we use an

equivalent volume of an inert solvent as a substitute for

the sample.

SreagSA


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If the identity and concentration of the interferent are

known OK! add to the reagent blankNot common!!!

Common: the identity or concentration of matrix

interferents is not known, and their contribution to Stotal

is not included in Sreag . Instead, the signal from theinterferent is included as an additional term

2) an interferent is a part of the samples matrix

total

total

find a method for separating the analyte and interferent

by removing one from the sample

Stotal,1= kA,1nA+ kI,1nI+ Sreag,1

Stotal,2= kA,2nA+ kI,2nI+ Sreag,2


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CALIBRATION

Calibrationensures that the equipment or instrument used

to measure the signal is operating correctly by using astandard known to produce an exact signal.

Standardization is the process of experimentally

determining the relationship between the signal and the

amount of analyte (the value of kby measuring the signal

for one or more standard samples, each containing a

known concentration of analyte).

Several standards with different concentrations of analyteare used the result is best viewed visually by plotting

Stotalversus the concentration of analyte in the standards

Calibration curve.


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how a methods signal changes with respect to the

amount of analyte

Example of a calibration curve. The filled circles () are the

individual results for the standard samples and the line is the best

fit to the data determined by a linear regression analysis.


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Analytical Standards

Primary Standards: a reagent extremely pure, stable,no waters of hydration, and a high molecular weight.

Ex:-sodium carbonate: Na2CO3, mol wt. = 105.99 g/mol

-potassium hydrogen iodate: KH(IO3

)2

, mol wt. = 389.92

g/mol

-potassium dichromate: K2Cr2O7, mol wt. = 294.19 g/mol

(see Appendix 2)

Secondary Standards: a standard prepared in the

laboratory for a specific analysis. It is usually

standardized against a primary standard.


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Analytical Standards

Other reagents: Preparing a standard often requires additional

substances that are not primary or secondary reagents.

Preparing a standard solution: require a suitable solvent, and

additional reagents to adjust the standardsmatrix.

reagent grade chemicals conforming to standards set by the

American Chemical Society should be used.

The label on the bottle of a reagent grade chemical lists

either the limits for specific impurities, or provides an assayfor the impurities. (We can improve the quality of a reagent

grade chemical by purifying it, or by conducting a more

accurate assay).


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Examples of typical packaging labels for reagent grade chemicals. Label (a) provides

the manufacturersassay for the reagent, NaBr. Note that potassium is fagged with an

asterisk (*) because its assay exceeds the limits established by the American Chemical

Society (ACS). Label (b) does not provide an assay for impurities, but indicates that thereagent meets ACS specifications. An assay for the reagent, NaHCO3 is provided.


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Preparing Standard Solutionswith larger ranges of concentration: standards are best

prepared by a serial dilution from a single stock solution.

Example: To carry out a serial "ten-fold" dilution

Add 9 mL of solvent to

each test tube.

To the first test tube,

add 1 mL of the stocksolution.

Mix or vortex.

Add 1 mL of this solution

to the second test tubeand mix.

Repeat until you have

reached your desired

concentration.

Serial dilutions must be prepared

with extra care because an error

in preparing one standard is

passed on to all succeeding

standards !!!


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Example: Use an analytical balance to weigh a standard for making

a calibration curve.

+ Take note the exact number appearing on the balance because

you will use this value to calculate the series of standards

concentration. For example, you have the number of 0.0209 g

appearing on the balance just take note as it is (although your

intentional number was 200 ppm). It doesnt matter if you take the

number of exact 200 ppm or 209 ppm because both of them are in

the range of the instrumentsdetection.+ Usually use a volumetric flask for stock solution: Dissolve 0.0209 g

of the standard in 100 mL volumetric flask by solvent A0.0209 g/

100 mL = 20.9 mg/ 100 mL = 20900 g/ 100 mL = 209 g/ mL

+ 209 ppm 20.9 2.09

104.5 10.45 1.045

52.25 5.225 0.5225

10 fold dilution:

1mL(209 ppm)+9mLsolvent A

From 209 ppm to 104.5 ppm

2 fold dilution: 5mL (209 ppm)+ 5mL solvent AFrom 104.5 ppm to 52.25 ppm2 fold dilution: 5mL (104.5ppm) + 5mL solvent A

10 fold dilution:

1mL(20.9 ppm)+9mLsolvent A

10 fold dilution:1mL(104.5ppm)+9mL solvent A

10 fold dilution:1mL(10.45ppm)+9mL solvent A 6 points for the

calibration curve inthis case


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the most desirable situation since the methods sensitivity

remains constant throughout the analytesconcentration range.

Find out analytesconcentration = xfrom its signal y

and the equationy=1020.38x-3.50


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0.90 < r < 0.95 : lin earity

0.95 < r < 0.99 : good linearity

0.99 < r : excellent lin earit y

Correlation Coefficient, r

where nis the number ofpairs of data

measures the strength and the direction of a linear

relationship between two variables

-1 < r< +1


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Correlation Coefficient, r

Posit ive correlat ion : Ifxand yhave a strong positive linearcorrelation, ris close to +1. An rvalue of exactly +1indicates a

perfect positive fit. Positive values indicate a relationship

betweenxand yvariables such that as values forxincrease,

values for y also increase.

Negative correlat ion :Ifxand yhave a strong negative linear

correlation, ris close to -1. An rvalue of exactly -1indicates a

perfect negative fit. Negative values indicate a relationship

between x and y such that as values for x increase, valuesfor ydecrease.


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The coefficient of determination(R2) is a measure of the

fraction of the total variation in ythat can be explained by

the linear relationship betweenxand y.

The closer R2 is to unity, the better the linear model

explains the y variations.

No correlat ion : If there is no linear correlation or a weak

linear correlation, r is close to 0. A value near zero means

that there is a random, nonlinear relationship between the two

variables. Note that r is a dimensionless quantity; that is, itdoes not depend on the units employed.

A perfect correlationof 1 occurs only when the data points

alllie exactly on a straight line. If r= +1, the slope of this lineis positive. If r= -1, the slope of this line is negative.

Coefficient of Determination, r2 or R2


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if r = 0.922, then r 2 = 0.850, which means that

85% of the total variation in ycan be explained by

the linear relationship between x and y (as

described by the regression equation). The other

15% of the total variation in y remains

unexplained.

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Vocabulary of Anal Chem (Cont.)