analytical chemistry definition: the science of extraction, identification, and quantitation of an...
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Analytical Chemistry
Definition: the science of extraction, identification, and quantitation of an unknown sample.
Example Applications:
•Human Genome Project
•Lab-on-a-Chip (microfluidics) and Nanotechnology
•Environmental Analysis
•Forensic Science
Course Philosophy
develop good lab habits and technique background in classical “wet chemical”
methods (titrations, gravimetric analysis, electrochemical techniques)
Quantitation using instrumentation (UV-Vis, AAS, GC)
Chapter 0:The Analytical Process (Example)
1. Formulating the Question
2. Selecting Analytical Procedures
3. Sampling
Random Heterogeneous Material
Segregated Heterogeneous Material
4. Sample Preparation
5. Analysis
6. Reporting and Interpretation
7. Drawing Conclusions
Terminology to Know From the Example
representative sampling – random vs. segregated sample preparation extraction, centrifugation, filtering chromatography, stationary phase, adsorption aliquot calibration curve
General Steps in a Chemical Analysis
1. Formulating the Question
2. Select an analytical procedure (literature search)
3. Sampling - representative samples (random vs. segregated)
4. Sample Preparation (extraction, separation, etc)
5. Analysis of an aliquot (homogeneous phase)
6. Reporting and Interpretation
7. Drawing Conclusions
Analyses you will perform
Basic statistical exercises %purity of an acidic sample %purity of iron ore %Cl in seawater Water hardness determination UV-Vis: Amount of caffeine and sodium benzoate in a
soft drink AAS: Composition of a metal alloy GC: Gas phase quantitation
titrations
Chapter 1:Chemical Measurements
Chemical Concentrations
liter
moles(M)Molarity
L
mg
grams 1000
mg
grams10
grams10
grams10
gram 1 ppm
3
-3
6
Dilution Equation
Concentrated HCl is 12.1 M. How many milliliters should be diluted to 500 mL to make 0.100 M HCl?
Chapter 3:Math Toolkit
accuracy = closeness to the true or accepted value
precision = reproducibility of the measurement
Significant Figures
Digits in a measurement which are known with certainty, plus a last digit which is estimated
beaker graduated cylinder buret
Rules for Determining How Many Significant Figures There are in a Number
All nonzero digits are significant (4.006, 12.012, 10.070)
Interior zeros are significant (4.006, 12.012, 10.070) Trailing zeros FOLLOWING a decimal point are
significant (10.070) Trailing zeros PRECEEDING an assumed decimal
point may or may not be significant Leading zeros are not significant. They simply locate
the decimal point (0.00002)
Reporting the Correct # of Sig Fig’s
Multiplication/Division 12.154
5.23
Rule: Round off to the fewest number of sig figs originally present
36462
24308
6077063.56542
ans = 63.5
Reporting the Correct # of Sig Fig’s
Addition/Subtraction 15.02
9,986.0
3.518
Rule: Round off to the least certain decimal place
10004.538
Rounding Off Rules
digit to be dropped > 5, round UP158.7 = 159
digit to be dropped < 5, round DOWN158.4 = 158
digit to be dropped = 5, round UP if result is EVEN
158.5 = 158157.5 = 157
Wait until the END of a calculation in order to Wait until the END of a calculation in order to avoid a “rounding error”avoid a “rounding error”
(1.23(1.2355 - 1.0 - 1.022) x 15.23) x 15.2399 = 2.923438 = = 2.923438 = 1.11.122
1.231.2355-1.0-1.022
0.20.21515 = 0.2 = 0.222
? sig figs? sig figs 5 sig figs5 sig figs
3 sig figs3 sig figs
Propagation of Errors
A way to keep track of the error in a calculation based on the errors of the variables used in the calculation
error in variable x1 = e1 = "standard deviation" (see Ch 4)
e.g. 43.27 0.12 mL
percent relative error = %e1 = e1*100 x1
e.g. 0.12*100/43.27 = 0.28%
Addition & Subtraction
Suppose you're adding three volumes together and you want to know what the total error (et) is:
43.27 0.12 42.98 0.22 43.06 0.15129.31 et
......eeee
......eeee
2
3
2
2
2
1t
2
3
2
2
2
1
2
t
Multplication & Division
......ee%ee
......eeee
2
3
2
2
2
1t
2
3
2
2
2
1
2
t
%%
%%%
0.02)( 0.59
0.02)( 1.89 x 0.03)( 1.76
4.0%
1.7
0.59
100*0.02
1.89
100*0.02
1.76
100*0.03e
222
t
222 )4.3()1.1(
Combined Example
0.35)( 2.57
0.020)( 0.25 0.10)( 1.10
Chapter 4:Statistics
Gaussian Distribution:
Fig 4.2
22 2/)(exp2
1);;(
ii xxP
N
xN
ii
1
2)(
1
)(1
2_
N
xx
s
N
ii
Standard Deviation – measure of the spread of the data (reproducibility)
Infinite population Finite population
Mean – measure of the central tendency or average of the data (accuracy)
N
iixN
1
1lim
Infinite population
N
iixN
x1
_ 1
Finite population
N
Standard Deviation and Probability
Confidence Intervals
Confidence Interval of the Mean
The range that the true mean lies within at a given confidence interval
x
True mean “” lies within this range
N
ts
N
ts
N
ts xμ
_
Example - Calculating Confidence Intervals
In replicate analyses, the carbohydrate content of a glycoprotein is found to be 12.6, 11.9, 13.0, 12.7, and 12.5 g of carbohydrate per 100 g of protein. Find the 50 and 90% confidence intervals of the mean.
Rejection of Data - the "Q" Test
A way to reject data which is outside the parent population.
value smallest-value largest
neighbor nearestvalue lequestionabQexp
Compare to Qcrit from a table at a given confidence interval.
Reject if Qexp > Qcrit
Example: Analysis of a calcite sample yielded CaO percentages of 55.95, 56.00, 56.04, 56.08, and 56.23. Can the last value be rejected at a confidence interval of 90%?
Linear Least Squares- finding the best fit to a straight line