Transcript Analytical Chemistry II

Budi Hastuti, S.Pd., M.Si.
INTRODUCTION
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Two step analysis:
1. Identify
 Qualitative Analysis
2. Estimation  Quantitative Analysis
Method
 Classical / conventional
 Modern
Analytical scale  Macro, semimakro
 Ultramikro,Micro
 Submikro
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ANALYSIS covers 3 aspects comprehensively:
1. Data collection
2. Data processing, interpretation
3. Judgement, decision making / conclusions
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Analytical Chemystry is a science that identify the types
of components in a sample (qualitative analysis) and
determine the relative amounts of each component
(quantitative analysis).
Generally, phase separation is necessary to isolate the
components in the samples analyzed.
The method used distinguished role in 2 groups
namely: Classical Methods
Instrumental Methods
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1.
2.
3.
CLASSICAL METHODS - also called wet method
Separation of analytes - extraction, distillation,
precipitation (precipitation), filtration (filtering), etc..
Qualitative Analysis - boiling point, freezing point,
color, odor, density, reactivity, refractive index, etc..
Quantitative Analysis - gravimetric and volumetric
analysis.
The classic analytical
The modern analytical
 Long way since the beginning  A new way, consistent
of analytical chemistry
development of science and
technology
 It takes more complicated
 Dispensable complicated
contraption
tools
 sufficient sample quantaty is  small sample size (micro,
ultramikro, submikro)
needed (macro, semi-macro)
 Based on chemical reactions  Based on the measurement
of physical quantities of non
and the Stoichiometry
stoichiometry
equation
 Based of energy-matter
 based of matter-matter
interactions
interactions
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Sensitive
Fast
Selective and specific
Objective
Often non-destructive
Easily automated
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expensive tools
Utilization and complexmaintenance
Need a special technician
Need additional tools, calibration and
standardization of cheese (sometimes
difficult)
needs a good environment
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Instrumental Method
exploit the physical properties of an analyte to
obtain information, both qualitative and
quantitative.
Separation of analytes
- Can be done in 2 ways:
a. Physical separation:
- Chromatography
- Electrophoresis
b. Spectroscopic separation:
isolate the signal that appears in spectroscophy
Instrumental Method
1. Separation of analytes
2. Qualitative Analysis
* X-Ray Spectroscopy
* Infrared Spectroscopy (IR)
* mass spectroscopy (MS)
* nuclear magnetic spectroscopy (NMR)
3. Quantitive Analysis
* UV-Vis Spectroscopy
* Atomic absorption & emission spectroscopy
(AAS and AES)
* mass spectroscopy (MS)
* Conductivity (pH)
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Type method of Instrumental
Analytical
Signal
Signal
Generator
Detector
or
Input Transducer
Transduced
Signal
Electrical or
Mechanical
Signal
Signal
Processor
Display Unit
Computer
Digital Readout
Digital Data
Chart Recorder
Analog Data
Meter
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To determine the appropriate analytical method
(the best), the analyst should ask the following
things:
a. Is accuracy required?
b. How many samples are available?
c. How much range of concentrations found in the
sample?
d. Are there any components in the sample that
cause interference?
e. How physical and chemical properties of the
matrix contained in the sample?
f. How many samples to be analyzed?
Performance characteristics
The criteria used to compare several analytical methods
 Precision
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Absolute standard deviation
Relative standard deviation
Coefficient of variation
Variance
 Accuracy/Bias
 Absolute systematic error
 Relative systematic error
 Sensitivity
 Calibration
 Analytical
 Detection Limit
 Blank plus three times Std.
Dev. of blank
 Limit of Linearity (LOL)
 Selectivity
 Effects of interferences
 Coefficient of Selectivity
The other criteria that need to be considered in
the selection of analytical methods:
a Velocity analysis
b Convenience analysismethods
c Operator skill level
d Cost and availability of equipment
(instruments)
e Cost of analysis every sample
Performance characteristics
1. PRECISION
Measure reproducibility of a determination set
N
2
i
(
x
x
)

a) Absolute standard deviation (s)
s=
b) Relative standard deviation (RSD)
RSD =
c) Coefficient of variance (CV)
CV =
c) Standard error of mean (SE)
_
i =1
N -1
s
_
x
s
_ ´ 100%
x
SE = s / n
Performance characteristics
2. ACCURACY (BIAS)
Measure the error of an analytical method.
a) Absolute bias (Ea)
a) Persen bias (% error)
Ea = x - 
% Error=
x-

 100
Performance characteristics
3. SENSITIVITY
The ability to distinguish effect of increasing
concentration on instrument response.
S = mc  Sbl
Signal (S )
a) Calibration sensitivity (m)
100
m2
80
S = signal or instrument response
Sbl = signal from blank sample
c = sample concentration
m = calibration sensitivity
(slope of calibration curve)
60
DSm2
DSm1
Sbl
m1
40
20
0
0
0 .2
0 .4
DC
0 .6
0 .8
1
Conce ntration (c )
b) Analytical sensitivity (g)
m
g =
sS
g = analytical sensitivity
m = calibration sensitivity
sS = std. dev. in signal measurement
Performance characteristics
4. DETECTION LIMIT
Concentration / minimum analyte mass that still can be detected
(still can be distinguished from the noise) by a analysis method
based on certain confidence level (usually 95%)
a) Minimum detectable signal (Sm)
S m = S avg,bl  ksbl
Sm = minimum detectable signal
Savg,bl = average signal of the blank
sbl = standard deviation in the blank signal
k = multiple of variation in the blank signal
• The analytical signal must be larger than the blank signal (Savg,bl) by some factor (k) of
the standard deviation in the blank (sbl). k is usually set to a value of three.
b) Minimum detectable concentration (cm)
• Limit of Detection (LOD)
• Expressed in terms of sbl
cm =
S m - S avg, bl
cm =
m
ks bl
m
cm = minimum detectable concentration
m = slope of the calibration curve
Performance characteristics
5. SELECTIVITY
Degree an analytical method is free from interference
that contained on the sample matrix
mA = slope
mB = slope
S
S = mAcA  mB cB  mC cC  Sbl
kB,A = mB / mA
mC = slope k
C,A
= m /m
C
A
S = m (c  k c  k c )  S
,
,
Sbl
A
cA
cB
cC
A
BA B
CA C
bl
k is the selectivity coefficient
K value ranging from 0 (not selective) up to a
certain figure. Increase k, the methods more
selective