(ANACHEM) 4.

Engineering (4)
a. Civil
INTRODUCTION TO ANALYTICAL CHEMISTRY b. Chemical
c. Electrical
Analytical Chemistry d. Mechanical
 a branch of chemistry involved with the analysis of chemical 5. Environmental Sciences (3)
substances a. Ecology
 it is called a measurement science b. Meteorology
 characterization of matter c. Oceanography
Involves: 6. Geology (4)
 Separating a. Geophysics
 Identifying b. Geochemistry
 Determining the relative amounts of the components of the c. Paleontology
sample d. Paleobiology
7. Materials Science (3)
Two Fields of Analytical Chemistry a. Metallurgy
1. Qualitative analysis b. Polymers
 involves identification of ions, elements, or compounds in a c. Solid Sate
sample of interest 8. Medicine (4)
a. Clinical Chemistry
2. Quantitative analysis b. Medicinal Chemistry
 determination of concentration or relative amount of c. Pharmacy
substances present in a given sample d. Toxicology
9. Physics (3)
Analyte – the components of a sample that are to be determined a. Astrophysics
b. Astronomy
c. Biophysics
QUALITATIVE QUANTITATIVE
10. Social Sciences (3)
deals with the identification of a. Archeology
elements, ions and compounds deals with the determination of
b. Anthropology
in a sample (we may be how much of one or more
c. Forensics
interested in whether a given constituent is present within a
substance is present or not) sample
The Role of Analytical Chemistry
tells “what“ is in a sample tells “how much“ is in a sample
1. Analytical chemists use science and technology to solve practical
identification of elements expressed in concentration
problems.
chemical test numerical data are collected 2. Analytical chemists work to improve the reliability of existing
There are two kinds of techniques to meet the demands of for better chemical
measure changes in color, quantitative analysis: measurements which arise constantly in our society.
melting point, boiling point, 1. Classical Chemical Analysis
odor, reactivity 3. Analytical chemists adapt proven methodologies to new kinds of
2. Instrumental Analysis
material or to answer new questions about their composition.
4. Analytical chemists carry out research to discover completely new
Analytical Chemistry is Applicable to Real World principles of measurements and are at the forefront of the
utilization of major discoveries such as medical devices for
1. Medicine practical purposes.
2. Industry
3. Environment
4. Food
5. Forensic NATURE OF ANALYTICAL CHEMISTRY
6. Biochemistry
7. Pharmaceutical Science
Methods of Analysis
The relationship of Analytical Chemistry to other branches of
Sciences
1. Qualitative Methods of Analysis
1. Agriculture (6) A. Chemical Test
a. Agronomy  a reagent or reagents are added to the sample to
b. Animal Science determine its composition
c. Crop Science EXAMPLE:
d. Food Science  Benedict’s test for glucose
e. Horticulture  Salkowski’s test for cholesterol
f. Soil Science  Phosphate test shows yellow precipitate
2. Biology (5)
a. Botany
b. Genetic
c. Microbiology
d. Molecular Biology
e. Zoology
3. Chemistry (4)
a. Biochemistry
b. Inorganic Chemistry
c. Organic Chemistry
d. Physical Chemistry
 B. Flame Tests b. Spectroscopic method
 detect the presence of certain elements, primarily metal o based on the measurement of the interaction
ions, based on each element’s characteristic emission between electromagnetic radiation and
spectrum analyte atoms or molecules
EXAMPLE: EXAMPLE:
 Sodium – intense yellow flame  UV-VIS Spectrophotometry which
 Calcium – red flame measures the concentration of solution
by the amount of light absorbed by the
substance across UV-Visible ranges of
the electromagnetic spectrum.

c. Flame photometry
o widely used analytical technique in the field of
chemistry and spectroscopy
o it involves the measurement of the intensity
2. Quantitative Method Analysis of light emitted by excited atoms or ions in a
A. Gravimetric method flame
 determine the mass of the analyte or some compound o by analyzing this emitted light, valuable
chemically related to it information about the composition and
 in this analysis, the analyte (substance of interest) is concentration of elements in a sample can be
converted to an insoluble substance (precipitate) that is obtained
isolated and weighed
EXAMPLE:
 In the analysis of lead (II), it is precipitated as lead
sulfate

d. Mass spectrometry
o an analytical tool useful for measuring the
mass-to-charge ration (m/z) of one or more
molecules present in a sample
B. Volumetric method o these measurements can often be used to
 the volume of a solution of a known concentration, calculate the exact molecular weight of the
containing suffiecient reagent to react completely with sample components as well
the analyte is measure
EXAMPLE:
 Acid-base titration

e. Chromatography (HPLC)
o an analytical technique used to identify the
components in a mixture and separate
mixtures and separate mixtures of very
similar compounds

C. Instrumentation methods
 with the use of scientific instruments
a. Electroanalytical method
o study an analyte by measuring potential
and/or current in an electrochemical cell
containing the analyte
EXAMPLE:
 Measuring pH using pH meter that uses
glass membrane electrode. The pH then
is related to the concentration of
hydronium ions in an analyte.
f. Electrophoresis (Capillary) Basic Analytical Process
o an analytical technique that separates ions
based on their electrophoretic mobility with 1. Select a method
the use of an applied voltage  Considerations:
 Level of Accuracy required
 Number of samples to be analyzed
 Complexity of sample and number of components to be
analyzed

2. Acquire the sample

 the sample should be carefully identified and collected as to
represent the entire bulk material

3. Process the sample

 Preparing laboratory samples
 Defining replicate samples
 Preparing Solutions – perform physical or chemical changes

4. Eliminating Interferences
g. Optical activity  Interferences
o Optical activity is an effect of an optical o is a species that causes error by enhancing or
isomer's interaction with plane-polarized light attenuating the quantity being measured
o the ability of a substance to rotate the plane  Selection of reagents or methods to be used that minimize
of polarization of a beam of light that is interferences should be done. This is what we call
passed through it “selectivity”
5. Calibrating and Measuring Concentration of Property X

6. Calculating Results
 These computations are based on the raw data collected in
the measurement step, the characteristics of the
measurement Instruments, and the stoichiometry of the
analytical reaction

h. Refractive Index 7. Evaluating the results by Estimating reliability

o dimensionless number that gives the The experimenter must provide some measure of the

indication of the light bending ability of that
uncertainties associated with computed results if the data
medium
are to have any value
o measure of the bending of a ray of light
when passing from one medium into another
o determine how much the path of light is bent, Types of Samples and Methods
or refracted, when entering a material
o is a value calculated from the ratio of the Types of Samples
speed of light in a vacuum to that in a second 1. Qualitative
medium of greater density  determination of identity of the chemical species
2. Quantitative
 determination of the relative amount of the chemical specie
in each amount of sample

Sample Size
1. Macro analysis
 amount of analyte is more than 0.10 grams (100 mg)
 suspected pollutant in a 1-gram soil sample
2. Semimicro analysis
 amount of analyte is between 0.010 – 0.10 grams
 amount of drug in a 5-mg sample of powder, determination
of glucose in a blood sample
3. Micro analysis
 amount of analyte is 10‫־‬⁴ to 10‫־‬² grams
 determination of creatinine in a urine sample
4. Ultramicro
 amount of analyte is less than 10‫־‬⁴ grams
 determination of arsenic, boron, nickel or silicon in the body
through urine test
 Types of Errors
Analyte Level
1. Major Constituent 1. Systematic Error or Determinate
 amount of analyte is 1-100% of the population 2. Random Error or Indeterminate
2. Minor Constituent
 amount of analyte is 0.1-1% of the population Systematic Error or Determinate
3. Trace Constituent
 amount of analyte is .01-0.1% (1ppb-100ppm) of the  errors that can be determined or eliminated
population  affects the accuracy (if we achieve our true value) of results
4. Ultratrace Constituent  have a definite value, an assignable cause, and are of the same
 amount of analyte is below 1ppb magnitude for replicate measurements made in the same way
 they lead to bias in measurements results
ppb – parts per billion  Bias
ppm – part per million  the deviation from the target value
 measures the systematic error associated with an analysis
Sampling  has a negative sign if it causes the results to be low and
a positive sign otherwise
 is the process of collecting a small mass of a material whose
composition accurately represents the bulk of the material being
Types of Systematic Error
sampled
 it is the most difficult aspect of analysis
 “Samples are analyzed, but species or concentrations are 1. Instrumental Errors
determined”  are cause by non-ideal instrument behavior, by faulty
calibrations, or by use under inappropriate conditions
 GOAL: Sampling process must ensure that the items chosen are
 e.g. A volumetric flask or pipette was graduated at
representative of the bulk of material or population
20°C and used at 25°C.
TYPES OF SAMPLES
2. Method Errors
1. Real samples
 arise from non-ideal chemical or physical behavior of
 Analysis of real samples are complicated because of the
analytical systems
presence of sample matrix --> remainder/ hindi kasali don
 e.g. In gravimetric method, if precipitate is not
sa analyte
sufficiently insoluble, a weight is less than the correct
EXAMPLE:
one
 Sampling of human blood for the determination of blood
3. Personal Errors
gases illustrates the difficulty of acquiring a
 result from the carelessness, inattention, or personal
representative sample from a complex biological
limitations of the experimenter
system. The concentration of oxygen and carbon
 e.g. Color blindness is a good example of a limitation
dioxide depends on different variables. By applying a
that could cause a personal error in a volumetric
tourniquet incorrectly or hand flexing by the patient, this
analysis
may cause the blood oxygen concentration to fluctuate
 Some personal errors in the medical laboratory:
2. Gross samples
 Patient ID error
 these are representative samples that are collected from
 Lost sample
the source
 Sample delayed in transit
 Yung g collect, may mixture pa, hindi pa na separate yung
 Contaminated samples
analyte
 Wrong test performed
3. Laboratory samples
 Test performed inconsistent with the written
 these are samples that are reduced in size and being
procedure
homogenized so that they are measurable in the lab
 Proficiency testing error
 No action on out-of range controls
 False negative result
ERRORS AND ANALYTICAL MEASUREMENTS  Late reports
 Missing reports
Analytical Results  Complaints
 are often used in the:  Laboratory accident
 diagnosis of disease  “near miss”
 assessment of hazardous wastes and pollution
 solving of major crimes Effects of Systematic Error
 quality control of industrial products
 errors in these results can have serious personal and societal 1. Constant Errors
effects  errors that are independent of the size of the sample
(decreasing or increasing) being analyzed; fixed
The CONSEQUENCES of wrong analyses in the field of:  Here the value of absolute value is constant with sample
 Environmental monitoring size, but the relative error varies when the sample is
 Drinking water changed
 Forensic  e.g. loss on the amount of precipitate due to large
 Businesses amount of liquid
 Healthcare 2. Proportional Errors
 Wrong diagnosis  errors that decrease or increase in proportion to the size of the
 The patient will suffer sample; can be reagents,concentration, or even the reaction
 License  Here the value of absolute error varies with sample size, but the
 Sue/lawsuit/malpractice relative error stays constant when the sample size is changed
 Wrong treatment  e.g. Presence of contaminants does not depend on
the size of the sample
 Random Error or Indeterminate Analytical Measurements

 errors that can not be determined or controlled  Accuracy and Precision are important in analytical
 it affects precision measurements
 are the cumulative effect of many small, uncontrollable variables
and personal judgments that lead to uncertainty in a measured ACCURACY
value  describes the nearness of an experimental value or a mean to
 e.g. Presence of bubbles in one of the trials, presence of the true value. Although true value can never be known exactly,
bubbles in the reading in the instruments, micro-clots in a accepted value is often used
plasma due to particulate matter  how close our measurement or experimental result to our true
 e.g. imprecise measurement value
 Statistically measured through absolute or relative error
3 ways to minimize Random Error
1. Repeated measurement PRECISION
2. Control variables  refers to the agreement between values in a set of data. It
3. Statistical measurement describes the reproducibility of measurements
 Statistically measured through standard deviation, variance,
coefficient of variation
QUANTIFYING EXPERIMENTAL ERRORS

 IT IS IMPOSSIBLE TO HAVE A PERFECT CHEMICAL

ANALYSIS, ONE THAT IS FREE FROM ERRORS AND
UNCERTAINTIES…

Assessment of Reliability of Results

 Evaluate the error – where did it come from? How?
 Perform same procedure from known values
 Compare from standard values
 Calibration of equipments
 Statistical treatments

Basic Statistical Treatments

 In order to improve the reliability and to obtain information about

the variability of results, two to five portions (replicates) of a
sample are usually carried through an entire analytical procedure
 Replicates - are samples of about the same size that are carried
through an analysis in exactly the same way
 Individual results from a set of measurements are seldom the
same, so we usually consider the “best” estimate to be the
central value for the set
MEAN ( )
 sum of numbers divided by numbers of measurements
 also known as arithmetic/average
 the average of all values given in a set of data
 If ever there is outliers, mean is not prefered to use as a
 The true mass of the wire is 2.000 g
statistical treatments or for computation
 Student B’s results are more precise than those of Student A
(1.972 g and 1.968 g deviate less from 1.970 g than 1.964 g and
1.978 g from 1.971 g) but neither set of results is very accurate.
 Student C’s results are not only the most precise, but also the
MEADIAN
most accurate, because the average value is closest to the true
 the middle value in a set of data that has been arranged in
value
numerical order --> should be arranged in increasing or
decreasing order
 is used advantageously when a set of data contain an outlier, a
result that differs significantly from others in the set
 An outlier can have a significant effect on the mean of the
set but has no effect on the median

RULES in terms of sample

 EVEN - choose the middle pair and divide by 2
 ODD - choose the middle number

EXAMPLE:
1. Compute the mean and the median of the following measurements:
65.5, 66.7, 68.8, 69.1, 69.2, 70.0
N (number of samples) = 6
MEAN = 65.5 + 66.7 + 68.8 + 69.1 + 69.2 + 70.0/6
= 68.2 or 68.21667
MEDIAN = 68.8 + 69.1/2
= 68.95 or 69,0
 Measurement of Accuracy

1. Absolute Error
 The absolute error of a system is equal to the difference
between the actual reading, xi (experimental result), and
the true (or accepted) value xt ; bears a sign

Interpretation:
 If the result of the measurement is positive sign, it means the
measurement result is high
 It means our experimental result is larger compared to the
accepted value
 If the result of the measurement is negative sign, the
measurement result is low
 It means our experimental result is smaller compared to
our true value

2. Relative Error
 describes the error in relation to the magnitude of the true value,
and may, therefore, be more useful than considering the
absolute error in isolation

Measurement of Precision

1. Sample standard deviation (s)

 describes the spread of data around the mean data point
for a set of replicate measurements

Reporting Computed Data

 This formula is used when replicates are less than 10
(which is common in analytical lab) Significant Figures
2. Relative Standard Deviation (RSD)  are all of the certain digits in a measurement plus the first
uncertain digit
 Follow rules in significant figures in reporting data after
computations
3. Coefficient of Variance (CV)
 the RSD in percentage

4. Variance (s²)
 Is the square of the standard deviation

 Shortcut = just square the sample standard deviation

 Significant Figures in Numerical Computations

1. Addition and Subtraction

 When adding or subtracting measurements with significant
figures, the result has the same number of decimal places as the
measurement with the lowest number of decimal places.

Significant Figures

 Laboratory investigations usually involve the taking of and

interpretation of measurements
 All physical measurements obtained by means of instruments
(meter sticks, thermometers, electrical meters, clocks, etc.) are 2. Multiplication and Division
to some extent uncertain  When multiplying or dividing measurements with significant
 The amount of uncertainty depends both upon the skill of the figures, the result has the same number of significant figures as
measurer and the quality of the measuring tool the measurement with the lowest number of significant
 The degree of uncertainty in physical measurements can be figures.
indicated by means of significant figures.


Rules in Determining Significant Figures

Multiplication

Rule 1: All nonzero digits in a measurement are significant.

 237 has 3 significant figures
 1.897 has 4 significant figures
Division
Rule 2: Interior zeros (zeros between nonzero numbers) are
significant.
 39,004 has 5 significant figures 3. Mix Operations (Add/Subtract and Multiply/Divide)
 5.02 has 3 significant figures  choose the rule of the last used operation
 PEMDAS
 Parenthesis
Rule 3: Leading zeros (zeros at the beginning of a number) are
 Exponent
NOT significant.
 Multiplication
 0.008 has 1 significant figure
 Division
 0.000416 has 3 significant figures
 Addiction
 Subtraction
Rule 4: Trailing zeros (zeros at the end of the number):
 are significant if and only if there is a decimal point present in the
number OR they carry overbars
 1400. has 4 significant figures
 1400 has 4 significant figures

 are NOT significant otherwise

 1000 has 1 significant figure
 190 has 2 significant figure

Scientific notation can be used to express the desired number of

significant figures.
 1.4×103 has 2 significant figure
 1.40×103 3 significant figures.
 1.400×103 has 4 significant figures

Practice
Practice
Give the number of significant figures in each.
Perform the following calculations to the correct number of significant
1. 5.87 - 3 sf
figures
2. 0.031 - 2 sf
1. 12.0550 + 9.05 = 21.105 --> 21.11
3. 52.90 - 4 sf
2. 257.2 – 19.789 = 237.411 --> 237.4
4. 00.2001 - 4 sf
3. (6.21x103) (0.150) = 95.9445 --> 95.9
5. 500 - 1 sf
4. 0.0577 ÷ 0.753 = 0.07662682603 --> 0.0766
6. 6 atoms - 1 sf
5. 27.5 x 1.82 ÷ 100.04 = 0.50029988 --> 0.500
 Significant Figures Logarithms and Antilogarithms

Logarithms and Antilogarithms

1. In a logarithm of a number, keep as many digits to the right of the
decimal point as there are significant figures in the original number.
2. In an antilogarithm of a number, keep as many digits as there are
digits to the right of the decimal point in the original number.

Rules for Rounding off Numbers

1. If the digit to be dropped is greater than 5, the last retained digit

is increased by one.
 12.6 is rounded to 13

2. If the digit to be dropped is less than 5, the last remaining digit

is left as it is.
 12.4 is rounded to 12

3. If the digit to be dropped is 5, and if any digit following it is not

zero, the last remaining digit is increased by one.
 12.51 is rounded to 13

4. If the digit to be dropped is 5 and is followed only by zeroes,

the last remaining digit is increased by one if it is odd, but left as
it is if even.
 11.5 is rounded to 12
 12.5 is rounded to 12

 This rule means that if the digit to be dropped is 5 followed only

by zeroes, the result is always rounded to the even digit. The
rationale is to avoid bias in rounding: half of the time we round up,
half the time we round down.

Practice

Round to the number of significant digits indicated.

1. 5.67498 to 1 sf. - 6

2. 0.04102 to 3 sf - 0.0410

3. 2.998 to 2 sf - 3.0

4. 26, 384 to 2 sf - 26,000 or 2.6 x10⁴

5. 37.446 to 3 sf - 37.4