Post on 02-Dec-2015
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Sampling
• Choosing a good representative sample is the underlying
basis for any good analysis.
Sampling: process of choosing a representative bulk sample from some total material (Lot).
Sample preparation: process of transforming a bulk sample into a sample ready for analysis (a lab sample).
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Sampling Plans
• A good sampling plan is dependant on the goals of the
analyst.
• In a qualitative analysis for example the sample does not need to be identical to the original lot as long as the analyte to be
detected is at detectable levels.
• Samples for quantitative analysis must accurately represent
the lot.
• This requires much more careful planning and the careful
consideration of several issues.
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Sampling Plans
• In a sampling plan for quantitative analysis the following five
questions must be considered:
• Where should the representative sample be collected
from the lot?
• What type of sample should be collected?
• What is the minimum amount of sample needed for the
analysis?
• How many samples need to be analyzed?
• How can the variance associated with the analysis be
minimized?
Representative samples
• When a lot has a homogeneous composition samples can be
taken of the lot without concern that they will be different then
the lot.
• Many lots are heterogeneous.
• In these cases this must take this into account.
• Simplest solution � Homogenization.
• Not always practical do to loss of information about analyte’s
distribution through space or time.
• Alternative implement sampling plan.
Sampling plans
• Types of sampling plans:
• Random Sampling:
• Samples are obtained at random from a lot.
• Truly random samples are difficult to obtain.
• Need a large number of samples.
Where to collect samples
• Types of sampling plans (continued):
• Judgmental Sampling:
• Opposite of random sampling.
• Prior information about lot is used to guide sample
selection.
• More biased then random but requires fewer samples.
• Types of sampling plans (continued):
• Systematic Sampling:
• A lot is sampled over regular intervals in space or
time.
• Not as biased as judgemental sampling nor requiring
as many samples as truly random sampling.
• Systematic-Judgemental Sampling:
• Prior knowledge of a lot is used to guide a systematic
sampling plan.
Where to collect samples
• Types of sampling plans (continued):
• Stratified Sampling:
• Also referred to as judgemental-random.
• Some lots consist of distinct units or strata.
• In stratified sampling the lot is divided into strata and
random samples are collected in each.
• Convenience Sampling:
• Sampling sites are chosen for reasons of convenience
and not to minimize error.
Where to collect samples
Type of Sample
• Once you have decided where and when to collect a sample
you must next decide what type of sample to collect.
• There are three main types of samples:
• Grab samples:
• A portion of a lot is collected at a specific time and/or
location.
• Composite samples:
• A sample made up of a set of grab samples.
• In Situ sampling:
• A sensor is inserted directly into a lot.
How much sample?
Origin of Sampling Variance:
• What is the chance that a random sample will have the same composition as the bulk sample?
• Consider a sample that is a mixture of two types of particles A and B.
• If the mixture contains nA particles of A and nB particles of B what is the chance of randomly drawing either particle?
BA
A Adrawing ofy probabilit nn
np
+
==
pnn
nq −=
+
== 1BA
B B drawing ofy probabilit
How much sample?
Origin of Sampling Variance:
• If we randomly pick n particles, how many should be type A?
• How may should be type B?
• If we know values for n, p and q an absolute standard deviation for the sampling operation can be calculated:
np particles A of number Expected =
)( particles B of number Expected pnnq −== 1
npqsn
=
How much sample?
Random Sampling:
• A mixture contains 1% KCl particles and 99% KNO3 particles.
� If 10,000 particles are taken what is the expected number of KCl particles, and what will be the standard deviation if the experiment is repeated many times?
• Standard deviation?
Relative Standard Deviation:
• Relative standard deviation of particle p and q:
• Relative Standard Deviation of KCl and KNO3:
np
q
np
npqs
np==
nq
p
nq
npqs
nq==
How much sample?
A box contains 120000 red marbles and 880000 yellow marbles.
(a) If you draw a random sample of 1000 marbles from the box what are the expected numbers of red and yellow marbles?
How much sample?
A box contains 120000 red marbles and 880000 yellow marbles.
(b) Now put those marbles back in the box and repeat the experiment. What will be the absolute and relative standard deviations for the numbers in part (a) after many drawings of 1000 marbles?
How much sample?
A box contains 120000 red marbles and 880000 yellow marbles.
(c) What will be the absolute and relative standard deviations after many drawings of 4000 marbles?
How much sample?
• In any experiment, random errors will be a factor.
• One source of these random errors is variations in the analytical procedures used.
• Another source is random errors due to variations in the sampling.
• The size of these random errors can be represented by the Variance:
• For any experiment the total variance can be given as:
2deviation) (standard Variance =
Variance Sampling Variance Method Variance Overall +=
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smosss +=
How many samples/minimizing variance
How many samples/minimizing variance
• The larger the number of samples the smaller the sampling
error and the smaller the sampling variance (ss2).
• Increasing the number of times each sample is analyzed
improves the method variance (sm2).
• If the sampling variance >> method variance there is no need
to analyze samples more then once.
• If the method variance >> sampling variance then only one sample needs to be collected and analyzed.
• If both types of variance are important then both multiple sample and replicate analyses of each sample are necessary.
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• Care must be taken in storing samples once chosen.
• Composition can change with time after collection due to:
• Chemical changes.
• Reaction with air.
• Interaction of sample with container.
Sampling
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Sample Preparation
• Once a bulk sample is selected, a laboratory sample must be
prepared.
• Sample preparation is the process of preparing a sample so it is
ready for analysis.
• Sample preparation may include:
• Grinding
• Dissolving the sample
� Acid digestion
� Fusion
• Removing or masking interfering species.
� Wet or dry ashing
• Extracting analyte from complex matrix.
• Concentrating dilute analyte.
• Converting analyte to detectible form.
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Sample Preparation
• The first step in preparing a solid sample is often to grind and
mix it in preparation for further treatment.
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Sample Preparation
• Laboratory samples are usually dissolved before analysis.
• Several sources of error exist at the sample dissolution stage
which can limit the accuracy of further analysis.• These errors include:
� Incomplete dissolution of the analyte.
� The sample must be dissolved completely.
� Loss of analyte by volatization.
� Care must be taken not to loose parts of the sample through conversion into gaseous forms and
subsequent evaporation.
� Introduction of analyte as solvent contamination.
� Trace amounts of an analyte in the solvent used can
lead to errors (especially in trace analysis).� Introduction of contaminants from vessel walls.
� Dissolution at high temperatures can lead to
contamination from the vessel they are carried out in.
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Sample Preparation
• Inorganic analytical samples usually require harsh conditions to
completely dissolve.
• The nonoxidizing acids HCl, HBr, HF, H3PO4, dilute H2SO4 and dilute HClO4 can dissolve most metals:
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Sample Preparation
• Some inorganic materials will not dissolve completely in acid.
• These samples can usually be dissolved by hot, molten
inorganic flux in a process known as fusion.
• In fusion:
• A finely powdered unknown is mixed with 2-20 time it
mass in flux.
• This mixture is then place in a crucible made of a material
chosen depending on the flux used.
• The crucible and mixture is then heated at 300 – 1200 °C
in a furnace or over a burner.
• The molten flux is then poured into beakers containing
10% aqueous HNO3 and dissolved.
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Sample Preparation
Decomposition of organic substances:
• Techniques used to decompose organic material can be organized into two broad categories:
� Wet ashing (requires a liquid).
� Carius method.
� High pressure asher
� Refluxing HNO3-HClO4.
� Kjeldahl digestion.
� Dry ashing (does not use a liquid).
� Combusition over open flame.
� Combustion-tube methods.
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Sample Preparation
Carius method:
• In this digestion method, fuming
HNO3 is sealed with the sample and
heated to 200 – 300 °C in a sealed, heavy-walled glass tube.
• The glass tube is placed inside a
steel vessel pressurized to the
same pressure as expected inside the glass tube.
• It is used to analyze organic
compounds for sulfur, halogens,
and phosphorus.
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Sample Preparation
High-pressure asher:
• High pressure allows acids
to be heated to high
temperature without boiling.
• This allows HNO3 to be
used instead of H2SO4.
• HNO3 can be produced
much purer then H2SO4.
• High-pressure ashers are used for trace analysis of
metallic elements.
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Sample Preparation
Wet ashing with refluxing HNO3-HClO4:
• A widely applicable method of
digestion but quite hazardous.
• Perchloric acid (HClO4) is an
extreme explosion hazard and
must be used with a blast shield.
• Bottles of HClO4 cannot be stored
on wooden shelves.
• Perchloric acid spilled on wood
can form explosive cellulose
perchlorate esters.