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CH 315

Analytical Instrumentation

Lecture 3

Sampling/Sample Preparation

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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 +=

222

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.

CH 315

Analytical Instrumentation

Lecture 3

Sample Preparation

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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.