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Chemical Analysis 1 summary
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- Radboud Universiteit Nijmegen (RU)
Large summary of Chemical analysis 1 MOL-121. Everthing you need to know for the exam
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Chemical Analysis:Chapter 0: The analytical process
0-1: The analytical chemist’s job
Chemical abstracts is the most comprehensive database of the chemical literature
The first step in any chemical analysis is producing a reprehensive, small sample to
measure sampling.
Homogenous: the composition is the same everywhere .
Heterogenous: the composition differs from place to place.
Decanting: pouring off liquid from a solid (the denser phase is left behind).
Analytes: substances being measured.
Quantitative transfer: transferring the entire contents from one vessel to another,
usually accomplished by rinsing the first vessel several times with fresh liquid and
pouring each rinse into the receiving vessel.
Slurry: a suspension of solid in a liquid.
A solution of anything in water is called an aqueous solution.
Supernatant liquid: liquid remaining above the solid after a precipitation.
Sample preparation: transforming sample into a state that is suitable for analysis.
Solid-phase extraction: sample preparation procedure in which a solution is passed
through a short column of chromatographic stationary phase. Unretained
components of the sample are washed through the column. Components of interest
can be eluted in batches with successively stronger solvents. Analyte can be partially
purified and preconcentrated by this mean.
Chromatography solvent is selected by a systematic trial-and-error process. Acetic
acid neutralizes charged oxygen atoms on the silica surface that would strongly
retain a small fraction of caffeine and theobromine.
Chromatogram: the graph of detector response versus time.
Qualitative analysis: identifying what is in an unknown.
Quantitative analysis: identifying how much is present.
Calibration curve: a graph showing the value of some property versus concentration
of analyte. When the corresponding property of an unknown is measured, its
concentration can be determined from the graph.
Standard solutions: a solution whose composition is known by virtue of the way that
is was made from a reagent of known purity or by virtue of its reaction with a known
quantity of a standard reagent.
Replicate: repeated measurements of the same quantity.
Quality assurance: practises that demonstrate the reliability of analytical data.
Spike: addition of a known compound to an unknown.
Lot: the total material from which sample is taken.
Bulk sample/gross sample: taken from the lot for analysis and archiving must be
representative of the lot.
Archiving: storing for future reference.
Laboratory sample: a sample that is taken from the bulk sample must have the
same composition as the bulk sample.
, Random heterogenous material: differences in composition are random on a fine
scale random sample is collected by taking portions from a desired region chosen
at random.
Segregated heterogenous material: large regions have obviously different
compositions composite sample is taken by drawing a map and then take the
same amount of samples as the area.
0-2: General steps in a chemical analysis
Formulating the question: translate general questions into specific questions to be
answered through chemical measurements.
Selecting analytical procedures: search the chemical literature to find appropriate
procedures or, if necessary, devise new procedures to make the measurements.
Sampling: select representative material to analyse. If you begin with a poorly
chosen sample or if the sample changes between the time it is collected and the
time it is analysed, results are meaningless.
Sample preparation: converting a representative sample into a form suitable for
analysis, which usually means dissolving the sample. Samples with a low
concentration of analyte may need to be concentrated. It may be necessary to
remove or mask species that interfere with the chemical analysis.
Analysis: measure the concentration of analyte in several identical aliquots
(portions). The purpose of replicate measurements (repeated measurements) is to
assess the variability (uncertainty) in the analysis and to guard against a gross error
in the analysis of a single aliquot. The uncertainty of a measurement is as important
as the measurements itself, because it tells us how reliable the measurement is. If
necessary, use different analytical methods on similar samples to make sure that all
methods give the same result and that the choice of analytical method is not biasing
the result. You may also wish to construct and analyse several different bulk samples
to see what variations arise from your sampling procedure. Steps taken to
demonstrate the reliability of the analysis are called quality assurance.
Species: any chemical of interest.
Interference occurs when a species other than analyte increases or decreases the
response of the analytical method and makes it appear that there is more or less
analyte than is actually present.
Masking transforms an interfering species into a form that is not detected.
, Chapter 3: Math toolkit
3-1: Significant figures:
Significant figures: the minimum number of digits required to express a value in
scientific notation without loss of precision.
Zeros are significant when they are either in the middle of a number or at the end of
a number on the right-hand side of a decimal point.
The last significant figure in a measured quantity always has some associated
uncertainty.
Interpolation: estimate all readings to the nearest tenth of the distance between
scale divisions.
3-2: Significant figures in arithmetic:
Rounding should be done only in the final answer, to avoid accumulating round-off
errors.
If the numbers to be added or subtracted, the answer is given to the same decimal
place as that of the least-certain one (the one with the least decimals).
When rounding off, look at all the digits beyond the last place desired. If the
insignificant figures are more than halfway round up, if the insignificant figures are
less than halfway round down.
In the special case where the number is exactly halfway, round to the nearest even
digit (1.45 becomes 1.4, but 1.451 becomes 1.5). The rationale for rounding to an
even digit is to avoid systematically increasing or decreasing results through
successive round-off errors (half the round-offs will be up and half down).
Addition and subtraction: express all the numbers with the same exponent and align
all numbers with respect to the decimal point. Round off the answer according to
the number of decimal places in the number with the fewest decimal places.
In multiplication and division, we are normally limited to the number of digits
contained in the number with the fewest significant figures.
3-3: Types of error
Every measurement has some uncertainty, which is called experimental error. There
are two types of experimental error: systematic and random.
Systematic error/determinate error: repeatable if you make the same measurement
over again in the same way. A systematic error can be detected and corrected.
(Examples pH is always 0.08 too low, uncalibrated buret). Systematic error might be
positive in some regions and negative in others.
Ways to detect systematic error:
Analyze known sample. You should observe the known answer.
Analyze ‘blank’ sample containing no analyte. If you observe a nonzero result,
your method responds to more than you intend.
Use different analytical methods for the same analyte. If results do not agree,
there is an error in one (or more) of the methods.
Round robin experiment: analyze identical samples in different laboratories by
different people using the same or different methods. Disagreement beyond the
expected random error is systematic error.
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