Instant notes in analytical chemistry

Section A – The nature and scope of analytical chemistryFUNCTIONS AND APPLICATIONS Definition Analytical chemistry involves the application of a range of techniques and methodologies to o

The INSTANT NOTES series

The INSTANT NOTES Chemistry series

Consulting editor: Howard Stanbury

First published 2002 (ISBN 1 85996 189 4)

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Abbreviations vii

Section A – The nature and scope of analytical chemistry 1

A1 Analytical chemistry, its functions and applications 1

Section C − Analytical reactions in solution 55

C7 Titrimetry II: complexation, precipitation and redox

D4 Gas chromatography: principles and instrumentation 137D5 Gas chromatography: procedures and applications 149D6 High-performance liquid chromatography: principles

D7 High-performance liquid chromatography: modes,

D8 Electrophoresis and electrochromatography: principles

D9 Electrophoresis and electrochromatography: modes,

Section E − Spectrometric techniques 189

E7 Atomic absorption and atomic fluorescence spectrometry 218

E8 Ultraviolet and visible molecular spectrometry:

E9 Ultraviolet and visible molecular spectrometry:

E10 Infrared and Raman spectrometry: principles and

E12 Nuclear magnetic resonance spectrometry: principles

E13 Nuclear magnetic resonance spectrometry: interpretation

F2 Sample identification using multiple spectrometric

G2 Differential thermal analysis and differential scanning

Section H – Sensors, automation and computing 323

ANOVA analysis of variance

CZE capillary zone electrophoresis

DSC differential scanning calorimetry

DTA differential thermal analysis

EDAX energy dispersive analysis

of X-raysEDTA ethylenediaminetetraacetic acid

spectometry

or free induction decay

HATR horizontal attenuated total

reflectance

chromatography

ICP-AES ICP-atomic emission spectrometry

ICP-OES ICP-optical emission spectrometry

LVDT linear variable differential

transformerMEKC micellar electrokinetic

SDS-PAGE SDS-polyacrylamide gel

electrophoresis

TISAB total ionic strength adjustment

buffer

Analytical chemists and others in many disciplines frequently ask questions such as: What is thissubstance?; How concentrated is this solution?; What is the structure of this molecule? The answers tothese and many other similar questions are provided by the techniques and methods of analyticalchemistry They are common to a wide range of activities, and the demand for analytical data of achemical nature is steadily growing Geologists, biologists, environmental and materials scientists,physicists, pharmacists, clinicians and engineers may all find it necessary to use or rely on some of thetechniques of analysis described in this book.

If we look back some forty or fifty years, chemical analysis concentrated on perhaps three main areas:qualitative testing, quantitative determinations, particularly by ‘classical’ techniques such as titrimetryand gravimetry, and structural analysis by procedures requiring laborious and time-consuming calcu-lations The analytical chemist of today has an armoury of instrumental techniques, automated systemsand computers which enable analytical measurements to be made more easily, more quickly and moreaccurately

However, pitfalls still exist for the unwary! Unless the analytical chemist has a thorough ing of the principles, practice and limitations of each technique he/she employs, results may be inaccu-rate, ambiguous, misleading or invalid From many years of stressing the importance of followingappropriate analytical procedures to a large number of students of widely differing abilities, backgroundsand degrees of enthusiasm, the authors have compiled an up-to-date, unified approach to the study ofanalytical chemistry and its applications Surveys of the day-to-day operations of many industrial andother analytical laboratories in the UK, Europe and the USA have shown which techniques are the mostwidely used, and which are of such limited application that extensive coverage at this level would beinappropriate The text therefore includes analytical techniques commonly used by most analyticallaboratories at this time It is intended both to complement those on inorganic, organic and physical

understand-chemistry in the Instant Notes series, and to offer to students in understand-chemistry and other disciplines some

guid-ance on the use of analytical techniques where they are relevant to their work We have not given extendedaccounts of complex or more specialized analytical techniques, which might be studied beyond first- andsecond-year courses Nevertheless, the material should be useful as an overview of the subject for thosestudying at a more advanced level or working in analytical laboratories, and for revision purposes The layout of the book has been determined by the series format and by the requirements of the overall analytical process Regardless of the discipline from which the need for chemical analysis arises,common questions must be asked:

● How should a representative sample be obtained?

● What is to be determined and with what quantitative precision?

● What other components are present and will they interfere with the analytical measurements?

● How much material is available for analysis, and how many samples are to be analyzed?

● What instrumentation is to be used?

● How reliable is the data generated?

These and related questions are considered in Sections A and B

Most of the subsequent sections provide notes on the principles, instrumentation and applications ofboth individual and groups of techniques Where suitable supplementary texts exist, reference is made

to them, and some suggestions on consulting the primary literature are made

We have assumed a background roughly equivalent to UK A-level chemistry or a US generalchemistry course Some simplification of mathematical treatments has been made; for example, in thesections on statistics, and on the theoretical basis of the various techniques However, the texts listedunder Further Reading give more comprehensive accounts and further examples of applications

We should like to thank all who have contributed to the development of this text, especially the manyinstrument manufacturers who generously provided examples and illustrations, and in particular PerkinElmer Ltd (UK) and Sherwood Scientific Ltd (UK) We would like also to thank our colleagues whoallowed us to consult them freely and, not least, the many generations of our students who foundquestions and problems where we had thought there were none!

DKPJH

Section A – The nature and scope of analytical chemistry

FUNCTIONS AND

APPLICATIONS

Definition Analytical chemistry involves the application of a range of techniques and

methodologies to obtain and assess qualitative, quantitative and structuralinformation on the nature of matter

● Qualitative analysis is the identification of elements, species and/or

compounds present in a sample

● Quantitative analysis is the determination of the absolute or relative amounts

of elements, species or compounds present in a sample

● Structural analysis is the determination of the spatial arrangement of atoms in

an element or molecule or the identification of characteristic groups of atoms(functional groups)

● An element, species or compound that is the subject of analysis is known as an

analyte

● The remainder of the material or sample of which the analyte(s) form(s) a part

is known as the matrix.

Purpose The gathering and interpretation of qualitative, quantitative and structural

infor-mation is essential to many aspects of human endeavor, both terrestrial andextra-terrestrial The maintenance of, and improvement in, the quality of lifethroughout the world, and the management of resources rely heavily onthe information provided by chemical analysis Manufacturing industries useanalytical data to monitor the quality of raw materials, intermediates and

Related topics Analytical problems and Computer control and data

Chemical sensors and biosensors Data enhancement and databases

finished products Progress and research in many areas is dependent on lishing the chemical composition of man-made or natural materials, and themonitoring of toxic substances in the environment is of ever increasing impor-tance Studies of biological and other complex systems are supported by thecollection of large amounts of analytical data.

estab-Analytical data are required in a wide range of disciplines and situations thatinclude not just chemistry and most other sciences, from biology to zoology, butthe arts, such as painting and sculpture, and archaeology Space exploration andclinical diagnosis are two quite disparate areas in which analytical data is vital.Important areas of application include the following

● Quality control (QC) In many manufacturing industries, the chemical

composition of raw materials, intermediates and finished products needs to

be monitored to ensure satisfactory quality and consistency Virtually allconsumer products from automobiles to clothing, pharmaceuticals and food-stuffs, electrical goods, sports equipment and horticultural products rely, inpart, on chemical analysis The food, pharmaceutical and water industries inparticular have stringent requirements backed by legislation for major compo-nents and permitted levels of impurities or contaminants The electronicsindustry needs analyses at ultra-trace levels (parts per billion) in relation to themanufacture of semi-conductor materials Automated, computer-controlledprocedures for process-stream analysis are employed in some industries

● Monitoring and control of pollutants The presence of toxic heavy metals

(e.g., lead, cadmium and mercury), organic chemicals (e.g., polychlorinatedbiphenyls and detergents) and vehicle exhaust gases (oxides of carbon,nitrogen and sulfur, and hydrocarbons) in the environment are health hazardsthat need to be monitored by sensitive and accurate methods of analysis, andremedial action taken Major sources of pollution are gaseous, solid and liquidwastes that are discharged or dumped from industrial sites, and vehicleexhaust gases

● Clinical and biological studies The levels of important nutrients, including

trace metals (e.g., sodium, potassium, calcium and zinc), naturally producedchemicals, such as cholesterol, sugars and urea, and administered drugs in thebody fluids of patients undergoing hospital treatment require monitoring.Speed of analysis is often a crucial factor and automated procedures have beendesigned for such analyses

● Geological assays The commercial value of ores and minerals is determined

by the levels of particular metals, which must be accurately established.Highly accurate and reliable analytical procedures must be used for thispurpose, and referee laboratories are sometimes employed where disputesarise

● Fundamental and applied research The chemical composition and structure

of materials used in or developed during research programs in numerousdisciplines can be of significance Where new drugs or materials with potentialcommercial value are synthesized, a complete chemical characterization may

be required involving considerable analytical work Combinatorial chemistry

is an approach used in pharmaceutical research that generates very largenumbers of new compounds requiring confirmation of identity and structure

Scope and

applications

Section A – The nature and scope of analytical chemistry

analyt-of the objectives analyt-of the analysis and an understanding analyt-of the capabilities analyt-of thevarious analytical techniques at his/her disposal without which the most appro-priate and cost-effective method cannot be selected or developed

The stages or steps in an overall analytical procedure can be summarized asfollows

● Definition of the problem Analytical information and level of accuracy

required Costs, timing, availability of laboratory instruments and facilities

● Choice of technique and method Selection of the best technique for the

required analysis, such as chromatography, infrared spectrometry, titrimetry,thermogravimetry Selection of the method (i.e the detailed stepwise instruc-tions using the selected technique)

● Sampling Selection of a small sample of the material to be analyzed Where

this is heterogeneous, special procedures need to be used to ensure that agenuinely representative sample is obtained (Topic A4)

Selecting or developing and validating appropriate methods of analysis

to provide reliable data in a variety of contexts are the principal problemsfaced by analytical chemists

Any chemical analysis can be broken down into a number of stages thatinclude a consideration of the purpose of the analysis, the quality of theresults required and the individual steps in the overall analyticalprocedure

Related topics Analytical chemistry, its functions Automated procedures (H2)

Sampling and sample handling collection (H3)

Chemical sensors and biosensors (H4)(H1)

Analytical problems

Analytical

procedures

● Sample pre-treatment or conditioning Conversion of the sample into a form

suitable for detecting or measuring the level of the analyte(s) by the selectedtechnique and method This may involve dissolving it, converting theanalyte(s) into a specific chemical form or separating the analyte(s) from other

components of the sample (the sample matrix) that could interfere with

detec-tion or quantitative measurements

● Qualitative analysis Tests on the sample under specified and controlled

conditions Tests on reference materials for comparison Interpretation of thetests

● Quantitative analysis Preparation of standards containing known amounts

of the analyte(s) or of pure reagents to be reacted with the analyte(s).Calibration of instruments to determine the responses to the standards undercontrolled conditions Measurement of the instrumental response for eachsample under the same conditions as for the standards All measurementsmay be replicated to improve the reliability of the data, but this has cost andtime implications Calculation of results and statistical evaluation

● Preparation of report or certificate of analysis This should include a

summary of the analytical procedure, the results and their statistical ment, and details of any problems encountered at any stage during theanalysis

assess-● Review of the original problem The results need to be discussed with regard

to their significance and their relevance in solving the original problem.Sometimes repeat analyses or new analyses may be undertaken

Section A – The nature and scope of analytical chemistry

AND METHODS

There are numerous chemical or physico-chemical processes that can be used toprovide analytical information The processes are related to a wide range ofatomic and molecular properties and phenomena that enable elements andcompounds to be detected and/or quantitatively measured under controlled

conditions The underlying processes define the various analytical techniques.

The more important of these are listed in Table 1, together with their suitability for

qualitative, quantitative or structural analysis and the levels of analyte(s) in asample that can be measured

Atomic and molecular spectrometry and chromatography, which together

comprise the largest and most widely used groups of techniques, can be further

subdivided according to their physico-chemical basis Spectrometric techniques may involve either the emission or absorption of electromagnetic radiation over

a very wide range of energies, and can provide qualitative, quantitative andstructural information for analytes from major components of a sample down

to ultra-trace levels The most important atomic and molecular spectrometric

techniques and their principal applications are listed in Table 2.

Chromatographic techniques provide the means of separating the nents of mixtures and simultaneous qualitative and quantitative analysis, asrequired The linking of chromatographic and spectrometric techniques, called

compo-hyphenation, provides a powerful means of separating and identifying

unknown compounds (Section F) Electrophoresis is another separation

tech-nique with similarities to chromatography that is particularly useful for theseparation of charged species The principal separation techniques and their

applications are listed in Table 3.

An analytical method consists of a detailed, stepwise list of instructions to befollowed in the qualitative, quantitative or structural analysis of a sample for one

or more analytes and using a specified technique It will include a summary and

Related topic Quality in analytical laboratories (A6)

Analytical methods

Analytical

techniques

Method validation

Table 1 Analytical techniques and principal applications

Gravimetry Weight of pure analyte or compound Quantitative for major or minor

Titrimetry Volume of standard reagent solution Quantitative for major or minor

reacting with the analyte componentsAtomic and molecular Wavelength and intensity of Qualitative, quantitative or structural spectrometry electromagnetic radiation emitted or for major down to trace level

absorbed by the analyte componentsMass spectrometry Mass of analyte or fragments of it Qualitative or structural for major

down to trace level componentsisotope ratios

Chromatography and Various physico-chemical properties Qualitative and quantitative

electrophoresis of separated analytes separations of mixtures at major to

trace levelsThermal analysis Chemical/physical changes in the Characterization of single or mixed

analyte when heated or cooled major/minor componentsElectrochemical analysis Electrical properties of the analyte Qualitative and quantitative for major

Radiochemical analysis Characteristic ionizing nuclear Qualitative and quantitative at major

radiation emitted by the analyte to trace levels

Table 2 Spectrometric techniques and principal applications

Plasma emission spectrometry Atomic emission after excitation in high Determination of metals and some

temperature gas plasma non-metals mainly at trace levelsFlame emission spectrometry Atomic emission after flame excitation Determination of alkali and alkaline

earth metalsAtomic absorption spectrometry Atomic absorption after atomization Determination of trace metals and

by flame or electrothermal means some non-metalsAtomic fluorescence Atomic fluorescence emission after Determination of mercury and

levelsX-ray emission spectrometry Atomic or atomic fluorescence Determination of major and minor

emission after excitation by electrons elemental components of

or radiation metallurgical and geological samplesγ-spectrometry γ-ray emission after nuclear excitation Monitoring of radioactive elements in

environmental samplesUltraviolet/visible spectrometry Electronic molecular absorption in Quantitative determination of

Infrared spectrometry Vibrational molecular absorption Identification of organic compoundsNuclear magnetic resonance Nuclear absorption (change of spin Identification and structural analysis

Mass spectrometry Ionization and fragmentation of Identification and structural analysis

lists of chemicals and reagents to be used, laboratory apparatus and glassware,and appropriate instrumentation The quality and sources of chemicals,including solvents, and the required performance characteristics of instrumentswill also be specified as will the procedure for obtaining a representative sample

of the material to be analyzed This is of crucial importance in obtaining ingful results (Topic A4) The preparation or pre-treatment of the sample will befollowed by any necessary standardization of reagents and/or calibration ofinstruments under specified conditions (Topic A5) Qualitative tests for theanalyte(s) or quantitative measurements under the same conditions as those usedfor standards complete the practical part of the method The remaining steps will

mean-be concerned with data processing, computational methods for quantitativeanalysis and the formatting of the analytical report The statistical assessment ofquantitative data is vital in establishing the reliability and value of the data, andthe use of various statistical parameters and tests is widespread (Section B)

Many standard analytical methods have been published as papers in

analyt-ical journals and other scientific literature, and in textbook form Collections bytrades associations representing, for example, the cosmetics, food, iron and steel,pharmaceutical, polymer plastics and paint, and water industries are available.Standards organizations and statutory authorities, instrument manufacturers’applications notes, the Royal Society of Chemistry and the US EnvironmentalProtection Agency are also valuable sources of standard methods Often, labora-

tories will develop their own in-house methods or adapt existing ones for specific purposes Method development forms a significant part of the work of most analytical laboratories, and method validation and periodic revalidation is

a necessity

Selection of the most appropriate analytical method should take into accountthe following factors:

● the purpose of the analysis, the required time scale and any cost constraints;

● the level of analyte(s) expected and the detection limit required;

● the nature of the sample, the amount available and the necessary samplepreparation procedure;

● the accuracy required for a quantitative analysis;

● the availability of reference materials, standards, chemicals and solvents,instrumentation and any special facilities;

● possible interference with the detection or quantitative measurement of

the analyte(s) and the possible need for sample clean-up to avoid matrix

interference;

Table 3 Separation techniques and principal applications

Differential rates of migration of Gas chromatography

analytes through a stationary phase Quantitative and qualitative

by movement of a liquid or gaseous determination of volatile compoundsHigh-performance liquid mobile phase Quantitative and qualitative

compoundsElectrophoresis Differential rates of migration of Quantitative and qualitative

analytes through a buffered medium determination of ionic compounds

● the degree of selectivity available − methods may be selective for a small number of analytes or specific for only one;

● quality control and safety factors

Method validation Analytical methods must be shown to give reliable data, free from bias and

suit-able for the intended use Most methods are multi-step procedures, and theprocess of validation generally involves a stepwise approach in which optimized

experimental parameters are tested for robustness (ruggedness), that is

sensi-tivity to variations in the conditions, and sources of errors investigated

A common approach is to start with the final measurement stage, using bration standards of known high purity for each analyte to establish the perfor-mance characteristics of the detection system (i.e specificity, range, quantitativeresponse (linearity), sensitivity, stability and reproducibility) Robustness interms of temperature, humidity and pressure variations would be included atthis stage, and a statistical assessment made of the reproducibility of repeatedidentical measurements (replicates) The process is then extended backwards insequence through the preceding stages of the method, checking that the optimumconditions and performance established for the final measurement on analytecalibration standards remain valid throughout Where this is not the case, newconditions must be investigated by modification of the procedure and the process

cali-repeated A summary of this approach is shown in Figure 1 in the form of a flow

diagram At each stage, the results are assessed using appropriate statistical tests(Section B) and compared for consistency with those of the previous stage Whereunacceptable variations arise, changes to the procedure are implemented and theassessment process repeated The performance and robustness of the overallmethod are finally tested with field trials in one or more routine analyticallaboratories before the method is considered to be fully validated

Fig 1 Flow chart for method validation.

Step 1 Performance characteristics of detector

for single analyte calibration standards

Step 2 Process repeated for mixed analyte

calibration standards

Step 6 Field trials in routine laboratory with

more junior personnel to test ruggedness

Step 5 Analysis of 'spiked' simulated sample

matrix i.e matrix with added knownamounts of analyte(s), to test recoveries

Step 3 Process repeated for analyte calibration

standards with possible interferingsubstances and for reagent blanks

Step 4 Process repeated for analyte calibration

standards with anticipated matrixcomponents to evaluate matrix

interference

A4 S AMPLING AND SAMPLE

HANDLING

The importance of obtaining a representative sample for analysis cannot beoveremphasized Without it, results may be meaningless or even grossly

misleading Sampling is particularly crucial where a heterogeneous material is to

be analyzed It is vital that the aims of the analysis are understood and an

appro-priate sampling procedure adopted In some situations, a sampling plan or

strategy may need to be devised so as to optimize the value of the analyticalinformation collected This is necessary particularly where environmentalsamples of soil, water or the atmosphere are to be collected or a complex indus-trial process is to be monitored Legal requirements may also determine asampling strategy, particularly in the food and drug industries A small sample

taken for analysis is described as a laboratory sample Where duplicate analyses

or several different analyses are required, the laboratory sample will be divided

into sub-samples which should have identical compositions.

Homogeneous materials (e.g., single or mixed solvents or solutions and mostgases) generally present no particular sampling problem as the composition ofany small laboratory sample taken from a larger volume will be representative of

the bulk solution Heterogeneous materials have to be homogenized prior to

obtaining a laboratory sample if an average or bulk composition is required.Conversely, where analyte levels in different parts of the material are to be

Due to varying periods of time that may elapse between samplecollection and analysis, storage conditions must be such as to avoidundesirable losses, contamination or other changes that could affect theresults of the analysis

Preliminary treatment of a sample is sometimes necessary before it is in asuitable form for analysis by the chosen technique and method This mayinvolve a separation or concentration of the analytes or the removal ofmatrix components that would otherwise interfere with the analysis

Samples generally need to be brought into a form suitable formeasurements to be made under controlled conditions This may involvedissolution, grinding, fabricating into a specific size and shape,

pelletizing or mounting in a sample holder

Related topic Analytical problems and procedures (A2)

measured, they may need to be physically separated before laboratory samples

are taken This is known as selective sampling Typical examples of

hetero-geneous materials where selective sampling may be necessary include:

● surface waters such as streams, rivers, reservoirs and seawater, where theconcentrations of trace metals or organic compounds in solution and in sedi-ments or suspended particulate matter may each be of importance;

● materials stored in bulk, such as grain, edible oils, or industrial organic icals, where physical segregation (stratification) or other effects may lead tovariations in chemical composition throughout the bulk;

chem-● ores, minerals and alloys, where information about the distribution of a ular metal or compound is sought;

partic-● laboratory, industrial or urban atmospheres where the concentrations of toxicvapors and fumes may be localized or vary with time

Obtaining a laboratory sample to establish an average analyte level in a highlyheterogeneous material can be a lengthy procedure For example, sampling alarge shipment of an ore or mineral, where the economic cost needs to bedetermined by a very accurate assay, is typically approached in the followingmanner

(i) Relatively large pieces are randomly selected from different parts of the

shipment

(ii) The pieces are crushed, ground to coarse granules and thoroughly mixed

(iii) A repeated coning and quartering process, with additional grinding to

reduce particle size, is used until a laboratory-sized sample is obtained.This involves creating a conical heap of the material, dividing it into fourequal portions, discarding two diagonally opposite portions and forming anew conical heap from the remaining two quarters The process is then

repeated as necessary (Fig 1).

The distribution of toxic heavy metals or organic compounds in a land velopment site presents a different problem Here, to economize on the number

rede-of analyses, a grid is superimposed on the site dividing it up into approximatelyone- to five-metre squares From each of these, samples of soil will be taken atseveral specified depths A three-dimensional representation of the distribution

of each analyte over the whole site can then be produced, and any localized high

concentrations, or hot spots, can be investigated by taking further, more

closely-spaced, samples Individual samples may need to be ground, coned andquartered as part of the sampling strategy

Repeated sampling over a period of time is a common requirement Examplesinclude the continuous monitoring of a process stream in a manufacturing plantand the frequent sampling of patients’ body fluids for changes in the levels ofdrugs, metabolites, sugars or enzymes, etc., during hospital treatment Studies ofseasonal variations in the levels of pesticide, herbicide and fertilizer residues insoils and surface waters, or the continuous monitoring of drinking water suppliesare two further examples

Having obtained a representative sample, it must be labeled and stored under

appropriate conditions Sample identification through proper labeling, ingly done by using bar codes and optical readers under computer control, is anessential feature of sample handling

increas-Sample storage Samples often have to be collected from places remote from the analytical

labora-tory and several days or weeks may elapse before they are received by the ratory and analyzed Furthermore, the workload of many laboratories is such thatincoming samples are stored for a period of time prior to analysis In bothinstances, sample containers and storage conditions (e.g., temperature, humidity,light levels and exposure to the atmosphere) must be controlled such that nosignificant changes occur that could affect the validity of the analytical data Thefollowing effects during storage should be considered:

labo-● increases in temperature leading to the loss of volatile analytes, thermal orbiological degradation, or increased chemical reactivity;

● decreases in temperature that lead to the formation of deposits or the tation of analytes with low solubilities;

precipi-● changes in humidity that affect the moisture content of hygroscopic solids andliquids or induce hydrolysis reactions;

● UV radiation, particularly from direct sunlight, that induces photochemicalreactions, photodecomposition or polymerization;

● air-induced oxidation;

● physical separation of the sample into layers of different density or changes incrystallinity

In addition, containers may leak or allow contaminants to enter

A particular problem associated with samples having very low (trace and

ultra-trace) levels of analytes in solution is the possibility of losses by tion onto the walls of the container or contamination by substances beingleached from the container by the sample solvent Trace metals may be depleted

adsorp-by adsorption or ion-exchange processes if stored in glass containers, whilstsodium, potassium, boron and silicates can be leached from the glass into thesample solution Plastic containers should always be used for such samples

Conversely, sample solutions containing organic solvents and other organicliquids should be stored in glass containers because the base plastic or additivessuch as plasticizers and antioxidants may be leached from the walls of plasticcontainers.

Samples arriving in an analytical laboratory come in a very wide assortment ofsizes, conditions and physical forms and can contain analytes from majorconstituents down to ultra-trace levels They can have a variable moisture contentand the matrix components of samples submitted for determinations of the same

analyte(s) may also vary widely A preliminary, or pre-treatment, is often used to

conditionthem in readiness for the application of a specific method of analysis or

to concentrate (enrich) analytes present at very low levels Examples of

pre-treatments are:

● drying at 100°C to 120°C to eliminate the effect of a variable moisture content;

● weighing before and after drying enables the water content to be calculated or

it can be established by thermogravimetric analysis (Topic G1);

● separating the analytes into groups with common characteristics by tillation, filtration, centrifugation, solvent or solid phase extraction (TopicD1);

dis-● removing or reducing the level of matrix components that are known to cause

interferencewith measurements of the analytes;

● concentrating the analytes if they are below the concentration range of theanalytical method to be used by evaporation, distillation, co-precipitation, ionexchange, solvent or solid phase extraction or electrolysis

Sample clean-up in relation to matrix interference and to protect

special-ized analytical equipment such as chromatographic columns and detection

systems from high levels of matrix components is widely practised using solid

phase extraction (SPE) cartridges (Topic D1) Substances such as lipids, fats,

proteins, pigments, polymeric and tarry substances are particularly mental

detri-A laboratory sample generally needs to be prepared for analytical measurement

by treatment with reagents that convert the analyte(s) into an appropriate ical form for the selected technique and method, although in some instances it is

chem-examined directly as received or mounted in a sample holder for surface

analysis If the material is readily soluble in aqueous or organic solvents, a simpledissolution step may suffice However, many samples need first to be decom-posed to release the analyte(s) and facilitate specific reactions in solution Samplesolutions may need to be diluted or concentrated by enrichment so that analytesare in an optimum concentration range for the method The stabilization of solu-tions with respect to pH, ionic strength and solvent composition, and the removal

or masking of interfering matrix components not accounted for in any ment may also be necessary An internal standard for reference purposes in

pre-treat-quantitative analysis (Topic A5 and Section B) is sometimes added before ment to the final prescribed volume Some common methods of decomposition

adjust-and dissolution are given in Table 1.

Table 1 Some methods for sample decomposition and dissolution

Heated with concentrated mineral Geological, metallurgicalacids (HCl, HNO3, aqua regia) or

strong alkali, including microwave digestion

Fusion with flux (Na2O2, Na2CO3, Geological, refractory materialsLiBO2, KHSO4, KOH)

Heated with HF and H2SO4or HClO4 Silicates where SiO2is not the analyteAcid leaching with HNO3 Soils and sediments

Dry oxidation by heating in a furnace Organic materials with inorganic analytes

or wet oxidation by boiling with concentrated H2SO4and HNO3or HClO4

Section A – The nature and scope of analytical chemistry

STANDARDS

Calibration With the exception of absolute methods of analysis that involve chemical

reac-tions of known stoichiometry (e.g., gravimetric and titrimetric determinareac-tions), a

calibration or standardization procedure is required to establish the relation

between a measured physico-chemical response to an analyte and the amount orconcentration of the analyte producing the response Techniques and methodswhere calibration is necessary are frequently instrumental, and the detectorresponse is in the form of an electrical signal An important consideration is theeffect of matrix components on the analyte detector signal, which may be

supressed or enhanced, this being known as the matrix effect When this is known to occur, matrix matching of the calibration standards to simulate the

gross composition expected in the samples is essential (i.e matrix componentsare added to all the analyte standards in the same amounts as are expected in thesamples)

There are several methods of calibration, the choice of the most suitabledepending on the characteristics of the analytical technique to be employed, thenature of the sample and the level of analyte(s) expected These include:

● External standardization A series of at least four calibration standards

containing known amounts or concentrations of the analyte and matrixcomponents, if required, is either prepared from laboratory chemicals of guar-anteed purity (AnalaR or an equivalent grade) or purchased as a concentratedstandard ready to use The response of the detection system is recorded foreach standard under specified and stable conditions and additionally for a

blank , sometimes called a reagent blank (a standard prepared in an identical

Key Notes

Calibration or standardization is the process of establishing the response

of a detection or measurement system to known amounts orconcentrations of an analyte under specified conditions, or thecomparison of a measured quantity with a reference value

A chemical standard is a material or substance of very high purityand/or known composition that is used to standardize a reagent orcalibrate an instrument

A reference material is a material or substance, one or more properties ofwhich are sufficiently homogeneous and well established for it to be usedfor the calibration of apparatus, the assessment of a measurement method

or for assigning values to materials

Related topic Calibration and linear regression (B4)

Calibration

Chemical standard

Reference material

fashion to the other standards but omitting the analyte) The data is either

plotted as a calibration graph or used to calculate a factor to convert detector

responses measured for the analyte in samples into corresponding masses orconcentrations (Topic B4)

● Standard addition

● Internal standardization

The last two methods of calibration are described in Topic B4

Instruments and apparatus used for analytical work must be correctly tained and calibrated against reference values to ensure that measurements areaccurate and reliable Performance should be checked regularly and records kept

main-so that any deterioration can be quickly detected and remedied Microcomputerand microprocessor controlled instrumentation often has built-in performancechecks that are automatically initiated each time an instrument is turned on.Some examples of instrument or apparatus calibration are

● manual calibration of an electronic balance with certified weights;

● calibration of volumetric glassware by weighing volumes of pure water;

● calibration of the wavelength and absorbance scales of spectrophotometerswith certified emission or absorption characteristics;

● calibration of temperature scales and electrical voltage or current readoutswith certified measurement equipment

Materials or substances suitable for use as chemical standards are generallysingle compounds or elements They must be of known composition, and high

purity and stability Many are available commercially under the name AnalaR.

Primary standards, which are used principally in titrimetry (Section C) tostandardize a reagent (titrant) (i.e to establish its exact concentration) must beinternationally recognized and should fulfil the following requirements:

● be easy to obtain and preserve in a high state of purity and of known chemicalcomposition;

● be non-hygroscopic and stable in air allowing accurate weighing;

● have impurities not normally exceeding 0.02% by weight;

● be readily soluble in water or another suitable solvent;

● react rapidly with an analyte in solution;

● other than pure elements, to have a high relative molar mass to minimizeweighing errors

Primary standards are used directly in titrimetric methods or to standardize

solutions of secondary or working standards (i.e materials or substances that do

not fulfill all of the above criteria, that are to be used subsequently as the titrant in

a particular method) Chemical standards are also used as reagents to effectreactions with analytes before completing the analysis by techniques other thantitrimetry

Some approved primary standards for titrimetric analysis are given in Table 1.

Reference materials are used to demonstrate the accuracy, reliability and

com-parability of analytical results A certified or standard reference material (CRM

or SRM) is a reference material, the values of one or more properties of which

have been certified by a technically valid procedure and accompanied by a able certificate or other documentation issued by a certifying body such as the

trace-Reference

material

Chemical

standard

Bureau of Analytical Standards CRMs or SRMs are produced in various formsand for different purposes and they may contain one or more certified compo-nents, such as

● pure substances or solutions for calibration or identification;

● materials of known matrix composition to facilitate comparisons of analyticaldata;

● materials with approximately known matrix composition and specifiedcomponents

They have a number of principal uses, including

● validation of new methods of analysis;

● standardization/calibration of other reference materials;

● confirmation of the validity of standardized methods;

● support of quality control and quality assurance schemes

Table 1 Some primary standards used in titrimetric analysis

Type of titration Primary standard

Sodium tetraborate, Na2B4O7.10H2OPotassium hydrogen phthalate, KH(C8H4O4)Benzoic acid, C6H5COOH

Redox Potassium dichromate, K2Cr2O7

Potassium iodate, KIO3Sodium oxalate, Na2C2O4Precipitation (silver halide) Silver nitrate, AgNO3

Sodium chloride, NaClComplexometric (EDTA) Zinc, Zn

Magnesium, MgEDTA (disodium salt), C10H14N2O8Na2

A6 Q UALITY IN ANALYTICAL

LABORATORIES

Quality control Analytical data must be of demonstrably high quality to ensure confidence in the

results Quality control (QC) comprises a system of planned activities in an

analytical laboratory whereby analytical methods are monitored at every stage toverify compliance with validated procedures and to take steps to eliminate thecauses of unsatisfactory performance Results are considered to be of sufficientlyhigh quality if

● they meet the specific requirements of the requested analytical work withinthe context of a defined problem;

● there is confidence in their validity;

● the work is cost effective

To implement a QC system, a complete understanding of the chemistry andoperations of the analytical method and the likely sources and magnitudes oferrors at each stage is essential The use of reference materials (Topic A5) during

method validation (Topic A3) ensures that results are traceable to certified

sources QC processes should include:

● checks on the accuracy and precision of the data using statistical tests (Section

B);

● detailed records of calibration, raw data, results and instrument performance;

● observations on the nature and behavior of the sample and unsatisfactoryaspects of the methodology;

● control charts to determine system control for instrumentation and repeat

analyses (Topic B5);

Key Notes

Quality control (QC) is the process of ensuring that the operationaltechniques and activities used in an analytical laboratory provide resultssuitable for the intended purpose

Quality assurance (QA) is the combination of planned and systematicactions necessary to provide adequate confidence that the process ofquality control satisfies specified requirements

This is a system whereby the quality control and quality assuranceprocedures adopted by a laboratory are evaluated by inspection andaccredited by an independent body

Related topics Analytical techniques and Quality control and chemometrics

● provision of full documentation and traceability of results to recognized

reference materials through recorded identification;

● maintenance and calibration of instrumentation to manufacturers’ tions;

specifica-● management and control of laboratory chemicals and other materials includingchecks on quality;

● adequate training of laboratory personnel to ensure understanding and competence;

● external verification of results wherever possible;

● accreditation of the laboratory by an independent organization

Quality assurance The overall management of an analytical laboratory should include the provision

of evidence and assurances that appropriate QC procedures for laboratory

activ-ities are being correctly implemented Quality assurance (QA) is a managerial

responsibility that is designed to ensure that this is the case and to generateconfidence in the analytical results Part of QA is to build confidence through the

laboratory participating in interlaboratory studies where several laboratories

analyze one or more identical homogeneous materials under specified

condi-tions Proficiency testing is a particular type of study to assess the performance

of a laboratory or analyst relative to others, whilst method performance studies and certification studies are undertaken to check a particular analytical method

or reference material respectively The results of such studies and their statisticalassessment enable the performances of individual participating laboratories to bedemonstrated and any deficiencies in methodology and the training of personnel

to be addressed

Because of differences in the interpretation of the term quality, which can be defined as fitness for purpose, QC and QA systems adopted by analyical labora-

tories in different industries and fields of activity can vary widely For this

reason, defined quality standards have been introduced by a number of

organi-zations throughout the world Laboratories can design and implement their ownquality systems and apply to be inspected and accredited by the organization forthe standard most appropriate to their activity A number of organizations thatoffer accreditation suitable for analytical laboratories and their corresponding

quality standards are given in Table 1.

Table 1 Accreditation organizations and their quality standards

Name of accreditation organization Quality standardOrganization for Economic Co-operation Good Laboratory Practice (GLP)and Development (OECD)

The International Organization for ISO 9000 series of quality standardsStandardization (ISO) ISO Guide 25 general requirements for

competence of calibration and testing laboratories

European Committee for Standardization EN 29000 series

British Standards Institution (BSI) BS 5750 quality standard

BS 7500 seriesNational Measurement Accreditation NAMASService (NAMAS)

Accreditation

system

Section B – Assessment of data

MEASUREMENTS

The causes of measurement errors are numerous and their magnitudes are

vari-able This leads to uncertainties in reported results However, measurement

errors can be minimized and some types eliminated altogether by careful imental design and control Their effects can be assessed by the application of

exper-statistical methods of data analysis and chemometrics (Topic B5) Gross errors

may arise from faulty equipment or bad laboratory practice; proper equipmentmaintenance and appropriate training and supervision of personnel shouldeliminate these

Nevertheless, whether it is reading a burette or thermometer, weighing asample or timing events, or monitoring an electrical signal or liquid flow, therewill always be inherent variations in the measured parameter if readings arerepeated a number of times under the same conditions In addition, errors may

go undetected if the true or accepted value is not known for comparison

purposes

Errors must be controlled and assessed so that valid analytical measurements

can be made and reported The reliability of such data must be demonstrated so that an end-user can have an acceptable degree of confidence in the results of

by the true or accepted value

Also known as systematic errors, or bias, these generally arise fromdeterminate or identifiable sources causing measured values to differfrom a true or accepted value

Also known as random errors, these arise from a variety of uncontrolledsources and cause small random variations in a measured quantity whenthe measurement is repeated a number of times

Where several different measurements are combined to compute anoverall analytical result, the errors associated with each individualmeasurement contribute to a total or accumulated error

Related topic Assessment of accuracy and precision (B2)

The absolute error, E A , in a measurement or result, x M, is given by the equation

E A = x M - x T

where x T is the true or accepted value Examples are shown in Figure 1 where a

200 mg aspirin standard has been analyzed a number of times The absolute

errorsrange from -4 mg to +10 mg

The relative error, E R , in a measurement or result, x M, is given by the equation

E R = (x M - x T )/x T

Often, E R is expressed as a percentage relative error, 100E R Thus, for the aspirin

results shown in Figure 1, the relative error ranges from -2% to +5% Relative

errors are particularly useful for comparing results of differing magnitude

Fig 1 Absolute and relative errors in the analysis of an aspirin standard.

There are three basic sources of determinate or systematic errors that lead to a

biasin measured values or results:

● the analyst or operator;

● the equipment (apparatus and instrumentation) and the laboratory ment;

environ-● the method or procedure

It should be possible to eliminate errors of this type by careful observation andrecord keeping, equipment maintenance and training of laboratory personnel

Operator errorscan arise through carelessness, insufficient training, illness or

disability Equipment errors include substandard volumetric glassware, faulty

or worn mechanical components, incorrect electrical signals and a poor or

insufficiently controlled laboratory environment Method or procedural errors

are caused by inadequate method validation, the application of a method tosamples or concentration levels for which it is not suitable or unexpected varia-tions in sample characteristics that affect measurements Determinate errors thatlead to a higher value or result than a true or accepted one are said to show a

positive bias ; those leading to a lower value or result are said to show a

nega-tive bias Particularly large errors are described as gross errors; these should be

easily apparent and readily eliminated

Determinate

errors

Determinate errors can be proportional to the size of sample taken for

analysis If so, they will have the same effect on the magnitude of a resultregardless of the size of the sample, and their presence can thus be difficult todetect For example, copper(II) can be determined by titration after reaction withpotassium iodide to release iodine according to the equation

2Cu2++ 4I-Æ 2CuI + I2However, the reaction is not specific to copper(II), and any iron(III) present inthe sample will react in the same way Results for the determination of copper in

an alloy containing 20%, but which also contained 0.2% of iron are shown in

Figure 2 for a range of sample sizes The same absolute error of +0.2% or relative

error of 1% (i.e a positive bias) occurs regardless of sample size, due to the

presence of the iron This type of error may go undetected unless theconstituents of the sample and the chemistry of the method are known

Sample size (g)0

Fig 2 Effect of a proportional error on the determination of copper by titration in the presence of iron.

Constant determinate errors are independent of sample size, and thereforebecome less significant as the sample size is increased For example, where avisual indicator is employed in a volumetric procedure, a small amount of

titrant is required to change the color at the end-point, even in a blank solution

(i.e when the solution contains none of the species to be determined) This

indicator blank(Topic C5) is the same regardless of the size of the titer when

the species being determined is present The relative error, therefore, decreases

with the magnitude of the titer, as shown graphically in Figure 3 Thus, for an

indicator blank of 0.02 cm3

, the relative error for a 1 cm3

titer is 2%, but this falls

to only 0.08% for a 25 cm3titer

Known also as random errors, these arise from random fluctuations in

measured quantities, which always occur even under closely controlled tions It is impossible to eliminate them entirely, but they can be minimized bycareful experimental design and control Environmental factors such as temper-ature, pressure and humidity, and electrical properties such as current, voltageand resistance are all susceptible to small continuous and random variations

condi-described as noise These contribute to the overall indeterminate error in any

Indeterminate

errors

physical or physico-chemical measurement, but no one specific source can beidentified.

A series of measurements made under the same prescribed conditions and

represented graphically is known as a frequency distribution The frequency of

occurrence of each experimental value is plotted as a function of the magnitude

of the error or deviation from the average or mean value For analytical data,

the values are often distributed symmetrically about the mean value, the most

common being the normal error or Gaussian distribution curve The curve

(Fig 4) shows that

● small errors are more probable than large ones,

● positive and negative errors are equally probable, and

● the maximum of the curve corresponds to the mean value

The normal error curve is the basis of a number of statistical tests that can beapplied to analytical data to assess the effects of indeterminate errors, to comparevalues and to establish levels of confidence in results (Topics B2 and B3)

2.521.510.5

Deviation from mean, µ

Fig 4 The normal error or Gaussian distribution curve.

Errors are associated with every measurement made in an analytical procedure,

and these will be aggregated in the final calculated result The accumulation or

propagationof errors is treated similarly for both determinate (systematic) andindeterminate (random) errors

Determinate (systematic) errors can be either positive or negative, hence somecancellation of errors is likely in computing an overall determinate error, and insome instances this may be zero The overall error is calculated using one of twoalternative expressions, that is

● where only a linear combination of individual measurements is required to

compute the result, the overall absolute determinate error, E T, is given by

E T = E 1 + E 2 + E 3+ ……

E 1 and E 2 etc., being the absolute determinate errors in the individual

measurements taking sign into account

● where a multiplicative expression is required to compute the result, the

overall relative determinate error, E TR, is given by

E TR = E 1R + E 2R + E 3R+ ……

E 1R and E 2Retc., being the relative determinate errors in the individual

measure-ments taking sign into account

The accumulated effect of indeterminate (random) errors is computed bycombining statistical parameters for each measurement (Topic B2)

Accumulated

errors

B2 A SSESSMENT OF ACCURACY

AND PRECISION

These two characteristics of numerical data are the most important and the mostfrequently confused It is vital to understand the difference between them, and

this is best illustrated diagrammatically as in Figure 1 Four analysts have

each performed a set of five titrations for which the correct titer is known to be20.00 cm3

The titers have been plotted on a linear scale, and inspection revealsthe following:

● the average titers for analysts B and D are very close to 20.00 cm3 - these two

sets are therefore said to have good accuracy;

● the average titers for analysts A and C are well above and below 20.00 cm3

respectively - these are therefore said to have poor accuracy;

● the five titers for analyst A and the five for analyst D are very close to one

another within each set – these two sets therefore both show good precision;

● the five titers for analyst B and the five for analyst C are spread widely

within each set - these two sets therefore both show poor precision.

The standard deviation of a set of values is a statistic based on the normalerror (Gaussian) curve and used as a measure of precision

Relative standard deviation (coefficient of variation) is the standarddeviation expressed as a percentage of the measured value

A standard deviation can be calculated for two or more sets of data bypooling the values to give a more reliable measure of precision

This is the square of the standard deviation, which is used in somestatistical tests

An estimate of the overall precision of an analytical procedure can bemade by combining the precisions of individual measurements

This is the range of values around an experimental result within whichthe true or accepted value is expected to lie with a defined level ofprobability

Related topic Errors in analytical measurements (B1)

It should be noted that good precision does not necessarily produce goodaccuracy (analyst A) and poor precision does not necessarily produce pooraccuracy (analyst B) However, confidence in the analytical procedure and theresults is greater when good precision can be demonstrated (analyst D).

Accuracyis generally the more important characteristic of quantitative data to

be assessed, although consistency, as measured by precision, is of particular

concern in some circumstances Trueness is a term associated with accuracy,

which describes the closeness of agreement between the average of a largenumber of results and a true or accepted reference value The degree of accuracyrequired depends on the context of the analytical problem; results must be shown

to be fit for the purpose for which they are intended For example, one result may

be satisfactory if it is within 10% of a true or accepted value whilst it may benecessary for another to be within 0.5% By repeating an analysis a number oftimes and computing an average value for the result, the level of accuracy will beimproved, provided that no systematic error (bias) has occurred Accuracycannot be established with certainty where a true or accepted value is not known,

as is often the case However, statistical tests indicating the accuracy of a result

with a given probability are widely used (vide infra).

Precision , which is a measure of the variability or dispersion within a set of

replicated values or results obtained under the same prescribed conditions, can

be assessed in several ways The spread or range (i.e the difference between the

highest and lowest value) is sometimes used, but the most popular method is to

estimatethe standard deviation of the data (vide infra) The precision of results

obtained within one working session is known as repeatability or within-run

precision The precision of results obtained over a series of working sessions is

known as reproducibility or between-runs precision It is sometimes necessary

to separate the contributions made to the overall precision by within-run and

Correctresult

between-runs variability It may also be important to establish the precision ofindividual steps in an analysis.

This is the most widely used measure of precision and is a parameter of the

normal erroror Gaussian curve (Topic B1, Fig 4) Figure 2 shows two curves for

the frequency distribution of two theoretical sets of data, each having an infinite

number of values and known as a statistical population.

The maximum in each curve corresponds to the population mean, which for

these examples has the same value, m However, the spread of values for the

two sets is quite different, and this is reflected in the half-widths of the two

curves at the points of inflection, which, by definition, is the population

stan-dard deviation, s As s 2 is much less than s 1, the precision of the second set is

much better than that of the first The abscissa scale can be calibrated inabsolute units or, more commonly, as positive and negative deviations from the

mean, m.

In general, the smaller the spread of values or deviations, the smaller the

value of s and hence the better the precision In practice, the true values of m and s can never be known because they relate to a population of infinite size.

However, an assumption is made that a small number of experimental values or

a statistical sample drawn from a statistical population is also distributed

normally or approximately so The experimental mean, x_

, of a set of values x 1 ,

x 2 , x 3 ,…….x nis therefore considered to be an estimate of the true or population

mean, m, and the experimental standard deviation, s, is an estimate of the true

or population standard deviation, s.

A useful property of the normal error curve is that, regardless of the

magni-tude of m and s, the area under the curve within defined limits on either side of

m (usually expressed in multiples of ±s) is a constant proportion of the total

area Expressed as a percentage of the total area, this indicates that a particularpercentage of the population will be found between those limits

Thus, approximately 68% of the area, and therefore of the population, will be

found within ±1s of the mean, approximately 95% will be found within ±2s and approximately 99.7% within ±3s More practically convenient levels, as shown

in Figure 3, are those corresponding to 90%, 95% and 99% of the population, which are defined by ±1.64s, ±1.96s and ±2.58s respectively Many statistical

tests are based on these probability levels.

The value of the population standard deviation, s, is given by the formula

(1)

where x i represents any individual value in the population and N is the total

number of values, strictly infinite The summation symbol, S, is used to show

that the numerator of the equation is the sum for i = 1 to i = N of the squares of the deviations of the individual x values from the population mean, m For very

large sets of data (e.g., when N >50), it may be justifiable to use this formula as the difference between s and s will then be negligible However, most analytical

data consists of sets of values of less than ten and often as small as three

Therefore, a modified formula is used to calculate an estimated standard

deviation, s, to replace s, and using an experimental mean, x_

, to replace the

population mean, m:

(2)冱