Qualitative Analysis: A Guide - Softcover

Hardcastle, William A

Softcover

ISBN 10: 0854044620 ISBN 13: 9780854044627

Publisher: Royal Society of Chemistry, 1998

Synopsis

This Guide is concerned with the practice of qualitative analysis and contains invaluable advice for laboratories undertaking such work. It is designed to assist laboratories in establishing and maintaining a working regime that will minimise the risk of error and maximise the quality of the analytical information they produce. It is aimed primarily at laboratory managers and those responsible for any part of the analysis process from designing qualitative tests or deciding which tests to apply in particular cases to those performing the requisite experimental work. Qualitative Analysis has been developed using the knowledge and experience of an advisory panel drawn from a representative cross-section of practising analytical scientists. It was produced as part of the VAM Programme, and will be a useful guide for laboratory staff, government agencies, researchers and professionals in industry and academia alike.

About this title

From the Back Cover

This guide is concerned with the practice of qualitative analysis and contains invaluable advice for laboratories undertaking such work. It is designed to assist laboratories in establishing and maintaining a working regime that will minimise the risk of error and maximise the quality of the analytical information they produce. It is aimed primarily at laboratory managers and those responsible for any part of the analysis process from designing qualitative tests or deciding which tests to apply in particular cases to those performing the requisite experimental work. Qualitative Analysis: A Guide to Best Practice has been developed using the knowledge and experience of an advisory panel drawn from a representative cross-section of practising analytical scientists. It was produced as part of the VAM Programme, and will be a useful guide for laboratory staff, government agencies, researchers and professionals in industry and academia alike.

Excerpt. © Reprinted by permission. All rights reserved.

Qualitative Analysis

A Guide to Best Practice

By W.A. Hardcastle

The Royal Society of Chemistry

Copyright © 1998 LGC (Teddington)
All rights reserved.

ISBN: 978-0-85404-462-7

Contents

1 This Document, 1, 
2 The VAM Principles, 1, 
3 Scope, 2, 
4 Health and Safety, 3, 
5 Establishing the Requirements, 3, 
6 The Sample, 7, 
7 The Analytical Process, 12, 
8 Quality Assurance, 16, 
9 Interpretation of Results, 20, 
10 Analysis Report, 20, 
11 Field Testing, 21, 
12 Further Information, 21, 
Appendix A: Requirements and Design Model, 22, 
Appendix B: Bibliography, 23, 

CHAPTER 1

Qualitative Analysis: A Guide to Best Practice

1 This Document

This document is about principles of good practice in qualitative analysis. These principles are themselves related to one or more of the six VAM principles. In order to highlight this point, relevant VAM principles are indicated within square brackets at the beginning of each numbered section e.g. [VAM principle #1]. To assist the reader in locating the "Best Practice" principles, they are presented in italic with each one being further indicated by a finger sign in the left margin. Each statement of a principle is followed by some explanatory text which elaborates on the theme and may provide examples of why it is important.

The document as a whole is structured to follow the logical sequence of issues surrounding: health and safety; initial customer contact; samples; the analytical process; and quality assurance. A section on field testing is included to cover the important area of out of laboratory analyses.

2 The VAM Principles

The VAM Programme was set up with the aim of assisting analysts to obtain reliable analytical measurements. To facilitate this a set of six principles has been formulated and is widely publicised. The main focus of these principles, listed below, is on quantitative measurement but it is, of course, crucially important for the analyst to know the identity of whatever it is that he or she has measured. The word 'identity' in this context has a somewhat broad meaning; it could be the name of a single substance but equally it could be a descriptor for a recognised mixture of substances e.g. kerosene or lavender oil.

Apart from being a necessary prerequisite to quantitation, the determination of identity is also frequently the sole purpose of an analysis. The VAM principles are equally applicable whether analysis is being performed for quantitation or for identification.

The VAM principles are:

(1) Analytical measurements should be made to satisfy an agreed requirement.

(2) Analytical measurements should be made using methods and equipment which have been tested to ensure that they are fit for their purpose.

(3) Staff making analytical measurements should be both qualified and competent to undertake the task.

(4) There should be regular independent assessment of the technical performance of a laboratory.

(5) Analytical measurements made in one location should be consistent with those made elsewhere.

(6) Organisations making analytical measurements should have well defined quality control and quality assurance procedures.

Each of the following section headings contains, where appropriate, numbered references to one or more of the above six principles. These references are intended to be indicative only, pointing to the more obvious principles which apply. Some sections could be considered to be covered by several of the principles and, in any given case, the referenced principles should not necessarily be taken to deny the relevance of any of the principles not cited.

3 Scope

The Guide has been developed as a generic document and is intended to cover a broad area of application ranging from traditional analytical chemistry/clinical chemistry to the more subjective assessments arising from activities such as organoleptic testing and document examination. For the purpose of the Guide therefore, qualitative analysis is loosely defined as follows:

Definition Qualitative Analysis: The classification of objects against specified criteria to meet an agreed requirement.

In order to classify an object, in the present context, a sample of it must be made available to an analyst. The methods of classification are taken to consist of the determination of chemical or physical properties or inspection by visual or other sensory means. Some examples of classification methods are:

• Chemical tests involving colour changes, e.g. addition of Schiff's reagent to aliphatic aldehydes.

• Chemical tests involving production of precipitates, e.g. BaSO4 in testing for SO42-.

• Measurement of specific gravity.

• Observation of crystalline form or other morphological features.

• Observation of particular absorption bands in an IR spectrum.

• Limit tests in which the magnitude of a measured parameter is compared to a predetermined boundary value.

Where analysis is by reference to chemical species, all concentration levels are covered from macro to trace level.

4 Health and Safety

[VAM Principle #2, 3]

laboratory staff should be made aware of any potential dangers associated with the collection, analysis or storage of sample materials.

The health and safety of laboratory staff is of paramount importance and where samples are sent to a laboratory for analysis, the laboratory should ensure that it is aware of any relevant Health & Safety information connected with the sample material. This could include extracts from hazard information sheets supplied by the customer for example.

Laboratories should have a hazard assessment policy to cover all materials received; this should cover reagents as well as sample materials. All material entering a laboratory should be assigned to a predefined hazard/toxicity class upon arrival. Materials of unknown or partially known composition should automatically be assigned to high hazard/toxicity classes.

When laboratory staff collect their own samples the host organisation has a duty to ensure that such visitors are aware of any hazards connected with the environment from which the samples are collected. That is to say, from other chemicals, biological organisms or sources of electrical, kinetic, or radiative energy.

For their part, laboratory field personnel have an obligation to inform a responsible person in the host organisation if they discover, whether as a result of their tests or otherwise, that a toxic threshold has been exceeded or that a hazard or potential hazard exists in the area in which they have been working (see Section 8 on Field Testing).

5 Establishing the Requirements

5.1 An Agreed Requirement

[VAM Principle #1]

The analyst and customer should agree on the business requirement and the technical solution.

The kind of information (chemical/physical/observational) to which this Guide relates will usually be required in order to enable the user to decide between alternative courses of action. For example:

• An industrial customer may wish to know if an impurity is present in a process feed stock so that he can avoid using it if it might poison a catalyst.

• In order to direct the course of an investigation, a police officer may wish to know if samples taken at the scene of a crime match those associated with a suspect.

• Many product specifications require that a material be present below a stated level, or between stated limits.

• It may be important for a pharmaceutical company to know that a particular chiral isomer is absent from a formulation.

These are all examples of classification, but the impact varies from economic to life-threatening. Whatever the application, however, it is crucial to ensure that the analysis performed will provide, as far as possible, the right information within the resources available and constraints operating. This can be best achieved by establishing a clear understanding between customer and analyst of the purpose of the work and of how the technical information provided will fulfil the requirement. This mutual understanding should result in an agreed statement of the requirement and the solution.

There are two important aspects to consider; the business context leading to the customer requirement, and the consequent technical requirement.

5.2 The Customer Requirement

[VAM principle #1]

The analyst and customer need a clear mutual understanding of the requirement to ensure that the work done meets the customer's needs.

It is important for the user of analytical information to know what purpose the information is intended to serve. The analyst also should know why the customer wants the analysis performed and, in general, what use will be made of the result. Effective communication of this purpose to the analyst is important since it places the analytical problem in a context and may enable the analyst to suggest more efficient or cost-effective solutions. This communication of purpose proceeds by way of a dialogue between customer and analyst and is a vital first step in meeting the customer requirement. Factors to consider in establishing the customer requirement may include, inter alia:

• Economic impact of the decision.

• Effects on health or livelihood.

• Environmental consequences.

• Regulatory compliance issues.

• Criticality (for example, whether the analytical result will be the sole decision criterion).

• Timeliness.

• Cost.

Individuals in customer organisations vary in their ability to identify the information they really require. Some have considerable expertise while others, perhaps less experienced, may focus on the wrong aspects of a problem. Then again when novel situations or problems arise nobody may be too sure about what information to seek. If care is not taken at this stage then unnecessary or inappropriate analyses may be undertaken.

The first action a customer should take is to formulate a clear statement of the 'problem'. This should indicate what the business requirement is, i.e. what the criteria for a successful resolution of the problem would be in business terms, and should not attempt to anticipate or impose a particular technical solution. For example, the problem might be a reduced yield of a new product from a batch reactor. Analysing reactants and products for anything unusual might be a waste of time and effort if the real reason is poor heat flow and consequent unfavourable reaction conditions. The solution here relates to process control and not necessarily to feed stock composition. In this example, a business criterion might be a yield of not less than 80%. How that is achieved is a matter for the technical specialists to determine but it need not involve analysis of feed stock.

5.3 The Technical Requirement

[VAM principle #1, 2]

The methodology selected should be technically capable of satisfying the business needs.

Once the customer and analyst have a clear understanding of the business requirement, the analytical requirements appropriate to satisfying the business need can be explored and developed. To begin with, as much relevant information as possible should be obtained about the materials. In particular:

• The expected composition if known.

• The stability of the analytes of interest. The stability of the matrix.

• Safety information.

• The nature and likelihood of possible interferents.

A set of decision criteria (see below) will then need to be established and a suitable methodology worked out. A sampling plan may also be needed and this will be influenced by the methodology selected. In establishing the analytical requirement there are two general matters to consider; the nature of the decision criteria used, and the performance of the methods selected (including the sampling regime where appropriate).

Decisions are, in general, based on specific properties of the material or object to be classified. Properties may be physical or chemical properties, or other attributes of various kinds. Depending on the properties of interest, different kinds of criteria may be appropriate, including (but not limited to):

• Threshold criteria, by which a material is classified according to a measured value compared against one or more limits. Such criteria include confirmation of presence against detection limits, compliance testing against set tolerances, or simply classification thresholds chosen by prior study which, of themselves or in conjunction with other criteria, serve to identify materials. In principle, any test producing a quantitative numerical output can be reduced to a threshold criterion, including, for example, quantification of a specified component, position of a chromatographic spot or peak, measurement of physical dimensions or other properties, or calculation of match quality parameters or multivariate distance metrics.

• Attributes, where the material or object is classified according to the presence or absence of specified attributes, often determined by inspection. Examples include colour, shape, aroma, physical state, or morphological features.

• Pattern matching, in which sets of features are compared directly with reference data. Examples include direct comparison of spectra and chromatographic patterns, composition profiles, or other sets of properties.

• Discrete classification tests, which typically provide information of a yes/no type or, occasionally, classification into one of a few discrete categories. Examples include pH indicators, chemical 'spot tests', and many routine screening tests.

• Interpretation, in which observed properties or measured values are compared with properties or values predicted by established theory or from experience, typically of similar, but not identical, materials. A particularly important example of this type is structure/spectrum correlation.

Note 1: This classification of criteria is somewhat arbitrary, in that some practical criteria might reasonably be placed in different classes. For example, spectral matching might be considered a clear case of pattern matching, but if conducted using library search software providing a numerical match quality index, might be treated in practice as a threshold test. The distinction is made primarily to illustrate the range of types of evidence which should be considered, and to permit discussion of appropriate performance indicators.

Note 2: Effective classification criteria will frequently include several different types of criterion. For example, spectral matching criteria might include the specific features required to be present (attributes) and permitted ranges for their position and intensity (threshold criteria).

The selection of criteria should reflect the environment in which the tests will be applied. For example, criteria based on complex analytical tests may be inappropriate for rapid field testing. However, the criteria chosen must satisfy the complete requirement. It will accordingly be necessary to confirm that test methods can be practically applied as needed, or to develop practical methodologies appropriate to the situation.

Criteria should be selected to give demonstrably acceptable performance against the business needs. The performance of the methodology on the subject materials must therefore be taken into account when selecting criteria and setting decision criteria. The test method must itself satisfy performance criteria which will ensure that it is capable of establishing whether the technical criteria have been met.

It should be noted that, initially, the appropriateness of the technical criteria identified could be uncertain and in these cases a certain amount of exploratory analysis may be necessary. When this happens a potentially iterative analysis/evaluation cycle may arise with each set of analytical results feeding back to assist in redefining the technical criteria needed to achieve a business solution.

The foregoing is summarised in the Requirements and Design model illustrated at Appendix A. This emphasises the necessity of a two way communication between the laboratory and the customer and shows how the analytical requirement can be met by an appropriate technical solution consisting of a design phase and an execution phase.

6 The Sample

6.1 Collection

[VAM principle #1]

Samples should be collected in such a way as to provide a representative portion of the source material free from contamination by the sampling process. In addition, the sampling process should not contaminate the source material.

Unless agreed otherwise, responsibility for taking samples is that of the customer. The customer should be informed that, for a single sample, the validity of any inferences drawn from the analytical result will depend upon how representative the sample is of the bulk material from which it was drawn. If there are any doubts about the homogeneity of the bulk material then several samples should be taken according to a carefully worked out sampling plan. The analyst should be prepared to advise on the construction of such a plan. For each individual sample, the quantity required for an analysis is a matter for the analyst to decide; sufficient should normally be allowed for at least one replicate analysis to be made.

(Continues...)

Excerpted from Qualitative Analysis by W.A. Hardcastle. Copyright © 1998 LGC (Teddington). Excerpted by permission of The Royal Society of Chemistry.
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Edition details

• Publisher: Royal Society of Chemistry
• Publication date: 1998
• Language: English
• ISBN 10: 0854044620
• ISBN 13: 9780854044627
• Binding: Paperback
• Edition number: 1
• Number of pages: 32