CH915: Elemental AnalysisCH915: Elemental Analysis Module leader: Dr. Claudia BlindauerModule leader: Dr. Claudia Blindauer Lecturers:Lecturers:

Dr. Claudia BlindauerDr. Claudia Blindauer Dr. John Fenlon (Statistics)Dr. John Fenlon (Statistics) Dr. Andrew Mead (Warwick HRI)Dr. Andrew Mead (Warwick HRI)

Lab classes:Lab classes: Dr. Abraha HabtemariamDr. Abraha Habtemariam

Book recommendations, e.g.:Book recommendations, e.g.: D.C. Harris: Quantitative Chemical AnalysisD.C. Harris: Quantitative Chemical Analysis Vogel’s textbook of quantitative chemical analysisVogel’s textbook of quantitative chemical analysis For the entire course: Skoog, Holler, Nieman: Principles of For the entire course: Skoog, Holler, Nieman: Principles of

Instrumental AnalysisInstrumental Analysis

Aims of the moduleAims of the module Introduce the Analytical ProcessIntroduce the Analytical Process Introduce concepts for Introduce concepts for quantitativequantitative

analysisanalysis Including Statistics for Data AnalysisIncluding Statistics for Data Analysis

Enable professional data analysisEnable professional data analysis Introduce important methods for elemental Introduce important methods for elemental

analysis of liquid and solid samplesanalysis of liquid and solid samples Enable selection of the best possible Enable selection of the best possible

method for a given analysis problemmethod for a given analysis problem Enable to design experimentsEnable to design experiments

Module OverviewModule Overview 5 sessions on chemical aspects of 5 sessions on chemical aspects of

quantitative and elemental analysis quantitative and elemental analysis (C. Blindauer, see handout)(C. Blindauer, see handout)

4 lab classes (A. Habtemariam)4 lab classes (A. Habtemariam) 8 sessions on understanding data and 8 sessions on understanding data and

statistical aspects of quantitative statistical aspects of quantitative analysis (J. Fenlon, A. Mead, J. Lynn) – analysis (J. Fenlon, A. Mead, J. Lynn) – together with MAOC and Systems together with MAOC and Systems Biology studentsBiology students

What is elemental analysis What is elemental analysis and where is it applied ?and where is it applied ?

What is Elemental What is Elemental Analysis ?Analysis ?

Determine the elemental composition of Determine the elemental composition of materialmaterial QualitativeQualitative Quantitative Quantitative

CHNX: Combustion analysis for CHNX: Combustion analysis for verification of compound identityverification of compound identity

Other elementsOther elements

Elemental Analysis is applied Elemental Analysis is applied in:in:

Materials SciencesMaterials Sciences Metallurgy, glass, ceramics, cements, superconductors, Metallurgy, glass, ceramics, cements, superconductors,

microelectronics…microelectronics… GeosciencesGeosciences

geochemistry, mineralogy, geochronology…geochemistry, mineralogy, geochronology… Environmental SciencesEnvironmental Sciences Biological Systems and MedicineBiological Systems and Medicine

In Industry:In Industry: Quality control: Establish that produced material conforms in Quality control: Establish that produced material conforms in

terms of composition and purityterms of composition and purity Process controlProcess control Food safety incl. packagingFood safety incl. packaging

Forensics:Forensics: Determine composition of soil, fibres, plastic, paint etc to Determine composition of soil, fibres, plastic, paint etc to

establish originestablish origin Trace analysis of Firearms Projectile Lead (FBI procedure)Trace analysis of Firearms Projectile Lead (FBI procedure)

Elemental Analysis – Method Elemental Analysis – Method overviewoverview

Classical methods:Classical methods: Qualitative Inorganic Analysis (Fresenius, Treadwell)Qualitative Inorganic Analysis (Fresenius, Treadwell) Quantitative: Quantitative: Gravimetry,Titrimetry, ColorimetryGravimetry,Titrimetry, Colorimetry……

Instrumental trace analysis in solutionInstrumental trace analysis in solution SpectroscopicSpectroscopic methods: AAS, ICP-AES/OES methods: AAS, ICP-AES/OES Mass spectrometryMass spectrometry: ICP-MS: ICP-MS Electrochemical methods (Electrochemical methods ( CH914) CH914)

Instrumental methods for solid materialsInstrumental methods for solid materials X-rayX-ray methods (also spectroscopic) methods (also spectroscopic) Mass spectrometry methods: Mass spectrometry methods: SIMSSIMS and many other and many other

NB: Most instrumental methods are based on NB: Most instrumental methods are based on physics, not chemistry of elementphysics, not chemistry of element

Acquire/define sample

Process sample

Soluble?Chemical dissolution

Change chemical

form

Eliminate interferences

Measure X

Calculate result

Determine error

No

Yes

YesNo

Solid state

methodsSelect method

Analysis in liquid

state

Process sample

Measurableproperty?

The analytical processGeneral

considerationsand steps

Acquire/define sample

Method selection - Method selection - considerationsconsiderations

Destructive/non-destructive ?Destructive/non-destructive ? Non-destructive methods of analysisNon-destructive methods of analysis

X-ray fluorescence, emission, etc.X-ray fluorescence, emission, etc. Destructive methods of analysisDestructive methods of analysis

Combustion analysesCombustion analyses Volumetric, gravimetric, electroanalytical analysesVolumetric, gravimetric, electroanalytical analyses Atomic absorbance (AA) and inductively coupled plasma (ICP) spectroscopyAtomic absorbance (AA) and inductively coupled plasma (ICP) spectroscopy Mass spectrometryMass spectrometry

Expected analyte concentrations and Expected analyte concentrations and performance performance characteristicscharacteristics of method must match of method must match

Sample must be compatible with required processing Sample must be compatible with required processing and measurementand measurement

Quantitative Analysis - Quantitative Analysis - PrinciplesPrinciples

1)1) Define sample amount (mass or volume)Define sample amount (mass or volume)2)2) Measure quantity proportional to analyte Measure quantity proportional to analyte

concentrationconcentration Measured property must vary in a defined way: Measured property must vary in a defined way:

calibrationcalibration with known standards necessary with known standards necessary Analysis must be specific: Analysis must be specific: InterferencesInterferences must be must be

known and if possible be eliminatedknown and if possible be eliminated AccuracyAccuracy: : Proximity of measured value to Proximity of measured value to

accepted (or "true") value: accepted (or "true") value: must be must be determineddetermined

PrecisionPrecision: : Closeness of measured values to one Closeness of measured values to one another:another: must be defined and reported must be defined and reported

Performance characteristic of Performance characteristic of quantitative analytical quantitative analytical

methodsmethods AccuracyAccuracy

BiasBias RecoveryRecovery

PrecisionPrecision Reproducibility and RepeatabilityReproducibility and Repeatability

Detection capabilityDetection capability SensitivitySensitivity Limit of Detection (LoD)Limit of Detection (LoD) Limit of Quantitation (LoQ)Limit of Quantitation (LoQ)

Selectivity and SpecificitySelectivity and Specificity LinearityLinearity Working RangeWorking Range Robustness/Ruggedness Robustness/Ruggedness

All these characteristics are intimately linked to the experimental error

For definitions see:http://www.nmschembio.org.uk/GenericArticle.aspx?m=98&amid=445

Experimental errorExperimental error

Systematic error:Systematic error: Sources:Sources:

InstrumentalInstrumental MethodMethod PersonalPersonal

Can be discovered and correctedCan be discovered and corrected Standard reference materialsStandard reference materials BlanksBlanks Controls, e.g. sControls, e.g. spiked samplespiked samples

Handle error by proper standardisation/calibration Handle error by proper standardisation/calibration or application of a correction factoror application of a correction factor

Systematic errors impact on Bias

Experimental errorExperimental error Random error:Random error:

Always present, can't be correctedAlways present, can't be corrected Consequence of uncertainty of measurementsConsequence of uncertainty of measurements

electrical noise from instrument, causing fluctuations electrical noise from instrument, causing fluctuations in readingin reading

uncertainties in measurements of mass and volume uncertainties in measurements of mass and volume Ultimate limitation in quantitationUltimate limitation in quantitation Must be aware of error and deal with itMust be aware of error and deal with it

Repeated measurementsRepeated measurements

Random errors impact on Precision, Reproducibility, Repeatability, LOD and

LOQBoth systematic and random errors affect

accuracy

Reporting quantitative dataReporting quantitative data Errors can be defined via:Errors can be defined via:

Standard deviation (SD)Standard deviation (SD) VarianceVariance Relative std. deviationRelative std. deviation Coefficient of variationCoefficient of variation

All quantitative data All quantitative data mustmust be reported with error be reported with error – SD and RSD most common – SD and RSD most common

Propagation of errors Propagation of errors must be consideredmust be considered

1

)(1

2

N

xxSD

N

ii

2SDV

xSDRSD

%100RSDCV

Sampling errors: dealing with Sampling errors: dealing with heterogeneityheterogeneity

““Real” samples are usually heterogeneousReal” samples are usually heterogeneous Examples: Foodstuffs, soils, water samples…Examples: Foodstuffs, soils, water samples…

Random sampling: Random sampling: Sample fractions selected randomlySample fractions selected randomly

Composite sampling:Composite sampling: Samples taken at regular intervals and mixedSamples taken at regular intervals and mixed

Homogeneouslab sample

Representative bulk sample

Aliquots

LotSampling

Sample preparation

Overall error is composed of the errors introduced by the Overall error is composed of the errors introduced by the analytical procedure (including sample preparation and analytical procedure (including sample preparation and actual measurement(s)) and the sampling error:actual measurement(s)) and the sampling error:

SDSDoo = overall standard deviation, = overall standard deviation, SDSDaa = sd of analytical procedure, = sd of analytical procedure, SDSDss = SD of sampling procedure= SD of sampling procedure

If If SDSDaa << << SDSDss or or SDSDss << << SDSDaa, there is little point in trying to , there is little point in trying to reduce the smaller onereduce the smaller one Eg. If Eg. If ssaa = 5% and = 5% and ssss = 10%, then = 10%, then ssoo = 11%. Using a more expensive = 11%. Using a more expensive

and time consuming method whose and time consuming method whose ssaa = 1% will only reduce = 1% will only reduce ssoo to 10% to 10%

Sampling errorSampling error

SDo2 = SDa

2 + SDs2

SummarySummary Elemental Analysis is important in a Elemental Analysis is important in a

range of sectorsrange of sectors The analytical process consists of many The analytical process consists of many

stepssteps Meaningful analysis must consider all steps Meaningful analysis must consider all steps

togethertogether Meaningful experimental design requires Meaningful experimental design requires

understanding data understanding data Awareness of performance characteristics of Awareness of performance characteristics of

methods methods Awareness of statisticsAwareness of statistics