Introduction Yongsik Lee

Classification of Analytical Methods Classical methods Instrumental methods

Instrumental Methods Photon Charge Heat Radioactive

Instruments Data domain Non-electrical domain Electrical domain Analog Time digital

Detectors Detectors Transducers Sensors 물리량의 변화를 기록 또는 표시 기계적, 전기적, 화학적 장치 Transducers 비전기적 영역 정보와 전기적 영역 정보 사이 변환 변환 함수 = 둘 사이의 수학적 관계식 Sensors 특정 화학종을 연속적으로, 가역적으로 검출하는 분석장치

Other Components of Instrument Readout device Microprocessor Computer

Selecting a method Defining the problem 요구되는 정확도 이용할 수 있는 시료의 양 분석물의 농도 범위 방해 성분 시료 매트릭스의 물리적, 화학적 성질 시료의 개수 신속성 실험자의 숙련도 기기 장치의 가격과 이용 가능성 시료당 비용

Characteristics of Instrument Precision Bias Sensitivity Detection limit Concentration range selectivity

Precision 정밀도 Measure of random, or indeterminate error 재현성 reproducibility 표준편차, 변동계수 등 표 1-5 성능 계수 (figure of merit)

Bias 고정 오차 Definition Measure of systematic or determinate error Bias = (population mean) – (true value)

Sensitivity Definition Measure of its ability to discriminate between small differences in analyte concentration Tow factors Slope of calibration curve - steeper slope Precision – better precision

Classification of Analytical Methods Qualitative instrumental analysis measured property indicates presence of analyte in matrix Quantitative instrumental analysis magnitude of measured property is proportional to concentration of analyte in matrix

Classical Qualitative - identification by color, indicators, boiling points, odors Quantitative - mass or volume e.g. gravimetric, volumetric Instrumental Qualitative - chromatography, electrophoresis and identification by measuring physical property e.g. spectroscopy, electrode potential Quantitative measuring property and determining relationship to concentration e.g. spectrophotometry, mass spectrometry Often, same instrumental method used for qualitative and quantitative analysis

Types of Instrumental Methods: Radiation emission Emission spectroscopy - fluorescence, phosphorescence, luminescence Radiation absorption Absorption spectroscopy - spectrophotometry, photometry, nuclear magnetic resonance, electron spin resonance Radiation scattering Turbidity, Raman Radiation refraction Refractometry, interferometry Radiation diffraction X-ray, electron

Radiation rotation Polarimetry, circular dichroism Electrical potential Potentiometry Electrical charge Coulometry Electrical current Voltammetry - amperometry, polarography Electrical resistance Conductometry

Mass Gravimetry Mass-to-charge ratio Mass spectrometry Rate of reaction Stopped flow, flow injection analysis Thermal Thermal gravimetry, calorimetry Radioactivity Activation, isotope dilution (Often combined with chromatographic or electrophoretic methods)

Example: Spectrophotometry Instrument: spectrophotometer Stimulus: monochromatic light energy Analytical response: light absorption Transducer: photocell Data: electrical current Data processor: current meter Readout: meter scale

Data Domains way of encoding analytical response in electrical or non-electrical signals 정보를 코드화하는 여러 방법들을 영역(도메인)이라고 한다 Interdomain conversions transform information from one domain to another. Light Intensity => Photocell Current => Current Meter Scale Detector (general): device that indicates change in environment Transducer (specific): device that converts non-electrical to electrical data Sensor (specific): device that converts chemical to electrical data

Non-Electrical Domains Physical (light intensity, color) Chemical (pH) Scale Position (length) Number (objects)

Electrical Domains Current Voltage Charge Frequency Pulse width Phase Count Serial Parallel

Time Domains 정보는 신호의 크기로서 보다는 시간에 따른 신호의 요동으로 시간 영역에 저장된다. Time Analog vary with time frequency, phase, pulse width Analog continuously variable magnitude current, voltage, charge Digital discrete values count, serial, parallel, number

Digital Binary Data Advantages easy to store not susceptible to noise

Figures of Merit Performance Characteristics: How to choose an analytical method? How good is measurement? How reproducible? - Precision How close to true value? - Accuracy/Bias How small a difference can be measured? - Sensitivity What range of amounts? - Dynamic Range How much interference? - Selectivity

Precision Indeterminate or random errors Absolute standard deviation 절대표준편차 Variance 분산 : s2 Relative standard deviation: 상대 표준편차 RSD = s/<x> Standard deviation of mean: 평균의 표준편차 sm

Accuracy Determinate errors (operator, method, instrumental) Bias: bias = <x> - x(true) Sensitivity Calibration sensitivity: S larger slope of calibration curve means more sensitive measurement

Analytical Sensitivity Mandel and Stiehler 분석감도 = 검정곡선기울기/측정표준편차 기기의 증폭률을 증가시키면 검정곡선 기울기는 증가하지만, 일반적으로 측정 표준편차도 같이 증가하므로 분석감도는 일정하다.

Detection Limit Signal must be bigger than random noise of blank Minimum signal: Signal min = Average Signal of blank + ks(blank) From statistics k=3 or more (at 95% confidence level) Suggested by Long and Winefordner

Dynamic Range At detection limit we can say confidently analyte is present but cannot perform reliable quantitation Level(Limit) of quantitation (LOQ): (k=10)s(blank) 정량적 측정을 할 수 있는 가장 낮은 농도, 정량 한계 Limit of linearity (LOL) when signal is no longer proportional to concentration, 선형 한계 Dynamic range 유용한 측정농도 범위

Selectivity: No analytical method is completely free from interference by concomitants. Best method is more sensitive to analyte than interfering species (interferent). Matrix with species A&B Signal = mAcA +mBcB + Signal blank Selectivity coefficient kB,A = mB/mA k's vary between 0 (no selectivity) and large number (very selective).

Calibration methods 검정 Basis of quantitative analysis is magnitude of measured property is proportional to concentration of analyte Signal ∝ µ[x] Signal = m[x]+ Signal of blank [x] = {Signal -Signal of blank}/m

Standard Addition Method spiking 같은 크기의 시료 분취량에 표준물 용액 일정량을 증가시키며 더하고 측정 매트릭스는 표준물 첨가후에도 거의 변화없다고 가정 최소제곱분석법

Internal Standard Method 내부 표준 모든 시료, 바탕, 그리고 분석 표준물에 일정량씩 더하는 물질 검정곡선 획득 신호비=표준 분석물의 신호/내부 표준물의 신호 신호비를 표준물의 농도에 대해 그려 얻는다. 우연오차와 계통오차를 보정할 수 있다 적당한 내부표준물 확보가 어렵다

Calibration curves (working or analytical curves)

Example

Calculate Precision

Calibration Expression

Species of interest All constituents including analyte. Matrix-analyte =concomitants Often need pretreatment - chemical extraction, distillation, separation, precipitation