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INSTRUMENTAL ANALYSISVT 2013 C HKD 2013 CLASSICAL ANALYTICAL METHODS ‰ Wet-chemical methods ‰ Separation of component of interest analyte from the sample by precipitation, extraction, or

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INSTRUMENTAL ANALYSIS

VT 2013

(C) HKD 2013

CLASSICAL ANALYTICAL METHODS

‰ Wet-chemical methods

‰ Separation of component of interest (analyte) from the sample by

precipitation, extraction, or distillation.

‰ Followed by gravimetric or titrimetric measurement for quantitative analysis

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INSTRUMENTAL ANALYSIS

(C) HKD 2013

INSTRUMENTAL ANALYSIS

‰ Instrument converts information stored in the physical or chemical characteristics of the analyte into useful information

‰ Require a source of energy to stimulate measurable response from analyte

‰ Data domains

9 Methods of encoding information electrically

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INSTRUMENTAL ANALYSIS

‰ Detector

9 Device that indicates a change in one variable in its environment (eg., pressure, temp, particles)

9 Can be mechanical, electrical, or chemical

‰ Sensor

9 Analytical device capable of monitoring specific chemical species continuously and reversibly

‰ Transducer

9 Devices that convert information in nonelectrical domains to electrical domains and the converse

(C) HKD 2013

METHOD SELECTION

‰ Whataccuracyis required

‰ How much sample is available

‰ What is theconcentration rangeof the analyte

‰ What components of the sample will causeinterference.

‰ What are the physical and chemical properties of thesample matrix

‰ How many samples are to be analyzed

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ACCURACY vs PRECISION

‰ Accuracy

9 Describes the correctness of an experimental result

9 Absolute error

9 Relative error

‰ Precision

9 Describes the reproducibility of results

9 Standard deviation

9 Variance

9 Coefficient of variation

9 Relative standard deviation

(C) HKD 2013

ACCURACY vs PRECISION

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‰ Sensitivity of aninstrument or method is its ability to discriminate between small differences in analyte concentration

‰ S = mc + Sbl

S = measured signal; c= analyte concentration;

Sbl= blank signal; m = sensitivity (Slope of line)

‰ Analytical sensitivity (J)

J = m/ss

m = slope of the calibration curve

ss= standard deviation of the measurement

‰ 2 factors limit sensitivity

9 Slope of calibration curve

9 Precision of measuring device

(C) HKD 2013

CALIBRATION CURVE

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CALIBRATION CURVE

‰ Least-square regression line

Y = b 0 + b 1 X

(C) HKD 2013

CALIBRATION CURVE

External Standard Method

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CALIBRATION CURVE

Internal Standard Method

(C) HKD 2013

CALIBRATION CURVE

Standard Addition Method

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DETECTION LIMIT

‰ Detection limit: the minimum concentration or mass of analyte that can be detected at a known confidence level LOD is determined by S/N, where, S/N = Signal-to-noise ratio = (magnitude of the signal)/(magnitude of the noise)

‰ Cm= (Sm– Sbl)/m, where, Cm= minimum concentration i.e., LOD, Sm=

minimum distinguishable analytical signal (i.e., S/N = 2 or S/N = 3), Sbl= mean blank signal

(C) HKD 2013

LINEARITY

‰ Linear range: extends from the lowest concentration at which quantitative measurements can be made (LOQ), to the concentration at which the calibration curve departs from linearity (LOL)

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INSTRUMENTAL METHODS

‰ Chromatographic methods

9 Gas chromatography

9 Liquid chromatography

‰ Spectrophotometric methods

9 Absorption: Atomic absorption, Molecular absorption (UV-Vis, IR)

9 Inductively coupled plasma

‰ Spectroscopic methods

9 Mass-spectrometry

9 Nuclear Magnetic Resonance spectrometry

(C) HKD 2013

APPLICATIONS

‰ Bioanalytical: biological molecules and/or biological matrices (e.g., proteins, amino acids, blood, urine)

‰ Environmental: pesticides, pollution, air, water, soil

‰ Material science: polymers, characterization of new materials

‰ Forensic science (application of science to the law): body fluids, DNA, gun shot residue, hair, fibers, elemental analysis, drugs, alcohols, poisoning, fingerprints, etc

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‰ Plan: Qualitative or quantitative or both; what kind of information have; which technique is suitable etc

‰ Sampling: Accuracy depends on proper sampling, characteristic of sample is very important, required good representative sample (from top, middle and bottom and mix up and take average sample)

‰ Sample preparation: depends on analytical techniques

‰ Analytical measurement

‰ Data Analysis: Whether the data make sense or not.

(C) HKD 2013

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