Introduction to Instrumental Methods

Introduction to Instrumental Methods

• Instrumental methods use instruments to identify and quantify analytes.
• Qualitative analysis determines the presence of an analyte.
• Quantitative analysis determines the concentration of an analyte.
• Classical methods involve separating components and treating them with reagents to identify them.
• Modern instrumental methods measure physical properties of analytes.

Classification of Analytical Methods

• Qualitative Analysis identifies the analyte by measuring a property which indicates its presence.
• Methods involve separation of components and treating them with reagents leading to product identification by color, solubility, odor, optical activity, boiling point (BP), or melting point (MP).
• Quantitative Analysis determines the amount (concentration) of the analyte by measuring a property proportional to its concentration.
• Involve measuring properties such as mass and volume to determine a concentration.

Instrumental Methods

• Instrumental methods use instruments to measure physical properties for quantitative analysis.
• They started with electrical and absorption measurements (early 20th century).
• Properties of analytes used for analysis include:
• Light absorption or emission
• Fluorescence
• pH
• Electric potential and current
• Mass to charge ratio
• New separation techniques replaced classical methods.

Types of Instrumental Methods

• Various methods for measuring radiation, electrical potential, charge, and mass based analysis methods.

The Analysis Concept

• Analytical process involves probing the sample with a probe (electrons, photons, atoms, molecules, ions, heat) that results in an observable response of the sample (e.g. heat, ions, molecules, atoms, photons, electrons or photons, heat).
• Analyzing a sample involves determining what is there, how much there is, and how it behaves.

Instrument

• Instruments convert chemical or physical characteristics of a sample into information that humans can manipulate.
• Stimuli such as EM, electrical or nuclear energy are used to obtain information from the analyte.

Data Domains

• Measurements are aided by devices that convert information from one form to another (e.g., non-electrical to electrical).
• Data encoding can occur in non-electrical (physical, chemical properties like color, length) and electrical domains (current, voltage, charge, frequency, pulse width, phase, count, and serial).

Examples of Data Domains

• Non-electrical: physical properties (light intensity, color), chemical properties (pH), scale position (length), number (objects)
• Electrical: current, voltage, charge, frequency, pulse width, phase, count, serial, parallel

Domain Conversion

• Analysts measure physical/chemical properties of a system.
• The instrument produces an electrical signal representing that datum.
• Instruments use transducers to convert signals into different forms.
• The analysis of an instrument's behavior is characterized as a series of data domain converters.

Data Domains - Way of Encoding Analytical Responses

• Inter-domain conversions transform information from one domain to another (e.g., light energy to an electrical signal).
• Detector: detects changes in the environment.
• Transducer: converts non-electrical data to electrical data or vice versa.
• Sensor: converts chemical data into electrical data. Glass electrodes continuously monitor and reversibly measure specific chemical species.

Instrumental Measurement Example: Spectrophotometry

• Instrument: Spectrophotometer
• Stimulus: Monochromatic light energy
• Analytical response: Light absorption
• Transducer: Photocell
• Data: Electrical current
• Data processor: Current meter

How Do We Choose an Analytical Method?

• The choice of method is based on the performance characteristics: figures of merit.
• Assessing the method involves:
• Reproducibility (Precision).
• Closeness to the true value (Accuracy/bias).
• Measurement of the smallest difference (Sensitivity).
• The range of measurable amounts (Dynamic range).
• Interference from other components (Selectivity).

Performance Characteristics

• Figures of merit are used to identify suitable methods. These include:
• Precision
• Bias
• Sensitivity
• Quantitation limit
• Dynamic range
• Accuracy
• Detection limit
• Linearity limit
• Selectivity

Figure of Merit

• A numerical value derived from experimental data used for evaluating and comparing analytical instruments or methods. It helps determine the technique's applicability for particular analysis issues and is expressed in numerical terms.
• Performance characteristics are measured in terms of figures of merit.

Precision

• Mutual agreement of replicate measurements.
• Standard deviation and variance are common precision metrics.
• Includes RSD and CV (relative standard deviation and coefficient of variation)

Bias

• Bias measures the systematic/determinate error of an analytical method.
• Bias = μ − X_t , where μ is the mean/average value expected for the analyte and X_t is the experimentally observed value or true concentration.

Accuracy

• Accuracy measures the closeness of measured values to the true value or the error of the mean.
• It arises from determinate or non-random errors (e.g., instrument errors, analyst errors, method errors).

Sensitivity

• A measure of an instrument's ability to distinguish small differences (e.g., differences in analyte concentration).
• It depends on the slope of the calibration curve. A larger slope represents more sensitive measurements.
• Precision plays a key role in sensitivity.

Calibration Sensitivity

• Calculated using the slope (m) of the calibration curve.
• Slope is independent of concentration.

Analytical Sensitivity

• Accounts for precision.
• Independent of measurement units but concentration-dependent.
• Incorporates slope (m) and standard deviation (s) as analytical sensitivity factor (y = m/s).

Detection Limit

• The smallest detectable analyte amount.
• Dependent on signal-to-noise ratio.
• Analysis signal needs to be greater than the blank signal (usually 3 times the standard deviation of the blank).

Dynamic Range

• The concentration range over which the technique is useful (from Quantitation Limit to Linearity Limit).
• Ideally a two orders or more magnitude range is useful.

Quantitation Limit

• The analyte amount that can be reliably quantified.
• Ten times the standard deviation from the blank.

Linearity Limit

• The upper concentration limit at which the response of the detector is linear.

Signals and Noise

• Analytical measurements consist of a signal and noise component.
• Signal is the desired information about the analyte.
• Noise (N)- is the extraneous information that degrades analysis performance.

Signal

• Every analytical procedure relies on a signal taken from a detector.
• Output from detector has a baseline (non-zero output).
• Background or baseline varies over time, this variation is called drift.
• Signal is calculated by subtracting expected baseline from output amplitude

Noise

• Variations in an output signal are collectively termed noise.
• Unwanted time-dependent changes.
• Noise is measured in the same units as the signal. (e.g., current, voltage, or power)

Signal-to-Noise Ratio (S/N)

• The importance of ratio. It influences measurability.
• A large S/N is desired (more signal and less noise)
• The ratio of the mean signal and standard deviation of noise.

Sources of Instrumental Noise

• Chemical noise: Uncontrollable variables affecting the chemistry (temperature, pressure, humidity).
• Instrument noise:
• Thermal (Johnson) noise: thermal agitation of electrons.
• Shot Noise: random electron movement across junctions

Hardware Devices for Noise Reduction

• Grounding and shielding: surrounds circuit with a conductive material, attenuating environmental noise.
• Difference amplifiers: subtract out the noise.
• Analog filtering: uses low-pass filters to remove high-frequency interference, reducing noise.
• Modulation: converts low frequency signals into higher frequencies for filtering before demodulation to the original frequency for amplification.