Infrared Spectroscopy Course

Lesson 1 • Beer-Lambert Law and Quantitative Basics

Introduces absorbance, transmittance, and the Beer-Lambert law for quantitative analysis. Provides the mathematical foundation for concentration measurements.

Lesson 2 • Molecular Vibrations and IR Activity

Explains stretching and bending modes and the dipole-moment change requirement for IR activity. Connects molecular symmetry to observable absorption bands.

Lesson 3 • Electromagnetic Radiation and the IR Region

Covers wavelength, frequency, wavenumber, and the IR spectral range (near, mid, far). Establishes the physical basis for all subsequent spectral interpretation.

Lesson 1 • Instrument Qualification and Calibration

Covers wavenumber accuracy checks, photometric linearity tests, and resolution verification using reference standards. Ensures data integrity before sample analysis.

Lesson 2 • IR Sources, Detectors, and Beam Splitters

Details common IR sources (globar, Nernst glower), detectors (DTGS, MCT), and beam splitter materials. Guides hardware selection for specific spectral ranges.

Lesson 3 • Fourier Transform and Spectral Computation

Covers the mathematical Fourier transform converting interferograms to spectra and apodization functions. Students understand how software processing affects spectral quality.

Lesson 4 • Data Acquisition Parameters and Best Practices

Teaches scan number, resolution, and aperture selection for optimal signal-to-noise ratio. Connects parameter choices to spectral quality outcomes.

Lesson 1 • Choosing the Right Preparation Method

Provides a decision framework matching sample state, quantity, and analytical goal to preparation technique. Reinforces all prior preparation methods through comparative analysis.

Lesson 2 • Liquid and Solution Sample Techniques

Explains fixed-path-length cells, variable cells, and thin-film casting for liquids. Addresses solvent selection and solvent subtraction procedures.

Lesson 3 • Attenuated Total Reflectance Sampling

Introduces ATR crystal materials, contact pressure, and depth-of-penetration concepts. Positions ATR as the preferred technique for routine and minimal-prep analysis.

Lesson 4 • Solid Sample Preparation Methods

Covers KBr pellet pressing, Nujol mull preparation, and diffuse reflectance techniques for solids. Each method's advantages and artifacts are compared.

Lesson 1 • The Fingerprint and Functional Group Regions

Distinguishes the functional group region (4000–1500 cm⁻¹) from the fingerprint region (1500–400 cm⁻¹). Establishes a two-region strategy for systematic interpretation.

Lesson 2 • Heteroatom Functional Groups

Covers O–H, N–H, C–N, C–O, and S–H stretching and bending bands for alcohols, amines, and related groups. Expands interpretation to polar functional groups.

Lesson 3 • Hydrocarbons and C–H Stretching Bands

Covers alkane, alkene, and alkyne C–H stretches and bending modes with characteristic wavenumbers. Builds the first layer of functional group recognition.

Lesson 4 • Carbonyl-Containing Functional Groups

Analyzes C=O stretching frequencies for ketones, aldehydes, esters, carboxylic acids, and amides. Teaches how conjugation and ring strain shift carbonyl frequencies.

Lesson 1 • Spectral Subtraction and Difference Spectra

Teaches scaled spectral subtraction to isolate analyte signals from matrix or solvent contributions. Identifies subtraction artifacts and scaling factor optimization.

Lesson 2 • Derivative Spectroscopy

Applies first and second derivative transformations to resolve overlapping bands and sharpen peaks. Connects derivative order to resolution enhancement and noise amplification.

Lesson 3 • Validation of Processed Spectra

Covers signal-to-noise ratio measurement, peak position reproducibility, and spectral quality metrics. Ensures processed data meets analytical acceptance criteria.

Lesson 4 • Baseline Correction Methods

Covers manual anchor-point, polynomial, and rubber-band baseline correction algorithms. Teaches when each method is appropriate and how to avoid over-correction artifacts.

Lesson 1 • Method Validation for Quantitative IR

Applies accuracy, precision, linearity, and robustness testing to IR quantitative methods. Aligns validation parameters with analytical regulatory expectations.

Lesson 2 • Multivariate Calibration Fundamentals

Introduces PLS and PCR regression for handling overlapping bands and complex matrices. Explains latent variables and their physical meaning in spectral data.

Lesson 3 • Quantitative Analysis of Real Samples

Applies calibration models to pharmaceutical, food, and polymer samples with matrix complexity. Reinforces model transfer and prediction uncertainty reporting.

Lesson 4 • Model Building and Cross-Validation

Covers training set design, cross-validation strategies, and optimal factor number selection. Prevents overfitting and ensures model generalizability.

Lesson 1 • TGA-IR: Thermogravimetric Analysis Coupling

Explains evolved gas analysis by coupling TGA effluent to an FTIR gas cell. Identifies decomposition products and thermal degradation pathways.

Lesson 2 • IR Imaging and Chemical Mapping

Introduces focal plane array (FPA) detectors for rapid IR imaging and multivariate image analysis. Produces spatially resolved chemical distribution maps.

Lesson 3 • GC-IR: Gas Chromatography Coupling

Covers light-pipe and matrix-isolation GC-IR interfaces, data acquisition, and Gram-Schmidt reconstruction. Enables identification of GC-separated volatile compounds.

Lesson 4 • Surface and Thin-Film IR Techniques

Covers IRRAS, RAIRS, and grazing-angle ATR for surface and thin-film characterisation. Addresses selection rules unique to surface-sensitive IR measurements.

Lesson 1 • Pharmaceutical Applications

Covers raw material identification, polymorphism detection, and blend uniformity testing in pharmaceutical manufacturing. Connects IR methods to regulatory quality expectations.

Lesson 2 • Process Analytical Technology and At-Line IR

Integrates IR probes into manufacturing processes for real-time reaction and quality monitoring. Covers fibre-optic probes, immersion probes, and data feedback loops.

Lesson 3 • Food and Agricultural Analysis

Uses IR for fat, protein, moisture, and adulteration analysis in food matrices. Highlights near-IR and mid-IR complementarity for food quality control.

Lesson 4 • Polymer Characterisation by IR

Applies IR to polymer identification, copolymer composition, crystallinity index, and degradation assessment. Covers spectral databases and reference matching for plastics.