Abstract This guide presents the use of spectral searching by curve matching search algorithms for data recorded using mid-infrared spectroscopy. The methods described herein may be applicable to the use of these algorithms for other types of spectroscopic data, but each type of data search should be assessed separately. The purpose of this evaluation is the classification and, where possible, identification of the unknown. Spectral searching is intended as a screening method to assist the analyst, and is not an absolute identification technique, and hence, not intended to replace an expert in infrared spectroscopy and should not be used without suitable training. The Euclidean distance algorithm and the first derivative Euclidean distance algorithm are described and their use discussed. The theory and common assumptions made when using search algorithms are also discussed, along with guidelines for the use and interpretation of the search results. Scope 1.1 Spectral searching is the process whereby a spectrum of an unknown material is evaluated against a library (database) of digitally recorded reference spectra. The purpose of this evaluation is classification of the unknown and, where possible, identification of the unknown. Spectral searching is intended as a screening method to assist the analyst and is not an absolute identification technique. Spectral searching is not intended to replace an expert in infrared spectroscopy. Spectral searching should not be used without suitable training. 1.2 The user of this guide should be aware that the results of a spectral search can be affected by the following factors described in Section 5: (1) baselines, (2) sample purity, (3) Absorbance linearity (Beer’s Law), (4) sample thickness, (5) sample technique and preparation, (6) physical state of the sample, (7) wavenumber range, (8) spectral resolution, and (9) choice of algorithm. 1.2.1 Many other factors can affect spectral searching results. 1.3 The scope of this guide is to provide a guide for the use of search algorithms for mid-infrared spectroscopy. The methods described herein may be applicable to the use of these algorithms for other types of spectroscopic data, but each type of data search should be assessed separately. 1.4 The Euclidean distance algorithm and the first derivative Euclidean distance algorithm are described and their use discussed. The theory and common assumptions made when using search algorithms are also discussed, along with guidelines for the use and interpretation of the search results. 1.5 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.
