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ASTM E 2310 : 2004

Superseded
Superseded

A superseded Standard is one, which is fully replaced by another Standard, which is a new edition of the same Standard.

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superseded

A superseded Standard is one, which is fully replaced by another Standard, which is a new edition of the same Standard.

Standard Guide for Use of Spectral Searching by Curve Matching Algorithms with Data Recorded Using Mid-infrared Spectroscopy
Available format(s)

Hardcopy , PDF

Superseded date

11-11-2014

Language(s)

English

Published date

01-02-2004

CONTAINED IN VOL. 03.06, 2015 Describes the process whereby a spectrum of an unknown material is evaluated against a library (database) of digitally recorded reference spectra.

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 document should be aware that the results of a spectral search can be affected by the following factors described in Section : (1) Baselines, (2) sample purity, (3) Absorbance linearity (Beers 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 document 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.

Committee
E 13
DocumentType
Guide
Pages
9
ProductNote
Reconfirmed 2004
PublisherName
American Society for Testing and Materials
Status
Superseded
SupersededBy

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