Predicting chance infrared spectroscopic matching frequencies

Ellison, Stephen L. R.; Gregory, Soumi

doi:10.1016/s0003-2670(98)00268-2

Cited by 9 publications

(3 citation statements)

References 13 publications

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“…M ost researchers use 1500 cm 2 1 as the dividing point between these two regions; at the same time, one can nd other personal preferences. 39,40 The functional group region provides evidence of functional groups in a m olecule based on the absorbance frequency. Peaks in this region are characteristic of speci c kinds of bonds and therefore can be used to identify whether a speci c functional group is present.…”

Section: Eth Odsmentioning

confidence: 99%

Spectral Code Index (SPECOIND): A General Infrared Spectral Database Search Method

Fan

Panaye

2003

Appl Spectrosc

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A new spectral code that can be used by Relational Database Management Systems (RDBMS) as an index for infrared (IR) spectra searches in Relational Database (RDB ) is presented and its suitability is evaluated. Spectral codes are constructed for all spectra in the database as the spectral indexes and three query strings are created with the same theory used for the creation of the index code for the query spectrum . Some effects of parameters used to create index strings and query strings are discussed. All spectra l searches are accomplished in structured query language (SQL) approach and the utilization examples of SQL have been shown. The sequential application of this procedure can reduce the original library of about 18 000 spectra to a few spectra that can be used as referen ces for subsequent detailed comparison. The software developed for the proposed system is particularly suitable for spectral search and structure interpretation.Index Headings: Infrared spectroscopy; Spectral database; Spectral code index; Index; Code string. INT RODUCTIO NBecause of the limitations of the knowledge of the natural world or the calculation power, empirical research methods, not calculation, play a signi cant role in the chemical research eld. The database is the data infrastructure of any empirical research. The spectra are a very important resource in chemistry applications and research domains. Searching spectral libraries of known compounds is one of the m ost important tools in spectral interpretation and structure elucidation.1-4 The key to using this tool is that the spectral collection m ust be large enough to give a decent probability of a match. In 1991, Warr 5 noted that ''no single spectral database contains m ore than app ro xim ately 1 00 00 0 co m pou nds ev en though there were ten m illion known chemical compounds in the CA Registry System. There were 20 -30 times as many hard-copy libraries of spectra as there were computer-readable spectral libraries''. The situation is changing. For example, Bio-Rad's Informatics Division 6 announced that it had the largest collection of infrared (IR ) data in the world of over 220 000 spectra of pure organic and commercial com pounds. Before the 1990s, most of the spectra were stored in printed format, 7-12 and some of the handbooks have indexes on compound name, molecular form ula, chemical class, numerical, and SpecFinder Code. Nowadays, there are m ore and more digital and on-line spectral databases that can provide more comprehensive search tools and higher quality spectra. NIST Chemistry WebBook, 16 and Integrated Spectral Data Base System for Organic Compounds (SDBS) 17 are fam ous on-line free-access public databases. Because spectral databases are very useful, not only big companies but also many research groups have given attention to creating and m anaging databases. As the power of personal computers has grown stronger, some publications can be found that discuss the application of personal computers to creating an IR spectral database and a spectral ret...

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Section: Eth Odsmentioning

confidence: 99%

Spectral Code Index (SPECOIND): A General Infrared Spectral Database Search Method

Fan

Panaye

2003

Appl Spectrosc

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“…Ellison and Gregory later reported that a sample spectrum exhibiting six of a reference spectrum's 12 peaks would result in a chance match probability of 2.8 3 10 À7 (or a 1/3.6 3 10 6 chance of mismatch), which is sufficiently low for most applications. 36 To this end, the goal of this study was to calculate theoretical detection limits and determine reproducible, unambiguous empirical detection limits for an IR spectroscopic imaging microscope operating in an ATR modality. Although the theoretical and experimental results reported here are exclusive to an instrument using an off-axis ATR instrument outfitted with a linear array detector and germanium hemisphere IRE, similar considerations can be adopted to evaluate the performance of other IR spectroscopic imaging instruments.…”

Section: Introductionmentioning

confidence: 99%

Approximating the Detection Limit of an Infrared Spectroscopic Imaging Microscope Operating in an Attenuated Total Reflection (ATR) Modality: Theoretical and Empirical Results for an Instrument Using a Linear Array Detector and a 1.5 Millimeter Germanium Hemisphere Internal Reflection Element

Lanzarotta

2015

Appl Spectrosc

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Theoretical and empirical detection limits have been estimated for aripiprazole (analyte) in alpha lactose monohydrate (matrix model pharmaceutical formulation) using a micro-attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopic imaging instrument equipped with a linear array detector and a 1.5 mm germanium hemisphere internal reflection element (IRE). The instrument yielded a theoretical detection limit of 0.0035% (35 parts per million (ppm)) when operating under diffraction-limited conditions, which was 49 times lower than what was achieved with a traditional macro-ATR instrument operating under practical conditions (0.17%, 1700 ppm). However, these results may not be achievable for most analyses because the detection limits will be particle size limited, rather than diffraction limited, for mixtures with average particle diameters greater than 8.3 μm (most pharmaceutical samples). For example, a theoretical detection limit of 0.028% (280 ppm) was calculated for an experiment operating under particle size-limited conditions where the average particle size was 23.4 μm. These conditions yielded a detection limit of 0.022% (220 ppm) when measured empirically, which was close to the theoretical value and only eight times lower than that of a faster, more simplistic macro-ATR instrument. Considering the longer data acquisition and processing times characteristic of the micro-ATR imaging approach (minutes or even hours versus seconds), the cost-benefit ratio may not often be favorable for the analysis of analytes in matrices that exhibit only a few overlapping absorptions (low-interfering matrices such as alpha lactose monohydrate) using this technique compared to what can be achieved using macro-ATR. However, the advantage was significant for detecting analytes in more complex matrices (those that exhibited several overlapping absorptions with the analyte) because the detection limit of the macro-ATR approach was highly formulation dependent while that of the micro-ATR imaging technique was not. As a result, the micro-ATR imaging technique is expected to be more valuable than macro-ATR for detecting analytes in high-interfering matrices and in products with unknown ingredients (e.g., illicit tablets, counterfeit tablets, and unknown powders).

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“…These algorithms sometimes lack of sensitivity for forensic paint samples, as the differentiation between brands and models relies specifically on minor peaks or shoulders of FTIR spectra. Because chance matching and errors are present [14], it is always necessary to visually verify a large number of hits and eliminate some of them. The benefits of these methods are often satisfactory in practice, although performance measures such as risks of false positives/negatives are often lacking.…”

Section: Introductionmentioning

confidence: 99%

Discrimination and classification of FTIR spectra of red, blue and green spray paints using a multivariate statistical approach

Muehlethaler¹,

Massonnet²,

Esseiva³

2014

Forensic Science International

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Predicting chance infrared spectroscopic matching frequencies

Cited by 9 publications

References 13 publications

Spectral Code Index (SPECOIND): A General Infrared Spectral Database Search Method

Spectral Code Index (SPECOIND): A General Infrared Spectral Database Search Method

Approximating the Detection Limit of an Infrared Spectroscopic Imaging Microscope Operating in an Attenuated Total Reflection (ATR) Modality: Theoretical and Empirical Results for an Instrument Using a Linear Array Detector and a 1.5 Millimeter Germanium Hemisphere Internal Reflection Element

Discrimination and classification of FTIR spectra of red, blue and green spray paints using a multivariate statistical approach

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