Identification of complex chemical mixtures using portable hand-held devices

Hand-held spectrometer © Shutterstock

Implementation of a Raman spectral decomposition technique that allows effective identification of complex mixtures. The computationally and memory efficient software enables new functionality to be added to portable hand-held devices.

Features   Benefits
Computationally and memory efficient Can be implemented on portable hand-held devices
Computational time in second range Provides real-time results
Quantitative and highly sensitive Effective identification of complex mixtures and component composition
Ability to handle a large reference spectra database Efficient analysis of unknown hazardous material

The Challenge

Raman spectroscopy is an established method for identifying unknown materials across various sectors. Conventional analysis methods are based on comparing the measured spectrum with a reference spectral library of known chemicals to find the best match. While effective for identifying a single spectrum from a library, a sample composed of a mixture of different chemicals provides a greater challenge.


Edinburgh researchers have developed a Raman spectral decomposition technique based on a new fast sparse approximation method. Inputting a set of reference spectra and an unknown mixture yields the identity of mixture elements and their contribution percentages. It also has the capability of detecting cases where the mixture has a spectrum outside the reference library. The method is highly computationally and memory efficient, which means that it can run on a low power real-time platform. Implemented as a hardware independent C package, which can handle a given library and input spectrum, the technology enables use with hand-held devices. This provides a portable, non-invasive approach for identification of real-life mixtures of chemical substances.

Exemplification Data

A hardware independent C version of the mixture-matching algorithm has been prepared. Performance has been successfully demonstrated in the identification of real mixtures in different measurement scenarios, including where components are close to noise level.


  • Software implemented on hand-held Raman spectrometers for use in Defence, Homeland Security, Life Sciences and Anti-counterfeiting.

IP Status

Software package

Development Status

Prototype Development


A Sparse Regularized Model for Raman Spectral Analysis, Wu et al, Sensor Signal Processing for Defence, Edinburgh, 2014

Commercial Offering

The University of Edinburgh is seeking potential industry partners to license this technology.

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