The existing technology for detecting chemical species is based on spectral decomposition of light from a multi-species sample. This approach is limited because of line overlapping from different species and is getting increasingly unreliable when the number of species is large. We propose a holographic species analyzer, which decomposes an input in terms of a prespecified set of species. The innovation is to replace a diffraction grating with a holographic memory element designed to recognize the whole light patterns of different species and generate in an output plane a position sensitive map of species present. The holographic element can be optically or computer generated. The proposed technology is shown using computer models to be both highly wavelength and position sensitive.The detection and measurement of individual chemical components in complex samples such as flue gases, tobacco smoke, car exhausts, and complex protein mixtures is a serious problem. The need to accurately determine the presence and concentration of chemical components is an every day concern for many industries. For example, just over a year ago the U.S. Congress passed into law the Clean Air Act Amendments (CAAA) requiring 189 chemical components to be regulated. Implementation of the CAAA presents a real challenge for both companies and government regulatory agencies.The existing technology for optically detecting the presence of chemical species is based on spectral decomposition and developed more than a hundred years ago it is now close to its limit in terms of performance and reliability, especially for complex mixtures. Spectral decomposition measures either the spectral distribution from an excited, fluorescing compound or the optical absorption of a material. The specificity of this approach is due to the quantum electronic transitions that are specific for each atom or molecule and are responsible for the emission or absorption of electromagnetic radiation. Atomic spectra are typically a set of sharp lines of varying intensities, whereas for molecules, particularly large ones, the spectra are complex patterns of sharp lines and continuous bands. When a sample is simple enough spectral analysis is an adequate method, but for complex samples overlap of lines of different species limits the reliability of the method.In short, the present technology is rapidly becoming insufficient to meet the growing regulatory demands. The significance of this problem is based on our urgent need to evaluate and control our environment in a time of intensive use of chemicals. It is our belief that a paradigm shift is necessary. We believe it is possible to design a highly dedicated and selective sensor, sensitive to a specific spectral pattern, rather than to specific lines.We suggest here that smart holographic optical elements can be designed to record the entire chemical signature, or "fingerprint", of a compound. Holographic recording of a spectrum 236 / SPIE Vol. 2570 0-8194-1929-X/95/$6.O0 Downloaded From: http://proceedings.spiedigitalli...

An existing analytical concept based on spectral decomposition has been developed more than hundred years ago, and is presently close to its limits in terms of performance and reliability, in particular, for complex samples. For molecules, a spectrum is a very complex pattern of sharp lines and continuous bands. So, in a classical spectrometer, detection is pruned to overlapping errors when two or more components of a sample have overlapping lines, and their separation is, generally, a non-unique problem. Indeed, a line can be assigned to, at least, two different transitions (in the same or different atom/molecules in a sample). Such an assignment based on line positions and transitions has limitations, and may not work at all for complex samples. As samples are getting more and more complex, the problem becomes increasingly intractable. In particular, algorithms and data processing to analyze complex spectra become very complex, require sophisticated peak analysis, etc. A mathematical "inversion" procedure for assignment and identification of components (species) also becomes unstable. That is, the current situation has all signs of a critical bottleneck, and requires an innovative approach. Meanwhile, selectivity is the first priority for many industries and applications. For instance, in the field of air toxics detection, the US EPA requires 189 components to be detected and regulated, and it is highly doubtful that any existing spectrometer is able to analyze reliably such a complex gaseous medium.

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