Optical Sciences

Biomolecules and nanostructures

The Optical Sciences group studies the interaction of light and matter at the nanoscale. We do this by exploring ways to shape light and its environment. It's what we call active and passive control. Our current focus is on the interaction of light with biomolecules and nanostructures. We are part of Twente University's Department of Science and Technology and member of the MESA+ institute.
We participate in the EU-COST actions MP1102: Coherent Raman microscopy (MicroCor) and CM1202: Supramolecular photocatalytic water splitting (PERSPECT-H2O)


Coherent control of vibrational transitions: Discriminating molecules in mixtures

(full pdf)

A. C. W. van Rhijn, A. Jafarpour, M. Jurna, H. L. Offerhaus and J. L. Herek
Faraday Discussions
issue 0, 153, 227-235 July 20, 2011

Identifying complex molecules often entails detection of multiple vibrational resonances, especially in the case of mixtures. Phase shaping of broadband pump and probe pulses allows for the coherent superposition of several resonances, such that specific molecules can be detected directly and with high selectivity. Our particular implementation of coherent anti-Stokes Raman scattering (CARS) spectroscopy and imaging employs broadband pump and probe fields in combination with a narrowband Stokes field. We describe our approach for combining spectral phase shaping and closed-loop optimization strategies to perform chemically-selective microscopy. To predict the optimal excitation profile we employ evolutionary algorithms that use the vibrational phase responses of five distinct molecules with overlapping resonances and investigate the effect of phase instability on the optimization. We have recently shown that modified polynomials and orthogonal rational functions can give rise to improved contours for CARS fitness landscapes. Now, by considering the landscapes associated with different basis sets, we introduce two figures of merit to quantitatively rank basis functions in terms of their “appropriateness” for modeling nonlinear phase-shaped processes.
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