Resonance Raman and theoretical investigation of the photodissociation dynamics of benzamide in S3 state

Excited state proton transfer dynamics of thioacetamide in S2(ππ*) state: resonance Raman spectroscopic and quantum mechanical calculations study

The photophysics and photochemistry of thioacetamide (CH3CSNH2) after excitation to the S2 electronic state were investigated by using resonance Raman spectroscopy in conjunction with the complete active space self-consistent field (CASSCF) method and density functional theory (DFT) calculations. The A-band resonance Raman spectra in acetonitrile, methanol, and water were obtained at 299.1, 282.4, 266.0, 252.7, and 245.9 nm excitation wavelengths to probe the structural dynamics of thioacetamide in the S2 state. CASSCF calculations were done to determine the transition energies and structures of the lower-lying excited states, the conical intersection points CI(S2/S1) and CI(S1/S0), and intersystem crossing points. The structural dynamics of thioacetamide in the S2 state was revealed to be along eight Franck-Condon active vibrational modes ν15, ν11, ν14, ν10, ν8, ν12, ν18, and ν19, mostly in the CC/CS/CN stretches and the CNH8,9/CCH5,6,7/CCN/CCS in-plane bends as indicated by the corresponding normal mode descriptions. The S2 → S1 decay process via the S2/S1 conical intersection point as the major channel were excluded. The thione-thiol photoisomerization reaction mechanism of thioacetamide via the S2,FC → S'1,min excited state proton transfer (ESPT) reaction channel was proposed.

A matrix-based two-dimensional regularization algorithm for signal-to-noise ratio enhancement of multidimensional spectral data

We present a new spectral image processing algorithm, the "matrix maximum entropy method" (MxMEM), which offers efficient signal-to-noise ratio (SNR) enhancement of multidimensional spectral data. MxMEM is based upon two previous regularization methods that employ the maximum entropy concept. The first is a one-dimensional (1D) algorithm, which smoothes individual vectors, called the two-point maximum entropy method (TPMEM). The second is a two-dimensional (2D) form called 2D TPMEM, that smoothes images but processes them one vector at a time. MxMEM is a truly two dimensional image processing algorithm in that its "smoothing engine" performs two-dimensional processing in every iteration. We demonstrate that this matrix-based construction makes more effective use of two-dimensionally embedded information and thus confers significant advantages over other regularization approaches. In addition, we utilize the concept that individual related Raman spectra can be combined in a matrix to form an artificial Raman "image". We show that, when processed as an image, superior SNR enhancement is achieved compared to processing the same data by TPMEM one spectrum at a time.