A. Bree

A study of the second order phase transition in biphenyl at 40 K through raman spectroscopy

Abstract The second order phase transition in biphenyl has been monitored using some lines unique to the Raman spectrum of the low temperature phase. The transition temperature is 40 K, and the number of molecules in the unit cell of the new low temperature phase is greater than 2 (probably 4). The equilibrium angle θ m between the planes of the two benzene rings gradually increases from zero at 40 K about 9° at 4.2 K. A 33 cm −1 interval observed in the crystal at 4.2 K moves to lower frequency and loses intensity as the transition temperature is approached from below; we believe this interval represents a “soft mode” associated with the torsion about the central single bond of biphenyl. A low barrier to planarity of the stable twisted molecular geometry in the solid at 4.2 K is estimated to be about 40 cm −1 .

Further evidence for phase transitions in biphenyl near 40 K and 16 K

Abstract Phase transitions have been detected in biphenyl at about 42 and 17 K by noting changes in the transmitted light intensity when the crystal is placed at extinction between crossed polaroids and the crystal temperature slowly varied. The phase transition at 42 K is gradual (i.e. it occurs over a range of temperature) while the 17 K transition is abrupt. The effect is observed only for light propagating normal to an a * b section which implies that the atomic displacements at the phase changes are largely restricted to this plane. An analogous behaviour is observed for biphenyl- d 10 except that the onset of the gradual transition on cooling is at 38 K and the abrupt transition is at 24 K.

SNR Enhancement and Deconvolution of Raman Spectra Using a Two-Point Entropy Regularization Method

A new method for Raman signal recovery, the two-point maximum entropy method (TPMEM), based on a regularization method using two-point entropy is presented. The method can be used for signal-to-noise ratio (SNR) enhancement in very low SNR measurements or for deconvolution, in order to remove the effects of the instrumental line shape on the measured spectrum. Unlike most SNR enhancement schemes, TPMEM requires no filter parameters and no a priori knowledge of the expected signal. A rigorous test on a randomly produced set of convolved and/or noise-corrupted simulated Raman spectra is presented in order to validate the method and compare it to Savitzky-Golay filtering and the maximum entropy method. The method is evaluated on the basis of the root mean square (rms) error and correlation coefficients of the recovered data with the original data, as well as on the basis of SNR improvement, and showed significant improvements in both performance and speed over conventional methods. The method is demonstrated in an application involving fiber-optic-linked Raman and resonance Raman spectroscopy.

The geometry of trans-stilbene in the liquid phase

Abstract The Raman spectrum of trans -stilbene in the solid, melt and solution has been measured. The dramatic intensification of the 960 cm −1 line in the liquid phase indicates that the molecule suffers an out-of-plane distortion. This distortion in the liquid is shown to involve the ethylenic hydrogen atoms in such a way that the inversion symmetry of the planar molecule is lost.

Calculated infrared intensities for the bending mode in some small linear molecules

Abstract Density functional theory was used to compute electric dipole moment derivatives along bending coordinates for the linear molecules HCN, DCN, FCN, ClCN, CO 2 , OCS, CS 2 , N 2 O, C 2 H 2 , C 2 D 2 and C 2 N 2 . The infrared intensities obtained in this way are in better agreement with experimental values than provided by earlier calculations.

Characteristics of Backpropagation Neural Networks Employed in the Identification of Neurotransmitter Raman Spectra

We have shown that neural networks are capable of accurately identifying the Raman spectra of aqueous solutions of small-molecule neurotransmitters. It was found that the networks performed optimally when the ratio of the number of hidden nodes to the number of input nodes was 0.16, that network accuracy increased with the number of input layer nodes, and that input features influenced the abilities of networks to discriminate or generalize between spectra. Furthermore, networks employing sine transfer functions for their hidden layers trained faster and were better at discriminating between closely related spectra, but they were less tolerant of spectral distortions than the networks using sigmoid transfer functions. The latter type of network produced superior results where generalization between spectra was required.

Vibronic coupling in the lowest singlet state of dibenzofuran

Abstract The low-energy absorption system of dibenzofuran vapour has been re-measured at high resolution. The origin band (O) and the prominent band at O + 445 have different contours, and so have opposite polarization. In the solid state, the frequency of the prominent vibrational interval is already known to be markedly affected by a change of matrix. The polarized spectrum of dibenzofuran in a stretched polyethylene sheet at 140°K is reported and is similar to the vapour phase spectrum so that the polyethylene matrix does not severely perturb the spectrum. Vibronic coupling is shown to involve a b 2 vibration of frequency 430 cm −1 in the polymer film, and estimates for the vibronic coupling matrix element are given.

The raman spectrum of anthracene - d10

Abstract A set of polarized Raman spectra obtained from suitably oriented anthracene-d10 single crystals together with depolarization measurements from the melt are presented, and an analysis is suggested. Some interesting effects that occur on melting are noted.

Artificial neural network and classical least-squares methods for neurotransmitter mixture analysis

Identification of individual components in biological mixtures can be a difficult problem regardless of the analytical method employed. In this work, Raman spectroscopy was chosen as a prototype analytical method due to its inherent versatility and applicability to aqueous media, making it useful for the study of biological samples. Artificial neural networks (ANNs) and the classical least-squares (CLS) method were used to identify and quantify the Raman spectra of the small-molecule neurotransmitters and mixtures of such molecules. The transfer functions used by a network, as well as the architecture of a network, played an important role in the ability of the network to identify the Raman spectra of individual neurotransmitters and the Raman spectra of neurotransmitter mixtures. Specifically, networks using sigmoid and hyperbolic tangent transfer functions generalized better from the mixtures in the training data set to those in the testing data sets than networks using sine functions. Networks with connections that permit the local processing of inputs generally performed better than other networks on all the testing data sets. and better than the CLS method of curve fitting, on novel spectra of some neurotransmitters. The CLS method was found to perform well on noisy, shifted, and difference spectra.

Two-photon excitation into low-energy singlet states of anthracene in mixed crystals

Abstract The two-photon excitation spectrum of the first excited state of anthracene in fluorene and biphenyl at 4.2 K has been measured. Intensity is induced into the origin by the static dipole moment of fluorene, and into b 1u vibrons through coupling to an A g state near 29400 cm −1 ; the nature of this A g state is discussed.