Spectral Difference Technique Research Articles

(Invited) Confocal Raman Microscopy in the Study of Ion Insertion Processes and Material Dimensional Change

Confocal Raman microscopy is being applied to quantify chemical composition at electrode-solution interfaces and within electrode-supported films under electrochemical potential control. Experimental strategies (i.e., cell designs and data acquisition and processing techniques) that are enabling sensitive in-situ spectral measurements will be discussed with focus on redox transformations at electrode-solution interfaces and within electrode-supported polymer membranes and thin films. Emphasis will be on the ability to investigate ion insertion/de-insertion processes and measure material dimensional (e.g., swelling/de-swelling) changes as the applied potential is varied (in-situ). The microscope system being utilized employs a high numerical aperture oil immersion objective to achieve (i) diffraction-limited focusing and probe volume characteristics and (ii) high efficiency in collecting Raman scattered radiation from molecules of interest. With the objective mounted to an inverted microscope frame, the electrochemical cell is positioned above the objective on the microscope stage. A glass microscope coverslip attached to the bottom of the electrochemical cell serves as the optical window. One electrochemical cell platform has been constructed around an optically transparent indium tin oxide (ITO) coated coverslip that serves as both the cell working electrode and optical window. The objective brings excitation radiation through the coverslip and to a focus a few micrometers above the ITO surface. Species diffusing into the confocal probe volume region are detected and quantified based on their Raman spectral band frequencies and intensities. A second electrochemical cell platform has a thin layer design and enables use of conventional disk working electrodes. The performance of this cell together with a spectral difference technique that allows detection of transformations within redox polymers supported on carbon electrodes will be discussed. The platform is being applied to detect swelling/de-swelling in electrode-supported redox polymers in response to changes in material redox state. Molecular composition (i.e., the mix of polymer framework, solvent and mobile ions) within the confocal probe volume is measured quantitatively from Raman spectra. Tracking the frequency and intensity of spectral bands as electrode potential is varied enables voltage-induced swelling and de-swelling to be correlated to changes in the composition of specific types of mobile species (solvent and ions). Similar application of the strategy to investigate material dimensional change with variation in atmospheric composition will be highlighted.

In Situ Confocal Raman Microscopy of Redox Polymer Films on Bulk Electrode Supports.

A spectroelectrochemical cell is described that enables confocal Raman microscopy studies of electrode-supported films. The confocal probe volume (∼1 μm3) was treated as a fixed-volume reservoir for the observation of potential-induced changes in chemical composition at microscopic locations within an ∼20 μm thickness layer of a redox polymer cast onto a 3 mm diameter carbon disk electrode. Using a Raman system with high collection efficiency and wavelength reproducibility, spectral subtraction achieved excellent rejection of background interferences, opening opportunities for measuring within micrometer-scale thickness redox films on widely available, low-cost, and conventional carbon disk electrodes. The cell performance and spectral difference technique are demonstrated in experiments that detect transformations of redox-active molecules exchanged into electrode-supported ionomer membranes. The in situ measurements were sensitive to changes in the film oxidation state and swelling/deswelling of the polymer framework in response to the uptake and discharge of charge-compensating electrolyte ions. The studies lay a foundation for confocal Raman microscopy as a quantitative in situ probe of processes within electrode-immobilized redox polymers under development for a range of applications, including electrosynthesis, energy conversion, and chemical sensing.

Assessment of firmness and soluble solids content of peaches by spatially resolved spectroscopy with a spectral difference technique

Spatially resolved spectroscopy (SRS) provides a new approach to the measurement of optical scattering and absorption properties and quality assessment of horticultural products. In this research, spatially resolved (SR) spectra over 550 – 1,650 nm were acquired for 600 peaches using a recently developed SRS system covering the light source-detector (S-D) distances from 1.5 to 36 mm with 30 fibers of three sizes (i.e., 50 µm, 105 µm and 200 µm). A new method of calculating spectral differences, between the first S-D distance and the remaining 14 S-D distances was proposed to enhance firmness and soluble solids content (SSC) predictions. Partial least squares (PLS) regression models based on SR and difference reflectance (DR) spectra were developed and compared for firmness and SSC prediction. Results showed that when using SR spectra, prediction results for firmness and SSC varied greatly with the S-D distance; SSC prediction results became worse with the increasing S-D distance, while larger S-D distances of 12–32 mm resulted in better firmness predictions. DR spectra gave consistently better results for both firmness and SSC predictions than SR spectra, with the best correlation coefficients of 0.853 and 0.839 for firmness and SSC prediction, respectively. Overall, SRS coupled with the spectral difference technique can enhance the prediction of firmness and SSC for peach fruit.

WindSat Radio-Frequency Interference Signature and Its Identification Over Greenland and Antarctic

A detection of radio-frequency interference (RFI) in the space-borne microwave radiometer data is difficult under snow and sea ice-covered conditions. The existing methods such as a spectral difference technique or a principal component analysis (PCA) of RFI indices produce many false RFI signals near the boundary of Greenland and Antarctic ice sheets. In this paper, a double PCA (DPCA) method is developed for RFI detection over Greenland and Antarctic regions. It is shown that the new DPCA method is effective in detecting RFI signals in the C- and X-band radiometer channels of WindSat while removing the false RFI signals over Greenland and Antarctic. It also worked well in other snow-free or snow-rich regions such as winter data over the United States. The proposed DPCA can be applied to satellite radiometer data orbit-by-orbit or granule-by-granule and is thus applicable in an operational environment for fast processing and data dissemination.

A fast parallel algorithm for solving block-tridiagonal systems of linear equations including the domain decomposition method

In this study, we develop a new parallel algorithm for solving systems of linear algebraic equations with the same block-tridiagonal matrix but with different right-hand sides. The method is a generalization of the parallel dichotomy algorithm for solving systems of linear equations with tridiagonal matrices \cite{terekhov:Dichotomy}. Using this approach, we propose a parallel realization of the domain decomposition method (\mbox{the Schur} complement method). The calculation of acoustic wave fields using the spectral-difference technique improves the efficiency of the parallel algorithms. A near-linear dependence of the speedup with the number of processors is attained using both several and several thousands of processors. This study is innovative because the parallel algorithm developed for solving block-tridiagonal systems of equations is an effective and simple set of procedures for solving engineering tasks on a supercomputer.

WindSat radio-frequency interference signature and its identification over land and ocean

Radio-frequency interference (RFI) in the spaceborne multichannel radiometer data of WindSat and the Advanced Microwave Scanning Radiometer-EOS is currently being detected using a spectral difference technique. Such a technique does not explicitly utilize multichannel correlations of radiometer data, which are key information in separating RFI from natural radiations. Furthermore, it is not optimal for radiometer data observed over ocean regions due to the inherent large natural variability of spectral difference over ocean. In this paper, we first analyzed multivariate WindSat and Scanning Multichannel Microwave Radiometer (SMMR) data in terms of channel correlation, information content, and principal components of WindSat and SMMR data. Then two methods based on channel correlation were developed for RFI detection over land and ocean. Over land, we extended the spectral difference technique using principal component analysis (PCA) of RFI indices, which integrates statistics of target emission/scattering characteristics (through RFI indices) and multivariate correlation of radiometer data into a single statistical framework of PCA. Over ocean, channel regression of X-band can account for nearly all of the natural variations in the WindSat data. Therefore, we use a channel regression-based model difference technique to directly predict RFI-free brightness temperature, and therefore RFI intensity. Although model difference technique is most desirable, it is more difficult to apply over land due to heterogeneity of land surfaces. Both methods improve our knowledge of RFI signatures in terms of channel correlations and explore potential RFI mitigation, and thus provide risk reductions for future satellite passive microwave missions such as the NPOESS Conical Scanning Microwave Imager/Sounder. The new RFI algorithms are effective in detecting RFI in the C- and X-band Windsat radiometer channels over land and ocean.

Hydrogen bonded rings, chains and lassos: the case of t-butyl alcohol clusters

Infrared OH stretching spectra of hydrogen bonded 2-methyl-propan-2-01 (t-butyl alcohol) clusters are investigated by ragout-jet FTIR spectroscopy. A spectral difference technique is used to discriminate approximately between neighbouring cluster sizes. Dimers, trimers and cyclic tetramers can be detected along with larger clusters, which exhibit a surprisingly structured vibrational fingerprint. Comparison is made to the spectra of related alcohols and to energetic and harmonic vibrational predictions from electronic structure calculations. The experimentally observed 32% increase in OH stretching wavenumber shift from methanol dimer to t-butyl alcohol dimer is reproduced at the HF/3-21G level (+ 33%). It is also qualitatively correct at the MP2/6-31 +G* level (+ l5%), whereas it has the wrong sign at the B3LYP/6-31+ G* level (5%) and is negligible at the HF/6-31+ G* level, disregarding anharmonic effects. The cyclic tetramer of t-butyl alcohol is found to be particularly stable due to a favourable updown alternation of the bulky t-butyl groups. Beyond the t-butyl alcohol tetramer, lasso structures are found to be energetically competitive with simple ring structures. A many-body decomposition shows that this is due to a reduced cooperativity in the sterically hindered pentamer ring. The resulting thermodynamic and kinetic relevance of cyclic tetramers is discussed.

Chiral self-recognition in the gas phase: the case of glycidol dimers

Supersonic jet FTIR spectra of the OH-stretching bands of glycidol monomers and clusters are presented. Chiral discrimination leads to marked differences in the absorption patterns of RR (SS) s. RS glycidol dimers. The dominant absorption peaks are located at 3492 (RR, SS) and 3488 cm−1 (RS) within a rich line spectrum with sizeable variations between enantiomerically pure and racemic dimers. A spectral difference technique is used to emphasize the intermolecular diastereomeric effects. Glycidol is possibly the first and likely the smallest molecule for which chiral self-recognition has been experimentally demonstrated in the gas phase. It thus lends itself very well to accurate quantum chemical calculations of the chiral discrimination effect. Qualitative results of exploratory calculations are reported.

In vivo liver differentiation by ultrasound using an artificial neural network.

A pattern recognition algorithm and instrumentation for in vivo ultrasound human liver differentiation are presented. An available 16-MHz microprocessor-based data acquisition and analysis system with 6-bit resolution is used to capture, digitize, and store the backscattered ultrasound signal. The algorithm is based on a multilayer perception neural network using the backpropagation training procedure. The network is implemented to differentiate between normal and abnormal liver. Data earlier obtained from 18 volunteers with normal liver history and from 12 volunteers with liver abnormalities are used to test the algorithm. The power spectra of the backscattered signal from depths of 5, 6.5, and 8 cm in the liver are calculated. The acoustic attenuation coefficient is calculated by the log spectral difference technique over the frequency range from 1.5 to 4.5 MHz. The change of speed of sound with frequency (dispersion) is estimated over the 3-MHz bandwidth. The attenuation and velocity dispersion are used as differentiation features. The results show that of the 22 tested cases, the system differentiated correctly 19 and 20 cases when using the attenuation and the velocity dispersion, respectively. The average magnitude of dispersion of liver is estimated to be 1.67 +/- 0.1 m/s/MHz and about 2.3 +/- 0.18 m/s/MHz in the normal and abnormal cases, respectively. The overall performance of the system for liver differentiation is 91% for normal cases, and 86% for abnormal cases. The data files are also differentiated using the nearest neighbor statistical classifier. The results show that of the 30 tested cases, 23 files are differentiated correctly using the attenuation coefficient.

Recurrence solution of a block tridiagonal matrix equation with Neumann, Dirichlet, mixed or periodic boundary conditions

In this study, we develop a new parallel algorithm for solving systems of linear algebraic equations with the same block-tridiagonal matrix but with different right-hand sides. The method is a generalization of the parallel dichotomy algorithm for solving systems of linear equations with tridiagonal matrices [1]. Using this approach, we propose a parallel realization of the domain decomposition method (the Schur complement method). The calculation of acoustic wave fields using the spectral-difference technique improves the efficiency of the parallel algorithms. A near-linear dependence of the speedup with the number of processors is attained using both several and several thousands of processors. This study is innovative because the parallel algorithm developed for solving block-tridiagonal systems of equations is an effective and simple set of procedures for solving engineering tasks on a supercomputer.