Numerical analysis of segmented-electrode Orbitraps

Simple geometries which are possible alternatives for the Orbitrap are studied in this paper. We have taken up for numerical investigation two segmented-electrode structures, ORB1 and ORB2, to mimic the electric field of the Orbitrap. In the ORB1, the inner spindle-like electrode and the outer barrel-like electrode of the Orbitrap have been replaced by 35 rings and 35 discs of fixed radii, respectively. In this structure two segmented end cap electrodes have been added. In this geometry, different potentials are applied to the different electrodes keeping top-bottom symmetry intact. In the second geometry, ORB2, the inner and outer electrodes of the Orbitrap were replaced by an approximate step structure which follows the profile of the Orbitrap electrodes. In the present study 45 steps have been used. In the ORB2, like the Orbitrap, the inner electrode is held at a negative potential and the outer electrode is at ground potential. For the purpose of comparing the performance of ORB1 and ORB2 with that of the Orbitrap, the following studies have been undertaken: (1) variation of electric potential, (2) computation of ion trajectories, (3) simulation of image currents. These studies have been carried out using both 2D and 3D Boundary Element Method (BEM), the 3D BEM was developed specifically for this study. It has been seen in these investigations that ORB1 and ORB2 have performance similar to that of the Orbitrap, with the performance of the ORB1 being seen to be marginally superior to that of the ORB2. It has been shown that with proper optimization, geometries containing far fewer electrodes can be used as mass analyzers. A novel technique of optimization of the electric field has been proposed with the objective of minimizing the dependence of axial frequency of ion motion on the initial position of an ion. The results on the optimization of 9 and 15 segmented-electrode traps having the same design as ORB1 show that it can provide accurate mass analysis. (C) 2015 Elsevier B.V. All rights reserved.

Numerical analysis of segmented-electrode Orbitraps

Simple geometries which are possible alternatives for the Orbitrap are studied in this paper. We have taken up for numerical investigation two segmented-electrode structures, ORB1 and ORB2, to mimic the electric field of the Orbitrap. In the ORB1, the inner spindle-like electrode and the outer barrel-like electrode of the Orbitrap have been replaced by 35 rings and 35 discs of fixed radii, respectively. In this structure two segmented end cap electrodes have been added. In this geometry, different potentials are applied to the different electrodes keeping top-bottom symmetry intact. In the second geometry, ORB2, the inner and outer electrodes of the Orbitrap were replaced by an approximate step structure which follows the profile of the Orbitrap electrodes. In the present study 45 steps have been used. In the ORB2, like the Orbitrap, the inner electrode is held at a negative potential and the outer electrode is at ground potential. For the purpose of comparing the performance of ORB1 and ORB2 with that of the Orbitrap, the following studies have been undertaken: (1) variation of electric potential, (2) computation of ion trajectories, (3) simulation of image currents. These studies have been carried out using both 2D and 3D Boundary Element Method (BEM), the 3D BEM was developed specifically for this study. It has been seen in these investigations that ORB1 and ORB2 have performance similar to that of the Orbitrap, with the performance of the ORB1 being seen to be marginally superior to that of the ORB2. It has been shown that with proper optimization, geometries containing far fewer electrodes can be used as mass analyzers. A novel technique of optimization of the electric field has been proposed with the objective of minimizing the dependence of axial frequency of ion motion on the initial position of an ion. The results on the optimization of 9 and 15 segmented-electrode traps having the same design as ORB1 show that it can provide accurate mass analysis. (C) 2015 Elsevier B.V. All rights reserved.

Raman and infra-red microspectroscopy: towards quantitative evaluation for clinical research by ratiometric analysis

Biomolecular structure elucidation is one of the major techniques for studying the basic processes of life. These processes get modulated, hindered or altered due to various causes like diseases, which is why biomolecular analysis and imaging play an important role in diagnosis, treatment prognosis and monitoring. Vibrational spectroscopy (IR and Raman), which is a molecular bond specific technique, can assist the researcher in chemical structure interpretation. Based on the combination with microscopy, vibrational microspectroscopy is currently emerging as an important tool for biomedical research, with a spatial resolution at the cellular and sub-cellular level. These techniques offer various advantages, enabling label-free, biomolecular fingerprinting in the native state. However, the complexity involved in deciphering the required information from a spectrum hampered their entry into the clinic. Today with the advent of automated algorithms, vibrational microspectroscopy excels in the field of spectropathology. However, researchers should be aware of how quantification based on absolute band intensities may be affected by instrumental parameters, sample thickness, water content, substrate backgrounds and other possible artefacts. In this review these practical issues and their effects on the quantification of biomolecules will be discussed in detail. In many cases ratiometric analysis can help to circumvent these problems and enable the quantitative study of biological samples, including ratiometric imaging in 1D, 2D and 3D. We provide an extensive overview from the recent scientific literature on IR and Raman band ratios used for studying biological systems and for disease diagnosis and treatment prognosis.

A mode-shape classification technique for robust speech rate estimation and syllable nuclei detection

Acoustic feature based speech (syllable) rate estimation and syllable nuclei detection are important problems in automatic speech recognition (ASR), computer assisted language learning (CALL) and fluency analysis. A typical solution for both the problems consists of two stages. The first stage involves computing a short-time feature contour such that most of the peaks of the contour correspond to the syllabic nuclei. In the second stage, the peaks corresponding to the syllable nuclei are detected. In this work, instead of the peak detection, we perform a mode-shape classification, which is formulated as a supervised binary classification problem - mode-shapes representing the syllabic nuclei as one class and remaining as the other. We use the temporal correlation and selected sub-band correlation (TCSSBC) feature contour and the mode-shapes in the TCSSBC feature contour are converted into a set of feature vectors using an interpolation technique. A support vector machine classifier is used for the classification. Experiments are performed separately using Switchboard, TIMIT and CTIMIT corpora in a five-fold cross validation setup. The average correlation coefficients for the syllable rate estimation turn out to be 0.6761, 0.6928 and 0.3604 for three corpora respectively, which outperform those obtained by the best of the existing peak detection techniques. Similarly, the average F-scores (syllable level) for the syllable nuclei detection are 0.8917, 0.8200 and 0.7637 for three corpora respectively. (C) 2016 Elsevier B.V. All rights reserved.