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RISS 인기검색어
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- 저자 : ( Minh T. L. Nguyen ) (검색결과 3 건)
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Tran Dang Thanh,Phan, T. L.,Le Mai Oanh,Nguyen Van Minh,Jong Suk Lee,Yu, S. C. IEEE 2014 IEEE transactions on magnetics Vol.50 No.6
<P>This paper presents the influence of Mn doping on the structural characterization, and optical and magnetic properties of SrTi<SUB>1-x</SUB>Mn<SUB>x</SUB>O<SUB>3</SUB>(x = 0.0-0.1) materials prepared by a solid-state reaction method. The detailed analyses of X-ray diffraction patterns indicate an incorporation of Mn dopants into Ti sites of the SrTiO<SUB>3</SUB> host lattice. There is a cubic to tetragonal transformation, which takes place at a threshold concentration x ≈ 0.04. The optical absorption spectra show a rapid increase in the absorption coefficient. The bandgap energy (Eg) related to the direct electron transition decreases with increasing Mn concentration: Eg decreases from 3.15 eV for x = 0 to 1.28 eV for x = 0.10. From this point of view, the SrTi<SUB>1-x</SUB>Mn<SUB>x</SUB>O<SUB>3</SUB> materials are considered as promising materials for photocatalytic applications. Interestingly, while the samples with x = 0.0-0.02 are diamagnetic, the others with x = 0.04-0.10 exhibit weak ferromagnetism. The ferromagnetic order increases with increasing Mn concentration. Based on the results of structural and optical analyses, the nature of magnetism in the samples is explained thoroughly.</P>
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Nielsen, Birthe V.,Abaye, Daniel A.,Nguyen, Minh T.L. Korean Society for Mass Spectrometry 2017 Mass spectrometry letters Vol.2 No.4
Understanding the mechanisms that control and concentrate the observed electrospray ionisation (ESI) response from peptides is important. Controlling these mechanisms can improve signal-to-noise ratio in the mass spectrum, and enhances the generation of intact ions, and thus, improves the detection of peptides when analysing mixtures. The effects of different mixtures of aqueous: organic solvents (25, 50, 75%; v/v): formic acid solution (at pH 3.26) compositions on the ESI response and charge-state distribution (CSD) during mass spectrometry (MS) were determined in a group of biologically active peptides (molecular wt range 1.3 - 3.3 kDa). The ESI response is dependent on type of organic solvent in the mobile phase mixture and therefore, solvent choice affects optimal ion intensities. As expected, intact peptide ions gave a more intense ESI signal in polar protic solvent mixtures than in the low polarity solvent. However, for four out of the five analysed peptides, neither the ESI response nor the CSD were affected by the volatility of the solvent mixture. Therefore, in solvent mixtures, as the composition changes during the evaporation processes, the $pK_b$ of the amino acid composition is a better predictor of multiple charging of the peptides.
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( Birthe V. Nielsen ),( Daniel A. Abaye ),( Minh T. L. Nguyen ) 한국질량분석학회 2017 Mass spectrometry letters Vol.8 No.2
Understanding the mechanisms that control and concentrate the observed electrospray ionisation (ESI) response from peptides is important. Controlling these mechanisms can improve signal-to-noise ratio in the mass spectrum, and enhances the generation of intact ions, and thus, improves the detection of peptides when analysing mixtures. The effects of different mixtures of aqueous: organic solvents (25, 50, 75%; v/v): formic acid solution (at pH 3.26) compositions on the ESI response and charge-state distribution (CSD) during mass spectrometry (MS) were determined in a group of biologically active peptides (molecular wt range 1.3 - 3.3 kDa). The ESI response is dependent on type of organic solvent in the mobile phase mixture and therefore, sol-vent choice affects optimal ion intensities. As expected, intact peptide ions gave a more intense ESI signal in polar protic solvent mixtures than in the low polarity solvent. However, for four out of the five analysed peptides, neither the ESI response nor the CSD were affected by the volatility of the solvent mixture. Therefore, in solvent mixtures, as the composition changes during the evaporation processes, the pKb of the amino acid composition is a better predictor of multiple charging of the peptides.
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