129 I and 119 Sn Mössbauer spectroscopy , reversibility window and nanoscale phase separation in binary Ge x Se 1 x glasses
The molecular structure of the prototypical chalcogenide glass system—GexSe1 x in the 0oxo3 range, has received much scrutiny over the years. These glasses have been probed by modulated DSC, Raman scattering, Sn absorption and I emission Mössbauer spectroscopy, and neutron scattering. The I measurements utilize Te parent as a dopant in glasses, and reveal a bimodal (A, B) distribution of sites, with the site intensity ratio, IB/IA (x), tracking changes in glass structure as a function of x. At low x (o0.15) Senchains are stochastically cross-linked by Ge additive, and IB/IA (x) sharply declines with x. But at x40:15, rigid regions nucleate at the expense of floppy ones, and the ratio IB/IA (x) reverses slope to display a global maximum in the 0:20oxo0:25 range. The latter coincides with the reversibility window usually taken as signature of self-organization of these networks. At x40:26, these glasses enter a stressed-rigid elastic phase and in the 0:31oxo1 3 range nanoscale phase separate into Se-rich and Ge-rich regions. The signature of the latter is saturation of IB/IA (x) at a high value of 1.5 at x 1⁄4 13. Sn Mossbauer spectroscopy measurements independently support the picture of broken chemical order of the stoichiometric glass inferred from the I Mössbauer experiments. These observations using local probes are well correlated to Raman scattering, modulated differential scanning calorimetric and diffraction measurements. r 2006 Elsevier B.V. All rights reserved. PACS: 61.40.Fs; 63.50.+x; 78.30.Ly; 76.80.+y
Intermediate phases, boson and floppy modes, and demixing of network structures of binary As-S and As-Se glasses
Binary AsxS1-x glasses are studied in modulated-DSC, Raman scattering, IR reflectance and molar volume experiments over a wide range (8% < x < 41%) of compositions. Calorimetric experiments reveal a reversibility window, which permits fixing the three elastic phases; flexible at x < 22.5%, intermediate in the 22.5% < x < 29.5% range, and stressed-rigid at x > 29.5%. Raman vibrational density of states supported by first principles cluster calculations show features of both pyramidal (PYR) [As(S1/2)3] and quasi-tetrahedral (QT) [S=As(S1/2)3] local structures. The QT unit concentrations maximize in the intermediate phase (IP) and both PYR and QT local structures contribute to the width of the IP. The IP centroid in the sulfides is shifted to lower As content x than in corresponding selenides, a feature identified with excess chalcogen partially segregating from the backbone in the sulfides, but forming part of the backbone in selenides. These ideas are corroborated by the proportionately larger free volumes of sulfides than selenides, and the absence of chemical bond strength scaling of Tg’s between As-sulfides and As-selenides. Low-frequency Raman modes (Boson modes) increase in scattering strength linearly as As content decreases from x = 20% to 8%, with a slope that is close to the floppy mode fraction in flexible glasses predicted by rigidity theory, showing that floppy modes contribute to the excess vibrations observed at low frequency, the Boson modes. Long term aging, extending from months to several years, is studied on several families of chalcogenide glasses including the Ge-Se, As-Se, Ge-P-Se and Ge-As-Se systems. Our results show all samples display sub-Tg endotherms typically 10°C to 70°C below Tg in glassy networks possessing a mean coordination number r in the 2.25 < r < 2.45 range. Special attention is given to the As-Se binary and XRD, m-DSC and Raman scattering experiments are undertaken. Two
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.