Correlation between the physical and optical properties of the<i>a</i>-Ge–Se–In–Bi system

Sharma, Ishu; Tripathi, S. K.; Barman, P. B.

doi:10.1080/14786430802552638

Cited by 24 publications

(6 citation statements)

References 30 publications

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“…In our case, the value of r varies from 2.2 to 2.4, which can be correlated with low connectivity glasses and no correlation is found between these two parameters. Similar behavior has been shown by different scientists conducting research on different compositions [25][26][27].…”

Section: Relation Between E 04supporting

confidence: 58%

Theoretical prediction of physical parameters of GexSb20−x Te80 (x = 11, 13, 15, 17, 19) bulk glassy alloys

Sharma

Maheshwari

2014

Materials Science-Poland

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Physical properties of Ge x Sb 20−x Te 80 (x = 11, 13, 15, 17, 19) bulk glassy alloys are examined theoretically. Lone pair electrons are calculated using an average coordination number ( r ) and the number of valence electrons, and are found to decrease with an addition of Ge. Mean bond energy ( E ) is proportional to glass transition temperature (T g ) and shows maxima near the chemical threshold. Cohesive energy of the system is calculated using chemical bond approach. A linear relation is found between cohesive energy, band gap (calculated theoretically and confirmed experimentally) and average heat of atomization. All these parameters are increasing with an increase in Ge content. A relation between average single bond energy and photon energy is discussed. Compactness of the structure is measured from the calculated density of the glass. An attempt is made to discuss the results in terms of structure of the glass or equivalently with average coordination number.

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Section: Relation Between E 04supporting

confidence: 58%

Theoretical prediction of physical parameters of GexSb20−x Te80 (x = 11, 13, 15, 17, 19) bulk glassy alloys

Sharma

Maheshwari

2014

Materials Science-Poland

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“…[44] and obtained values are listed in Table 3. Figure 6 shows the relationship between theoretically calculated physical parameters such as mean bond energy E, glass transition temperature ðT th g Þ, theoretical band gap ðE th g Þ and average single bond energy H s /Z as a function of increasing In content.…”

Section: Experimental Methodsmentioning

confidence: 99%

Analysis of chemical ordering and fragility for Ge–Se–In glasses

et al. 2015

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Decreasing the band gap of a material due to metal impurities has been approved through several studies, and this subject is considered as a major area of interest within the optoelectronic applications. Indium-based chalcogenides have been considered good candidates in nonlinear optics due to their ability to transmit in the infrared region. Hence, Ge 18 Se 82 has been alloyed with In. The nature of the chemical ordering of amorphous samples of Ge 18 Se 82-x In x (x = 0, 2, 4 and 6) have been systematically studied. The aim of present investigation is to understand the role of chemical composition and meancoordination number in determining their structural and physical properties. The compactness, d, of alloyed samples has been calculated from their measured densities, and values obtained have been interpreted using the topological model proposed to describe the atomic arrangements in these alloys. The variation of the glass transition temperature, T g , with the average coordination number, Z, has been investigated. The compositional dependence of the mean atomic volume, V m , has also been determined. The free volume percentage, FVP, in Ge 18 Se 82-x In x amorphous samples and their fragility indices, m, have been determined to examine the relationship with the mean-coordination number. We have also analyzed the obtained results on the basis of average single bond energy and electronegativity.

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“…To overcome the unavailability of compositions (4 ≤ x ≤ 9) of As 30 Se 70−x Sn x thin films, energy gaps were calculated theoretically for compositions (0 ≤ x ≤ 9) and tabulated in Table 1. The band gap for the compositions under investigations has also been calculated theoretically using the formula (Sharma, Tripathi, & Barman, 2008) E th g (As-Se-Sn) = aE g (As) + bE g (Se)…”

Section: Resultsmentioning

confidence: 99%

Optical constants characterization of As 30 Se 70−x Sn x thin films using neural networks

Attia

El-Bana

Habashy

et al. 2017

Journal of Applied Research and Technology

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This paper uses an artificial neural network (ANN) and resilient back-propagation (Rprop) training algorithm to determine the optical constants of As 30 Se 70−x Sn x (0 ≤ x ≤ 3) thin films. The simulated values of the ANN are in good agreement with the experimental data. The ANN models performance was also examined to predict the simulated values for As 30 Se 67 Sn 3 which was not included in the training and was found to be in accordance with the experimental data. The high precision of the ANN models as well as a great guessing performance have been exhibited. Moreover, the energy gap E g of As 30 Se 70−x Sn x (0 ≤ x ≤ 9) thin films were calculated theoretically.

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Correlation between the physical and optical properties of thea-Ge–Se–In–Bi system

Cited by 24 publications

References 30 publications

Theoretical prediction of physical parameters of GexSb20−x Te80 (x = 11, 13, 15, 17, 19) bulk glassy alloys

Theoretical prediction of physical parameters of GexSb20−x Te80 (x = 11, 13, 15, 17, 19) bulk glassy alloys

Analysis of chemical ordering and fragility for Ge–Se–In glasses

Optical constants characterization of As 30 Se 70−x Sn x thin films using neural networks

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