QSPR Analysis of Degree-Based Topological Indices with physical properties of Benzenoid Hydrocarbons

Kanabur, Rachanna; Shigehalli, V S

doi:10.31559/glm2016.2.3.6

Cited by 10 publications

(1 citation statement)

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“…In this section, we analyze the entropies given above with the following physical characteristics of the benzene derivatives [32,33]: critical pressure (CP), critical temperature (CT), critical volume (CV), Gibb's energy (qE), log(P), molar refractivity (MR), and Henry's law (HL). e experimental values of physical characteristics of benzene derivatives have been referred to from [34] and presented in Table 1. We have presented the values of the proposed indices for the benzene derivatives in Tables 2 and 3.…”

Section: Curvilinear Regression Analysis Of Proposed Entropiesmentioning

confidence: 99%

On Curvilinear Regression Analysis via Newly Proposed Entropies for Some Benzene Models

et al. 2022

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To avoid exorbitant and extensive laboratory experiments, QSPR analysis, based on topological descriptors, is a very constructive statistical approach for analyzing the numerous physical and chemical properties of compounds. Therefore, we presented some new entropy measures which are based on the sum of the neighborhood degree of the vertices. Firstly, we made the partition of the edges of benzene derivatives which are based on the degree sum of neighboring vertices and then computed the neighborhood version of entropies. Secondly, we made use of the software SPSS for developing a correlation between newly introduced entropies and the physicochemical properties of benzene derivatives. Our obtained results demonstrated that the critical temperature C T , critical pressure C P , and critical volume C V can be predicted through fifth geometric arithmetic entropy, second S K entropy, and fifth N D entropy, respectively. Other remaining physical characteristics include Gibb’s energy qℰ , log P , molar refractivity ℳℛ , and Henry’s law ℋℒ that can be predicted by using sixth N D entropy.

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Section: Curvilinear Regression Analysis Of Proposed Entropiesmentioning

confidence: 99%