SiO4 characterization in a chain and C6 H6 embedded in a Non-kekulean structure for Kulli Temperature indices

Ghani, Muhammad Usman; Sultan, Faisal; Din, El Sayed M. Tag El; Cancan, Murat; Ali, Shahbaz

doi:10.21203/rs.3.rs-2187351/v1

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…In this case, the innovation is proposed by using the heat generated from reaction in the reactor to reheat the excess hydrogen which will be reused for further process. This modification improves heat efficiency of the nitrobenzene hydrogenation process [29]. The aim of this research is to improve heat efficiency in the aniline production through nitrobenzene hydrogenation process by utilizing heat transfer fluid looping system in heating and cooling process using Aspen HYSYS.…”

Section: Introductionmentioning

confidence: 99%

Improving Heat Efficiency of Aniline Production Process by Modifying Heat Transfer Fluid Looping System in Heating and Cooling Process

Ahdan,

Saputra,

Ivan

et al. 2024

J. Chem. Eng. Res. Prog.

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The nitrobenzene hydrogenation process is a highly exothermic reaction which causes the product temperature will increase and then needs to be cooled down with a heat exchanger. The modification process is needed to improve the heat efficiency of the nitrobenzene hydrogenation process by utilizing the heat from reactor product. Heat transfer fluid is used as a medium of heat transfer for both heating and cooling, so that will create a looping heat transfer process. The looping system of heat transfer fluid receives heat from reactor product and then reuses the heat to reheat the recycled hydrogen and for other utilities, so additional energy for these processes is not required. The process modification was simulated using Aspen HYSYS and the comparison of heat efficiency between the basic and the modified process is calculated using the net-energy formula. The results obtained that the net-energy (NE) value for both basic and modified process is 96,714,359.832 kJ/h and 9.869 kJ/h. This shows that the modified process has better energy efficiency compared to the basic process as the net-energy value is closer to zero. Therefore, this modification increases the heat efficiency of the aniline production through nitrobenzene hydrogenation process. Copyright © 2024 by Authors, Published by Universitas Diponegoro and BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

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Section: Introductionmentioning

confidence: 99%

Improving Heat Efficiency of Aniline Production Process by Modifying Heat Transfer Fluid Looping System in Heating and Cooling Process

Ahdan,

Saputra,

Ivan

et al. 2024

J. Chem. Eng. Res. Prog.

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“…Chemical indices are important tools for studying different physico-chemical properties of molecules without having to conduct several tests. In the investigation of medicines, quantitative structure-activity relationships (QSAR) use mathematical computations to decipher the chemical properties [ 14 , 15 ]. Some researchers have analyzed the topological and K -Banhatti indices in [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Entropy Related to K-Banhatti Indices via Valency Based on the Presence of C6H6 in Various Molecules

et al. 2023

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Entropy is a measure of a system’s molecular disorder or unpredictability since work is produced by organized molecular motion. Shannon’s entropy metric is applied to represent a random graph’s variability. Entropy is a thermodynamic function in physics that, based on the variety of possible configurations for molecules to take, describes the randomness and disorder of molecules in a given system or process. Numerous issues in the fields of mathematics, biology, chemical graph theory, organic and inorganic chemistry, and other disciplines are resolved using distance-based entropy. These applications cover quantifying molecules’ chemical and electrical structures, signal processing, structural investigations on crystals, and molecular ensembles. In this paper, we look at K-Banhatti entropies using K-Banhatti indices for C6H6 embedded in different chemical networks. Our goal is to investigate the valency-based molecular invariants and K-Banhatti entropies for three chemical networks: the circumnaphthalene (CNBn), the honeycomb (HBn), and the pyrene (PYn). In order to reach conclusions, we apply the method of atom-bond partitioning based on valences, which is an application of spectral graph theory. We obtain the precise values of the first K-Banhatti entropy, the second K-Banhatti entropy, the first hyper K-Banhatti entropy, and the second hyper K-Banhatti entropy for the three chemical networks in the main results and conclusion.

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“…), and toxicological properties of a chemical molecule have a link with these invariants [3][4][5]. Topological indices have the amazing feature of remaining constant over graph isomorphisms, making them typically graph-invariant [6][7][8][9][10][11][12][13][14]. Numerous topological indices based on chemical graphs that rely on the number of vertices have been discovered and studied [15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Entropies Via Various Molecular Descriptors of Layer Structure of H3BO3

et al. 2022

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Entropy is essential. Entropy is a measure of a system’s molecular disorder or unpredictability, since work is produced by organized molecular motion. Entropy theory offers a profound understanding of the direction of spontaneous change for many commonplace events. A formal definition of a random graph exists. It deals with relational data’s probabilistic and structural properties. The lower-order distribution of an ensemble of attributed graphs may be used to describe the ensemble by considering it to be the results of a random graph. Shannon’s entropy metric is applied to represent a random graph’s variability. A structural or physicochemical characteristic of a molecule or component of a molecule is known as a molecular descriptor. A mathematical correlation between a chemical’s quantitative molecular descriptors and its toxicological endpoint is known as a QSAR model for predictive toxicology. Numerous physicochemical, toxicological, and pharmacological characteristics of chemical substances help to foretell their type and mode of action. Topological indices were developed some 150 years ago as an alternative to the Herculean, and arduous testing is needed to examine these features. This article uses various computational and mathematical techniques to calculate atom–bond connectivity entropy, atom–bond sum connectivity entropy, the newly defined Albertson entropy using the Albertson index, and the IRM entropy using the IRM index. We use the subdivision and line graph of the H3BO3 layer structure, which contains one boron atom and three oxygen atoms to form the chemical boric acid.

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SiO4 characterization in a chain and C6 H6 embedded in a Non-kekulean structure for Kulli Temperature indices

Cited by 7 publications

References 12 publications

Improving Heat Efficiency of Aniline Production Process by Modifying Heat Transfer Fluid Looping System in Heating and Cooling Process

Improving Heat Efficiency of Aniline Production Process by Modifying Heat Transfer Fluid Looping System in Heating and Cooling Process

Entropy Related to K-Banhatti Indices via Valency Based on the Presence of C6H6 in Various Molecules

Entropies Via Various Molecular Descriptors of Layer Structure of H3BO3

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