Startseite Banhatti, revan and hyper-indices of silicon carbide Si2C3-III[n,m]
Artikel Open Access

Banhatti, revan and hyper-indices of silicon carbide Si2C3-III[n,m]

  • Dongming Zhao , Manzoor Ahmad Zahid , Rida Irfan EMAIL logo , Misbah Arshad , Asfand Fahad , Zahid Ahmad und Li Li
Veröffentlicht/Copyright: 4. Juni 2021

Abstract

In recent years, several structure-based properties of the molecular graphs are understood through the chemical graph theory. The molecular graph G of a molecule consists of vertices and edges, where vertices represent the atoms in a molecule and edges represent the chemical bonds between these atoms. A numerical quantity that gives information related to the topology of the molecular graphs is called a topological index. Several topological indices, contributing to chemical graph theory, have been defined and vastly studied. Recent inclusions in the class of the topological indices are the K-Banhatti indices. In this paper, we established the precise formulas for the first and second K-Banhatti, modified K-Banhatti, K-hyper Banhatti, and hyper Revan indices of silicon carbide Si 2 C 3 - III [ n , m ] . In addition, we present the graphical analysis along with the comparison of these indices for Si 2 C 3 - III [ n , m ] .

MSC 2010: 05C05; 05C07; 05C35

1 Introduction

The chemical, physical, and physicochemical properties of a compound, which depends on its structure, can be effectively studied by means of the graph theory. A chemical structure of a compound can be described by a graph G , where the vertex set of G consists of the atoms of the compound and the edge set consists of the chemical bonds between the atoms. A graph can be recognized by connection table, polynomial, sequence of numbers, matrix or numeric number which is also called a topological index that represents the whole graph. A topological index got special attention as it predicts several information related to the molecular structure of the compounds. In the description of a chemical structure, a topological index is one of the most powerful tools with several intense applications in such as mathematical chemistry, the fields of control theory and quantitative structure–property relation (QSPR) and quantitative structure–activity relation (QSAR) investigations, see refs. [1,2]. For details regarding the recent contributions on the topological indices, see refs. [3,4,5, 6,7,8, 9,10,11].

Before proceeding further regarding the definitions of the topological indices studied in this paper, we recall the relevant notions and set the corresponding notations. For the notions and notations not described here we refer [12] to the readers. Throughout this paper, we denote a simple connected graph by G , distance between u and v by d ( u , v ) , the degree of a vertex u in G by d ( u ) , an edge e between the vertices u and v by e = u v , degree of an edge e by d ( e ) (where d ( e ) = d ( u ) + d ( v ) 2 ), and the maximum and minimum degree in a graph by Δ ( G ) and δ ( G ) , respectively.

According to the settings described in the previous paragraph, the first K-Banhatti index B 1 ( G ) and second K-Banhatti index B 2 ( G ) are defined as follows:

B 1 ( G ) = u e E ( G ) [ d ( u ) + d ( e ) ] , B 2 ( G ) = u e E ( G ) [ d ( u ) × d ( e ) ] .

The modified first K-Banhatti index B 1 m ( G ) and second K-Banhatti index B 2 m ( G ) are defined as follows:

B 1 m ( G ) = u e E ( G ) 1 d ( u ) + d ( e ) , B 2 m ( G ) = u e E ( G ) 1 d ( u ) × d ( e ) .

The first K-hyper Banhatti index H B 1 ( G ) and second K-hyper Banhatti index H B 2 ( G ) are defined as follows:

H B 1 ( G ) = u e E ( G ) [ d ( u ) + d ( e ) ] 2 , H B 2 ( G ) = u e E ( G ) [ d ( u ) × d ( e ) ] 2 .

The first- and second-hyper Revan indices of G are defined as follows:

H R 1 ( G ) = u v E ( G ) [ r G ( u ) + r G ( v ) ] 2 , H R 2 ( G ) = u v E ( G ) [ r G ( u ) r G ( v ) ] 2 ,

where r G ( v ) = Δ ( G ) + δ ( G ) d ( v ) and u v means that the vertex u and vertex v are adjacent in G . We refer [13,14, 15,16] for details about these indices.

On the other hand, silicon is a nontoxic semiconductor material that has a very low cost when compared with other materials of the same type. Silicon is a vital part of all electronic devices. The well-constructed structures of two-dimensional (2D) silicon–carbon single layer compounds having different stoichiometric compositions were concluded in ref. [17]. The 2D silicon–carbon single layer may be seen as configurable materials between the pure 2D carbon single layer, graphene, and the pure 2D silicon single layer, silicene. After many attempts, the structure of the SiC sheet (with remarkable stability) was predicted, and for further details about this structure, we refer [18,19,20] to the readers. We consider 2D SiC compounds with a different types of silicon carbide structure-based on low-energy metastable structures for each silicon, that is, Si 2 C 3 -III.

By keeping in view the importance of the topological indices in theoretical and computational nano-sciences, we compute B 1 ( G ) , B 2 ( G ) , B 1 m ( G ) , B 2 m ( G ) , H B 1 ( G ) , H B 2 ( G ) , H R 1 ( G ) , H R 2 ( G ) of the nanostructure silicon carbide Si 2 C 3 - III [ n , m ] .

2 Materials and methods

In Figure 1, the structure of silicon carbide Si 2 C 3 - III [ n , m ] is presented, where silicon (Si) and carbon (C) are shown by blue and brown colors, respectively. By graphical visualization of silicon carbide, we fix some notations, that is, here n represents the number of connected unit cells in a row and m show the number of connected rows each with n number of cell. Figure 2 demonstrates the connections of cell in a row and connection of row with another row. In Figure 2(a), we have one row with n = 5 and m = 1 and red edges show the connection between the unit cell in a row. In Figure 2(b), we presented Si 2 C 3 -III[5,2], green edges show the connection of the upper and lower rows. Hence, the number of vertices Si 2 C 3 - III [ n , m ] is 10 m n and the number of edges are 15 m n 2 n 3 m . For further details of silicon carbide, we refer [17,21,22,23].

Figure 1 
               (a) Unit cell of 
                     
                        
                        
                           
                              
                                 Si
                              
                              
                                 2
                              
                           
                           
                              
                                 C
                              
                              
                                 3
                              
                           
                        
                        {{\rm{Si}}}_{2}{{\rm{C}}}_{3}
                     
                  -
                     
                        
                        
                           III
                           
                              [
                              
                                 n
                                 ,
                                 m
                              
                              ]
                           
                        
                        {\rm{III}}\left[n,m]
                     
                  , (b) 
                     
                        
                        
                           
                              
                                 Si
                              
                              
                                 2
                              
                           
                           
                              
                                 C
                              
                              
                                 3
                              
                           
                        
                        {{\rm{Si}}}_{2}{{\rm{C}}}_{3}
                     
                  -III[5,4].
Figure 1

(a) Unit cell of Si 2 C 3 - III [ n , m ] , (b) Si 2 C 3 -III[5,4].

Figure 2 
               (a) 2D structure of 
                     
                        
                        
                           
                              
                                 Si
                              
                              
                                 2
                              
                           
                           
                              
                                 C
                              
                              
                                 3
                              
                           
                        
                        {{\rm{Si}}}_{2}{{\rm{C}}}_{3}
                     
                  -III[5,1], (b) 2D structure of 
                     
                        
                        
                           
                              
                                 Si
                              
                              
                                 2
                              
                           
                           
                              
                                 C
                              
                              
                                 3
                              
                           
                        
                        {{\rm{Si}}}_{2}{{\rm{C}}}_{3}
                     
                  -III[5,2].
Figure 2

(a) 2D structure of Si 2 C 3 -III[5,1], (b) 2D structure of Si 2 C 3 -III[5,2].

To compute the topological indices, we defined the partitions of vertices and edges of Si 2 C 3 - III [ n , m ] . In Si 2 C 3 - III [ n , m ] , for n , m 1 , we partitioned the vertex set V ( G ) into three subsets depending upon the degrees of vertices. Let V 1 = { v V ( G ) d ( v ) = 1 } and it has only two elements, and V 2 = { v V ( G ) d ( v ) = 2 } and it has 4 n + 3 m 1 elements. Similarly, the set V 3 = { v V ( G ) d ( v ) = 3 } and it has 10 m n 4 n 3 m 1 elements. In a similar way, according to the degrees of the end vertices of the elements of E ( G ) , the set E ( G ) of Si 2 C 3 - III [ n , m ] may also be partitioned into its four subsets E 1 , E 2 , E 3 , and E 4 . Let u v E 1 , if d ( u ) = 1 , d ( v ) = 3 , then E 1 contains 2 edges. If u v E 2 , then d ( u ) = 2 and d ( v ) = 2 , then by simple counting, we observe that E 2 contains 2 m + 2 edges. The set E 3 contains 8 n + 8 m 12 edges u v , where d ( u ) = 2 and d ( v ) = 3 . The set E 4 contains 15 m n 10 n 13 m + 8 edges u v , where d ( u ) = d ( v ) = 3 . Table 1 gives the details of partition of edges of Si 2 C 3 - III [ n , m ] for m , n 1 depending upon degrees.

Table 1

Degree-based partition of edges of Si 2 C 3 - III [ n , m ]

( d ( u ) , d ( v ) ) Number of edges d ( e )
(1, 3) 2 2
(2, 2) 2 m + 2 2
(2, 3) 8 n + 8 m 12 3
(3, 3) 15 m n 10 n 13 m + 8 4

To establish our results, we adopt an approach for combinatorial enrolling, an edge allocate, a vertex portion strategy, enlist hypothetical instruments, and degree counting procedure for vertices and edges. Moreover, we use Matlab and Maple for the estimations, attestation and plotting the obtained results. For further details, see refs. [8,24,25, 26,27].

3 Main results

In this section, we computed the formulas for the first and second K-Banhatti, modified K-Banhatti, K-hyper Banhatti, and hyper Revan indices of silicon carbide Si 2 C 3 - III [ n , m ] .

Theorem 1

Let G Si 2 C 3 - III [ n , m ] be the graph of silicon carbide. Then,

B 1 [ G ] = 210 m n 52 n 78 m + 12 , B 2 [ G ] = 360 m n 120 n 176 m + 44 .

Proof

Let G Si 2 C 3 - III [ n , m ] be the graph of silicon carbide. The edge partition of Si 2 C 3 - III [ n , m ] based on degrees of edges is given in Table 1. Then by using Table 1 the first K-Banhatti index of G is calculated as

B 1 [ G ] = u e [ d ( u ) + d ( e ) ] = u v = e [ d ( u ) + d ( e ) + d ( v ) + d ( e ) ] = 2 [ ( 1 + 2 ) + ( 3 + 2 ) ] + ( 2 m + 2 ) [ ( 2 + 2 ) + ( 2 + 2 ) ] + ( 8 n + 8 m 12 ) [ ( 2 + 3 ) + ( 3 + 3 ) ] + ( 15 m n 10 n 13 m + 8 ) [ ( 3 + 4 ) + ( 3 + 4 ) ] = 210 m n 52 n 78 m + 12 .

Second K-Banhatti index of G is calculated as

B 2 [ G ] = u e [ d ( u ) d ( v ) ] = u v = e [ d ( u ) × d ( e ) + d ( v ) × d ( e ) ] = 2 [ ( 1 × 2 ) + ( 3 × 2 ) ] + ( 2 m + 2 ) [ ( 2 × 2 ) + ( 2 × 2 ) ] + ( 8 n + 8 m 12 ) [ ( 2 × 3 ) + ( 3 × 3 ) ] + ( 15 m n 10 n 13 m + 8 ) [ ( 3 × 4 ) + ( 3 × 4 ) ] = 360 m n 120 n 176 m + 44 .

Theorem 2

Let G Si 2 C 3 - III [ n , m ] be the graph of silicon carbide. Then,

B 1 m [ G ] = 30 7 m n 8 105 n 23 105 m 1 21 , B 2 m [ G ] = 5 2 m n 5 9 n 19 18 m 1 3 .

Proof

Let G Si 2 C 3 - III [ n , m ] be the graph of silicon carbide. Then, by definition of B 1 m [ G ] , we have

B 1 m [ G ] = u e 1 d ( u ) + d ( e ) = u v = e 1 d ( u ) + d ( e ) + 1 d ( v ) + d ( e ) = 2 1 3 + 1 5 + ( 2 m + 2 ) 1 4 + 1 4 + ( 8 n + 8 m 12 ) 1 5 + 1 6 + ( 15 m n 10 n 13 m + 8 ) 1 7 + 1 7 = 30 7 m n 8 105 n 23 105 m 1 21 .

Moreover, from the definition B 2 m [ G ] , we have

B 2 m [ G ] = u e 1 d ( u ) × d ( e ) = u v = e 1 d ( u ) × d ( e ) + 1 d ( v ) × d ( e ) = 2 1 2 + 1 6 + ( 2 m + 2 ) 1 4 + 1 4 + ( 8 n + 8 m 12 ) 1 6 + 1 9 + ( 15 m n 10 n 13 m + 8 ) 1 12 + 1 12 = 5 2 m n 5 9 n 19 18 m 1 3 .

Theorem 3

Let G Si 2 C 3 - III [ n , m ] be the graph of silicon carbide. Then,

H B 1 [ G ] = 1470 m n 492 n 722 m + 184 , H B 2 [ G ] = 4320 m n 1944 n 2744 m + 1044 .

Proof

Let G Si 2 C 3 - III [ n , m ] be the graph of silicon carbide. Then, the first K-hyper Banhatti index of G is calculated as

H B 1 [ G ] = u e [ d ( u ) + d ( e ) ] 2 = u v = e E [ ( d ( u ) + d ( e ) ) 2 + ( d ( v ) + d ( e ) ) 2 ] = 2 [ ( 1 + 2 ) 2 + ( 3 + 2 ) 2 ] + ( 2 m + 2 ) [ ( 2 + 2 ) 2 + ( 2 + 2 ) 2 ] + ( 8 n + 8 m 12 ) [ ( 2 + 3 ) 2 + ( 3 + 3 ) 2 ] + ( 15 m n 10 n 13 m + 8 ) [ ( 3 + 4 ) 2 + ( 3 + 4 ) 2 ] = 1470 m n 492 n 722 m + 184 .

Second K-hyper Banhatti index of G is calculated as

H B 2 [ G ] = u e [ d ( u ) d ( v ) ] 2 = u v = e E [ ( d ( u ) × d ( e ) ) 2 + ( d ( v ) × d ( e ) ) 2 ] = 2 [ ( 1 × 3 ) 2 + ( 3 × 2 ) 2 ] + ( 2 m + 2 ) [ ( 2 × 2 ) 2 + ( 2 × 2 ) 2 ] + ( 8 n + 8 m 12 ) [ ( 2 × 3 ) 2 + ( 3 × 3 ) 2 ] + ( 15 m n 10 n 13 m + 8 ) [ ( 3 × 4 ) 2 + ( 3 × 4 ) 2 ] = 4320 m n 1944 n 2744 m + 1044 .

Table 2 shows partition of edges of Si 2 C 3 - III [ n , m ] for m , n 1 based on degrees along with r G ( u ) and r G ( v ) .

Table 2

Edge partition of Si 2 C 3 - III [ n , m ] silicon carbide

( d ( u ) , d ( v ) ) Number of edges r G ( u ) r G ( v )
( 1 , 3 ) 2 3 1
( 2 , 2 ) 2 m + 2 2 2
( 2 , 3 ) 8 n + 8 m 12 2 1
( 3 , 3 ) 15 m n 10 n 13 m + 8 1 1

Theorem 4

Let G Si 2 C 3 - III [ n , m ] be the graph of silicon carbide. Then,

H R 1 [ G ] = 60 m n + 32 n + 52 m 12 , H R 2 [ G ] = 60 m n 8 n + 12 m + 34 .

Proof

Let G Si 2 C 3 - III [ n , m ] be the graph of silicon carbide. Then, by definition of H R 1 [ G ] , we have

H R 1 [ G ] = u v E [ r G ( u ) + r G ( v ) ] 2 = 2 [ 3 + 1 ] 2 + ( 2 m + 2 ) [ 2 + 2 ] 2 + ( 8 n + 8 m 12 ) [ 2 + 1 ] 2 + ( 15 m n 10 n 13 m + 8 ) [ 1 + 1 ] 2 = 60 m n + 32 n + 52 m 12 .

Moreover, from the definition of H R 2 [ G ] , we have

H R 2 [ G ] = u v E [ r G ( u ) r G ( v ) ] 2 = 2 [ 3 × 1 ] 2 + ( 2 m + 2 ) [ 2 × 2 ] 2 + ( 8 n + 8 m 12 ) [ 2 × 1 ] 2 + ( 15 m n 10 n 13 m + 8 ) [ 1 × 1 ] 2 = 60 m n 8 n + 12 m + 34 .

4 Graphical analysis

In Figure 3, K-Banhatti B 1 index is represented by blue color and K-Banhatti B 2 index is represented by cyan color. From this graph, we observe that number of unit cells in K-Banhatti B 2 index is greater than K-Banhatti B 1 index.

Figure 3 
               Comparison of K-Banhatti 
                     
                        
                        
                           
                              
                                 B
                              
                              
                                 1
                              
                           
                        
                        {B}_{1}
                     
                   and K-Banhatti 
                     
                        
                        
                           
                              
                                 B
                              
                              
                                 2
                              
                           
                        
                        {B}_{2}
                     
                   indices.
Figure 3

Comparison of K-Banhatti B 1 and K-Banhatti B 2 indices.

In Figure 4, modified K-Banhatti B 1 m index is represented by green color and modified K-Banhatti B 2 m index is represented by yellow color. From this graph, we observe that number of unit cells in modified K-Banhatti B 1 m index is greater than modified K-Banhatti B 2 m index.

Figure 4 
               Comparison of modified K-Banhatti 
                     
                        
                        
                           
                              
                                 B
                              
                              
                                 1
                              
                              
                              
                              
                              
                                 m
                              
                           
                        
                        {}^{m}B_{1}
                     
                   and modified K-Banhatti 
                     
                        
                        
                           
                              
                                 B
                              
                              
                                 2
                              
                              
                              
                              
                              
                                 m
                              
                           
                        
                        {}^{m}B_{2}
                     
                   indices.
Figure 4

Comparison of modified K-Banhatti B 1 m and modified K-Banhatti B 2 m indices.

In Figure 5, K-hyper Banhatti H B 1 index is represented by purple color and K-hyper Banhatti H B 2 index is represented by red color. From this graph, we observe that number of unit cells in K-hyper Banhatti H B 2 index is greater than K-hyper Banhatti H B 1 index.

Figure 5 
               Comparison of K-hyper Banhatti 
                     
                        
                        
                           H
                           
                              
                                 B
                              
                              
                                 1
                              
                           
                        
                        H{B}_{1}
                     
                   and K-hyper Banhatti 
                     
                        
                        
                           H
                           
                              
                                 B
                              
                              
                                 2
                              
                           
                        
                        H{B}_{2}
                     
                   indices.
Figure 5

Comparison of K-hyper Banhatti H B 1 and K-hyper Banhatti H B 2 indices.

Figure 6 represents K-Banhatti B 1 , modified K-Banhatti B 1 m , and K-hyper Banhatti H B 1 indices, and Figure 7 represents K-Banhatti B 2 , modified K-Banhatti B 2 m , and K-hyper Banhatti H B 2 indices.

Figure 6 
               Comparison of first K-Banhatties indices.
Figure 6

Comparison of first K-Banhatties indices.

Figure 7 
               Comparison of second K-Banhatties indices.
Figure 7

Comparison of second K-Banhatties indices.

5 Discussion

In reticular chemistry, it is very difficult to investigate the physico-chemical properties and characterization of large chemical structures. However, topological indices are very useful in order to study such properties of large networks. The structural characteristics of the molecules are numerically represented by using the topological indices which may be obtained by applying the theoretical concept on these large networks. In this article, we gave precise formulas of some well-known topological indices for silicon carbide. In Figures 35, we have compared K-Banhatti B 1 and K-Banhatti B 2 indices, modified first K-Banhatti B 1 m and modified second K-Banhatti B 2 m indices, and first K-hyper Banhatti H B 1 and second K-hyper Banhatti H B 2 indices, graphically. Similarly, Figure 6(a) represents a comparison of K-Banhatti B 1 , modified K-Banhatti B 1 m and K-hyper Banhatti H B 1 indices, and Figure 6(b) represents a comparison of K-Banhatti B 2 , modified K-Banhatti B 2 m and K-hyper Banhatti H B 2 indices. Therefore, these results show that the number of unit cells in modified K-Banhatti B 1 m index and modified K-Banhatti B 2 m index is smaller than among all the above indices.

6 Conclusion and future work

Topological indices are helpful in predicting seeveral physico-chemical properties of the chemical compound. The applications of silicon carbide Si 2 C 3 - III [ n , m ] have a vital role in chemistry, especially it helps in assembly procedures and host–guest reaction. Moreover, silicon carbide is also used in bullet proof vests, car clutches, car breaks, LED lights, and detectors. We have computed topological indices, namely first and second K-Banhatti, modified K-Banhatti, K-hyper Banhatti, Revan, and hyper Revan indices of silicon carbide Si 2 C 3 - III [ n , m ] . These formulas may help to correlate the silicon carbide Si 2 C 3 - III [ n , m ] structure with chemical engineering. This work motivates to explore much more about silicon carbide and raise many questions in the minds of relevant researchers, which may lead to new know more facts about it. Furthermore, the topological indices considered in this article can be computed for crystal cubic carbon structure, benzenoid systems, or some other chemical structures.

Acknowledgment

The authors are thankful to the anonymous reviewers for their valuable comments, remarks, and suggestions to improve the quality of the paper.

  1. Funding information: This research was conducted for the fulfillment of job requirement, no external funding was available for this research.

  2. Author contributions: D.Z. – writing, review & editing; M.A.Z. – validation; R.I. – conceptualization, supervision; M.A. – writing, original draft, validation; A.F. – formal analysis, resources; Z.A. – methodology; L.L. – writing, review & editing.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Ethical approval: The conducted research is not related to either human or animal use.

  5. Data availability statement: Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Received: 2018-10-19
Revised: 2020-04-28
Accepted: 2020-06-19
Published Online: 2021-06-04

© 2021 Dongming Zhao et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  14. Evaluation of the performance of immunoblot and immunodot techniques used to identify autoantibodies in patients with autoimmune diseases
  15. Computational studies by molecular docking of some antiviral drugs with COVID-19 receptors are an approach to medication for COVID-19
  16. Synthesis of amides and esters containing furan rings under microwave-assisted conditions
  17. Simultaneous removal efficiency of H2S and CO2 by high-gravity rotating packed bed: Experiments and simulation
  18. Design, synthesis, and biological activities of novel thiophene, pyrimidine, pyrazole, pyridine, coumarin and isoxazole: Dydrogesterone derivatives as antitumor agents
  19. Content and composition analysis of polysaccharides from Blaps rynchopetera and its macrophage phagocytic activity
  20. A new series of 2,4-thiazolidinediones endowed with potent aldose reductase inhibitory activity
  21. Assessing encapsulation of curcumin in cocoliposome: In vitro study
  22. Rare norisodinosterol derivatives from Xenia umbellata: Isolation and anti-proliferative activity
  23. Comparative study of antioxidant and anticancer activities and HPTLC quantification of rutin in white radish (Raphanus sativus L.) leaves and root extracts grown in Saudi Arabia
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  25. Sodium borohydride (NaBH4) as a high-capacity material for next-generation sodium-ion capacitors
  26. Aroma components of tobacco powder from different producing areas based on gas chromatography ion mobility spectrometry
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  28. Synthesis, properties, and activity of MoVTeNbO catalysts modified by zirconia-pillared clays in oxidative dehydrogenation of ethane
  29. Synthesis and crystal structure of N,N′-bis(4-chlorophenyl)thiourea N,N-dimethylformamide
  30. Quantitative analysis of volatile compounds of four Chinese traditional liquors by SPME-GC-MS and determination of total phenolic contents and antioxidant activities
  31. A novel separation method of the valuable components for activated clay production wastewater
  32. On ve-degree- and ev-degree-based topological properties of crystallographic structure of cuprite Cu2O
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  35. A nitric oxide-releasing prodrug promotes apoptosis in human renal carcinoma cells: Involvement of reactive oxygen species
  36. Machine vision-based driving and feedback scheme for digital microfluidics system
  37. Study on the application of a steam-foam drive profile modification technology for heavy oil reservoir development
  38. Ni–Ru-containing mixed oxide-based composites as precursors for ethanol steam reforming catalysts: Effect of the synthesis methods on the structural and catalytic properties
  39. Preparation of composite soybean straw-based materials by LDHs modifying as a solid sorbent for removal of Pb(ii) from water samples
  40. Synthesis and spectral characterizations of vanadyl(ii) and chromium(iii) mixed ligand complexes containing metformin drug and glycine amino acid
  41. In vitro evaluation of lactic acid bacteria with probiotic activity isolated from local pickled leaf mustard from Wuwei in Anhui as substitutes for chemical synthetic additives
  42. Utilization and simulation of innovative new binuclear Co(ii), Ni(ii), Cu(ii), and Zn(ii) diimine Schiff base complexes in sterilization and coronavirus resistance (Covid-19)
  43. Phosphorylation of Pit-1 by cyclin-dependent kinase 5 at serine 126 is associated with cell proliferation and poor prognosis in prolactinomas
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  45. Optimization of Murrayafoline A ethanol extraction process from the roots of Glycosmis stenocarpa, and evaluation of its Tumorigenesis inhibition activity on Hep-G2 cells
  46. Highly sensitive determination of α-lipoic acid in pharmaceuticals on a boron-doped diamond electrode
  47. Synthesis, chemo-informatics, and anticancer evaluation of fluorophenyl-isoxazole derivatives
  48. In vitro and in vivo investigation of polypharmacology of propolis extract as anticancer, antibacterial, anti-inflammatory, and chemical properties
  49. Topological indices of bipolar fuzzy incidence graph
  50. Preparation of Fe3O4@SiO2–ZnO catalyst and its catalytic synthesis of rosin glycol ester
  51. Construction of a new luminescent Cd(ii) compound for the detection of Fe3+ and treatment of Hepatitis B
  52. Investigation of bovine serum albumin aggregation upon exposure to silver(i) and copper(ii) metal ions using Zetasizer
  53. Discoloration of methylene blue at neutral pH by heterogeneous photo-Fenton-like reactions using crystalline and amorphous iron oxides
  54. Optimized extraction of polyphenols from leaves of Rosemary (Rosmarinus officinalis L.) grown in Lam Dong province, Vietnam, and evaluation of their antioxidant capacity
  55. Synthesis of novel thiourea-/urea-benzimidazole derivatives as anticancer agents
  56. Potency and selectivity indices of Myristica fragrans Houtt. mace chloroform extract against non-clinical and clinical human pathogens
  57. Simple modifications of nicotinic, isonicotinic, and 2,6-dichloroisonicotinic acids toward new weapons against plant diseases
  58. Synthesis, optical and structural characterisation of ZnS nanoparticles derived from Zn(ii) dithiocarbamate complexes
  59. Presence of short and cyclic peptides in Acacia and Ziziphus honeys may potentiate their medicinal values
  60. The role of vitamin D deficiency and elevated inflammatory biomarkers as risk factors for the progression of diabetic nephropathy in patients with type 2 diabetes mellitus
  61. Quantitative structure–activity relationship study on prolonged anticonvulsant activity of terpene derivatives in pentylenetetrazole test
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  63. Cannabis sativa L. chemical compositions as potential plasmodium falciparum dihydrofolate reductase-thymidinesynthase enzyme inhibitors: An in silico study for drug development
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  65. Identification of synthetic cannabinoid methyl 2-{[1-(cyclohexylmethyl)-1H-indol-3-yl] formamido}-3-methylbutanoate using modern mass spectrometry and nuclear magnetic resonance techniques
  66. Study on the speciation of arsenic in the genuine medicinal material honeysuckle
  67. Two Cu(ii)-based coordination polymers: Crystal structures and treatment activity on periodontitis
  68. Conversion of furfuryl alcohol to ethyl levulinate in the presence of mesoporous aluminosilicate catalyst
  69. Review Articles
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  73. Mechanism underlying sevoflurane-induced protection in cerebral ischemia–reperfusion injury
  74. COVID-19 and SARS-CoV-2: Everything we know so far – A comprehensive review
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  76. Advances in the design and application of transition metal oxide-based supercapacitors
  77. Color and composition of beauty products formulated with lemongrass essential oil: Cosmetics formulation with lemongrass essential oil
  78. The structural chemistry of zinc(ii) and nickel(ii) dithiocarbamate complexes
  79. Bioprospecting for antituberculosis natural products – A review
  80. Recent progress in direct urea fuel cell
  81. Rapid Communications
  82. A comparative morphological study of titanium dioxide surface layer dental implants
  83. Changes in the antioxidative properties of honeys during their fermentation
  84. Erratum
  85. Erratum to “Corrosion study of copper in aqueous sulfuric acid solution in the presence of (2E,5E)-2,5-dibenzylidenecyclopentanone and (2E,5E)-bis[(4-dimethylamino)benzylidene]cyclopentanone: Experimental and theoretical study”
  86. Erratum to “Modified TDAE petroleum plasticiser”
  87. Corrigendum
  88. Corrigendum to “A nitric oxide-releasing prodrug promotes apoptosis in human renal carcinoma cells: Involvement of reactive oxygen species”
  89. Special Issue on 3rd IC3PE 2020
  90. Visible light-responsive photocatalyst of SnO2/rGO prepared using Pometia pinnata leaf extract
  91. Antihyperglycemic activity of Centella asiatica (L.) Urb. leaf ethanol extract SNEDDS in zebrafish (Danio rerio)
  92. Selection of oil extraction process from Chlorella species of microalgae by using multi-criteria decision analysis technique for biodiesel production
  93. Special Issue on the 14th Joint Conference of Chemistry (14JCC)
  94. Synthesis and in vitro cytotoxicity evaluation of isatin-pyrrole derivatives against HepG2 cell line
  95. CO2 gas separation using mixed matrix membranes based on polyethersulfone/MIL-100(Al)
  96. Effect of synthesis and activation methods on the character of CoMo/ultrastable Y-zeolite catalysts
  97. Special Issue on Electrochemical Amplified Sensors
  98. Enhancement of graphene oxide through β-cyclodextrin composite to sensitive analysis of an antidepressant: Sulpiride
  99. Investigation of the spectroelectrochemical behavior of quercetin isolated from Zanthoxylum bungeanum
  100. An electrochemical sensor for high sensitive determination of lysozyme based on the aptamer competition approach
  101. An improved non-enzymatic electrochemical sensor amplified with CuO nanostructures for sensitive determination of uric acid
  102. Special Issue on Applied Biochemistry and Biotechnology 2020
  103. Fast discrimination of avocado oil for different extracted methods using headspace-gas chromatography-ion mobility spectroscopy with PCA based on volatile organic compounds
  104. Effect of alkali bases on the synthesis of ZnO quantum dots
  105. Quality evaluation of Cabernet Sauvignon wines in different vintages by 1H nuclear magnetic resonance-based metabolomics
  106. Special Issue on the Joint Science Congress of Materials and Polymers (ISCMP 2019)
  107. Diatomaceous Earth: Characterization, thermal modification, and application
  108. Electrochemical determination of atenolol and propranolol using a carbon paste sensor modified with natural ilmenite
  109. Special Issue on the Conference of Energy, Fuels, Environment 2020
  110. Assessment of the mercury contamination of landfilled and recovered foundry waste – a case study
  111. Primary energy consumption in selected EU Countries compared to global trends
  112. Modified TDAE petroleum plasticiser
  113. Use of glycerol waste in lactic acid bacteria metabolism for the production of lactic acid: State of the art in Poland
  114. Topical Issue on Applications of Mathematics in Chemistry
  115. Theoretical study of energy, inertia and nullity of phenylene and anthracene
  116. Banhatti, revan and hyper-indices of silicon carbide Si2C3-III[n,m]
  117. Topical Issue on Agriculture
  118. Occurrence of mycotoxins in selected agricultural and commercial products available in eastern Poland
  119. Special Issue on Ethnobotanical, Phytochemical and Biological Investigation of Medicinal Plants
  120. Acute and repeated dose 60-day oral toxicity assessment of chemically characterized Berberis hispanica Boiss. and Reut in Wistar rats
  121. Phytochemical profile, in vitro antioxidant, and anti-protein denaturation activities of Curcuma longa L. rhizome and leaves
  122. Antiplasmodial potential of Eucalyptus obliqua leaf methanolic extract against Plasmodium vivax: An in vitro study
  123. Prunus padus L. bark as a functional promoting component in functional herbal infusions – cyclooxygenase-2 inhibitory, antioxidant, and antimicrobial effects
  124. Molecular and docking studies of tetramethoxy hydroxyflavone compound from Artemisia absinthium against carcinogens found in cigarette smoke
  125. Special Issue on the Joint Science Congress of Materials and Polymers (ISCMP 2020)
  126. Preparation of cypress (Cupressus sempervirens L.) essential oil loaded poly(lactic acid) nanofibers
  127. Influence of mica mineral on flame retardancy and mechanical properties of intumescent flame retardant polypropylene composites
  128. Production and characterization of thermoplastic elastomer foams based on the styrene–ethylene–butylene–styrene (SEBS) rubber and thermoplastic material
  129. Special Issue on Applied Chemistry in Agriculture and Food Science
  130. Impact of essential oils on the development of pathogens of the Fusarium genus and germination parameters of selected crops
  131. Yield, volume, quality, and reduction of biotic stress influenced by titanium application in oilseed rape, winter wheat, and maize cultivations
  132. Influence of potato variety on polyphenol profile composition and glycoalcaloid contents of potato juice
  133. Carryover effect of direct-fed microbial supplementation and early weaning on the growth performance and carcass characteristics of growing Najdi lambs
  134. Special Issue on Applied Biochemistry and Biotechnology (ABB 2021)
  135. The electrochemical redox mechanism and antioxidant activity of polyphenolic compounds based on inlaid multi-walled carbon nanotubes-modified graphite electrode
  136. Study of an adsorption method for trace mercury based on Bacillus subtilis
  137. Special Issue on The 1st Malaysia International Conference on Nanotechnology & Catalysis (MICNC2021)
  138. Mitigating membrane biofouling in biofuel cell system – A review
  139. Mechanical properties of polymeric biomaterials: Modified ePTFE using gamma irradiation
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