On statistical evaluation of reverse degree based topological indices for iron telluride networks.

In the context of graph theory and chemical graph theory, this research conducts a detailed mathematical investigation of reverse topological indices as they relate to iron telluride networks, clarifying their complex interactions. Graph theory is a branch of abstract mathematics that carefully studies the connections and structural features of graphs made up of edges and vertices. These theoretical ideas are expanded upon in chemical graph theory, which models molecular architectures with atoms acting as vertices and chemical bonds as edges. By extending these concepts, this work investigates the reverse topological indices in the context of Iron Telluride networks and outlines their significant effects on chemical reactivity, molecular topology and statistical modeling. By navigating intricate mathematical formalisms and algorithmic approaches, the analysis provides profound insights into the reactivity patterns and structural dynamics of Iron Telluride compounds, enhancing our knowledge of solid-state chemistry and materials science.

On analysis of silicon dioxide based on topological indices and entropy measure via regression model.

The construction sector accounts for around 95% of the commercial usage of silicon dioxide (sand), for example, in the making of concrete. There are several uses for quartz, however in order to get a purer material, chemical processing is needed. Graph theory proved to be very beneficial for other research, especially in the applied sciences. In particular, graph theory has greatly influenced the field of chemistry. To do this, a transformation is needed to produce a graph with the vertices representing the atoms in the chemical compound and the edges indicating the bonds between the atoms. This graph then represents a chemical network or structure. In a graph, a vertex's valency (or degree) is determined by the number of edges that are incident to it. The entropy of a probability quantifies a system's level of uncertainty. In this article, we compute Zagreb-type indices and then compute the entropy measure. In order to evaluate the relevance of each kind, this article builds several edge degree-based entropies that link to the indices and establish how to adjust them. We also create the logarithmic regression model between indices and entropy.

On physical analysis of topological indices for iron disulfide network via curve fitting model.

In this study, we conduct a comprehensive physical analysis of topological indices for the Iron Disulfide (FeS 2 ) network using a curve-fitting model. Iron Disulfide is a cubic compound. In metamorphic rock, sedimentary rock, and quartz veins, it is typically found in combination with other sulfides or oxides. The numerical properties of molecular structures are referred to as topological indices. There are several different kinds of topological indices, including those that are based on distance, degree, or counting, among other factors. The real process of creating a topological index involves turning a chemical structure into a numerical value. In this paper, we calculate the iron disulfide network topological indices using the degrees of vertices in a chemical network of Iron Disulfide (FeS 2 ). Thereafter, we discovered the physical parameters of FeS 2 production, such as heat of formation. We then fitted curves between the thermodynamic properties and several indices. Several techniques based on rationality, linearity, and nonlinearity were used to fit curves in MATLAB. These quantitative results imply that a variety of thermodynamic characteristics of semiconducting materials may be accurately predicted by topological indices. These findings have significant ramifications as they provide the groundwork for the application of topological indices in semiconducting network design and optimization, which might result in more effective and economical material creation.

On physical analysis of phthalocyanine iron (II) using topological descriptor and curve fitting models.

A new area of applied chemistry called chemical graph theory uses combinatorial techniques to explain the complex interactions between atoms and bonds in chemical systems. This work investigates the use of edge partitions to decipher molecular connection patterns. The main goal is to use topological indices that capture important topological features to create a connection between the thermodynamic properties and structural characteristics of chemical molecules. We specifically examine the complex web of atoms and links that make up the Fe phthalocyanine chemical graph. Moreover, our study demonstrates a relationship between the calculated topological indices and the thermodynamic properties of Fe phthalocyanine (Phthalocyanine Iron (II)). This work offers insight into the thermodynamic consequences of molecule structures. It advances the subject of chemical graph theory, providing a useful perspective for future applications in catalysis and materials science.

On curve fitting between topological indices and Gibb's energy for semiconducting carbon nitrides network.

Quantitative structure relationships linked to a chemical structure that shed light on its properties and chemical reactions are called topological indices. This structure is upset by the addition of silicon (Si) doping, which changes the electrical and optical characteristics. In this article, we examine the connection between a chemical structure's Gibbs energy (GE) and K-Banhatti indices. In this article, we compute the K-Banhatti indices and then show the correlation between the indices and Gibb's energy of the molecule using curve fitting. Through the curve fitting, we see that there is a strong correlation between indices and Gibb's energy of a molecule. We use the polynomial curve fitting approach to see the correlation between indices and Gibb's energy.

On analysis of topological indices and heat of formation for benzyl sulfamoyl network via curve fitting model.

The study explores the intricate relationship between topological indices and the heat of formation in the benzyl sulfamoyl network. Topological indices of benzyl sulfamoyl networks are studied and also emphasize their properties statistically. The benzyl sulfamoyl has unique properties due to its crystalline structure and it is used in the form of artificial substance. We analyze the distributions and correlations of the benzyl sulfamoyl network with others by using statistical methods and also build a computational analysis for topological indices. The findings show a strong association between the variables, indicating that topological indices may be used to accurately predict thermodynamic characteristics and improve the effectiveness of molecular modelling and simulation procedures.

On comparative analysis of a two dimensional star gold structure via regression models.

In this research, the star gold structure with beta graphene is thoroughly examined. We mainly focus on computing degree-based topological indices, which provide information about the network's connectivity and complexity as well as structural features. In addition, we compute an entropy measure to represent the uncertainty, information richness, and degree of unpredictability in the network. Furthermore, this study explores the relationships between topological descriptors and entropy using regression models that are logarithmic, linear, and quadratic. By merging these regression models, we uncover hidden patterns and understand the underlying ideas governing the network's behaviour. Our findings shed light on the connection between topological indices and entropy. This work improves our understanding of star gold structure dynamics and provides a visual framework for interpreting their behaviour.

Topological indices and patterns in iron telluride networks.

This paper explores the complex interplay between topological indices and structural patterns in networks of iron telluride (FeTe). We want to analyses and characterize the distinct topological features of (FeTe) by utilizing an extensive set of topological indices. We investigate the relationship that these indicators have with the network's physical characteristics by employing sophisticated statistical techniques and curve fitting models. Our results show important trends that contribute to our knowledge of the architecture of the (FeTe) network and shed light on its physiochemical properties. This study advances the area of material science by providing a solid foundation for using topological indices to predict and analyses the behavior of intricate network systems. More preciously, we study the topological indices of iron telluride networks, an artificial substance widely used with unique properties due to its crystal structure. We construct a series of topological indices for iron telluride networks with exact mathematical analysis and determine their distributions and correlations using statistical methods. Our results reveal significant patterns and trends in the network structure when the number of constituent atoms increases. These results shed new light on the fundamental factors that influence material behavior, thus offering a deeper understanding of the iron telluride network and may contribute to future research and engineering of these materials.

Unleashing the biomimetic targeting potential of platelet-derived nanocarriers on atherosclerosis.

Atherosclerosis, the primary mechanism underlying the development of many cardiovascular illnesses, continues to be one of the leading causes of mortality worldwide. Platelet (PLT), which are essential for maintaining body homeostasis, have been strongly linked to the onset of atherosclerosis at various stages due to their inherent tendency to bind to atherosclerotic lesions and show an affinity for plaques. Therefore, mimicking PLT's innate adhesive features may be necessary to effectively target plaques. PLT-derived nanocarriers have emerged as a promising biomimetic targeting strategy for treating atherosclerosis due to their numerous advantages. These advantages include excellent biocompatibility, minimal macrophage phagocytosis, prolonged circulation time, targeting capability for impaired vascular sites, and suitability as carriers for anti-atherosclerotic drugs. Herein, we discuss the role of PLT in atherogenesis and propose the design of nanocarriers based on PLT-membrane coating and PLT-derived vesicles. These nanocarriers can target multiple biological elements relevant to plaque development. The review also emphasizes the current challenges and future research directions for the effective utilization of PLT-derived nanocarriers in treating atherosclerosis.

On topological analysis of two-dimensional covalent organic frameworks via M-polynomial.

Covalent organic frameworks (ZnP-COFs) made of zinc-porphyrin have become effective materials with a variety of uses, including gas storage and catalysis. To simulate the structural and electrical features of ZnP-COFs, this study goes into the computation of polynomials utilizing degree-based indices. We gave a methodical study of these polynomial computations using Excel, illustrating the complex interrelationships between the various indices. Degree-based indices provide valuable insights into the connectivity of vertices within a network. M-polynomials, on the other hand, offer a mathematical framework for representing and studying the properties of 2D COFs. By encoding structural information into a polynomial form, M-polynomials facilitate the calculation of various topological indices, including the Wiener index, Zagreb indices, and more. The different behavior of ZnP-COFs based on degree-based indices was illustrated graphically, and this comparison provided insightful information for prospective applications and the construction of innovative ZnP-COF structures. Moreover, we discuss the relevance of these techniques in the broader context of materials science and the design of functional covalent organic frameworks.

pH-sensitive docetaxel-loaded chitosan/thiolated hyaluronic acid polymeric nanoparticles for colorectal cancer.

Aim: This study aimed to develop and evaluate pH-sensitive docetaxel-loaded thiolated hyaluronic acid (HA-SH) nanoparticles (NPs) for targeted treatment of colon cancer. Materials & methods: HA-SH, synthesized via oxidation and subsequent covalent linkage to cysteamine, served as the precursor for developing HA-SH NPs through polyelectrolyte complexation involving chitosan and thiol-bearing HA. Results & conclusion: HA-SH NPs displayed favorable characteristics, with small particle sizes (184-270 nm), positive zeta potential (15.4-18.6 mV) and high entrapment efficiency (91.66-95.02%). In vitro, NPs demonstrated potent mucoadhesion and enhanced cytotoxicity compared with free docetaxel. In vivo assessments confirmed safety and biocompatibility, suggesting HA-SH NPs as promising pH-sensitive drug carriers with enhanced antitumor activity for colorectal cancer treatments.

On analysis of iron (II) chloride via graph entropy measures and statistical models.

The crystalline material that is greenish-white and dissolves in water is iron chloride. It is utilized in sewage treatment, dyeing, and medicine. Graph entropy plays a significant role in measuring the complexity of atoms, molecules, and structures in nature. It has specific chemical applications in biology, neuroscience, and chemistry. A compound's molecular structure consists of many atoms. Particularly, hydrocarbons are a chemical combination of hydrogen and carbon atoms. In this article, we discuss the entropy of the chemical structure Iron (II) Chloride. Additionally, we discuss the idea of degree-based indices and compute the Shannon entropy(ENT) using these indices. The linear regression(LR) of various indices and entropies for iron chloride, FeCl2, is also discussed. Also, we link the degree-based indices and entropies via line fit.

On K-Banhatti indices and entropy measure for rhodium (III) chloride via linear regression models.

Rhodium (III) chloride is a metallic compound characterized by its shiny and silvery-white appearance. It possesses high reflectivity and exhibits excellent resistance to corrosion. This makes it a popular choice for applications such as plating materials in jewelry and other decorative items, imparting a lustrous and reflective surface to the coated objects. Topological indices are numerical parameters employed to characterize the topology of a molecular structure. These indices are derived from the connectivity of atoms within the molecule and serve as predictors for various molecular properties, including reactivity, stability, and solubility. On the other hand, the Shannon entropy of a graph finds extensive applications in network science. It is utilized in the analysis of diverse networks, such as social networks, biological networks, and transportation networks. The Shannon entropy allows for the characterization of a network's topology and structure, aiding in the identification of crucial nodes or structures that play significant roles in network functionality and stability. In this paper, our primary objective is to compute different K-Banhatti indices and employ them to evaluate the entropy measure of Rhodium (III) chloride RhCl3. Additionally, we conducted an examination through linear regression analysis involving various indices and entropies associated with Rhodium chloride. Moreover, we established a correlation between degree-based Banhatti indices and entropies via the line fit method.

Computing the Entropy Measures for the Line Graphs of Some Chemical Networks.

Chemical Graph entropy plays a significant role to measure the complexity of chemical structures. It has explicit chemical uses in chemistry, biology, and information sciences. A molecular structure of a compound consists of many atoms. Especially, the hydrocarbons is a chemical compound that consists of carbon and hydrogen atoms. In this article, we discussed the concept of subdivision of chemical graphs and their corresponding line chemical graphs. More preciously, we discuss the properties of chemical graph entropies and then constructed the chemical structures namely triangular benzenoid, hexagonal parallelogram, and zigzag edge coronoid fused with starphene. Also, we estimated the degree-based entropies with the help of line graphs of the subdivision of above mentioned chemical graphs.

Natural polysaccharide-based biodegradable polymeric platforms for transdermal drug delivery system: a critical analysis.

Natural biodegradable polymers generally include polysaccharides (starch, alginate, chitin/chitosan, hyaluronic acid derivatives, etc.) and proteins (collagen, gelatin, fibrin, etc.). In transdermal drug delivery systems (TDDS), these polymers play a vital role in controlling the device's drug release. It is possible that natural polymers can be used for TDDS to attain predetermined drug delivery rates due to their physicochemical properties. These polymers can be employed to market products and scale production because they are readily available and inexpensive. As a result of these polymers, new pharmaceutical delivery systems can be developed that is both regulated and targeted. The focus of this article is the application of a biodegradable polymeric platform based on natural polymers for TDDS. Due to their biocompatibility and biodegradability, natural biodegradable polymers are frequently used in biomedical applications. Additionally, these natural biodegradable polymers are being studied for their characteristics and behaviors.

Computation and Analysis of Topological Co-Indices for Metal-Organic Compound.

A topological descriptor is a mathematical illustration of a molecular construction that relates particular physicochemical properties of primary molecular structure as well as its mathematical depiction. Topological co-indices are usually applied for quantitative structure action relationships (QSAR) and quantitative structure property relationships (QSPR). Topological co-indices are topological descriptor which consider the noncontiguous vertex set. In this study, we studyied some of the accompanied renowned topological co-indices: the 1st and 2nd Zagreb co-indices, the 1st and 2nd multiplicative Zagreb co-indices, and the F-coindex. By applying structure based examinations and deductions, we discuss the earlier stated co-indices of few synthetic atomic structures that are frequently used in clinical, synthetic, and material designing.