Preparation of ultra-sensitive and selective hydrogen peroxide-based colorimetric sensor using highly exfoliated g-C3N4 nanosheets with peroxidase-like activity.

A highly sensitive, portable, rapid, and accurate colorimetric sensing method is presented. It is based upon exfoliated g-C3N4 nanosheets (E-g-C3N4 NSs), having peroxidase nanozyme-like properties. The as-prepared catalyst (E-g-C3N4 NSs) tends to oxidize the colorless tetramethyl-benzidine (TMB) into oxidized-TMB in the presence of hydrogen peroxide (H2O2) generating a dark blue color and corresponding ultraviolet visible-spectral changes following a Michaelis-Menten kinetic. The prepared colorimetric sensor exhibited response within the range 0.001-0.450 µM having R2 value of 0.999 and a detective limit (LOD) of 0.15 ± 0.04 nM. Furthermore, the sensor also displayed outstanding selectivity, ample stability (10 weeks), and excellent practicability in real sample applications. All these outstanding properties were highly attributed to the large surface area with exposed actives sites, high surface energy, and large conductive structure of E-g-C3N4 NSs. For comparison of the catalytic study, we have also explored the sensing mechanism of B-g-C3N4, using the same optimized experimental conditions. Resultantly, we concluded that the proposed sensor (E-g-C3N4 NSs) will gain considerable attention for on-site environmental and health monitoring in future endeavor.

Deep convolutional neural network with sine cosine algorithm based wastewater treatment systems.

Wastewater treatment systems are essential in today's business to meet the ever-increasing requirements of environmental regulations while also limiting the environmental impact of the sector's discharges. A new control and management information system is needed to handle the residual fluids. This study advises that Wastewater Treatment System (WWTS) operators use intelligent technologies that analyze data and forecast the future behaviour of processes. This method incorporates industrial data into the wastewater treatment model. Deep Convolutional Neural Network (DCNN) and Since Cosine Algorithm (SCA), two powerful artificial neural networks, were used to predict these properties over time. Remediation actions can be taken to ensure procedures are carried out in accordance with the specifications. Water treatment facilities can benefit from this technology because of its sophisticated process that changes feature dynamically and inconsistently. The ultimate goal is to improve the precision with which wastewater treatment models create their predictions. Using DCNN and SCA techniques, the Chemical Oxygen Demand (COD) in wastewater treatment system input and effluent is estimated in this study. Finally, the DCNN-SCA model is applied for the optimization, and it assists in improving the predictive performance. The experimental validation of the DCNN-SCA model is tested and the outcomes are investigated under various prospects. The DCNN-SCA model has achieved a maximum accuracy performance and proving that it outperforms compare with the prevailing techniques over recent approaches. The DCNN-SCA-WWTS model has shown maximum performance Under 600 data, DCNN-SCA-WWTS has a precision of 97.63%, a recall of 96.37%, a F score of 95.31%, an accuracy of 96.27%, an RMSE of 27.55%, and a MAPE of 20.97%.

Comparative Study of Chemically Treated Sugarcane and Kevlar Fiber to Develop Brake Resistance Composites.

Recently, much research has revealed the increasing importance of natural fiber in modern applications. Natural fibers are used in many vital sectors like medicine, aerospace and agriculture. The cause of increasing the application of natural fiber in different fields is its eco-friendly behavior and excellent mechanical properties. The study's primary goal is to increase the usage of environmentally friendly materials. The existing materials used in brake pads are detrimental to humans and the environment. Natural fiber composites have recently been studied and effectively employed in brake pads. However, there has yet to be a comparison investigation of natural fiber and Kevlar-based brake pad composites. Sugarcane, a natural fabric, is employed in the present study to substitute trendy materials like Kevlar and asbestos. The brake pads have been developed with 5-20 wt.% SCF and 5-10 wt.% Kevlar fiber (KF) to make the comparative study. SCF compounds at 5 wt.% outperformed the entire NF composite in coefficient of friction (µ), (%) fade and wear. However, the values of mechanical properties were found to be almost identical. Although it has been observed that, with an increase in the proportion of SCF, the performance also increased in terms of recovery. The thermal stability and wear rate are maximum for 20 wt.% SCF and 10 wt.% KF composites. The comparative study indicated that the Kevlar-based brake pad specimens provide superior outcomes compared to the SCF composite for fade (%), wear performance and coefficient of friction (Δµ). Finally, the worn composite surfaces were examined using a scanning electron microscopy technique to investigate probable wear mechanisms and to comprehend the nature of the generated contact patches/plateaus, which is critical for determining the tribological behavior of the composites.

Optimization of water reuse and modelling by saline composition with nanoparticles based on machine learning architectures.

Water is a necessary resource that enables the existence of all life forms, including humans. Freshwater usage has become increasingly necessary in recent years. Facilities for treating seawater are less dependable and effective. Deep learning methods have the ability to improve salt particle analysis in saltwater's accuracy and efficiency, which will enhance the performance of water treatment plants. This research proposes a novel technique in optimization of water reuse with nanoparticle analysis based on machine learning architecture. Here, the optimization of water reuse is carried out based on nanoparticle solar cell for saline water treatment and the saline composition has been analyzed using a gradient discriminant random field. Experimental analysis is carried out in terms of specificity, computational cost, kappa coefficient, training accuracy, and mean average precision for various tunnelling electron microscope (TEM) image datasets. The bright-field TEM (BF-TEM) dataset attained a specificity of 75%, kappa coefficient of 44%, training accuracy of 81%, and mean average precision of 61%, whereas the annular dark-field scanning TEM (ADF-STEM) dataset produced specificity of 79%, kappa coefficient of 49%, training accuracy of 85%, and mean average precision of 66% as compared with the existing artificial neural network (ANN) approach.

Nanobioremediation: A sustainable approach towards the degradation of sodium dodecyl sulfate in the environment and simulated conditions.

Nanotechnology has gained huge importance in the field of environmental clean-up today. Due to their remarkable and unique properties, it has shown potential application for the remediation of several pesticides and textile dyes. Recently it has shown positive results for the remediation of sodium dodecyl sulfate (SDS). One of the highly exploited surfactants in detergent preparation is anionic surfactants. The SDS selected for the present study is an example of anionic linear alkyl sulfate. It is utilized extensively in industrial washing, which results in the high effluent level of this contaminant and ubiquitously toxic to the environment. The present review is based on the research depicting the adverse effects of SDS in general and possible strategies to minimizing its effects by bacterial degradation which are capable of exploiting the SDS as an only source of carbon. Moreover, it has also highlighted that how nanotechnology can play a role in the remediation of such recalcitrant pesticides.

Seaweed-Based Molecules and Their Potential Biological Activities: An Eco-Sustainable Cosmetics.

Amongst the countless marine organisms, seaweeds are considered as one of the richest sources of biologically active ingredients having powerful biological activities. Seaweeds or marine macroalgae are macroscopic multicellular eukaryotic photosynthetic organisms and have the potential to produce a large number of valuable compounds, such as proteins, carbohydrates, fatty acids, amino acids, phenolic compounds, pigments, etc. Since it is a prominent source of bioactive constituents, it finds diversified industrial applications viz food and dairy, pharmaceuticals, medicinal, cosmeceutical, nutraceutical, etc. Moreover, seaweed-based cosmetic products are risen up in their demands by the consumers, as they see them as a promising alternative to synthetic cosmetics. Normally it contains purified biologically active compounds or extracts with several compounds. Several seaweed ingredients that are useful in cosmeceuticals are known to be effective alternatives with significant benefits. Many seaweeds' species demonstrated skin beneficial activities, such as antioxidant, anti-melanogenesis, antiaging, photoprotection, anti-wrinkle, moisturizer, antioxidant, anti-inflammatory, anticancer and antioxidant properties, as well as certain antimicrobial activities, such as antibacterial, antifungal and antiviral activities. This review presents applications of bioactive molecules derived from marine algae as a potential substitute for its current applications in the cosmetic industry. The biological activities of carbohydrates, proteins, phenolic compounds and pigments are discussed as safe sources of ingredients for the consumer and cosmetic industry.

COVID-19 transmission, vulnerability, persistence and nanotherapy: a review.

End 2019, the zoonotic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), named COVID-19 for coronavirus disease 2019, is the third adaptation of a contagious virus following the severe acute respiratory syndrome coronavirus in 2002, SARS-CoV, and the Middle East respiratory syndrome virus in 2012, MERS-CoV. COVID-19 is highly infectious and virulent compared to previous outbreaks. We review sources, contagious routes, preventive measures, pandemic, outbreak, epidemiology of SARS-CoV, MERS-CoV and SARS-CoV-2 from 2002 to 2020 using a Medline search. We discuss the chronology of the three coronaviruses, the vulnerability of healthcare workers, coronaviruses on surface and in wastewater, diagnostics and cures, and measures to prevent spreading.

Revealing the Structural, Elastic, Electronic, and Optical Properties of K2ScCuCl6 and K2YCuCl6: An In-Depth Exploration Using Density Functional Theory.

The optoelectronic, structural, and elastic properties of K2ScCuCl6 and K2YCuCl6 double perovskite compounds were thoroughly investigated in this study using density functional theory. It is observed that both compounds exhibit exceptional structural and mechanical stability. The structural stability is assessed using Goldsmith's tolerance factor (tG), with values approaching unity indicating a reliable cubic perovskite structure. Phonon stability was ensured by the absence of negative energy formations and only real frequencies in the phonon calculations. Applying the finite displacement method also provided further evidence of the compounds' thermodynamic stability. The electronic properties analysis revealed that K2ScCuCl6 and K2YCuCl6 are narrow band gap semiconductors, with band gap values of 1.8 and 2.5 eV, respectively. This was confirmed by analyzing the density of states. Furthermore, the optical properties exhibited transparency at lower photon energies and significant absorption at higher energies. These exciting findings suggest that K2ScCuCl6 and K2YCuCl6 have promising applications in high-frequency UV devices.

Computational investigation on physical properties of lead based perovskite RPbBr3 (R = Cs, Hg, and Ga) materials for photovoltaic applications.

In the modern era, the major problem is solving energy production and consumption. For this purpose, perovskite materials meet these issues and fulfill energy production at a low cost. Density functional theory and the Cambridge Serial Total Energy Package (CASTEP) are used to examine the characteristics of the cubic inorganic perovskites RPbBr3 (R = Cs, Hg, and Ga). In the context of the generalized gradient approximation (GGA), the ultrasoft pseudo-potential plane wave technique and the Perdew-Burke-Ernzerhof exchange-correlation functional are used for investigations. Structural, mechanical, electronics, and optical properties are investigated using CASTEP code. According to structural properties, compounds have a cubic nature with space 221 (Pm3m). Compounds formation energy (- 3.46, - 2.21, and - 3.14 eV)of (CsPbBr3, HgPbBr3, and GaPbBr3) and phonon calculations are studied and find that compounds are stable. The results of our investigation show that the compounds have narrow bandgaps of direct kind, with 1.85 eV for CsPbBr3, 1.56 eV for HgPbBr3, and 1.71 eV for GaPbBr3, respectively, indicating that they may be used to improve conductivity. Additionally, anisotropy (2.135, 3.651, 10.602), Pugh's ratio (1.87, 2.25, 2.14), and Poison's ratio (0.27, 0.31, 0.29) are traits that the compounds (CsPbBr3, HgPbBr3, GaPbBr3) display a ductile nature. The CsPbBr3 compound showed significant optical conductivity and absorption in terms of their optical properties, especially in the visible region, which makes them suitable for use in solar cell applications as well as for LED applications.

Computational insights of double perovskite Na2CaCdH6 hydride alloy for hydrogen storage applications: a DFT investigation.

Prospective use of perovskite hydride materials in H storage a crucial element of clean energy systems has drawn a lot of attention. The structural, electrical, mechanical, thermodynamic, and H storage qualities of Na2CaCdH6 hydride alloys were examined in this work using DFT. According to the structural properties, Na2CaCdH6 has space group 225 (Fm3m), and optimized lattice parameters and volume of Na2CaCdH6 are 3.3485 Å and 593.764 Å3. The measured gravimetric H storage capacity of Na2CaCdH6 hydrides is 2.956 wt%. The hydrides under research are semiconductors, as indicated by the computed electronic characteristics. Elastic constants, Pugh's ratio, modulus, Poisson's ratio, anisotropic, and microhardness of Na2CaCdH6 are calculated under mechanical properties. The hydrides are dynamically stable, as indicated by the phonon dispersion curves, but mechanically stable according to the Born criterion for elastic constant (Cij). The Cauchy's pressure (C″ = 7.836) revealed the ductile behavior. The electronic and mechanical characteristics imply that Na2CaCdH6 hydride can conduct electricity and is also mechanically stable. Our findings shed light on the possibilities of Na2CaCdH6 perovskite hydride material for H storage utilization.

Tailoring of structural, morphological, electrical, and magnetic properties of LaMn1-x Fe x O3 ceramics.

This study undertakes a comparative analysis of the structural, morphological, electrical, and magnetic characteristics of Fe-doped LaMnO3 ceramics. The solid-state reaction method was used to prepare Fe-doped LaMnO3 at different concentrations (0.00 ≤ x ≤ 1.00) and has been characterized using X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR), Field emission scanning electron microscopy (FE-SEM), energy-dispersive spectroscopy (EDS), and vibrating sample magnetometry (VSM). The structural transformation from rhombohedral to orthorhombic with Fe-doping is demonstrated by Rietveld's refined XRD patterns. The positive slope in Williamsons-Hall's (W-H) plots confirms the presence of tensile strain with increasing average crystallite size. Quasi-spherical morphology of all the compositions with similar uniformity was confirmed by FESEM images. The chemical distribution of all the elements has been identified by EDS mapping images. Normal dielectric dispersion behaviour of all the samples with NTCR response is confirmed by dielectric and impedance analysis respectively. Increasing lattice volume with Fe-concentration results is increasing E a. The presence of antiferromagnetic ordering, in addition to weak ferromagnetic ordering, is indicated by the unsaturated magnetization even up to a high external field. The decrease in M S and increase in H C values due to Fe-doping reflect the influence of particle size on various magnetic parameters.

Structural, electronic and thermoelectric properties of boron phosphorous nitride B2PN via first principles study.

A theoretical study of monolayer boron phosphorous nitride (B2PN) is performed to explore its electronic and thermoelectric properties. The thermodynamic stability is determined by the formation energy of a monolayer. The dynamic stability is obtained from the phonon dispersion curve. We performed an AMID simulation to ensure the thermal stability and found that our material is thermally stable at 700 K. The system possesses direct band gaps of 0.25 eV and 0.4 eV with Perdew-Burke-Ernzerhof (PBE) and hybrid functional (HSE), respectively. The Seebeck coefficient is found to be the same in both directions, and the maximum value is 1.55 mV K-1. The relaxation time is found to be longer for the hole-doped system than the electron-doped system. It is observed that electrical conductivity is greater for hole-doped system in both directions, and a similar trend is observed for electronic thermal conductivity. We found that the lattice thermal conductivity of our systems is anisotropic. The lattice thermal conductivity along the Y-direction is greater than that in the X-direction. The calculation performed for the figure of merit (ZT) reveals that the system has a high ZT of 1.14 for a hole-doped system. The figure of merit makes the system a promising candidate for potential thermoelectric device applications.

Impact of samarium on magnetic and optoelectronic properties of magnesium-based MgSm2X4 (X = S and Se) spinels for spintronics.

Investigating novel compounds has become necessary due to the need for sophisticated materials in optoelectronic devices and spintronics. Because of their unique properties, magnesium-based spinels MgSm2X4 (X = S and Se) are very promising for these applications. We used the spin-polarized PBEsol for structural properties and the PBEsol functional for mechanical behavior, both using the WIEN2k code. Both compounds' stability in the magnetic and non-magnetic phases was validated by the Birch-Murnaghan equation of state, and their stability in the cubic phase was verified by the Born stability criterion. Their ductile character was shown by the computation of Pugh's ratio and Poisson ratio. Both MgSm2S4 and MgSm2Se4 display metallic behavior in the spin-up channel and semiconducting behavior in the spin-down channel, indicating a half-metallic nature, according to TB-mBJ potential calculations. With total magnetic moments of 20 µB, both materials showed ferromagnetic properties. Samarium ions contributed 5.27 µB for MgSm2S4 and 5.34 µB for MgSm2Se4. Furthermore, we computed optical parameters in the energy range of 0 to 15 eV, such as absorption, extinction coefficient, reflectivity, dielectric function, and refractive index. Our results demonstrate the potential of MgSm2X4 spinels for future technological developments by revealing their prospective optoelectronic and spintronic applications.

Investigating the Antibacterial and Anti-inflammatory Potential of Polyol-Synthesized Silver Nanoparticles.

Silver nanoparticles (Ag-NPs) were synthesized by using the polyol method. The structural and morphological characteristics of Ag-NPs were studied by using X-ray diffraction (XRD) and field-emission scanning electron microscopy (FE-SEM). The XRD analysis revealed the formation of single-phase polycrystalline Ag-NPs with an average crystallite size and lattice constant of ∼23 nm and 4.07 Å, respectively, while the FE-SEM shows the formation of a uniform and spherical morphology. Energy-dispersive X-ray spectroscopy confirmed the formation of single-phase Ag-NPs, and no extra elements were detected. A strong absorption peak at ∼427 nm was observed in the UV-vis spectrum, which reflects the surface plasmon resonance (SPR) behavior characteristic of Ag-NPs with a spherical morphology. Fourier-transform infrared (FTIR) spectra also supported the XRD and EDX results with regard to the purity of the prepared Ag-NPs. Anti-inflammatory activity was tested using HRBCs membrane stabilization and heat-induced hemolysis assays. The antibacterial activity of Ag-NPs was evaluated against four different types of pathogenic bacteria by using the disc diffusion method (DDM). The Gram-negative bacterial strains used in this study are Escherichia coli (E. coli), Klebsiella, Shigella, and Salmonella. The analysis suggested that the antibacterial activities of Ag-NPs have an influential role in inhibiting the growth of the tested Gram-negative bacteria, and thus Ag-NPs can find a potential application in the pharmaceutical industry.

Intelligent computing with Levenberg-Marquardt artificial neural network for Carbon nanotubes-water between stretchable rotating disks.

Hybrid Nano fluid has emerged to be an important field of study due to its better thermal performance compared to other Nano fluids. The problem of carbon nanotubes rotating between two stretchable discs while suspended in water is investigated in this research. Due to numerous uses of this problem, such as metal mining, drawing plastic films, and cooling continuous filaments, this problem is essential to industry. Considerations here include suction/injection, heat radiation, and the Darcy-Forchheimer scheme with convective boundary conditions. The partial differential equations are reduced to ordinary differential equations by using appropriate transformation. To examine the approximate solution validation, training and testing procedures are interpreted and the performance is verified through error histogram and mean square error results. To describe the behavior of flow quantities, several tabular and graphical representations of a variety of physical characteristics of importance are presented and discussed in detail. The basic aim of this research is to examine the behaviour of carbon nanotubes (nanoparticles) between stretchable disks while considering the heat generation/absorption parameter by using the Levenberg-Marquardt technique of artificial neural network. Heat transfer rate is accelerated by a decrease in velocity and temperature and an increase in the nanoparticle volume fraction parameter which is a significant finding of the current study.

Room-Temperature Ferromagnetism in Mn-Doped ZnO Nanoparticles Synthesized by the Sol-Gel Method.

In the current work, pure ZnO and Mn-doped ZnO nanoparticles were synthesized by the sol-gel autocombustion method. Structural analysis and phase determination were done by X-ray diffraction, and a hexagonal wurtzite structure was exhibited with disparate microstructures for all samples. Mn2+ ions were well composed, as evidenced by the fluctuation of lattice parameters, dislocation density, and lattice strain. Crystallite size decreases from 38.42 to 27.54 nm by increasing the doping concentration. Field emission scanning electron microscopy results shows the combination of evenly distributed spherical-like and hexagon-like structures. Fourier transform infrared spectra revealed that when Mn content increased, the absorption bands red-shifted. The drop in the energy band gap from 3.25 eV for ZnO to 2.99 eV for Zn0.96Mn0.04O was predicted by ultraviolet-visible absorption spectra. This red shift in the energy band gap can be explained by the sp-d exchange interaction between the band electrons of ZnO and localized d electrons of Mn. A study of magnetic properties revealed the change of the diamagnetic attribute for pure ZnO to the room-temperature ferromagnetic attribute of doped samples. In the current study, room-temperature ferromagnetism was achieved for Mn-doped ZnO nanoparticles, which can serve as a desirable option for practical applications in the future.

Investigation of conduction mechanism and UV light response of vertically grown ZnO nanorods on an interdigitated electrode substrate.

Vertically aligned zinc oxide nanorod (ZnO-NR) growth was achieved through a wet chemical route over a comb-shaped working area of an interdigitated Ag-Pd alloy signal electrode. Field-emission scanning electron microscopy images confirmed the formation of homogeneous ZnO-NRs grown uniformly over the working area. X-ray diffraction revealed single-phase formation of ZnO-NRs, further confirmed by energy-dispersive X-ray spectroscopy analysis. Temperature-dependent impedance and modulus formalisms showed semiconductor-type behavior of ZnO-NRs. Two electro-active regions i.e., grain and grain boundary, were investigated which have activation energy ∼0.11 eV and ∼0.17 eV, respectively. The conduction mechanism was investigated in both regions using temperature-dependent AC conductivity analysis. In the low-frequency dispersion region, the dominant conduction is due to small polarons, which is attributed to the grain boundary response. At the same time, the correlated barrier hopping mechanism is a possible conduction mechanism in the high dispersion region attributed to the bulk/grain response. Moreover, substantial photoconductivity under UV light illumination was achieved which can be attributed to the high surface-to-volume ratio of zinc oxide nanorods as they provide high density of trap states which causes an increase in the carrier injection and movement leading to persistent photoconductivity. This photoconductivity was also facilitated by the frequency sweep applied to the sample which suggests the investigated ZnO nanorods based IDE devices can be useful for the application of efficient UV detectors. Experimental values of field lowering coefficient (ßexp) matched well with the theoretical value of ßS which suggests that the possible operating conduction mechanism in ZnO nanorods is Schottky type. I-V characteristics showed that the significantly high photoconductivity of ZnO-NRs as a result of UV light illumination is owing to the increase in number of free charge carriers as a result of generation of electron-hole pairs by absorption of UV light photons.

Investigation of structural, electronic, mechanical, & optical characteristics of Ra based-cubic hydrides RbRaX3 (X= F and cl) perovskite materials for solar cell applications: First principle study.

Perovskite materials are considered the gateway of various physical applications to meet the production and consumption of energy and medical fields. Density Functional Theory (DFT) becomes the most important field in the modern era to investigate perovskite materials for various physical properties. DFT nowadays is used to explore the perovskite materials for a lot of applications like photocatalytic, optoelectronic, and photovoltaics. We discussed radium based cubic hydrides RbRaX3 (while X = F & Cl) perovskite material's electrical, optical, elastic, & physical characteristics with the help of DFT-based CASTEP code with PBE exchange-correlation efficient of GGA. The RbRaF3 & RbRaCl3 have three-dimensional nature by means of space group 221 (Pm3 m). According to electronic characteristics, the direct bandgap of RbRaF3 RbRaCl3 are 3.18eV and 2.209eV, respectively. Both compounds are brittle in nature via Poisson's ratio & Pugh's criteria. Thus, our novel RbRaX3 (X = F and Cl) compounds have excellent applications for solar cell and medical areas.

Structural and Functional Characterization of Novel Phosphotyrosine Phosphatase Protein from Drosophila melanogaster (Pupal Retina).

A novel pair of protein tyrosine phosphatases in Drosophila melanogaster (pupal retina) has been identified. Phosphotyrosyl protein phosphatases (PTPs) are structurally diverse enzymes increasingly recognized as having a fundamental role in cellular processes including effects on metabolism, cell proliferation, and differentiation. This study presents identification of novel sequences of PTPs and their comparative homology modeling from Drosophila melanogaster (Dr-PTPs) and complexation with the potent inhibitor HEPES. The 3D structure was predicted based on sequence homology with bovine heart low molecular weight PTPs (Bh-PTPs). The sequence homologies are approximately 50% identical to each other and to low molecular weight protein tyrosine phosphatases (PTPs) in other species. Comparison of the 3D structures of Bh-PTPs and Dr-PTPs (primo-2) reveals a remarkable similarity having a four stranded central parallel ß sheet with flanking α helices on both sides, showing two right handed ß-α-ß motifs. The inhibitor shows similar binding features as seen in other PTPs. The study also highlights the key catalytic residues important for target recognition and PTPs' activation. The structure guided studies of both proteins clearly reveal a common mechanism of action and inhibitor binding at the active site and will be expected to contribute toward the basic understanding of functional association of this enzyme with other molecules.

Investigation of structural, opto-electronic and thermoelectric properties of titanium based chloro-perovskites XTiCl3 (X = Rb, Cs): a first-principles calculations.

Perovskites are a significant class of materials with diverse uses in modern technology. The structural, electronic, elastic, thermoelectric, and optical properties of RbTiCl3 and CsTiCl3 perovskites were estimated using the FP-LAPW method within the framework of density functional theory. The exchange-correlation energy of both analyzed systems was calculated using the Generalized Gradient Approximation (GGA) functional. The structures are optimized and lattice constants of 5.08 Å and 5.13 Å are found for XTiCl3 (X = Rb, Cs), respectively. The structural analysis reveals that they have cubic symmetry. Their half metallic nature was proved by their metallic nature in one spin channel and semiconducting nature in the opposing spin channel. Densities of states are calculated to predict the interaction of orbitals of distinct atoms in the compounds. From the results of optical response, it is found that these compounds show high optical absorption in the visible region of light. Moreover, thermoelectric properties of the studied materials are calculated as a function of chemical potential at different temperatures using the theory of semi-classical Boltzmann transport within BoltzTrap code. The thermoelectric response shows that the investigated compounds as p-type can be beneficial in overcoming the global warming issue.