Low Energy Research Articles

Exploring malaria parasite surface proteins to devise highly immunogenic multi-epitope subunit vaccine for Plasmodium falciparum

BackgroundMalaria has remained a major health concern for decades among people living in tropical and sub-tropical countries. Plasmodium falciparum is one of the critical species that cause severe malaria and is responsible for major mortality. Moreover, the parasite has generated resistance against all WHO recommended drugs and therapies. Therefore, there is an urgent need for preventive measures in the form of reliable vaccines to achieve the target of a malaria-free world. Surface proteins are the preferable choice for subunit vaccine development because they are rapidly detected and engaged by host immune cells and vaccination-induced antibodies. Additionally, abundant surface or membrane proteins may contribute to the opsonization of pathogens by vaccine-induced antibodies. ResultsIn our study, we have listed all those surface proteins from the literature that could be functionally important and essential for infection and immune evasion of the malaria parasite. Eight Plasmodium surface and membrane proteins from the pre-erythrocyte and erythrocyte stages were shortlisted. Thirty-seven epitopes (B-cell, CTL, and HTL epitopes) from these proteins were predicted using immune-informatic tools and joined with suitable peptide linkers to design a vaccine construct. A TLR-4 agonist peptide adjuvant was added at the N-terminus of the multi-epitope series, followed by the PADRE sequence and EAAAK linker. The TLR-4 receptor was docked with the construct’s anticipated model structure. The complex of vaccine and TLR-4, with the lowest energy −1514, was found to be stable under simulated physiological settings. ConclusionThis study has provided a novel multi-epitope construct that may be exploited further for the development of an efficient vaccine for malaria.

A computational discovery of hexokinase 2 inhibitors from Newbouldia laevis for Hepatocellular carcinoma (HCC) treatment

Newbouldia laevis, also known as the African Border Tree or Fever Tree, is a deciduous tree native to West Africa. The plant is valued for its medicinal properties and is used in traditional medicine for its antimicrobial and anti-inflammatory effects. N. laevis, is a storage tank of phytochemicals with huge health benefits and performances globally for the treatment and management of numerous disease conditions. Limited research exists on the usage of N. laevis for hepatocellular carcinoma (HCC) treatment. This study aims to explore the inhibitory activities of phytochemicals from N. laevis against the hexokinase 2 protein, a target in hepatocarcinoma (HCC) treatment. This study presents a unique in silico approach that includes ligand binding site prediction, molecular docking, molecular dynamics simulation, and Molecular Mechanics Poisson–Boltzmann Surface Area (MM/PBSA) methods. A total of 35 phytochemicals with available 3D structures were identified through literature mining. The literature review highlighted the significance of hexokinase 2 protein as a target inhibitor in the treatment of hepatocellular carcinoma (HCC). Molecular docking experiment with the all the identified phytochemicals and hexokinase 2 revealed that all the identified phytochemicals had potential inhibitory activities against the target protein. Moreover, chrysarobin, apigenin and ursolic acid were the best inhibitors with lowest binding energy of −8.9 kcal/mol, −8.7 kcal/mol, and −8.5 kcal/mol, respectively. The docking experiment was validated by comparing the binding affinities with known reference drug Cabozantinib-S-malate (−8.3 kcal/mol). Further, molecular dynamics studies of complexes with the best docking scores and reference drug complexes were described in detail here. The results of 100 ns modeling (RMSD, RMSF, Rg and SASA) show extraordinary stability during the establishment of complexes with apigenin and ursolic acid, as well as favorable binding energy, which was determined theoretically by means of the MM/PBSA method, thereby increase the probability of their acting as promising and likely hexokinase 2 inhibitors. Therefore, the study predicted that apigenin and ursolic acid could be used as a potential inhibitor/antagonist for the hexokinase 2 enzyme.

[formula omitted] anomaly effect on crystallization and mechanical properties of soda-lime silicate glasses

In the present investigation, the effect of B2O3 is investigated on the theoretical mechanical properties and crystallization kinetics of (64-x)SiO2 - xB2O3 - 16Na2O - 12CaO - 2Al2O3 - 6MgO (x = 2, 4, and 6 mol%) glasses. To understand the mechanical properties elastic moduli are calculated using two theoretical models i.e., Makishima-Mackenzie and Rocherulle. Whereas, in crystallization kinetics, activation energies (Eg, Ec, and Ep) are computed using two distinct methods, i.e., the Kissinger model and the Augis and Bennett model. The replacement of SiO2 by B2O3 enhances the strengthening of the glass network which makes the B6-S58 glass network more rigid. The B6-S58 and B2-S62 glasses have the highest and lowest activation energy (Eg) for crystallization, respectively. B4-S60 glass shows non-linear behavior in characteristics temperature as well as in activation energy due to boron anomaly. The present finding could be helpful in designing windshield automobile glasses.

Energy efficient reliable data transmission for optimizing IoT data transmission in smart city

The rapid proliferation of the internet of things (IoT) technology has significantly transformed urban landscapes, giving rise to smart city frameworks that leverage interconnected devices for enhanced efficiency and functionality. In these environments, vast amounts of data are generated by diverse sensors and devices, necessitating advanced strategies for effective data collection and transmission. This paper introduces a novel approach to address data collection and transmission challenges in IoT-enabled smart city frameworks. The proposed design integrates IoT-Cloud for efficient data collection and employs the energy efficient reliable data transmission (EERDT) model, optimizing IoT data transmission. The enhanced dragonfly routing algorithm, incorporating the firefly algorithm, enhances data routing efficiency. Experimental results demonstrate EERDT's superiority over energy-aware iot-routing (EAIR) and location-centric energy-harvesting aware-routing (LCEHAR), revealing significant improvements in communication overhead, data processing latency, and network lifetime. The EERDT exhibits substantial reductions in communication overhead, enhancing overall network performance. The EERDT model showcases lower data processing latency and energy consumption, highlighting its potential for resource-efficient IoT data transmission. This work contributes an innovative solution for smart city IoT networks, emphasizing performance enhancements and resource efficiency.

Understanding the behavior of a potential anticancer lamotrigine in explicit solvent (water and DMSO) using quantum mechanical tools and abinitio molecular dynamics

Lamotrigine is a medication used to treat epilepsy and help stabilize mood in individuals with bipolar disorder. Epilepsy includes different types of seizures, such as focal seizures, tonic-clonic seizures, and Lennox-Gastaut syndrome, and Lamotrigine is specifically designed to manage this condition. The effectiveness of the drug relies on how it interacts with different liquid environments. In our study, we employed two methods, namely PBE0-D3/def2-TZVP, for optimizations and various calculations. We utilized this approach for NBO, NCI, and wavefunction assay. Additionally, we used PBE0-D3/def2-TZVP and DLPNO-CCSD(T) for analyzing LED, MD, and the bond energy of Lamotrigine in both a vacuum and a complex setting (with water and DMSO). Our findings revealed that Lamotrigine can break down into four fragments: triazine, dichlorophenyl-, 10 amine at the second position in triazine, and 10 amines at the fourth position in triazine. The bond energy for these fragments is measured at 351.84 kcal/mol. NBO provided insights into the electronic transition energies of Lamotrigine in different environments, including a vacuum and with solvents. NCI helped us understand the non-covalent interactions of Lamotrigine in both a vacuum and with water and DMSO (complex) molecules through their two pores: inter and intra interactions. We further explored binding energies and total binding energies of Lamotrigine with water and DMSO. Simulations indicated that Lamotrigine with DMSO pore1 exhibited the highest energy changes over time with a positive sign, while Lamotrigine with water pore2 showed the lowest energy changes over time with a negative sign. In our implicit solvation assay using the SMD model and the CPCM method, we found that Lamotrigine with water had a lower free energy compared to the Lamotrigine-DMSO system.

Atomic S, H and C adsorption on MnO(001) surface and the interaction between H and LaCrO3(001) surface: A computational analysis

S poisoning and C deposition are key factors to cause performance degradation of solid oxide fuel cells (SOFC) anodes. The adsorptions of atomic S, H and C on MnO(001) surface and atomic H on LaCrO3(001) surface are systematically investigated using density functional theory (DFT) calculations. The analysis of surface relaxation shows that surface Mn ion slightly moves toward the slab center and surface O ion moves outward on MnO(001) surface. According to the result of adsorption energy, it can be inferred that the MnO weakens the adsorption of atomic S with lower adsorption energies compared to LaCrO3 surface. In addition, the findings show that the preferred site for atomic H adsorption is O site, with the adsorption energy of －1.361eV, which results in the formation of –OH surface species. Compared to O sites on LaCrO3(001) surface, the atomic H is found to interact weakly with the La and Cr sites. The distances and charges transfer between adsorbate and substrate have also been analyzed. The obtained results are expected to providesome fundamental information for future research on mechanism of S poisoning and C deposition on SOFC anodes.

Eco-Innovation in Energy: Solid Degradation Kinetics of Rejected Red Macroalgae (Kappaphycopsis cottonii) for Bio-Oil and Biochar Production

In the pursuit of renewable energy sources, biomass conversion into biofuels has garnered attention as a sustainable alternative to fossil fuels. This research focuses on the pyrolytic conversion of red macroalgae, specifically rejected Kappaphycus cottonii, an underutilized biomass in Indonesia, into valuable bio-energy carriers, while analyzing the solid degradation kinetics involved. The dried K. cottonii underwent slow pyrolysis at varying temperatures (400‒600 °C) and time intervals (10‒50 min). The impact of these variables on the yield of bio-oil and biochar, alongside the thermogravimetric profiles indicating mass loss, was thoroughly assessed. The study also explores the chemical kinetics of the decomposition process, utilizing the first-order reaction model to analyze the solid biomass conversion rate, activation energy, and frequency factor. Key findings demonstrate that the optimal pyrolysis temperature for maximizing bio-oil yield was precisely 500 °C, beyond which thermal cracking led to yield reductions. Reaction times also greatly affect yield, highlighting the importance of optimized pyrolysis conditions. The determined activation energy and frequency factor, based on the Arrhenius equation, highlighted K. cottonii's lower decomposition energy barrier relative to terrestrial biomass. This distinction is largely ascribed to its unique chemical makeup, notably a lower lignin content, positioning K. cottonii as an advantageous feedstock for biofuel production through pyrolysis.

PVDF-Halloysite-Ceria Multifunctional Membrane for One-step Treatment to Industrial Effluent

Industrial wastewater, containing diverse pollutants like dyes and oils, poses detrimental environmental challenges. Membrane technology addresses this complexity well but requires tailored nanofiller modifications that enhance hydrophilicity, oleophobicity, and antifouling potential for efficient separation. In this context, our work focuses on the development of mixed matrix membranes (PV-H-C) – PVDF, halloysite nanotubes (HNTs), and ceria nanoparticles – for effective dye and oil-water emulsion separation, enabling high flux recovery. The tubular structure of HNTs, with a lumen, enables the encapsulation and controlled distribution of ceria nanoparticles, preventing their agglomeration and leading to more uniform dispersion within the membrane matrix. HNTs porous structure, high surface area, and numerous adsorption sites within its nanotubes excel in rapid dye adsorption and ceria’s inherent hydrophobic properties along with low surface energy, forms a barrier against oil adhesion and spreading. Optimal results were achieved by loading 2% HNT and 1% ceria in the PVDF matrix, ensuring improved membrane performance. HNTs enhanced hydrophilicity and achieved pure water permeate flux of 1698L/m2.h.bar. Developed membranes are super-oleophobic with an underwater contact angle of 132° + 3°and show a 100% increase in dyes and oils separation efficiency as compared to the pristine PVDF membranes. This unique integration of ceria with halloysite nanotubes in PV-H-C membranes is pivotal, bestowing exceptional anti-fouling characteristics and reusability, while providing a one-step, comprehensive solution for the effective treatment of complex industrial wastewater that encompasses both oil and complex dyes.

Temperature dependence of photoluminescence kinetics and scintillation properties of LuY2(Al5-xScx)O12:Ce (x = 1, 1.5, 2) garnet single-crystalline films

The temperature dependence of photoluminescence (PL) kinetics and scintillation properties were investigated in LuY2(Al5-xScx)O12:Ce (x = 1, 1.5, 2) garnet single-crystalline films grown by the isothermal liquid phase epitaxy method. With the increase of Sc content, the Ce3+ 5d1 level was shifted to higher energy while the Ce3+ 5d2 level was shifted to lower energy due to the decrease in crystal field splitting of the 5d levels. Activation energy of thermal quenching, determined from temperature-dependent PL decay times, decreased with increasing Sc content. At room temperature, the decrease of light yield (LY) value with increasing Sc content is caused by the thermal ionization process. LuY2(Al4Sc)O12:Ce showed a LY value of 510 photons/MeV when excited by 5.5 MeV α-particles, which is ∼21 % larger than that of Lu2Y(Al4Sc)O12:Ce due to a smaller bandgap Eg of the former.

Learner’s attention detection in connected smart classroom using internet of things and convolutional neural networks

Detecting learner attention is an essential part of learning assessment. Consequently, it becomes an essential requirement for adaptive intelligent teaching systems, to identify specific needs and anticipate orientations. In this article, we propose a new model of a connected smart classroom, based on the internet of things, artificial intelligence and machine learning to detect in real time learners' attention and marking their presence during the execution of a teacher-assisted pedagogical activity, as well as to adapt the most suitable learning objects to these learners. The proposed model is based on head position, gaze direction, yawning and eye-state analysis as facial landmarks detected by cameras connected via the Bluetooth low energy network and transmitted to a developed convolutional neural network. In addition, a series of experiments have been conducted to evaluate the performance and efficiency of the model developed. The findings demonstrate that the model developed can be used to precisely capture the status of learners in the classroom in terms of attention and identification. In this way, these interesting findings can be used to adapt teaching activities to the individual needs of learners, and to identify areas where they have difficulties and needs extra help.

Effect of ratio of desulfurization gypsum to carbide slag on low-carbon phase change composites for energy storage

To recycle industrial wastes sufficiently, this work innovatively proposed a mixture of desulfurization gypsum and carbide slag as skeleton material to fabricate phase-change composites with NaNO3 as phase change material in a mass ratio of 5 to 5. Four phase-change composites were fabricated with different ratio of desulfurization gypsum to carbide slag by the cold compression-hot sintering method, and then key thermal and mechanical properties, microscopic morphology and chemical compatibility between components were investigated in detail. Results show that the mixture of desulfurization gypsum and carbide slag as skeleton material is feasible and reliable and an optimal mass ratio of desulfurization gypsum to carbide slag was obtained to be 3.5 to 1.5; the phase-change composite with the optimal mass ratio possesses good mechanical strength of up to 134.116 MPa and an energy storage capacity of 483.151 J/g in the range of 100 to 400 °C, as well as excellent thermal stability and chemical compatibility between components, inside which the NaNO3 is well encapsulated. Moreover, the phase-change composites fabricated in this work have far low energy consumption and carbon dioxide emission.

High nitrogen removal and electricity generation of anaerobic fluidized bed coupled microbial fuel cell for Anammox

The current challenge in wastewater denitrification lies in the treatment of low carbon to nitrogen ratio(C/N) wastewater. Integrating Anaerobic Ammonia Oxidation(Anammox) with a microbial fuel cell(MFC) enables simultaneous pollutant removal and electricity generation, leading to enhanced treatment efficiency and reduced energy consumption. However, achieving stable and effective treatment effects under high nitrogen concentration conditions remains a general research difficulty. The Anaerobic fluidized bed MFC(AFB-MFC) experiment successfully integrated Anammox ammonia oxidizing bacteria (AnAOB) into the anode and cathode chambers, resulting in a continuous operation for 258 days. The reactor successfully initiated operation within 48 days and maintained stable performance within an NLR range of 0.5-1.0 kgN/m3/d. The system performance was found to be influenced by DO and substrate concentration, demonstrating consistent high nitrogen removal ability across different HRT. Ultimately, the Anammox AFB-MFC achieved a nitrogen removal efficiency (NRE) of 96.89%, while its power generation performance gradually improved, yielding a final output voltage ranging from 370 to 420mV. The microbial community within the reactor comprised diverse electricity-producing bacteria and AnAOB. This study highlights the excellent denitrification and power generation potential of Anammox AFB-MFC under low energy consumption conditions and provides theoretical groundwork for the practical implementation of Anammox.

Nanocrystal Materials for Resistive Memory and Artificial Synapses: Progress and Prospects.

Resistive random-access memory (RRAM) is considered to be the most promising next-generation non-volatile memory because of its low cost, low energy consumption, and excellent data storage characteristics. However, the on/off (SET/RESET) voltages of RRAM are too random to replace the traditional memory. Nanocrystals (NCs) offer an appealing option for these applications since they combine excellent electronic/optical properties and structural stability and can address the requirements of low-cost, large-area, and solution-processed technologies. Therefore, the doping NCs in the function layer of RRAM are proposed to localize the electric field and guide conductance filaments (CFs) growth. The purpose of this article is to focus on a comprehensive and systematical survey of the NC materials, which are used to improve the performance of resistive memory (RM) and optoelectronic synaptic devices and review recent experimental advances in NC-based neuromorphic devices from artificial synapses to light-sensory synaptic platforms. Extensive information related to NCs for RRAM and artificial synapses and their associated patents were collected. This review aimed to highlight the unique electrical and optical features of metal and semiconductor NCs for designing future RRAM and artificial synapses. It was demonstrated that doping NCs in the function layer of RRAM could not only improve the homogeneity of SET/RESET voltage but also reduce the threshold voltage. At the same time, it could still increase the retention time and provide the probability of mimicking the bio-synapse. NC doping can significantly enhance the overall performance of RM devices, but there are still many problems to be solved. This review highlights the relevance of NCs for RM and artificial synapses and also provides a perspective on the opportunities, challenges, and potential future directions.

Ad hoc wireless network implementing BEE-LEACH

Adaptations have been key to the development and advancement of the low energy adaptive clustering hierarchy (LEACH) protocol. Presented is an alteration to the traditional LEACH, low energy adaptive clustering hierarchy, algorithm. This algorithm focuses on the battery life optimization of sensors within a wireless sensor network (WSN). These sensors will be grouped into clusters with the aim of maximizing the battery life of the overall system by sorting each sensor by residual energy and assigning the highest residual energy the role of cluster head. The protocol will then assign sensors to cluster heads based on distance relative to the head. This algorithm achieves the goal of extending battery life and offers itself as a promising alternative to standard LEACH algorithms. The algorithm is tested by comparing sensor battery life, total sensors communicating at a given time, and sensors with residual energy. This paper addresses the strengths and vulnerabilities of the algorithm, as well as proposed work for further implementation for the following groups looking to create their own LEACH protocol.

Enhancing energy efficiency in tyre pressure and temperature monitoring systems

This study addresses the pivotal challenge of enhancing power efficiency in tyre pressure and temperature monitoring systems (TPMS) for heavy vehicles and trailers. Employing field-programmable gate arrays (FPGA) and adaptive channel frequency hopping in bluetooth low energy (BLE) communication, the research focuses on mitigating power consumption issues specific to heavy vehicles with multiple tyres. The proposed solution incorporates strategic BLE channel blocking and adaptive frequency hopping on the FPGA platform to alleviate channel congestion and interference, ultimately reducing TPMS power consumption. The FPGA's adaptability tailors frequency hopping strategies to automotive TPMS nuances, optimizing channel selection and minimizing energy-intensive processes. Empirical results showcase a significant reduction in power consumption, with the TPMS operating at 100 MHz during active mode consuming 66 mW, dropping to 11 mW in sleep mode, and reaching 0 mW in hibernate mode for the majority of operational time. This research establishes a practical FPGA-based approach for power optimization in commercial TPMS, promising heightened reliability, safety improvements, and environmental impact reduction in the automotive sector.

Performance evaluation of low energy adaptive clustering hierarchy-based cluster routing protocols in wireless sensor networks using a new graphical user interface

Wireless sensor network (WSN) is widely used for field data acquisition and monitoring in different domains. To make this type of network functional, efficient routing protocols must be implemented. Nevertheless, WSNs have an energy constraint due to limited batteries. Many clustered protocols are proposed to overcome it. However, the implementation of these protocols would be difficult to understand without a simulation tool, as some problems may arise during their development. Testing real-world applications requires a lot of effort and cost because they often use many nodes in large networks. Therefore, the simulation tool is the most relative way to evaluate these protocols. This paper presents graphical-based cluster protocols simulation interface for WSN(GCPS-WSN), a new interface to simulate some clustered protocols in WSNs. GCPS-WSN allows the user to evaluate the performance of certain low energy adaptive clustering hierarchy (LEACH) enhanced protocols to choose the most appropriate one for his system. The user can simulate protocols without any knowledge of software programming.

Bamboo Housing - A Sustainable Housing with Low Energy and Cost Effective Solution in India

Bamboo Housing - A Sustainable Housing with Low Energy and Cost Effective Solution in India

Unvealing the Super App for Tourism with QR and Machine Learning

Abstract: In today’s dynamic world of travel and tourism, the demand for innovative solutions that improve user experience and simplify booking processes is constantly increasing. In response to this need, our research introduces an innovative travel super- app poised to revolutionize the way travelers explore and interactwith travel destinations. This comprehensive application uses cutting-edge technologies such as QR code and Bluetooth Low Energy (BLE) technology, as well as advanced machine learning algorithms, to provide users with a seamless and personalized booking experience. By combining various tourist attractions such as cafes, water parks, monuments and museums into one platform, Super App eliminates the need for multiple apps, offering unparalleled convenience and efficiency. With person- alized recommendations, dynamic price predictions and preview tools, users can receive personalized recommendations and makeinformed decisions about their travel plans. Integrating BLE technology into check-in and check-out processes ensures a frictionless and secure authentication experience that increases operational efficiency and visitor satisfaction in tourism desti- nations. Our research aims not only to answer the immediate challenges that tourists face, but also to pave the way for the further development of the tourism industry. With its innovative features and user-centric design, Super App is a significant step towards passenger navigation and communication in today’s digital age.

Role of Passivation Ligand in Exciton Diffusion and Emission Mechanism of Metal Halide Perovskite Nanocrystal Solid

Shorter-ligand passivated metal halide perovskite nanocrystal (PNC) solids possess smaller inter-NC edge distance which can potentially activate shorter-range nonradiative routes of energy transfer. However, these PNCs are prone to develop surface defects due to ligand detachment and the photogenerated excitons also have high probability to undergo dissociation. It remains unclear how these factors influence the exciton diffusion and emission mechanism of PNC solids. Herein, we prepare two PNC solids passivated with alkylamine and alkylacid ligands of different chain lengths and investigate the exciton diffusion and emission properties by combining time-resolved photoluminescence (PL) and low temperature PL spectroscopy. Our results show that due to the easy ligand detachment and rich surface defects, no prominent exciton transfer occurs in PNC solid passivated with short ligands, despite of the shorter distance between adjacent PNCs. In comparison, the PNC solid passivated with long ligands shows significant occurrence of exciton diffusion from high energy sites towards low energy sites. Accordingly, the PL spectra of thick PNC solid passivated with different ligands show a strikingly different evolution trend with decreasing temperature: in short ligand passivated PNC solid, an intrinsic emission is observed along with a defect-related emission arising from carrier trapping and subsequent radiative recombination, and both emissions are enhanced at lower temperature; in long ligand passivated PNC solid, high energy emission quenches while low energy emission is strengthened due to enhanced exciton transfer at lower temperature. This work reveals that the exciton diffusion and emission properties of PNC solid is strongly mediated by the passivation ligands, providing important insights for their applications in optoelectronic devices.

Designing efficient materials for high-performance of non-fullerene organic solar cells through side-chain engineering on DBT-4F derivatives by non-fused-ring electron acceptors.

For the advancement in fields of organic and perovskite solar cells, various techniques of structural alterations are being employed on previously reported chromophores. In this study, the end-capped engineering is carried out on DBT-4F (R) by modifying terminal acceptors to improve optoelectronic and photovoltaic attributes. Seven molecules (AD1-AD7) are modeled using different push-pull acceptors. DFT/B3LYP/6-31G along with its time-dependent approach (TD-DFT) are on a payroll to investigate ground state geometries, absorption maxima (λmax), energy gap (Eg), excitation energy (Ex), internal reorganization energy, light harvesting efficiency (LHE), dielectric constant, open circuit voltage (VOC), fill factor (FF), etc. of OSCs. AD1 displayed the lowest band gap (1.76eV), highest λmax (876nm), lowest Ex (1.41eV), and lowest binding energy (0.21eV). Among various calculated parameters, all of the sketched molecules demonstrated greater dielectric constant when compared to R. The highest dielectric constant was exhibited by AD3 (56.26). AD5 exhibited maximum LHE (0.9980). Lower reorganization energies demonstrated improved charge mobility. AD5 and AD7 (1.63 and 1.68eV) have higher values of VOC than R (1.51eV). All novel molecules having outperforming attributes will be better candidates to enhance the efficacy of OSCs for future use. Precisely, a DFT and TD-DFT analysis on all of the proposed organic molecules were conducted, using the functional MPW1PW91 at 6-31G (d,p) basis set to examine their optoelectronic aspects, additionally the solvent-state computations were studied with a TD-SCF simulation. For all these simulations, Guassian 09 and GuassView 5.0 were employed. Moreover, the Origin 6.0, Multiwfn 3.8, and PyMOlyze 1.1 software were utilized for the visual depiction of the graphs of absorption, TDM, and DOS, respectively of the studied molecules. A number of crucial aspects such as FMOs, bandgaps, light-harvesting efficiency, electrostatic potential, dipole moment, ionization potential, open-circuit voltage, fill factor, binding energy, interaction coefficient, chemical hardness-softness, and electrophilicity index were also investigated for the studied molecules.