Enhanced sensing of bacteria biomarkers by ZnO and graphene oxide decorated PEDOT film.

Developing a biofilm biomarker detector and inhibitor will immensely benefit efforts geared at curbing infectious diseases and microbiologically induced corrosion of medical implants, marine vessels and buried steel pipelines. N-Acyl homoserine lactones (AHLs) are important biomarkers gram-negative bacteria use for communication. In this work, we investigated the interactions between three AHL molecules and graphene oxide (GO) and ZnO nanomaterials embedded in conjugated poly(3,4-ethylenedioxythiophene) (PEDOT) film. The results show that PEDOT/GO/ZnO detected AHLs to a considerable extent with adsorption enthalpies of -4.02, -4.87 and -4.97 KJ/mol, respectively, for N-(2-oxotetrahydrofuran-3-yl)heptanamide (AHL1), 2-hydroxy-N-(2-oxotetrahydrofuran-3-yl)nonanamide (AHL2) and (E)-3-(3-hydroxyphenyl)-N-(2-oxotetrahydrofuran-3-yl)acrylamide (AHL3) molecules. The ZnO nanoparticles facilitated charge redistribution and transfer, thereby enhancing the conductivity and overall sensitivity of the substrate toward the AHLs. The adsorption distance and sites of interactions further tuned the charge migration and signal generation by the substrate, thus affirming the suitability of the modeled thin film as a sensor material. Excellent stability and conductivity were maintained before and after the adsorption of each AHL molecule. Moreover, the desorption time for each AHL molecule was calculated, and the result affirmed that the modeled film materials are promising for developing highly sensitive biosensors.Communicated by Ramaswamy H. Sarma.

Adsorption and sensor performance of transition metal-decorated zirconium-doped silicon carbide nanotubes for NO2 gas application: a computational insight.

Owing to the fact that the detection limit of already existing sensor-devices is below 100% efficiency, the use of 3D nanomaterials as detectors and sensors for various pollutants has attracted interest from researchers in this field. Therefore, the sensing potentials of bare and the impact of Cu-group transition metal (Cu, Ag, Au)-functionalized silicon carbide nanotube (SiCNT) nanostructured surfaces were examined towards the efficient detection of NO2 gas in the atmosphere. All computational calculations were carried out using the density functional theory (DFT) electronic structure method at the B3LYP-D3(BJ)/def2svp level of theory. The mechanistic results showed that the Cu-functionalized silicon carbide nanotube surface possesses the greatest adsorption energies of -3.780 and -2.925 eV, corresponding to the adsorption at the o-site and n-site, respectively. Furthermore, the lowest energy gap of 2.095 eV for the Cu-functionalized surface indicates that adsorption at the o-site is the most stable. The stability of both adsorption sites on the Cu-functionalized surface was attributed to the small ellipticity (ε) values obtained. Sensor mechanisms confirmed that among the surfaces, the Cu-functionalized surface exhibited the best sensing properties, including sensitivity, conductivity, and enhanced adsorption capacity. Hence, the Cu-functionalized SiCNT can be considered a promising choice as a gas sensor material.

Cobalt group transition metals (TM: Co, Rh, Ir) coordination of S-doped porphyrins (TM_S@PPR) as sensors for molecular SO2 gas adsorption: a DFT and QTAIM study.

CONTEXT: The intricate challenges posed by SO2 gas underscore the imperative for meticulous monitoring and detection due to its adverse effects on health, the environment, and equipment integrity. Hence, this research endeavors to delve deeply into the intricate realm of transition-metals functionalized sulfur-doped porphyrins (S@PPR) surfaces through a comprehensive computational study. The electronic properties revealed that upon adsorption, Ir_S@PPR surface reflects the least energy gap of 0.109 eV at the O-site of adsorptions, indicating an increase in electrical conductivity which is a better adsorption trait. Owing to the negative adsorption energy observed, the adsorption behavior is described as chemisorption, with the greatest adsorption energy of - 10.306 eV for Ir_S@PPR surface at the S-site of adsorption. Based on the mechanistic attributes, iridium-functionalized S@PPR surface is a promising detecting material towards the sensing of SO2 gas. This report will provide useful insight for experimental researchers in selecting and engineering materials to be used as detectors for SO2 gas pollutant. METHOD: All theoretical investigations were carried out using density functional theory (DFT), calculated at PW6B95-D3/GenECP/Def2svp/LanL2DZ computational method.

A data-guided approach for the evaluation of zeolites for hydrogen storage with the aid of molecular simulations.

CONTEXT: This study employs a data-guided approach to evaluate zeolites for hydrogen storage, utilizing molecular simulations. The development of efficient and practical hydrogen storage materials is crucial for advancing clean energy technologies. Zeolites have shown promise as potential candidates due to their unique porous structure and tunable properties. However, the selection and design of suitable zeolites for hydrogen storage remain challenging. Therefore, this work aims to address this materials science question by utilizing molecular simulations and data-guided approaches to evaluate zeolites' performance for hydrogen storage. The results obtained from this study provide valuable insights into the evaluation of zeolites for hydrogen storage. Through molecular simulations, we analyze the adsorption behavior of hydrogen molecules in various zeolite structures. The performance of different zeolite frameworks in terms of hydrogen storage capacity, adsorption energy, and diffusion properties is assessed. Linde type A zeolite (LTA) had the highest capacity with a hydrogen capacity of 4.8wt% out of the 233 investigated zeolites. Furthermore, we investigate the influence of different factors such as mass (M), density (D), helium void fraction (HVF), accessible pore volume (APV), gravimetric surface area (GSA), and largest overall cavity diameter (Di) on the hydrogen storage performance of zeolites. The results show that Di, D, and M have a negative effect on the percentage weight capacity, while GSA and VSA have the highest positive contribution to the percentage weight. This study, therefore, provides new insights into the factors that affect their hydrogen storage capacity by exhibiting the importance of considering multiple factors when evaluating the performance of zeolites and demonstrates the potential of combining different computational methods to provide a more comprehensive understanding of materials. The current study contributes to the understanding of zeolite-based materials for hydrogen storage applications, aiding in the development of more efficient and practical hydrogen storage systems. METHODS: Computational techniques were employed to investigate the hydrogen storage properties of zeolites. Molecular simulations were performed using classical force fields and molecular dynamics methods. The calculations were carried out at a force field level of theory with the GGA functional. To accurately capture the thermodynamics and kinetics of hydrogen adsorption, enhanced sampling techniques such as Monte Carlo simulations and molecular dynamics with metadynamics were utilized. We employed Grand Canonical Monte Carlo (GCMC) simulations to model hydrogen adsorption in zeolite structures for hydrogen storage. Our approach involved performing a substantial number of Monte Carlo steps (10,000) to ensure system equilibration and precise results. We defined a cutoff distance for particle interactions as 12.5 Ǻ and considered 0.000e framework charge per cell and 0.000e sorbate charge in energy calculations. The choice of an appropriate simulation cell size (50 × 50 × 50) Ǻ was crucial, mirroring real-world conditions. We specified lower and upper fugacity values (1 to 10 atm) to capture the range of gas pressures in the simulations. These methodical steps collectively enabled us to accurately model hydrogen adsorption within zeolites, forming the core of our hydrogen storage evaluation. In this research, we utilized DFT calculations to thoroughly investigate the interactions between zeolites and hydrogen. We employed pseudopotentials to describe electron behavior in zeolite systems, choosing them in line with DFT norms and basis set compatibility. Our simulation cell design replicated zeolite periodicity and eliminated boundary effects. Pre-geometry optimization was performed with HyperChem29, ensuring stable conformations with strict convergence criteria. We utilized 6-31 + G(d) and LanL2DZ basis sets for light and heavy atoms, aligning with field standards for computational efficiency and precision. A machine learning algorithm was used to rank the importance of various structural features such as mass (M), density (D), helium void fraction (HVF), accessible pore volume (APV), gravimetric surface area (GSA), and largest overall cavity diameter (Di) and how they affect the capacity of the zeolites. Machine learning analysis was performed with the Scikit-learn library, an open-source Python tool. We employed a range of machine learning models, including SVMs, random forests, and neural networks, primarily for data analysis and feature extraction. Pearson correlation analysis, a classical statistical technique, was used to evaluate linear relationships between variables and assess the strength and direction of these relationships. It served as a complementary tool to understand the interplay of variables in our dataset, distinguishing it from machine learning algorithms. Further quantum chemical calculations were also performed to calculate the adsorption energy, global reactivity electronic descriptors, and natural bond orbital analysis in order to provide insights into the interaction of the zeolites with hydrogen. The simulations and data analysis were performed using BIOVIA material studio software, Gaussian, and Origin Pro software.

Inflammatory Studies of Dehydroandrographolide: Isolation, Spectroscopy, Biological Activity, and Theoretical Modeling.

Dehydroandrographolide (DA) was isolated and experimentally characterized utilizing FT-IR, UV-Vis, and NMR spectroscopy techniques along with detailed theoretical modelled at the DFT/B3LYP-D3BJ/6-311 + + G(d,p) level of theory. Substantially, molecular electronic property investigations in the gaseous phase alongside five different solvents (ethanol, methanol, water, acetonitrile and DMSO) were comprehensively reported and compared with the experimental results. The globally harmonized scale (GHS), which is used to identify and label chemicals, was also utilized to demonstrate that the lead compound predicted an LD50 of 1190 mg/kg. This finding implies that consumers can safely consume the lead molecule. Notable impacts on hepatotoxicity, cytotoxicity, mutagenicity, and carcinogenicity were likewise found to be minimal to nonexistent for the compound. Additionally, in order to account for the biological performance of the studied compound, in-silico molecular docking simulation analysis was examined against different anti-inflammatory target of enzymes (3PGH, 4COX, and 6COX). From the examination, it can be inferred that DA@3PGH, DA@4COX, and DA@6COX, respectively, showed significant negative binding affinities of -7.2 kcal/mol, -8.0 kcal/mol, and - 6.9 kcal/mol. Thus, the high mean binding affinity in contrast to conventional drugs further reinforces these results as an anti-inflammatory agent.

Novel antioxidant peptides identified from coix seed by molecular docking, quantum chemical calculations and invitro study in HepG2 cells.

The aim of the study was to identify potent antioxidant peptides sourced from coix seed, analyze the structure-activity relationship through molecular docking and quantum chemical calculation. Molecular docking results showed that among thirteen peptides selected in silico, eight had favourable binding interaction with the Keap1-Kelch domain (2FLU). Promising peptides with significant binding scores were further evaluated using quantum calculation. It was shown that peptide FFDR exhibited exceptional stability, with a high energy gap of 5.24 eV and low Highest Occupied Molecular Orbitals (HOMO) and Lowest Unoccupied Molecular Orbitals (LUMO) values. Furthermore, FFDR displayed the capacity to enhance the expression of Nrf2-Keap1 antioxidant genes (CAT, SOD, GSH-Px) and improved cellular redox balance by increasing reduced glutathione (GSH) while reducing oxidized glutathione (GSSG) and malonaldehyde (MDA) levels. These findings highlight the potential of coix seed peptides in developing novel, effective and stable antioxidant-based functional foods.

Potentially toxic metals in irrigation water, soil, and vegetables and their health risks using Monte Carlo models.

Food safety has become a serious global concern because of the accumulation of potentially toxic metals (PTMs) in crops cultivated on contaminated agricultural soils. Amongst these toxic elements, arsenic (As), cadmium (Cd), chromium (Cr), and lead (Pb) receive worldwide attention because of their ability to cause deleterious health effects. Thus, an assessment of these toxic metals in the soils, irrigation waters, and the most widely consumed vegetables in Nigeria; Spinach (Amaranthushybridus), and Cabbage (Brassica oleracea) was evaluated using inductively coupled plasma-optical emission spectroscopy (ICP-OES). The mean concentration (measured in mg kg-1) of the PTMs in the soils was in the sequence Cr (81.77) > Pb(19.91) > As(13.23) > Cd(3.25), exceeding the WHO recommended values in all cases. This contamination was corroborated by the pollution evaluation indices. The concentrations (measured in mg l-1) of the PTMs in the irrigation water followed a similar pattern i.e. Cr(1.87) > Pb(1.65) > As(0.85) > Cd(0.20). All the PTMs being studied, were found in the vegetables with Cr (5.37 and 5.88) having the highest concentration, followed by Pb (3.57 and 4.33), and As (1.09 and 1.67), while Cd (0.48 and 1.04) had the lowest concentration (all measured in mg kg-1) for cabbage and spinach, respectively. The concentration of the toxic metals was higher in spinach than in cabbage, which may be due to the redistribution of the greater proportion of the metals above the ground tissue, caused by the bioavailability of metals in the aqueous phase. Expectedly, the hazard index (HI),and carcinogenic risk values of spinach were higher than that of cabbage. This implies that spinach poses potentially higher health risks. Similarly, the Monte Carlo simulation results reveal that the 5th percentile, 95th percentile, and 50th percentile of the cumulative probability of cancer risks due to the consumption of these vegetables exceeds the acceptable range of 1.00E-6 and 1.00E-4. Thus, the probable risk of a cancerous effect is high, and necessary remedial actions are recommended.

Single-atoms (N, P, S) encapsulation of Ni-doped graphene/PEDOT hybrid materials as sensors for H2S gas applications: intuition from computational study.

This comprehensive study was dedicated to augmenting the sensing capabilities of Ni@GP_PEDOT@H2S through the strategic functionalization with nitrogen, phosphorus, and sulfur heteroatoms. Governed by density functional theory (DFT) computations at the gd3bj-B3LYP/def2svp level of theory, the investigation meticulously assessed the performance efficacy of electronically tailored nanocomposites in detecting H2S gas-a corrosive byproduct generated by sulfate reducing bacteria (SRB), bearing latent threats to infrastructure integrity especially in the oil and gas industry. Impressively, the analysed systems, comprising Ni@GP_PEDOT@H2S, N_Ni@GP_PEDOT@H2S, P_Ni@GP_PEDOT@H2S, and S_Ni@GP_PEDOT@H2S, unveiled both structural and electronic properties of noteworthy distinction, thereby substantiating their heightened reactivity. Results of adsorption studies revealed distinct adsorption energies (- 13.0887, - 10.1771, - 16.8166, and - 14.0955 eV) associated respectively with N_Ni@GP_PEDOT@H2S, P_Ni@GP_PEDOT@H2S, S_Ni@GP_PEDOT@H2S, and Ni@GP_PEDOT systems. These disparities vividly underscored the diverse strengths of the adsorbed H2S on the surfaces, significantly accentuating the robustness of S_Ni@GP_PEDOT@H2S as a premier adsorbent, fuelled by the notably strong sulfur-surface interactions. Fascinatingly, the sensor descriptor findings unveiled multifaceted facets pivotal for H2S detection. Ultimately, molecular dynamic simulations corroborated the cumulative findings, collectively underscoring the pivotal significance of this study in propelling the domain of H2S gas detection and sensor device innovation.

The iron group transition-metal (Fe, Ru, Os) coordination of Se-doped graphitic carbon (Se@g-C3N4) nanostructures for the smart therapeutic delivery of zidovudine (ZVD) as an antiretroviral drug: a theoretical calculation perspective.

This study employed density functional theory (DFT) computational techniques at the ωB97XD/def2svp level of theory to comprehensively explore the electronic behavior of Fe-group transition metal (Fe, Ru, Os) coordination of Se-doped graphitic carbon (Se@g-C3N4) nanosystems in the smart delivery of zidovudine (ZVD), an antiretroviral drug. The HOMO-LUMO results of the interactions show a general reduction in energy gap values across all complexes in the following order: ZVD_Se@C3N4 < ZVD_Ru_Se@C3N4 < ZVD_Fe_Se@C3N4 < ZVD_Os_Se@C3N4. ZVD_Se@C3N4 exhibits the smallest post-interaction band gap of 3.783 eV, while ZVD_Os_Se@C3N4 presents the highest energy band gap of 5.438 eV. Results from the corrected adsorption energy (BSSE) revealed that Os_Se@C3N4 and Ru_Se@C3N4 demonstrated more negative adsorption energies of -2.67 and -2.701 eV, respectively, pointing to a more favorable interaction between ZVD and these systems, thus potentially enhancing the drug delivery efficiency. The investigation into the drug release mechanism from the adsorbents involved a comprehensive examination of the dipole moment and the influence of pH, shedding light on the controlled release of ZVD. Additionally, investigating the energy decomposition analysis (EDA) revealed that ZVD_Ru_Se@C3N4 and ZVD_Fe_Se@C3N4 exhibited the same total energy of -787.7 kJ mol-1. This intriguing similarity in their total energy levels suggested that their stability was governed by factors beyond reactivity, possibly due to intricate orbital interactions. Furthermore, analyzing the bond dissociation energies showed that all systems exhibited negative enthalpy values, indicating that these systems were exothermic at both surface and interaction levels, thus suggesting that these processes emitted heat, contributing to the surrounding thermal energy.

Mechanism and dynamics of Baeyer-Villiger oxidation of furfural to maleic anhydride in presence of H2O2 and Au clusters.

CONTEXT: The increasing demand for fuels and chemicals in the world has prompted the exploration of various forms of renewable energy resources. Using C5-based furfural as the platform to replace the fossil energy resources is greatly attractive because of its abundance and environmental friendliness. Here we study the activity, selectivity, and possible reaction pathways for the Baeyer-Villiger oxidation of furfural over small Au clusters using hydrogen peroxide as oxidant. Furfural reacts with hydrogen peroxide in the presence of the catalysts with 93% selectivity towards maleic anhydride. Natural population analysis, frontier molecular orbital analysis, and spectroscopic analysis are used to illustrate the interaction mechanism between C5H4O2, H2O2, and Au. Reaction pathways leading to the formation of maleic anhydride are also explored. The reaction of C5H4O2 with H2O2 in the absence of a catalyst bears a relatively high transition state energy barrier of 2.98 eV for the first step involving absorption of H atom of H2O2 on the -OH group of C5H4O2. This is in agreement with the blank experiment where there were rare oxidation products observed in the absence of the metal cluster catalysts. On the other hand, transition state energies in the presence of the Au metal clusters are lower and the most feasible pathway is where the substrate and H2O2 co-bind on the Au catalyst and H2O2 molecule transfers an oxygen to the substrate, leading to the cleavage of the O-O bond. METHODS: DFT calculations were done with B3PW91 functional. 6-311G(df, p) basis set was used for C, O, and H and aug-cc-pVDZ-PP was used for gold atoms. Gaussian 09 software was used for the calculations. Multiwfn 3.7 dev was used for the quantum theory of atoms-in-molecules (QTAIM) investigations.

Impact of Polythiophene ((C4H4S)n; n = 3, 5, 7, 9) Units on the Adsorption, Reactivity, and Photodegradation Mechanism of Tetracycline by Ti-Doped Graphene/Boron Nitride (Ti@GP_BN) Nanocomposite Materials: Insights from Computational Study.

This study addresses the formidable persistence of tetracycline (TC) in the environment and its adverse impact on soil, water, and microbial ecosystems. To combat this issue, an innovative approach by varying polythiophene ((C4H4S)n; n = 3, 5, 7, 9) units and the subsequent interaction with Ti-doped graphene/boron nitride (Ti@GP_BN) nanocomposites was applied as catalysts for investigating the molecular structure, adsorption, excitation analysis, and photodegradation mechanism of tetracycline within the framework of density functional theory (DFT) at the B3LYP-gd3bj/def2svp method. This study reveals a compelling correlation between the adsorption potential of the nanocomposites and their corresponding excitation behaviors, particularly notable in the fifth and seventh units of the polythiophene configuration. These units exhibit distinct excitation patterns, characterized by energy levels of 1.3406 and 924.81 nm wavelengths for the fifth unit and 1.3391 and 925.88 nm wavelengths for the seventh unit. Through exploring deeper, the examination of the exciton binding energy emerges as a pivotal factor, bolstering the outcomes derived from both UV-vis transition analysis and adsorption exploration. Notably, the calculated exciton binding energies of 0.120 and 0.103 eV for polythiophene units containing 5 and 7 segments, respectively, provide compelling confirmation of our findings. This convergence of data reinforces the integrity of our earlier analyses, enhancing our understanding of the intricate electronic and energetic interplay within these intricate systems. This study sheds light on the promising potential of the polythiophene/Ti-doped graphene/boron nitride nanocomposite as an efficient candidate for TC photodegradation, contributing to the advancement of sustainable environmental remediation strategies. This study was conducted theoretically; hence, experimental studies are needed to authenticate the use of the studied nanocomposites for degrading TC.

Exploring the potential of single-metals (Cu, Ni, Zn) decorated Al12N12 nanostructures as sensors for flutamide anticancer drug.

In recent years, scientists have been actively exploring and expanding biosensor technologies and materials to meet the growing societal demands in healthcare and other fields. This study aims to revolutionize biosensors by using density functional theory (DFT) at the cutting-edge B3LYP-GD3BJ/def2tzsvp level to investigate the sensing capabilities of (Cu, Ni, and Zn) doped on Aluminum nitride (Al12N12) nanostructures. Specifically, we focus on their potential to detect, analyze, and sense the drug flutamide (FLU) efficiently. Through advanced computational techniques, we explore molecular interactions to pave the way for highly effective and versatile biosensors. The adsorption energy values of -38.76 kcal/mol, -39.39 kcal/mol, and -39.37 kcal/mol for FLU@Cu-Al12N12, FLU@Ni-Al12N12, and FLU@Zn-Al12N12, respectively, indicate that FLU chemically adsorbs on the studied nanostructures. The reactivity and conductivity of the system follow a decreasing pattern: FLU@Cu-Al12N12 > FLU@Ni-Al12N12 > FLU@Zn-Al12N12, with a band gap of 0.267 eV, 2.197 eV, and 2.932 eV, respectively. These results suggest that FLU preferably adsorbs on the Al12N12@Cu surface. Natural bond orbital analysis reveals significant transitions in the studied system. Quantum theory of atom in molecule (QTAIM) and Non-covalent interaction (NCI) analysis confirm the nature and strength of interactions. Overall, our findings indicate that the doped surfaces show promise as electronic and biosensor materials for detection of FLU in real-world applications. We encourage experimental researchers to explore the use of (Cu, Ni, and Zn) doped on Aluminum nitride (Al12N12), particularly Al12N12@Cu, for biosensor applications.

Molecular modeling of the structural, electronic, excited state dynamic, and the photovoltaic properties of the oligomers of n-corannulene (n = 1-4).

Despite the fact that n-corannulene oligomers (n = 1-4) have a variety of electronic and optical properties, including the ability to be tuned and the potential to be used as light-harvesting materials, there has not been a computational assessment of their structural, electronic, and optical properties. Herein, a computational evaluation of the concerned materials regarding their potent use in solar cell technology has been conducted via DFT/CAM-B3LYP and M062X/6-311+G level of theory. It was observed that the calculated 1st frequency of the n-Corannulene (n = 1-4) were 144.15, 106.36, 48.96 and 42.21 respectively. Notably, the computed cohesive energy value increased as the number of Corannulene units increases while the electronic characteristics revealed that the chemical activity of the structures increased as the number of oligomers rose. Both calculation techniques demonstrate that the number of n-Corannulene oligomers increases the HOMO energy while decreasing the LUMO energy based on the external electric field (EF) effect. The findings demonstrated that as EF intensity increases, the energy gap (Eg/eV = |EHOMO-ELUMO|) of these molecular systems decreases which can be attributed to a decrease in the electron transfer potential barrier. The 4-Corannulene systems showed the highest wave length of adsorption for the investigated compound at 546.18 nm, with the highest oscillator strength of 0.2708 and the lowest transition energy of 2.2700 eV, arising from S0-S1 (H-L) and the highest major percentage contribution of 93.34 % in comparison to the investigated compounds. We are hopeful that this research will help experimental researchers understand the potential of n-Corannulene, specifically 4-corannulene, as powerful material for a variety of applications ranging from solar cell, photovoltaic properties and many others.

Investigating the structure, bonding, and energy decomposition analysis of group 10 transition metal carbonyls with substituted terminal germanium chalcogenides [M(CO)3GeX] (M = Ni, Pd, and Pt; X = O, S, Se, and Te) complexes: insight from first-principles calculations.

CONTEXT: This research focused on the theoretical investigation of transition metal carbonyls [M(CO)4] coordinated with terminal germanium chalcogenides complexes [M(CO)3GeX], where M represents Ni, Pd, and Pt and X represents O, S, Se, and Te labeled 1-15. While the notable complexes M(CO)4 (where M = Ni, Pd, Pt) numbered 1, 6, and 11 are of significance, substituting one of the CO ligands in 1, 6, and 11 with a GeX ligand (where X = O, S, Se, or Te) result in substituted complexes (2-5, 7-10, and 11-15). Substituting of the CO ligand slightly alters these bond angles. Specifically, the ∠CMC bond angles for [Ni] complexes range from 111.9° to 112.2°, for [Pd] complexes from 111.4° to 111.7°, and for [Pt] complexes from 112.4° to 112.8°. These findings indicate a minor deviation from the tetrahedral geometry due to the influence of the new GeX ligand. Similarly, there is a slight change in the geometry of the metal complexes, where the ∠GeMC angles for [Ni] complexes are between 106.7° and 106.9°, for [Pd] complexes between 107.2° and 107.5°, and for [Pt] complexes between 105.9° and 106.4°. Comparing among the substituted GeX complexes, those containing GeTe exhibit a higher natural bond orbital (NBO) contribution from the Ge atom compared to the M atom. Consequently, based on the above observations, it can be inferred that GeX acts as an effective sigma donor in contrast to carbonyl compounds. Results of energy decomposition analysis (EDA) for the M-CO bond in 1, 6, and 11 and for the M-GeX bond in the other [M(CO)3(GeX)] complexes where M = Ni, Pd and Pt. The percentage contribution of ΔEelstat and ΔEorb shows a relatively identical behavior for all ligands in case of each metal complexes. METHODS: Density functional theory (DFT) calculations were conducted using the B3LYP/gen/6-31G*/LanL2DZ level of theory to examine transition metal carbonyls [M(CO)4] coordinated with terminal germanium chalcogenides complexes [M(CO)3GeX], where M represents Ni, Pd, and Pt, and X represents O, S, Se, and Te labeled 1-15 utilized through the use of Gaussian 09W and GaussView 6.0.16 software packages. Post-processing computational code such as multi-wave function was employed for results analysis and visualization.

Yttrium- and zirconium-decorated Mg12O12-X (X = Y, Zr) nanoclusters as sensors for diazomethane (CH2N2) gas.

Diazomethane (CH2N2) presents a notable hazard as a respiratory irritant, resulting in various adverse effects upon exposure. Consequently, there has been increasing concern in the field of environmental research to develop a sensor material that exhibits heightened sensitivity and conductivity for the detection and adsorption of this gas. Therefore, this study aims to provide a comprehensive analysis of the geometric structure of three systems: CH2N2@MgO (C1), CH2N2@YMgO (CY1), and CH2N2@ZrMgO (CZ1), in addition to pristine MgO nanocages. The investigation involves a theoretical analysis employing the DFT/ωB97XD method at the GenECP/6-311++G(d,p)/SDD level of theory. Notably, the examination of bond lengths within the MgO cage yielded specific values, including Mg15-O4 (1.896 Å), Mg19-O4 (1.952 Å), and Mg23-O4 (1.952 Å), thereby offering valuable insights into the structural properties and interactions with CH2N2 gas. Intriguingly, after the interaction, bond length variations were observed, with CH2N2@MgO exhibiting shorter bonds and CH2N2@YMgO showcasing longer bonds. Meanwhile, CH2N2@ZrMgO displayed shorter bonds, except for a longer bond in Mg19-O4, suggesting increased stability due to shorter bond distances. The study further investigated the electronic properties, revealing changes in the energy gap that influenced electrical conductivity and sensitivity. The energy gap increased for Zr@MgO, CH2N2@MgO, CH2N2@YMgO, and CH2N2@ZrMgO, indicating weak interactions on the MgO surface. Conversely, Y@MgO showed a decrease in energy, suggesting a strong interaction. The pure MgO surface exhibited the ability to donate and accept electrons, resulting in an energy gap of 4.799 eV. Surfaces decorated with yttrium and zirconium exhibited decreased energies of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), as well as decreased energy gap, indicating increased conductivity and sensitivity. Notably, Zr@MgO had the highest energy gap before CH2N2 adsorption, but C1 exhibited a significantly higher energy gap after adsorption, implying increased conductivity and sensitivity. The study also examined the density of states, demonstrating significant variations in the electronic properties of MgO and its decorated surfaces due to CH2N2 adsorption. Moreover, various analysis techniques were employed, including natural bond orbital (NBO), quantum theory of atoms in molecules (QTAIM), and noncovalent interaction (NCI) analysis, which provided insights into bonding, charge density, and intermolecular interactions. The findings contribute to a deeper understanding of the sensing mechanisms of CH2N2 gas on nanocage surfaces, shedding light on adsorption energy, conductivity, and recovery time. These results hold significance for gas-sensing applications and provide a basis for further exploration and development in this field.

Combined Experimental and Computational Study of V-Substituted Lindqvist Polyoxotungstate: Screening by Docking for Potential Antidiabetic Activity.

In the current work, a novel vanadotungstate compound, (C6H9N2)4[V2W4O19]·2H2O (1), is isolated by a simple stepwise synthesis method and characterized by a combined experimental and computational study. Molecular docking is conducted for the first time for this kind of substituted Lindqvist polyoxometalates to elucidate for potential antidiabetic activity. Hence, the modeling results revealed a significant docking score of the reported compound to bind to the active sites of α-glucosidase with the lowest binding energy of -5.7 kcal/mol, where the standard drug acarbose (ACB) had -4.6 kcal/mol binding energy. The stability of binding was enhanced by strong H-bonding, van der Waals, and electrostatic interactions occurring in the three-dimensional (3D) supramolecular network of polyanionic vanadotungstate subunits templated with organic moieties as shown by X-ray diffraction and Hirshfeld analyses. Furthermore, density functional theory (DFT) calculations supported with photophysical measurements are also discussed to predict the most chemical and biological reactivity. In this view, the complete description of electronic and biological features of (1) is enhanced by determination of the highest occupied molecular orbital (HOMO)/least unoccupied molecular orbital (LUMO) energy, electronic density, ionization potential, electron affinity, etc. These chemical descriptors, intermolecular interactions, docking score, and binding free energy estimation are essential in understanding the reactivity of this bioactive compound offering potential inhibition of the α-glucosidase enzyme.

Synthesis, characterization, and molecular modeling of phenylenediamine-phenylhydrazine-formaldehyde terpolymer (PPHF) as potent anti-inflammatory agent.

Inflammation, a characteristic physiological response to infections and tissue damage, commences with processes involving tissue repair and pathogen elimination, contributing to the restoration of homeostasis at affected sites. Hence, this study presents a comprehensive analysis addressing diverse aspects associated with this phenomenon. The investigation encompasses the synthesis, spectral characterizations (FT-IR, 1H NMR, and 13C NMR), and molecular modeling of p-phenylenediamine-phenylhydrazine-formaldehyde terpolymer (PPHF), a potent agent in promoting inflammation. To explore the reactivity, bonding nature, and spectroscopy, as well as perform molecular docking for in-silico biological evaluation, density functional theory (DFT) utilizing the def2svp/B3LYP-D3BJ method was employed. The results reveal significant biological activity of the tested compound in relation to anti-inflammatory proteins, specifically 6JD8, 5TKB, and 4CYF. Notably, upon interaction between PPHF and 6JD8, a binding affinity of -4.5 kcal/mol was observed. Likewise, the interaction with 5TKB demonstrated an affinity of -7.8 kcal/mol. Furthermore, a bonding affinity of -8.1 kcal/mol was observed for the interaction with 4CYF. Importantly, these values closely correspond to those obtained from the interaction between the proteins and the standard drug ibuprofen (IBF), which exhibited binding affinities of -5.9 kcal/mol, -7.0 kcal/mol, and -6.1 kcal/mol, respectively. Thus, these results provide compelling evidence affirming the tremendous potential of p-phenylenediamine-phenylhydrazine-formaldehyde (PPHF) as a highly promising anti-inflammatory agent, owing to the presence of nitrogen-a heteroatom within the compound.

Increasing the Photovoltaic Power of the Organic Solar Cells by Structural Modification of the R-P2F-Based Materials.

CONTEXT: The present study aims to improve the performance of optoelectronics and photovoltaics by constructing an acceptor-donor-acceptor (A-D-A) molecule with a fullerene-free acceptor moiety. The study utilizes malononitrile and selenidazole derivatives to tailor the molecule for enhanced photovoltaic abilities. The study analyzes molecular properties and parameters like charge density, charge transport, UV absorption spectra, exciton binding energies, and electron density difference maps to determine the effectiveness of the tailored derivatives. METHODS: To optimize the geometric structures, the study used four different functionals (B3LYP, CAM-B3LYP, MPW1PW91, and É·B97XD) along with a double zeta valence basis set 6-31G(d, p) basis set. The study compared the results of the tailored derivatives with a reference molecule (R-P2F) to determine improvements in performance. The light harvesting efficiency of the molecules was analyzed by performing simulations in the gas and solvent phases (chloroform) based on the spectral overlap between the solar irradiance and the absorption spectra of the molecules. The open-circuit voltage (VOC) of each molecule was also analyzed, representing the maximum voltage that can be obtained from the cell under illuminated conditions. The findings indicated that the M1-P2F designed derivative is a more effective, with energy gap of 2.14 eV, and suitable candidate for non-fullerene organic solar cell application, based on various analyses such as power conversion efficiency, quantum chemical reactivity parameters, and electronic features.

High throughput computations of the effective removal of liquified gases by novel perchlorate hybrid material.

The utilization of hybrid materials in separation technology, sorbents, direct air capture (DAC) technology, sensors, adsorbents, and chiral material recognition has increased in the past decade due to the recognized impact of atmospheric pollutants and hazardous industrial gases on climate change. A novel hybrid material, perchlorate hybrid (PClH), has been proposed in this study for the effective sensory detection and trapping of atmospheric pollutants and industrial hazardous gases. The study evaluated the structural properties, adsorption mechanism, electronic sensitivity, and topological analysis of PClH using highly accurate computational methods (M062X-D3BJ/def2-ccpVTZ and DSDPBEP86/def2-ccpVTZ). The computational analysis demonstrated that PClH has considerable adsorption energies and favorable interaction with CO2, NO2, SO2, COCl2, and H2S. PClH is more suitable for detecting liquefiable gases such as COCl2, CO2, and SO2, and can be easily recovered under ambient conditions. Developing such materials can contribute to reducing hazardous gases and pollutants in the atmosphere, leading to a cleaner and safer environment.