Search Results (24)

Low-viscosity epoxy-containing diluents are used to reduce the initial viscosity of highly filled, wear-resistant epoxy systems and to improve filler wetting and dispersion. This study determined physical parameters by an atomic-increment approach and electronic descriptors using the Parametric Method 3 (PM3) semi-empirical method. Clear relationships were established between the effective molar cohesion energy and the solubility parameter with van der Waals volume. Linear dependencies were also obtained between the diluent surface tension and spreading coefficients on model high-hardness fillers, including silicon carbide, boron carbide, and normal corundum. The activity of epoxy diluents depends on the lowest unoccupied molecular orbital energy. These diluents influence processing and the final physical and mechanical properties of composites, making their selection critical for strength, hardness, and wear resistance. Computational analysis enables prediction of diluent behavior, reducing experimental time and cost. Integrating physical and quantum-chemical data into epoxy diluent design accelerates the search for optimal components and improves production of durable, high-performance epoxy composites. Full article

Phytoecdysteroids represent a class of naturally occurring substances known for their diverse biological functions, particularly their strong ability to stimulate protein anabolism. In this study, a computational machine learning-driven quantitative structure–activity relationship (QSAR) approach was applied to analyze the anabolic potential of 23 ecdysteroid compounds. The ML-based QSAR modeling was conducted using a combined approach that integrates Genetic Algorithm-based feature selection with Multiple Linear Regression Analysis (GA-MLRA). Additionally, structure optimization by semi-empirical quantum-chemical method was employed to determine the most stable molecular conformations and to calculate an additional set of structural and electronic descriptors. The most effective QSAR models for describing the anabolic activity of the investigated ecdysteroids were developed and validated. The proposed best model demonstrates both strong statistical relevance and high predictive performance. The predictive performance of the resulting models was confirmed by an external test set based on R²_test values, which were within the range of 0.89 to 0.97. Full article

Imidazolium-based ionic liquids (ILs) have been regarded as green solvents owing to their unique properties. Among these, the melting point is key to their excellent performance in applications such as catalysis, biomass processing, and energy storage, where stability and operational temperature range are critical. The utilization of neural networks for forecasting the melting point is highly significant. Nevertheless, the excessive selection of descriptors obtained by density functional theory (DFT) calculations always leads to huge computational costs. Herein, this study strategically selected only 12 kinds of quantum chemical descriptors by employing a much more efficient semi-empirical method (PM7) to reduce computational costs. Four principles of data pre-processing were proposed, and the innovative use of a simulated annealing algorithm to search for the lowest energy molecular conformation improved accuracy. Based on these descriptors, a multi-layer perceptron neural network model was constructed to efficiently predict the melting points of 280 imidazolium-based ILs. The R² value of the current model reached 0.75, and the mean absolute error reached 25.03 K, indicating that this study achieved high accuracy with very little computational cost. This study reveals a strong correlation between descriptors and melting points. Additionally, the model accurately predicts unknown melting points of imidazolium-based ILs, achieving good results efficiently. Full article

Density functional theory and a semi-empirical quantum chemical approach were used to evaluate the photocatalytic efficiency of ceria (CeO₂) combined with reduced graphene oxide (rGO) and graphene (GP) for degrading methylene blue (MB). Two main aspects were examined: the adsorption ability of rGO and GP for MB, and the separation of photogenerated electrons and holes in CeO₂/rGO and CeO₂/GP. Our results, based on calculations of the adsorption energy, population analysis, bond strength index, and reduced density gradient, show favorable energetics for MB adsorption on both rGO and GP surfaces. The process is driven by weak, non-covalent interactions, with rGO showing better MB adsorption. A detailed analysis involving parameters like fractional occupation density, the centroid distance between molecular orbitals, and the Lewis acid index of the catalysts highlights the effective charge separation in CeO₂/rGO compared to CeO₂/GP. These findings are crucial for understanding photocatalytic degradation mechanisms of organic dyes and developing efficient photocatalysts. Full article

This work is devoted to the study of nanosized polymer polyvinylidene fluoride (PVDF) thin ferroelectric films (two-dimensional ferroelectrics) and their composites with graphene layers, using molecular dynamics methods to (1) study and calculate the polarization switching time depending on the electric field and film thickness, (2) study and calculate the polarization switching time depending on changes of the PVDF in PVDF-TrFE film, and (3) study the polarization switching time in PVDF under the influence of graphene layers. All calculations at each MD run step were carried out using the semi-empirical quantum method PM3. A comparison and analysis of the results of these calculations and the kinetics of polarization switching within the framework of the Landau–Ginzburg–Devonshire theory for homogeneous switching in ferroelectric polymer films is carried out. The study of the composite heterostructures of the “graphene-PVDF” type, and calculations of their polarization switching times, are presented. It is shown that replacing PVDF with PVDF-TrFE significantly changes the polarization switching times in these thin polymer films, and that introducing various graphene layers into the PVDF layered structure leads to both an increase and a decrease in the polarization switching time. It is shown that everything here depends on the position and displacement of the coercive field depending on the damping parameters of the system. These phenomena are very important for various ferroelectric coatings. Full article

Resorcin[4]arenes (R[4]A) are a group of macrocyclic compounds whose peculiar feature is the presence of eight hydroxyl groups in their structure. The directional formation of intramolecular hydrogen bonds with their participation leads to the formation of a cyclochiral racemic mixture of these compounds. Their stability strongly depends on the substituent and especially the environment in which they are located. The paper discusses the cyclochiral nature of aminomethylene derivatives of R[4]A (AMD-R[4]A). Their cyclochiral rigidity in non-polar solvents has been shown. The influence of the size of the alkyl groups in the amino substituents of AMD-R[4]A on their cyclochiral nature was noted. To calculate the reaction paths for their racemization, the nudged elastic band (NEB) method was employed using the semi-empirical DFT (GFN1-xTB) approach. The calculated activation barrier energies for their racemization in chloroform, obtained through various semi-empirical quantum chemical methods (SE), Hartree–Fock (HF), and density functionals theory (DFT), show good correlation with experimental observations. Among the tested methods, the B38LYP-D4 method is highly recommended due to its fast computational speed and accuracy, which is comparable to the time-consuming double-hybrid DH-revDSD-PBEP86 approach. Full article

In light of the escalating environmental concerns regarding pesticide accumulation, it is imperative to devise efficient strategies for their removal. Among the various options, activated carbons have emerged as promising candidates for adsorptive pesticide removal due to their many advantages, such as large surface area, well-developed porosity, and cost-effectiveness. However, the intricate relationship between the properties of these materials and their performance in pesticide adsorption remains largely unexplored. This study primarily focuses on examining the adsorption kinetics of three organophosphate pesticides: dimethoate, malathion (aliphatic), and chlorpyrifos (aromatic), using a range of cellulose-based activated carbon fibers with diverse specific surface areas, pore size distributions, and elemental compositions. By employing sophisticated data analysis tools, principal component analysis, and semi-empirical quantum chemical calculations, this study uncovers the importance of these distinct properties in efficiently removing structurally diverse pesticides. The results of the adsorption experiments suggested that these processes can be described using a pseudo-second-order kinetic model, which is confirmed via multiple linear regression. The obtained data suggest that the most effective carbon material for pesticide removal should have a pore diameter of approximately 4 nm, low oxygen content, a unimodal pore size distribution, and a high presence of sp² domains. The insights from this research have the potential to guide the development of improved adsorbents and facilitate the rational selection of adsorbents tailored to specific pollutants based on their physicochemical properties and the pollutants’ chemical structure. By shedding light on the vital connection between adsorbent properties and performance, our findings significantly advance sustainable and effective pesticide removal, thereby fostering a cleaner and healthier environment. Full article

Polymeric films made from chitosan (CS) doped with metal oxide (MO = cobalt (II) oxide and strontium oxide) nanoparticles at different concentrations (5, 10, 15, and 20% wt. MO/CS) were fabricated with the solution cast method. FTIR, SEM, and XRD spectra were used to study the structural features of those nanocomposite films. The FTIR spectra of chitosan showed the main characteristic peaks that are usually present, but they were shifted considerably by the chemical interaction with metal oxides. FTIR analysis of the hybrid chitosan-CoO nanocomposite exhibited notable peaks at 558 and 681 cm⁻¹. Conversely, the FTIR analysis of the chitosan-SrO composite displayed peaks at 733.23 cm⁻¹, 810.10 cm⁻¹, and 856.39 cm⁻¹, which can be attributed to the bending vibrations of Co-O and Sr-O bonds, respectively. In addition, the SEM graphs showed a noticeable morphological change on the surface of chitosan, which may be due to surface adsorption with metal oxide nanoparticles. The XRD pattern also revealed a clear change in the crystallinity of chitosan when it is in contact with metal oxide nanoparticles. The presence of characteristic signals for cobalt (Co) and strontium (Sr) are clearly shown in the EDX examinations, providing convincing evidence for their incorporation into the chitosan matrix. Moreover, the stability of the nanoparticle-chitosan coordinated bonding was verified from the accurate and broadly parametrized semi-empirical tight-binding quantum chemistry calculation. This leads to the determination of the structures’ chemical hardness as estimated from the frontier’s orbital calculations. We characterized the dielectric properties in terms of the real and imaginary dielectric permittivity as a function of frequency. Dielectric findings reveal the existence of extensive interactions of CoO and SrO, more pronounced for SrO, with the functional groups of CS through coordination bonding. This induces the charge transfer of the complexes between CoO and SrO and the CS chains and a decrease in the amount of the crystalline phase, as verified from the XRD patterns. Full article

This paper deals with the results of quantum chemical modeling of the monoacyl-sn-glycerol 2D cluster formation at the air/water interface using a semi-empirical PM3 method. The impact of the 2 or 3 positions of the acyl substituent on the thermodynamics of the monolayer formation is assessed for surfactants with an acyl substituent C_nH_2n+1COO chain length of n = 6–17 carbon atoms. The calculation shows a significant change in the spontaneous clusterization threshold for isomeric compounds, which differs only in the position of the acyl substituent with respect to the glycerol backbone. This change is almost equal to substituent shortening by approximately two methylene fragments. At the same time, the geometric parameters of the unit cell for resulting monolayers are not affected so drastically. The 2D films in question possess an oblique or orthorhombic unit cell with parameters for 2 and 3-monoacyl-sn-glycerol monolayers, as follows: a = 4.91 Å and 4.82 Å and b = 5.00 Å and 4.92 Å, with hydrocarbon chains tilted at t = 23.0° and 23.5°. The calculated results are in accordance with existing experimental data obtained using grazing incidence X-ray diffraction measurements and the π-A isotherm technique. Full article

Nonconventional luminescent materials (NLMs) which do not contain traditional aromatic chromophores are of great interest due to their unique chemical structures, optical properties, and their potential applications in various areas, such as cellular imaging and chemical sensing. However, most reported NLMs show weak or no emission in dilute solutions, which severely limits their applications. In this work, dynamic hydrogen bonds were utilized to design NLMs with efficient emission in dilute solutions. To further validate the results, polymers P1 and P2 were successfully prepared and investigated. It was found that the luminescence quantum efficiency of P1 and P2 at a concentration of 0.1 mg/mL in water solution was 8.9 and 0.6%, respectively. The high efficiency can be attributed to the fact that polymer P1 has more intra- or intermolecular dynamic hydrogen bonds and other short interactions than P2 in dilute solutions, allowing P1 to achieve the through-space conjugation effect to increase the degree of system conjugation, restrict molecular motion, and decrease nonradiative transitions, which can effectively improve luminescence. In addition, polymer P2 exhibits the characteristics of clustering-triggered emission, excitation wavelength-dependent and concentration-dependent fluorescence properties, excellent photobleaching resistance, low cytotoxicity, and selective recognition of Fe³⁺. The present study investigates the manipulation of luminescence properties of NLMs in dilute solutions through the modulation of dynamic hydrogen bonds. This approach can serve as a semi-empirical technique for designing and building innovative NLMs in the times ahead. Full article

Environment-friendly materials (e.g., Honey and Mint) are used as corrosion inhibitors for aluminum in hydrochloric acid (HCl) using both the density functional theory (DFT) at the B3LYP/6–31G* basis set level and semi-empirical methods (AM1, PM3, MINDO, and RM1). The aim of this study is to investigate the inhibition efficiency (%IE) in terms of their molecular structure. The quantum chemical parameters such as the highest occupied molecular orbital energy (E_HOMO), the lowest unoccupied molecular orbital energy (E_LUMO), the energy gap (ΔE), the charge on the reactive core, the hardness (η), and the total energy have all been computed. The MINDO method was used to measure the electronic energies and charge densities of the inhibitors that were used. Theoretical calculations were also carried out, with the findings correlating well with the experimental data. Gravimetry and gasometry measurements were used to investigate the effects of honey and mint on aluminum corrosion in a 1.0 M hydrochloric acid (HCl) solution. In acid solutions, honey and mint were found to be effective inhibitors of aluminum corrosion, with honey being the better option. Because of the adsorption of its components on aluminum surfaces, the inhibitory effect of the used inhibitors was addressed. The higher dipole moment of honey than that of mint caused the adsorption of honey on the aluminum surface better. The IEs measured by gravimetry and gasometry are almost identical. Full article

This article aims to review the application of various quantum chemical methods (semi-empirical, density functional theory (DFT), second order Møller–Plesset perturbation theory (MP2)) in the studies of cyclodextrin host–guest complexes. The details of applied approaches such as functionals, basis sets, dispersion corrections or solvent treatment methods are analyzed, pointing to the best possible options for such theoretical studies. Apart from reviewing the ways that the computations are usually performed, the reasons for such studies are presented and discussed. The successful applications of theoretical calculations are not limited to the determination of stable conformations but also include the prediction of thermodynamic properties as well as UV–Vis, IR, and NMR spectra. It has been shown that quantum chemical calculations, when applied to the studies of CD complexes, can provide results unobtainable by any other methods, both experimental and computational. Full article

The corannulene pincer (also known in the literature as the buckycatcher) is a fascinating system that may encapsulate, among other molecules, the $C_{60}$ and $C_{70}$ fullerenes. These complexes are held together by strong π-stacking interactions. Although these are quantum mechanical effects, their description by quantum chemical methods has proved very hard. We used three semi-empirical methods, PM6-D3H4X, PM6-D3H+ and GFN2-xTB, to model the interactions. Binding to fullerenes was extended to all open conformations of the buckycatcher, and with the proper choice of solvation model and partition functions, we obtained Gibbs free energies of binding that deviated by 1.0–1.5 kcal/mol from the experimental data. Adding three-body dispersion to PM6-D3H+ led to even better agreement. These results agree better with the experimental data than calculations using higher-level methods at a significantly lower fraction of the computational cost. Furthermore, the formation of adducts with $C_{60}$ was studied using dynamical simulations, which helped to build a more complete picture of the behavior of the corannulene pincer with fullerenes. We also investigated the use of exchange-binding models to recover more information on this system in solution. Though the final Gibbs free energies in solution were worsened, gas-phase enthalpies and entropies better mirrored the experimental data. Full article

The COVID-19 pandemic is still affecting many people worldwide and causing a heavy burden to global health. To eliminate the disease, SARS-CoV-2, the virus responsible for the pandemic, can be targeted in several ways. One of them is to inhibit the 2′-O-methyltransferase (nsp16) enzyme that is crucial for effective translation of viral RNA and virus replication. For methylation of substrates, nsp16 utilizes S-adenosyl methionine (SAM). Binding of a small molecule in the protein site where SAM binds can disrupt the synthesis of viral proteins and, as a result, the replication of the virus. Here, we performed high-throughput docking into the SAM-binding site of nsp16 for almost 40 thousand structures, prepared for compounds from three libraries: Enamine Coronavirus Library, Enamine Nucleoside Mimetics Library, and Chemdiv Nucleoside Analogue Library. For the top scoring ligands, semi-empirical quantum-chemical calculations were performed, to better estimate protein–ligand binding enthalpy. Relying upon the calculated binding energies and predicted docking poses, we selected 21 compounds for experimental testing. Full article

High-throughput computational screening (HTCS) is an effective tool to accelerate the discovery of active materials for Li-ion batteries. For the evaluation of organic cathode materials, the effectiveness of HTCS depends on the accuracy of the employed chemical descriptors and their computing cost. This work was focused on evaluating the performance of computational chemistry methods, including semi-empirical quantum mechanics (SEQM), density-functional tight-binding (DFTB), and density functional theory (DFT), for the prediction of the redox potentials of quinone-based cathode materials for Li-ion batteries. In addition, we evaluated the accuracy of three energy-related descriptors: (1) the redox reaction energy, (2) the lowest unoccupied molecular orbital (LUMO) energy of reactant molecules, and (3) the highest occupied molecular orbital (HOMO) energy of lithiated product molecules. Among them, the LUMO energy of the reactant compounds, regardless of the level of theory used for its calculation, showed the best performance as a descriptor for the prediction of experimental redox potentials. This finding contrasts with our earlier results on the calculation of quinone redox potentials in aqueous media for redox flow batteries, for which the redox reaction energy was the best descriptor. Furthermore, the combination of geometry optimization using low-level methods (e.g., SEQM or DFTB) followed by energy calculation with DFT yielded accuracy as good as the full optimization of geometry using the DFT calculations. Thus, the proposed calculation scheme is useful for both the optimum use of computational resources and the systematic generation of robust calculation data on quinone-based cathode compounds for the training of data-driven material discovery models. Full article