Journal of Molecular Modeling最新文献

Context

SO_x emissions from diesel fuel necessitate the development of efficient and environmentally friendly desulfurization technologies. This study investigates the catalyst-free photochemical desulfurization mechanism of a diesel model compound, 2-decyl-7-(10-phenyldecyl)dibenzo[b,d]thiophene (D-PD-DBT), under red light irradiation, providing a theoretical foundation for experimentally observed phenomena. Experimental validation confirmed a desulfurization efficiency of up to 46.2%, which was accompanied by the degradation of aromatic structures as observed by FTIR. The proposed three-step mechanism, elucidated computationally, reveals that population of the triplet state (T₁), likely via photosensitization from other chromophores in the diesel matrix, is the critical initiating step. This excited state drastically reduces the HOMO–LUMO gap and chemical hardness, facilitating the initial C–S bond cleavage. The reaction proceeds through the decomposition of intermediates, culminating in the formation of highly stable end products, including benzene, which thermodynamically drives the process to be unidirectional. These findings highlight the fundamental role of excited energy surfaces in enabling C–S bond cleavage without a catalyst.

Methods

All quantum chemical calculations were performed using density functional theory (DFT) at the B3LYP/6-31G level of theory. Excited state analyses were conducted using time-dependent DFT (TD-DFT) to map the photochemical reaction pathway. Reactant, intermediate, and product structures were geometrically optimized and confirmed as minima through harmonic frequency analysis. A set of conceptual DFT reactivity descriptors was calculated from the frontier molecular orbital energies (HOMO and LUMO). The Gaussian 09 software package was used for all computational modeling, with visualization performed using Gaussview and Avogadro.

Context

Quantitative structure–retention relationship is a key method for rapidly predicting the retention time of compounds. However, there have been few systematic studies on the application of QSRR to predict the retention time of phenolic acids, and there are many molecular descriptors and reference standards. This model utilized the experimental chromatographic retention parameter (t_R value) of ten phenolic acid compounds as the dependent variable, while the solubility energy of the compounds in water (E_W) and in methanol (E_M) served as the independent variables. A new QSRR method was established to predict the retention time of phenolic acid compounds, and the QSRR model maintained stable and good prediction performance under a variety of reasonable calculation methods. This study also investigates for the first time the impact of different computational methods under DFT on the accuracy of phenolic acid solvation energy calculations and the predictive performance of QSRR. This research has significantly improved the capability, efficiency, and reliability of theoretical studies, data analysis, and practical applications of phenolic acids throughout our entire field by establishing an optimal computational method. Statistical analysis showed no significant difference in prediction error between models built using the 6-31G basis set and larger, more computationally expensive methods, and the model has been validated to demonstrate good predictive performance. Therefore, using the 6-31G basis set for descriptor calculation is a highly cost-effective choice for phenolic acid QSRR studies.

Methods

HPLC was used to obtain the retention times of the compounds. GaussView 5.0 and Gaussian 09W were employed to perform structural optimization and molecular descriptor calculations for the corresponding compounds using different methods. Stepwise multiple linear regression fitting was then used to calculate the absolute values of the errors in the chromatographic retention parameters for each model. Paired sample t-tests were subsequently conducted to compare the effects of using different methods to calculate solubility on the model performance. The structure optimization was performed employing the DFT-RB3LYP method from the Gaussian09W package, with various calculation settings including 6-31G, 6-31G-D3, 6-31 +  + G-D3, 6-31G*, 6-31G*-D3, 6-31G**, 6-31G**-D3, 6-31 +  + G**-D3, 6-311G, 6-311G-D3, 6-311 +  + G-D3, 6-311G*, 6-311G*-D3, 6-311G**, 6-311G**-D3, and 6-311 +  + G** (a total of 16 different methods) that were calculated. The solubility energies (E_W and E_M) of the phenolic acids in water/methanol were calculated using the DFT-RB3LYP 6-311 +  + G**/methods for structural optimization.

Context

Spontaneous imbibition plays an important role in enhancing oil recovery for shale oil reservoirs after hydraulic fracturing. In this work, the spontaneous imbibition of the water-oil system in the hydroxylated silica nanoslit is investigated by the molecular dynamics simulation (MD) method. The effects of slit width, temperature, and surfactant on the imbibition behavior are mainly considered from the molecular level. Our results indicate that among the simulated slits with widths of 2 nm, 4 nm, 6 nm, and 8 nm, the medium-width slits of 4 nm and 6 nm are relatively better suited for the spontaneous imbibition of fluids. Meanwhile, the simulation results are in good agreement with those obtained by a modified LW model in the nanoslit. For the imbibition system with the same slit width, the imbibition efficiency of water can be significantly improved by increasing the temperature. This is because the high temperature increases the kinetic energy of the water molecules, making them easier to break the hydrogen bonds between the water molecules and the silica surface. In the imbibition systems containing different concentrations of surfactant molecules, the imbibition velocity is usually faster with the increase in surfactant concentration. Compared with pure water, surfactant aqueous solutions can generally promote imbibition. However, excessive concentrations of surfactant may have the opposite effect.

Method

The open-source software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) is used to perform the molecular dynamics calculations, and VMD (Visual Molecular Dynamics) software is used to visualize the simulation results. The intermolecular interactions are described by 12-6 Lennard–Jones and Coulombic potential functions. The Nosé-Hoover algorithm is used to control the temperature of the system. The periodic boundary condition is used for all simulations. The MD simulations are carried out over a time of 2 ns or 4 ns with a timestep of 1 fs under the NVT ensemble.

Context

This study employs density functional theory (DFT) to investigate the structural, electronic, transport, optical, and mechanical properties of cubic boron phosphide (c-BP), intending to elucidate its structure–property relationships. The findings reveal that c-BP exhibits an indirect bandgap of 1.93 eV. The valence band maximum (VBM) shows triple degeneracy and pronounced dispersion, resulting in the formation of light-hole bands that provide additional transport channels for holes. A notably high hole mobility of 888.34 cm²·V⁻¹·s⁻¹ is achieved, demonstrating excellent p-type transport characteristics. Furthermore, c-BP possesses very low dielectric loss, broad optical transparency, and mechanical properties characterized by high stiffness and brittleness. This research not only deepens the mechanistic understanding of c-BP’s multifunctional behavior but also provides theoretical underpinnings for the design of advanced semiconductor devices.

Methods

All calculations were performed within the density functional theory (DFT) framework implemented in the CASTEP code, employing norm-conserving pseudopotentials. Structural relaxation used the GGA-PW91 functional, while electronic and optical properties were computed with the HSE06 hybrid functional.

Context

A hybrid vibrational model is developed to study the thermal properties of ozone (O₃), using the molecular Pöschl-Teller (MPT) oscillator to describe the symmetric stretch mode, while treating the remaining vibrational modes with harmonic oscillators. Analytical expressions derived from the total partition function are used to compute key thermodynamic quantities: Gibbs free energy (ΔG), entropy (S), enthalpy (ΔH), and heat capacity at constant pressure (C_p). Model predictions are evaluated over a wide temperature range (300–6000 K) and compared against NASA Glenn polynomial estimates and NIST-JANAF reference data using the relative error in absolute percentage (REAP). The MPT model achieves mean REAP values of 0.107% for ΔG, 0.130% for S, 1.386% for ΔH, and 3.205% for C_p, demonstrating improved accuracy, especially at elevated temperatures. These results highlight the model’s enhanced ability to capture anharmonic vibrational effects in ozone, with relevance to atmospheric chemistry, combustion processes, and high-temperature aerospace applications.

Methods

The symmetric stretching vibration of O₃ is modeled using the molecular Pöschl-Teller (MPT) oscillator, while the bending and antisymmetric stretch modes are treated as harmonic oscillators. Rotational and translational motions are modeled using classical statistical mechanics. Closed-form expressions for the partition function and derived thermodynamic quantities are obtained analytically and evaluated across the 300–6000 K temperature range. Model performance is assessed using the relative error in absolute percentage (REAP) by comparing predictions with those from the NASA Glenn polynomial method and NIST-JANAF tabulations. All numerical evaluations and visualizations are performed using custom MATLAB scripts.

Introduction

Dengue virus (DENV) is a mosquito-borne disease that spreads in the tropics and subtropics mainly by the Aedes aegypti mosquito, infecting more than 100 million people every year and causing copious deaths every year. As of now, no direct-acting antiviral drugs or vaccines are available to combat DENV. Therefore, the identification of novel small molecules from natural origin becomes inevitable for the management of DENV fever. Here, fucoidan from Padina gymnospora was analyzed for competitive binding within the active site of nonstructural protein NS3 proteases selected as a potential therapeutic target for direct-acting antivirals.

Methodology

The 3D structure of fucoidan was retrieved from Pubchem and molecular targets was fetched from the Protein Data Bank. Molecular docking was performed with Glide module of Schrodinger and molecular dynamics was studied using GROMACS software. Further, density functional theory (DFT) analysis, ADME properties, and BOILED-egg plot analysis were also studied.

 Results and discussion

The fucoidan compound was docked with the active site of NS3 proteases, showing docking score variation between −6.458 and −7.483 kcal/mol and strong interaction with the catalytic dyad His51, Asp75, and Ser135 amino acids. Furthermore, binding free energy was calculated by using prime MM/GBSA to assess the binding affinity of fucoidan towards the target protein. Moreover, molecular dynamics simulation was performed to evaluate the structural stability of the docked complexes. In addition, the small HOMO-LUMO gap of −0.189 eV given by DFT analysis indicated the structural stability between the ligand and the protein. The fucoidan phytocompound has satisfied all the relevant pharmacokinetic properties and is also highly absorbed by the gastrointestinal tract.

Conclusion

From the overall findings of this study, it is concluded that the fucoidan from Padina gymnospora has effectively blocked the catalytic dyad of NS3 proteases, which could be considered a potent inhibitor to control the DENV multiplication infection.

Context

Hexanitrostilbene (HNS) is an explosive characterized by low mechanical sensitivity, high thermal stability, and excellent physicochemical and radiation resistance. It is widely used in both military and civilian applications. HNS-IV, known for its appropriate impact sensitivity to narrow pulse detonation, is currently the primary filling in shock wave detonators. However, due to the large specific surface area and high surface activity of ultrafine HNS-IV, it exhibits significant static electricity and poor flowability, which adversely affect the accuracy of its mass loading and subsequently density. To address the issues of poor flowability and moldability between ultrafine HNS-IV particles, this study utilized molecular dynamics simulations to select a high-performance, heat-resistant binder. Using this binder and graphite as an antistatic agent, a modified sample of ultrafine HNS-IV was prepared via the solvent evaporation method. The modified and unmodified samples were then subjected to comprehensive tests for morphology and composition, differential scanning calorimetry (DSC), repose angle, bulk density, explosion point, and charge amount.

Methods

Using molecular dynamics (MD) methods within the Materials Studio software, we computed the binding energies, initiation bond lengths, and mechanical properties of four types of polymer-bonded explosives (PBX) following a 1 ns NPT dynamic simulation. The MD simulation was conducted over a total duration of 1 ns with a time step of 1 fs. The simulations utilized the COMPASS force field, and the temperature was maintained at 298 K.

Context

While most studies on graphite intercalation compounds (GICs) as hydrogen storage materials use molecular dynamics and first principles approaches, few focus on the detailed hydrogen adsorption characteristics of the intercalators themselves. Usually, intercalators are divided into metals, halogens, and compounds. However, the hydrogen adsorption mechanisms of the common intercalators such as alkali metals Li and Na, halogen elements F, and compounds FeCl₃ have not yet been revealed. Therefore, we studied the microscopic interactions between Li, Na, F, FeCl₃ intercalators, and H₂, including charges, potentials, intermolecular forces, and molecular orbital mixing, using density functional theory (DFT). Our study results show that compared to current hydrogen storage materials like planar graphite, GICs have better hydrogen storage capacity due to their interlayer hydrogen adsorption properties. Each Li, Na, and F atom can adsorb 6 H₂, while 8 H₂ was adsorbed by the FeCl₃ molecule. Using Li and Na atoms as intercalators, GICs adsorb hydrogen through van der Waals forces with adsorption energy values of 0.15 eV and 0.16 eV, respectively, exhibiting a physical adsorption form. Using F atoms as intercalators, the adsorption energy is similar to alkali metals, and the adsorption form is also similar. However, F atoms gain charge from H₂ when adsorbing, which is opposite to the alkali metals losing charge characteristic. Using FeCl₃ as an intercalator, GICs have reached a maximum interlayer spacing distance of 9.40 Å, with an adsorption energy value of 1.06 eV, exhibiting a slight polarisation phenomenon. The adsorption form is a type of physical–chemical adsorption similar to metal dihydrogen complexes caused by Kubas coordination. By comparison, we found that FeCl₃ intercalators have the highest hydrogen adsorption energy and demonstrate considerable stability, making them the most promising intercalators for hydrogen adsorption among the four. In addition, compared to the strong chemical adsorption of H₂ by transition metals loaded at the boundary of carbon nanomaterials, FeCl₃ in the interlayer space evenly adsorbs each H₂ through physical–chemical adsorption, which helps to dissociate and release H₂.

Method

The GIC structure in this study was constructed and optimised using the Dmol3 module based on the GGA-PBE method from the Materials Studio 2020 software package. The hydrogen adsorption system was calculated using the Gaussian 09W software package based on the B3LYP functional with 6-31G * basis set, and metal elements were calculated using the SDD basis set. The charge transfer, electrostatic potential, and independent gradient model based on Hirshfeld partition and density of states are processed using the Multiwfn 3.8 package. All images are rendered using the VMD