Characterization of graphene–fullerene interactions: Insights from density functional theory

Exploring Antiviral Drugs on Monolayer Black Phosphorene: Atomistic Theory and Explainable Machine Learning-Assisted Platform

Favipiravir (FP) and ebselen (EB) belong to a diverse class of antiviral drugs known for their significant efficacy in treating various viral infections. Utilizing molecular dynamics (MD) simulations, machine learning, and van der Waals density functional theory, we accurately elucidate the binding properties of these antiviral drugs on a phosphorene single-layer. To further investigate these characteristics, this study employs four distinct machine learning models-Random Forest, Gradient Boosting, XGBoost, and CatBoost. The Hamiltonian of antiviral molecules within a monolayer of phosphorene is appropriately trained. The key aspect of utilizing machine learning (ML) in drug design revolves around training models that are efficient and precise in approximating density functional theory (DFT). Furthermore, the study employs SHAP (SHapley Additive exPlanations) to elucidate model predictions, providing insights into the contribution of each feature. To explore the interaction characteristics and thermodynamic properties of the hybrid drug, we employ molecular dynamics and DFT calculations in a vacuum interface. Our findings suggest that this functionalized 2D complex exhibits robust thermostability, indicating its potential as an effective and enabled entity. The observed variations in free energy at different surface charges and temperatures suggest the adsorption potential of FP and EB molecules from the surrounding environment.

Synergy of Small Antiviral Molecules on a Black-Phosphorus Nanocarrier: Machine Learning and Quantum Chemical Simulation Insights

Favipiravir (FP) and Ebselen (EB) belong to a broad range of antiviral drugs that have shown active potential as medications against many viruses. Employing molecular dynamics simulations and machine learning (ML) combined with van der Waals density functional theory, we have uncovered the binding characteristics of these two antiviral drugs on a phosphorene nanocarrier. Herein, by using four different machine learning models (i.e., Bagged Trees, Gaussian Process Regression (GPR), Support Vector Regression (SVR), and Regression Trees (RT)), the Hamiltonian and the interaction energy of antiviral molecules in a phosphorene monolayer are trained in an appropriate way. However, training efficient and accurate models for approximating the density functional theory (DFT) is the final step in using ML to aid in the design of new drugs. To improve the prediction accuracy, the Bayesian optimization approach has been employed to optimize the GPR, SVR, RT, and BT models. Results revealed that the GPR model obtained superior prediction performance with an R2 of 0.9649, indicating that it can explain 96.49% of the data's variability. Then, by means of DFT calculations, we examine the interaction characteristics and thermodynamic properties in a vacuum and a continuum solvent interface. These results illustrate that the hybrid drug is an enabled, functionalized 2D complex with vigorous thermostability. The change in Gibbs free energy at different surface charges and temperatures implies that the FP and EB molecules are allowed to adsorb from the gas phase onto the 2D monolayer at different pH conditions and high temperatures. The results reveal a valuable antiviral drug therapy loaded by 2D biomaterials that may possibly open a new way of auto-treating different diseases, such as SARS-CoV, in primary terms.

Computational Studies of Auto-Active van der Waals Interaction Molecules on Ultra-Thin Black-Phosphorus Film

Using the van der Waals density functional theory, we studied the binding peculiarities of favipiravir (FP) and ebselen (EB) molecules on a monolayer of black phosphorene (BP). We systematically examined the interaction characteristics and thermodynamic properties in a vacuum and a continuum, solvent interface for active drug therapy. These results illustrate that the hybrid molecules are enabled functionalized two-dimensional (2D) complex systems with a vigorous thermostability. We demonstrate in this study that these molecules remain flat on the monolayer BP system and phosphorus atoms are intact. It is inferred that the hybrid FP+EB molecules show larger adsorption energy due to the van der Waals forces and planar electrostatic interactions. The changes in Gibbs free energy at different surface charge fluctuations and temperatures imply that the FP and EB are allowed to adsorb from the gas phase onto the 2D film at high temperatures. Thereby, the results unveiled beneficial inhibitor molecules on two dimensional BP nanocarriers, potentially introducing a modern strategy to enhance the development of advanced materials, biotechnology, and nanomedicine.

Role of Stone-Wales defects on the interfacial interactions among graphene, carbon nanotubes, and Nylon 6: A first-principles study

We investigate computationally the role of Stone-Wales (SW) defects on the interfacial interactions among graphene, carbon nanotubes (CNTs), and Nylon 6 using density functional theory (DFT) and the empirical force-field. Our first-principles DFT calculations were performed using the Quantum ESPRESSO electronic structure code with the highly accurate van der Waals functional (vdW-DF2). Both pristine and SW-defected carbon nanomaterials were investigated. The computed results show that the presence of SW defects on CNTs weakens the CNT-graphene interactions. Our result that CNT-graphene interaction is much stronger than CNT-CNT interaction indicates that graphene would be able to promote the dispersion of CNTs in the polymer matrix. Our results demonstrate that carbon nanomaterials form stable complexes with Nylon 6 and that the van der Waals interactions, as revealed by the electronic charge density difference maps, play a key stabilizing role on the interfacial interactions among graphene, CNTs, and Nylon 6. Using the density of states calculations, we observed that the bandgaps of graphene and CNTs were not significantly modified due to their interactions with Nylon 6. The Young's moduli of complexes were found to be the averages of the moduli of their individual constituents.

Does C60 fullerene act as a transporter of small aromatic molecules?

C₆₀ fullerene is reported to directly interact with biomolecules, such as aromatic mutagens or anticancer drugs. Therefore, it is extensively studied for its potential application in the fields of drug delivery and chemoprevention. Understanding the nature of fullerene-drugs interactions might contribute to optimization and modification of the existing chemotherapy systems. Possible interactions between ICR-191, a model acridine mutagen, with well-established biophysical properties and mutagenic activity, and C₆₀ fullerene aqueous solution were investigated by broad range of biophysical methods, such as Dynamic Light Scattering, Isothermal Titration Calorimetry, and Atomic Force Microscopy. Additionally, to determine biological activity of ICR-191-C₆₀ fullerene mixtures, Ames mutagenicity test was employed. It was demonstrated that C₆₀ fullerene interacts non-covalently with ICR-191 and has strong affinity to bacterial membranes. The obtained results provide practical insight into C₆₀ fullerene interactions with aromatic compounds.

Optoelectronic Properties of Van Der Waals Hybrid Structures: Fullerenes on Graphene Nanoribbons

The search for new optical materials capable of absorbing light in the frequency range from visible to near infrared is of great importance for applications in optoelectronic devices. In this paper, we report a theoretical study of the electronic and optical properties of hybrid structures composed of fullerenes adsorbed on graphene and on graphene nanoribbons. The calculations are performed in the framework of the density functional theory including the van der Waals dispersive interactions. We found that the adsorption of the C 60 fullerenes on a graphene layer does not modify its low energy states, but it has strong consequences for its optical spectrum, introducing new absorption peaks in the visible energy region. The optical absorption of fullerenes and graphene nanoribbon composites shows a strong dependence on photon polarization and geometrical characteristics of the hybrid systems, covering a broad range of energies. We show that an external electric field across the nanoribbon edges can be used to tune different optical transitions coming from nanoribbon-fullerene hybridized states, which yields a very rich electro-absorption spectrum for longitudinally polarized photons. We have carried out a qualitative analysis on the potential of these hybrids as possible donor-acceptor systems in photovoltaic cells.

Design of Assembled Systems Based on Conjugated Polyphenylene Derivatives and Carbon Nanohorns

Promising materials have been designed and fully characterised by an effective interaction between versatile platforms such as carbon nanohorns (CNHs) and conjugated molecules based on thiophene derivatives. Easy and non-aggressive methods have been described for the synthesis and purification of the final systems. Oligothiophenephenylvinylene (OTP) systems with different geometries and electron density are coupled to the CNHs. A wide range of characterization techniques have been used to confirm the effective interaction between the donor (OTP) and the acceptor (CNH) systems. These hybrid materials show potential for integration into solar cell devices. Importantly, surface-enhanced Raman spectroscopy (SERS) effects are observed without the presence of any metal surface in the system. Theoretical calculations have been performed to study the optimised geometries of the noncovalent interaction between the surface and the organic molecule. The calculations allow information on the monoelectronic energies of HOMO-LUMO orbitals and band gap of different donor systems to be extracted.