Molecular simulations of interfacial systems: challenges, applications and future perspectives

Imidazole[1,5-a]pyridine derivatives as EGFR tyrosine kinase inhibitors unraveled by umbrella sampling and steered molecular dynamics simulations

Although the use of the tyrosine kinase inhibitors (TKIs) has been proved that it can save live in a cancer treatment, the currently used drugs bring in many undesirable side-effects. Therefore, the search for new drugs and an evaluation of their efficiency are intensively carried out. Recently, a series of eighteen imidazole[1,5-a]pyridine derivatives were synthetized by us, and preliminary analyses pointed out their potential to be an important platform for pharmaceutical development owing to their promising actions as anticancer agents and enzyme (kinase, HIV-protease,…) inhibitors. In the present theoretical study, we further analyzed their efficiency in using a realistic scenario of computational drug design. Our protocol has been developed to not only observe the atomistic interaction between the EGFR protein and our 18 novel compounds using both umbrella sampling and steered molecular dynamics simulations, but also determine their absolute binding free energies. Calculated properties of the 18 novel compounds were in detail compared with those of two known drugs, erlotinib and osimertinib, currently used in cancer treatment. Inspiringly the simulation results promote three imidazole[1,5-a]pyridine derivatives as promising inhibitors into a further step of clinical trials.

On the Statistical Mechanics of Mass Accommodation at Liquid-Vapor Interfaces

We propose a framework for describing the dynamics associated with the adsorption of small molecules to liquid-vapor interfaces using an intermediate resolution between traditional continuum theories that are bereft of molecular detail and molecular dynamics simulations that are replete with them. In particular, we develop an effective single particle equation of motion capable of describing the physical processes that determine thermal and mass accommodation probabilities. The effective equation is parametrized with quantities that vary through space away from the liquid-vapor interface. Of particular importance in describing the early time dynamics is the spatially dependent friction, for which we propose a numerical scheme to evaluate from molecular simulation. Taken together with potentials of mean force computable with importance sampling methods, we illustrate how to compute the mass accommodation coefficient and residence time distribution. Throughout, we highlight the case of ozone adsorption in aqueous solutions and its dependence on electrolyte composition.

Study on the Transport Properties of SO2 and NO at the Interface of H2O2 Solutions Using Molecular Dynamics

Gas-liquid interfaces have a unique structure different from the bulk phase due to the complex intermolecular interactions within them and are regarded as barriers that prevent gases from entering solution or as channels that affect gas reactions. In this study, the adsorption and mass-transfer mechanisms of sulfur dioxide and nitric oxide at the gas-liquid interface of a H2O2 solution were comprehensively analyzed using molecular dynamics (MD) simulations. The analysis on molecule angle showed that H2O molecules tended to align parallel to the solution surface on the surface of the H2O2 solution. Regardless of whether the gas was adsorbed on the surface of the solution or not, H2O2 molecules were always perpendicular to the interface of the solution. The analysis on molecule angle and radial distribution function revealed that the H atoms of H2O molecules had a corresponding turn, and SO2 molecules were greatly affected by the attraction of H2O2 molecules during the adsorption of gas molecules on the interface. Steered MD was utilized to investigate the mass-transfer process of SO2 and NO molecules across the gas-liquid interface. The S atoms of SO2 molecules were significantly influenced by H2O2 molecules, while the O atoms of NO molecules gradually transitioned from the gas phase to the liquid phase. The results provided information on how gas molecules interacted with the surface of the solution and the specific details of the molecular orientation at the solution surface.

The molecular scale mechanism of deposition ice nucleation on silver iodide

Heterogeneous ice nucleation is a ubiquitous process in the natural and built environment. Deposition ice nucleation, i.e. heterogeneous ice nucleation that - according to the traditional view - occurs in a subsaturated water vapor environment and in the absence of supercooled water on the solid, ice-forming surface, is among the most important ice formation processes in high-altitude cirrus and mixed-phase clouds. Despite its importance, very little is known about the mechanism of deposition ice nucleation at the microscopic level. This study puts forward an adsorption-based mechanism for deposition ice nucleation through results from a combination of atomistic simulations, experiments and theoretical modelling. One of the most potent laboratory surrogates of ice nucleating particles, silver iodide, is used as a substrate for the simulations. We find that water initially adsorbs in clusters which merge and grow over time to form layers of supercooled water. Ice nucleation on silver iodide requires at minimum the adsorption of 4 molecular layers of water. Guided by the simulations we propose the following fundamental freezing steps: (1) Water molecules adsorb on the surface, forming nanodroplets. (2) The supercooled water nanodroplets merge into a continuous multilayer when they grow to about 3 molecular layers thick. (3) The layer continues to grow until the critical thickness for freezing is reached. (4) The critical ice cluster continues to grow.

Mechanism Analysis and Property Prediction of Extended Surfactants Based on the Respectively Optimized Force Field

Extended surfactants represent a novel class of anionic-nonionic surfactants with exceptional performance and unique application value in chemically enhanced oil recovery. Although molecular dynamics (MD) simulations can efficiently screen these surfactants, the current research is limited. Here, it is proven for the first time that existing generic force fields (GAFF and CHARMM) cannot accurately describe extended surfactants, and traditional approaches are insufficient for obtaining precise charge parameters. The concept of the respectively optimized force field (ROFF) with the purports of specialization and accuracy is proposed to construct high-accuracy models for MD simulations, and a new approach is developed to simulate the interface model. By combining the newly specialized alkane model, ROFF-based surfactant models, and the innovative simulation protocol, high accuracy and reliability can be obtained in predicting hydration free energies, minimum of area per molecule, and critical micelle concentration of extended surfactants. Key properties of the newly designed extended surfactants in conventional oil-water interfaces and oil reservoir environments are comprehensively predicted by using advanced analytical and characterization methods. Furthermore, the more rigorous mechanism underlying the special amphiphilicity of the extended surfactant is revealed, potentially offering significant improvements over previous empirical perspectives.

Gas-liquid interface of a Lennard-Jones binary mixture controlled by differential activity: phase transition and interfacial stability

We perform molecular dynamics simulations of a two-dimensional binary mixture of Lennard-Jones particles, characterized by some degree of "activity" inside. Starting from a base state that features a gas-liquid interface and a completely segregated system at thermodynamic equilibrium, we introduce differential scalar activity between the two species by prescribing two different effective temperatures. The differential activity is measured as the ratio of the two temperatures. Previous studies showed segregation in a homogeneously mixed system induced by high activity. In this study, we investigate the effect of activity on a pre-existing gas-liquid interface between two separated species. Whereas a high activity ratio induces the formation of new interfaces, we show that a low activity ratio destabilizes existing ones. Moreover, the combination of a pre-existent interface with differential activity leads to partial crystallization and thus to triple phase coexistence (solid, liquid and gas), which is observed over a wide range of moderate differential activities. Findings from this idealized system can guide our understanding of interfacial behaviors in certain biological systems.

Absorption of Volatile Organic Compounds Toluene and Acetaldehyde in Choline Chloride-Based Deep Eutectic Solvents

Unrestricted emission of volatile organic compounds (VOCs)─a threat to human health and the environment─can be controlled to a large extent by the capturing mechanism. Few recent experimental studies explored the efficacy of the deep eutectic solvent (DES), a designer solvent with some fascinating properties, as a VOC-capturing medium. Through the partition coefficient measurement, it was found that the choline chloride-based DESs exhibit excellent VOC-capturing potencies. However, a molecular picture of the above absorption process is still lacking. Here, we study the molecular mechanism of the absorption of two commonly occurring VOCs, toluene and acetaldehyde, in two different choline chloride-based DESs with varying donor molecules, urea, and levulinic acid via the molecular dynamics simulation technique. Strong absorption of the VOCs is observed in both the DESs. The free energy profile for the absorption process has been explored using the umbrella sampling method. The VOCs are preferentially solvated near the liquid/vapor interface. The simulated partition coefficients for the VOCs from the vapor to the liquid phase show good agreement with the experimental results. Detailed analyses of the spatial and orientational structure of the VOCs and different components of DESs are performed to elucidate the interaction among them. The above analyses have indicated that DES is a better VOC-capturing medium compared to a room-temperature ionic liquid, which is more extensively studied in the literature.

DPD Simulation on the Transformation and Stability of O/W and W/O Microemulsions

The dissipative particle dynamics simulation method is adopted to investigate the microemulsion systems prepared with surfactant (H1T1), oil (O) and water (W), which are expressed by coarse-grained models. Two topologies of O/W and W/O microemulsions are simulated with various oil and water ratios. Inverse W/O microemulsion transform to O/W microemulsion by decreasing the ratio of oil-water from 3:1 to 1:3. The stability of O/W and W/O microemulsion is controlled by shear rate, inorganic salt and the temperature, and the corresponding results are analyzed by the translucent three-dimensional structure, the mean interfacial tension and end-to-end distance of H1T1. The results show that W/O microemulsion is more stable than O/W microemulsion to resist higher inorganic salt concentration, shear rate and temperature. This investigation provides a powerful tool to predict the structure and the stability of various microemulsion systems, which is of great importance to developing new multifunctional microemulsions for multiple applications.

Computer Simulation of the Surface of Aqueous Ionic and Surfactant Solutions

The surface of aqueous solutions of simple salts was not the main focus of scientific attention for a long while. Considerable interest in studying such systems has only emerged in the past two decades, following the pioneering finding that large halide ions, such as I^-, exhibit considerable surface affinity. Since then, a number of issues have been clarified; however, there are still several unresolved points (e.g., the effect of various salts on lateral water diffusion at the surface) in this respect. Computer simulation studies of the field have largely benefited from the appearance of intrinsic surface analysis methods, by which the particles staying right at the boundary of the two phases can be unambiguously identified. Considering complex ions instead of simple ones opens a number of interesting questions, both from the theoretical point of view and from that of the applications. Besides reviewing the state-of-the-art of intrinsic surface analysis methods as well as the most important advances and open questions concerning the surface of simple ionic solutions, we focus on two such systems in this Perspective, namely, the surface of aqueous mixtures of room temperature ionic liquids and that of ionic surfactants. In the case of the former systems, for which computer simulation studies have still scarcely been reported, we summarize the theoretical advances that could trigger such investigations, which might well be of importance also from the point of view of industrial applications. Computer simulation methods are, on the other hand, widely used in studies of the surface of surfactant solutions. Here we review the most important theoretical advances and issues to be addressed and discuss two areas of applications, namely, the inclusion of information gathered from such simulations in large scale atmospheric models and the better understanding of the airborne transmission of viruses, such as SARS-CoV-2.

Data-Centric Architecture for Self-Driving Laboratories with Autonomous Discovery of New Nanomaterials

Artificial intelligence (AI) approaches continue to spread in almost every research and technology branch. However, a simple adaptation of AI methods and algorithms successfully exploited in one area to another field may face unexpected problems. Accelerating the discovery of new functional materials in chemical self-driving laboratories has an essential dependence on previous experimenters' experience. Self-driving laboratories help automate and intellectualize processes involved in discovering nanomaterials with required parameters that are difficult to transfer to AI-driven systems straightforwardly. It is not easy to find a suitable design method for self-driving laboratory implementation. In this case, the most appropriate way to implement is by creating and customizing a specific adaptive digital-centric automated laboratory with a data fusion approach that can reproduce a real experimenter's behavior. This paper analyzes the workflow of autonomous experimentation in the self-driving laboratory and distinguishes the core structure of such a laboratory, including sensing technologies. We propose a novel data-centric research strategy and multilevel data flow architecture for self-driving laboratories with the autonomous discovery of new functional nanomaterials.