Ab Initio Molecular Dynamics Simulation of Water Transport through Short Carbon Nanotubes

Point defect-mediated hot carrier relaxation dynamics of lead-free FASnI3 perovskites

In search of a promising optoelectronic performance, we herein investigated the hot carrier relaxation dynamics of a lead-free cubic phased bulk formamidinium tin triiodide (FASnI3) perovskite. To gain detailed theoretical insights, we should estimate the carrier relaxation dynamics of this pristine perovskite. To control the dynamics, point defects like central tin (Sn), iodine(I) anions, and formamidinium (FA) cations were introduced. With the iodine vacancy in the FASnI3 perovskite, the system seems to be unstable at room temperature, whereas the other three types of FASnI3 perovskites (pristine, Sn vacancy, and FA vacancy) are significantly stable at 300 K having semiconducting nature and excellent optical absorption in the UV-visible range. The computed electron-hole recombination time for the pristine system is 3.9 nanoseconds, which is in good agreement with the experimental investigation. The exciton relaxation processes in Sn and FA vacancy perovskites require 2.8 and 4.8 nanoseconds, respectively. These variations in the hot carrier relaxation dynamics processes are caused by the generation of significant changes in non-adiabatic coupling between energy levels, electron-phonon coupling, and quantum decoherence in different point defect analogous systems. The results presented here offer deeper insight into the temperature-dependent carrier relaxation dynamics of FASnI3 perovskites and thus open up opportunities for future exploration of their optoelectronic properties.

Design of MoS2 edge-anchored single-atom catalysts for propane dehydrogenation driven by DFT and microkinetic modeling

The design of efficient catalysts for direct propane dehydrogenation (PDH) to inhibit coke formation and deactivation of traditional Pt-based catalysts are challenging tasks. Herein, by exploiting the unique geometric feature and tunability of single atom catalysts (SACs), a wide range of 3d-5d transition metals anchored on the MoS2 edge in the single atom form (TM1-S4/edge) are comprehensively investigated for the PDH application by first-principles calculations, ab initio molecular dynamics (AIMD) simulations and microkinetic modeling. Five criteria are assessed in terms of the feasibility of preparation, practical stability, feasibility of recovery after air oxidation, activity and selectivity. We identified Ru1-S4/edge SAC as the most promising candidate with activity six times higher than that of the conventional Pt(111) catalyst. Interestingly, AIMD simulations show that the motif region of the highly reactive TM1-S4/edge SACs (such as Ru, Os, Rh, and Ir) exhibits a dynamic change, with a TM-coordinated S atom tending to flutter at reaction temperatures and return to its initial position when the species is adsorbed on TMs, thereby affecting the PDH activities. In addition to identifying the potential PDH catalyst from a practical application point of view, we believe that this study also provides a comprehensive picture for the theoretical screening of low-coordination single-atom catalysts.

Uniqueness of Nanoscale Confinement for Fast Water Transport: Effect of Nanotube Diameter and Hydrophobicity

Inspired by the enhanced water permeability of carbon nanotubes (CNTs), molecular dynamics simulations were performed to investigate the transport behavior through nanotubes made of boron nitride (BNNT), silicon carbide (SiC), and silicon nitride (SiN) alongside carbon nanotubes (which have different hydrophobic attributes) considering their implication for reverse osmosis (RO) membranes under different practical environments. According to our findings, not only do CNTs but also other kinds of nanotubes exhibit transition anomalies with increasing diameter. Utilizing the robust two-phase thermodynamic (2PT) methods, the current examinations shed light on thermodynamic origin of favorable water filling of these nanotubes. The results show that regardless of the nanotube material, the filling of water inside small nanopores (d < 10 Å) as well as within pores of diameter larger than 15 Å will always be favored by the entropy of filling. However, the entropic preference for filling nanotubes with a diameter of 10-15 Å depends on the constituent material. In particular, the enhancement in total entropy of confined water was mainly due to the increased rotational freedom of confined water molecules. The thermodynamic origin of water transport was correlated with the structural and fluidic behavior of water inside these nanotubes. The observed data for density, flow, structure correlation functions, water-water coordination, tetrahedral order parameter, hydrogen bonds, and density of states functions quantitatively support the observed entropy behavior. Of critical importance is that the present study demonstrates the effectiveness of RO filtration using nanotubes of boron nitride rather than carbon. Furthermore, it was found that one should avoid the use of silicon nanotubes unless filtration needs to be performed under harsh environments where nanotube of other materials cannot survive. Specifically, the results show that both the structural and dynamic properties of water confined in BNNTs are similar to those of CNT's, and for SiNT it is similar as SiC. Our results show that besides the nanotube material, the chirality index of the nanotube also plays a significant role in determining the structure, dynamics and thermodynamics of confined water molecules.

Modeling water transport properties in carbon nanotubes: Interplay between force-field flexibility and geometrical parameters

Modeling water and other liquids in computational simulations requires a large set of parameters. Many works have been devoted to finding new, improved water models, with almost all of them designed for bulk systems. Here, we use carbon nanotubes as a play model to investigate the effects of introducing flexibility in water force fields during molecular dynamics simulations of nanoconfined water. We explore six different models to show that viscosity, diffusion, and dipole orientation are vastly influenced by the flexibility and the family of force fields used. Particularly, we found the level of confinement (decreasing the nanotube's diameter) to increase discrepancies in the description of the dipole alignment. In smaller (10,10) nanotubes, the flexible version of the transferable intermolecular potential with three points (TIP3P/Fs) features a high directionality, while its rigid counterpart shows a more distributed dipole orientation. Both viscosity and diffusion are also extremely dependent on the force-field family, with the flexible version of the simple point charge (SPC/Fw) featuring the lower confidence interval.

Transferability evaluation of the deep potential model for simulating water-graphene confined system

Machine learning potentials (MLPs) are poised to combine the accuracy of ab initio predictions with the computational efficiency of classical molecular dynamics (MD) simulation. While great progress has been made over the last two decades in developing MLPs, there is still much to be done to evaluate their model transferability and facilitate their development. In this work, we construct two deep potential (DP) models for liquid water near graphene surfaces, Model S and Model F, with the latter having more training data. A concurrent learning algorithm (DP-GEN) is adopted to explore the configurational space beyond the scope of conventional ab initio MD simulation. By examining the performance of Model S, we find that an accurate prediction of atomic force does not imply an accurate prediction of system energy. The deviation from the relative atomic force alone is insufficient to assess the accuracy of the DP models. Based on the performance of Model F, we propose that the relative magnitude of the model deviation and the corresponding root-mean-square error of the original test dataset, including energy and atomic force, can serve as an indicator for evaluating the accuracy of the model prediction for a given structure, which is particularly applicable for large systems where density functional theory calculations are infeasible. In addition to the prediction accuracy of the model described above, we also briefly discuss simulation stability and its relationship to the former. Both are important aspects in assessing the transferability of the MLP model.