Structural localization in the classical and quantum Fermi-Pasta-Ulam model

In-silico study on perovskites application in capturing and distorting coronavirus

The COVID-19 pandemic, known as coronavirus pandemic, a global pandemic, emerged from the beginning of 2020 and became dominant in many countries. As COVID-19 is one of the deadliest pandemics in history and has a high rate of distribution, a fast and extensive reaction was needed. Considering its composition, revealing the infection mechanism is beneficial for effective decisions against the spread and attack of COVID-19. Investigating data from numerous studies confirms that the penetration of SARS-CoV-2 occurs along with bonding spike protein (S protein) and through ACE2; Therefore, these two parts were the focus of research on the suppression and control of the infection. Performing lab research on all promising candidates requires years of experimental study, which is time-consuming and not an acceptable solution. Molecular dynamic simulation can decipher the performance of nano-structures in preventing the spread of coronavirus in a shorter time. This study surveyed the effect of three nano-perovskite structures (SrTiO3, CaTiO3, and BaTiO3), a cutting-edge group of perovskite materials with outstanding properties on coronavirus. Various computational parameters evaluate the effectiveness of these structures. Results of the simulation indicated that SrTiO3 performs better in SARS-CoV-2 suppression.

Introducing Memory in Coarse-Grained Molecular Simulations

Preserving the correct dynamics at the coarse-grained (CG) level is a pressing problem in the development of systematic CG models in soft matter simulation. Starting from the seminal idea of simple time-scale mapping, there have been many efforts over the years toward establishing a meticulous connection between the CG and fine-grained (FG) dynamics based on fundamental statistical mechanics approaches. One of the most successful attempts in this context has been the development of CG models based on the Mori-Zwanzig (MZ) theory, where the resulting equation of motion has the form of a generalized Langevin equation (GLE) and closely preserves the underlying FG dynamics. In this Review, we describe some of the recent studies in this regard. We focus on the construction and simulation of dynamically consistent systematic CG models based on the GLE, both in the simple Markovian limit and the non-Markovian case. Some recent studies of physical effects of memory are also discussed. The Review is aimed at summarizing recent developments in the field while highlighting the major challenges and possible future directions.