Convergence Acceleration in Machine Learning Potentials for Atomistic Simulations

Machine learning potentials (MLPs) for atomistic simulations have an enormous prospective impact on materials modeling, offering orders of magnitude speedup over density functional theory (DFT) calculations without appreciably sacrificing accuracy...

Oligomeric approach to 2D materials modeling

Oligomeric approach has been originally developed to study electronic properties of conjugated polymers. This approach allows to access electronic properties of 1D systems otherwise difficult to calculate. We successfully extended this method to study electronic properties of 2D materials. In this review we summarize our recent work in this area. It has been established that large graphene nanoflake possess multiconfigurational singlet or even high spin ground state. Doping of 2D systems has also been explored and it has been demonstrated that doping allows to tune their electronic properties, including ionization potentials, electron affinities, reorganization energies and the very nature of the ground state. The electronic properties of novel 2D allotropies of carbon, phosphorus, germanium and silicon have been studied as well as their complexes with Li. Heterostructures, of different 2D allotropies are readily formed. This is an alternative method for tuning of their electronic properties.

Piezoelectric Energy Harvesting: A Systematic Review of Reviews

In the last decade, an enormous amount of attention has been paid to piezoelectric harvesters due to their flexibility in design and the increasing need for small-scale energy generation. As a result, various energy review papers have been presented by many researchers to cover different aspects of piezoelectric-based energy harvesting, including piezo-materials, modeling approaches, and design points for various applications. Most of these papers have tried to shed light on recent progress in related interdisciplinary fields, and to pave the road for future prospects in the development of these technologies. However, there are some missing parts, overlaps, and even some contradictions in these review papers. In the present review of these review articles, recommendations for future research directions suggested by the review papers have been systematically summed up under one umbrella. In the final section, topics for missing review papers, concluding remarks on outlooks and possible research topics, as well as potentially misleading strategies, have been presented. The review papers have been evaluated based on their merits and subcategories and the authors’ choice papers have been presented for each section based on clear classification criteria.

Investigation of the transport properties for saline water in porous materials - Modeling of the permeability coefficient for saline water-

Salt weathering is a major concern for cultural heritages such as ruins and tombs, and desalination by poulticing is an interesting potential method to efficiently remove contaminating salt. Predicting the degree of achievable desalination is very important. However, many existing models used to consider saline water transport in porous materials have been developed based on the theory of pure water. To understand saline water flow in porous materials, we determined the saline water permeability of a tuff stone by the falling-head method. We found that the permeability of the tuff stone was affected by factors other than the density and dynamic viscosity of the saline water.

Memristive Equivalent Circuit Model for Battery

The design of mathematical models is based on conservation laws and also on the fundamental principles of modeling: structure, parameters, and physical meaning. Those kinds of modeling should have specific capabilities to deal with different working conditions and environments coping with challenges that include but are not limited to battery capacity, life-cycle, or the attempts to manipulate the current profiles during operation. Introducing memristive elements in batteries will be ideal to satisfy these fundamentals and goals of modeling, whereas addressing the recycling and sustainability concerns on the environmental impact by the placement of TiO2 memristor into this model can promote a recovery hierarchy via recycling and dispatching a slight amount to disposal as the previous focus was mainly concentrated on availability. As for battery materials, modeling, performing, and manufacturing all have proliferated to grasp the possible sustainability challenges inherited in these systems. This paper investigated electrochemical impedance spectroscopy to study this model and the dynamic behavior inside the battery. We found a solution to address the existing battery limitations that elucidate the battery degradation without affecting the performance, correspondingly by employing the dampest least-squares combination with nonlinear autoregressive exogenous for identifying such model and its associated parameters because of its embedded memory and fast convergence to diminish the influence of the vanishing gradient. Lastly, we found that this model is proven to be efficient and accurate compared to actual experimented data to validate our theory and show the value of the proposed model in real life while assuming Normal Gaussian distribution of data error with outstanding results; the auto-correlations were within the 95% confidence limit, the best validation was 2.7877, and an overall regression of 0.99993 was achieved.