In this work, we present a deep collocation method (DCM) for three-dimensional potential problems in non-homogeneous media. This approach utilizes a physics-informed neural network with material transfer learning reducing ...

In machine learning, if the training data is independently and identically distributed as the test data then a trained model can make an accurate predictions for new samples of data. Conventional machine learning has a ...

Machine learning (ML) methods have shown powerful performance in different application. Nonetheless, designing ML models remains a challenge and requires further research as most procedures adopt a trial and error strategy. ...

Recently, benzotrithiophene graphdiyne (BTT-GDY), a novel two-dimensional (2D) carbon-based material, was grown via a bottom-up synthesis strategy. Using the BTT-GDY lattice and by replacing the S atoms with N, NH and O, ...

Density functional theory calculations are robust tools to explore the mechanical properties of pristine structures at their ground state but become exceedingly expensive for large systems at finite temperatures. Classical ...

The mechanical analog to the topological insulators brings anomalous elastic wave properties which diversifies classic wave functions for potential broad applications. To obtain topological mechanical wave states with good ...

Non-aqueous reactive foamed polyurethanes are widely used in the non-excavation rehabilitation of infrastructures and fundamental engineering. However, the effect of a microscopic cell on the understanding of micro-mechanical ...

In this work, extensive reactive molecular dynamics simulations are conducted to analyze the nanopore creation by nanoparticles impact over single-layer molybdenum disulfide (MoS2) with 1T and 2H phases. We also compare ...

Machine-learning (ML) models are novel and robust tools to establish structure-to-property connection on the basis of computationally expensive ab-initio datasets. For advanced technologies, predicting novel materials and ...

We propose a surrogate model for two-scale computational homogenization of elastostatics at finite strains. The macroscopic constitutive law is made numerically available via an explicit formulation of the associated ...