Nano computational modeling

Due to the very demanding and surprising features of nanomaterials and nanosystems, nanoscience and nanotechnology have risen to the forefront of a wide range of research topics in recent decades. Nanomaterials in various forms (0D, 1D, 2D, 3D) and phases or nanosystems can be used in a wide range of applications, from biomedical to industrial engineering, thanks to these features. Furthermore, these resources frequently serve as an interdisciplinary link between many scientific and technological fields. Models and simulations combined, when accounting for the effects of numerous processes occurring at the nanoscale, tend to highlight unsolved challenges while permitting remarkable breakthroughs that drive forward the wide spectrum of nanostructured materials-based technologies. By addressing the blind spots of current empirical models, computational and mathematical modelling tools have shown promise as a promising strategy for broadening the horizon of nanomedicine.

• Carbon Nanotube Nanocomposites
• Coupled, Multi-Physics Problems
• Machine Learning and Artificial Intelligence
• Mathematical Modelling
• Mesoscopic/Macroscopic Formulations
• Modelling Of Nanophase Separations
• Multi-Scale Computational Approaches
• Nano-Bio Interactions Modelling
• Numerical Studies of Nanocrystals and Nanocomposites
• Physical Nanomaterial Models for Experimental Design and Characterization
• Quantitative Structure-Activity Relationship (QSAR)
• Quantitative Structure-Property Relationship (QSPR)