Editorial: Nanofluidics: computational methods and applications

Filippos Sofos*, Konstantinos Ritos*, Aggelos Avramopoulos*

*Corresponding author for this work

Research output: Contribution to journalEditorialpeer-review

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Abstract

This Research Topic from Frontiers in Nanotechnology, “Nanofluidics: Computational Methods and Applications”, presents computational, analytical, simulation and experimental techniques aimed at advancing our understanding of nanofluidic phenomena and paving the way for novel applications that can play a leading role in today’s technology. With a Research Topic of four studies, the reader will find i) an interesting paper presenting the novel use of single-layer MoS2 nanopores as sensors for the identification of biomarkers, ii) a seminal paper using various machine learning and deep learning methods to reproduce particle trajectories from molecular dynamics simulations taking into account physical laws, iii) a new paper investigating the mechanisms of heat transfer in a vertical double-passage channel with a permeable fluid and, iv) a significant study on the quantification of hydrophobicity in nanoparticle systems with environmental considerations.
Original languageEnglish
Article number1431198
JournalFrontiers in Nanotechnology
Volume6
DOIs
Publication statusPublished - 13 Jun 2024

Keywords

  • physics-based machine learning
  • hydrophobicity
  • molecular dynamics
  • heat transfer
  • porous flow
  • nanoparticles

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