Your browser doesn't support javascript.
loading
Computational studies and biosensory applications of graphene-based nanomaterials: a state-of-the-art review.
More, Mahesh P; Deshmukh, Prashant K.
Afiliação
  • More MP; Department of Pharmaceutics, H. R. Patel Institute of Pharmaceutical Education and Research, Karwand Naka, Shirpur, Maharashtra, India. Department of Pharmaceutics, Shri Vile Parle Kelavani Mandal's Institute of Pharmacy, Dhule, Maharashtra, India.
Nanotechnology ; 31(43): 432001, 2020 Oct 23.
Article em En | MEDLINE | ID: mdl-32498048
ABSTRACT
Graphene, graphene oxide (GO) and graphene quantum dots (GQDs) are expected to play a vital role in the diagnosis of severe ailments. Computer-based simulation approaches are helpful for understanding theoretical tools prior to experimental investigation. These theoretical tools still have a high computational requirement. Thus, more efficient algorithms are required to perform studies on even larger systems. The present review highlights the recent advancement in structural confinement using computer simulation approaches along with biosensory applications of graphene-based materials. The computer simulation approaches help to identify the interaction between interacting molecules and sensing elements like graphene sheets. The simulation approach reduces the wet-lab experiment time and helps to predict the interaction and interacting environment. The experimental investigation can be tuned at a molecular level easily to predict small changes in structural configuration. Here, the molecular simulation study could be useful as an alternative to actual wet experimental approaches. The sensing ability of graphene-based materials is a result of interactions like hydrogen bonding, base-base interaction, and base-to-pi interaction to name a few. These interactions help in designing and engineering a substrate for sensing of various biomolecules.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article