Your browser doesn't support javascript.
loading
Performance analysis of solution-processed nanosheet strain sensors-a systematic review of graphene and MXene wearable devices.
Boland, Conor S.
Afiliação
  • Boland CS; School of Mathematical and Physical Sciences, University of Sussex, Brighton, BN1 9QH, United Kingdom.
Nanotechnology ; 35(20)2024 Mar 01.
Article em En | MEDLINE | ID: mdl-38324912
ABSTRACT
Nanotechnology has led to the realisation of many potentialInternet of Thingsdevices that can be transformative with regards to future healthcare development. However, there is an over saturation of wearable sensor review articles that essentially quote paper abstracts without critically assessing the works. Reported metrics in many cases cannot be taken at face value, with researchers overly fixated on large gauge factors. These facts hurt the usefulness of such articles and the very nature of the research area, unintentionally misleading those hoping to progress the field. Graphene and MXenes are arguably the most exciting organic and inorganic nanomaterials for polymer nanocomposite strain sensing applications respectively. Due to their combination of cost-efficient, scalable production and device performances, their potential commercial usage is very promising. Here, we explain the methods for colloidal nanosheets suspension creation and the mechanisms, metrics and models which govern the electromechanical properties of the polymer-based nanocomposites they form. Furthermore, the many fabrication procedures applied to make these nanosheet-based sensing devices are discussed. With the performances of 70 different nanocomposite systems from recent (post 2020) publications critically assessed. From the evaluation of these works using universal modelling, the prospects of the field are considered. Finally, we argue that the realisation of commercial nanocomposite devices may in fact have a negative effect on the global climate crisis if current research trends do not change.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Systematic_reviews Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Systematic_reviews Idioma: En Ano de publicação: 2024 Tipo de documento: Article