Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Patterning porous networks through self-assembly of programmed biomacromolecules

Carloni, Laure-Elie, Bezzu, C. Grazia and Bonifazi, Davide ORCID: https://orcid.org/0000-0001-5717-0121 2019. Patterning porous networks through self-assembly of programmed biomacromolecules. Chemistry - A European Journal 25 (71) , pp. 16179-16200. 10.1002/chem.201902576

[thumbnail of Carloni_et_al-2019-Chemistry_-_PP.pdf]
Preview
PDF - Accepted Post-Print Version
Download (3MB) | Preview

Abstract

Two‐dimensional (2D) porous networks are of great interest for the fabrication of complex organized functional materials for potential applications in nanotechnologies and nanoelectronics. This review aims at providing an overview of bottom‐up approaches towards the engineering of 2D porous networks by using biomacromolecules, with a particular focus on nucleic acids and proteins. The first part illustrates how the advancements in DNA nanotechnology allowed for the attainment of complex ordered porous two‐dimensional DNA nanostructures, thanks to a biomimetic approach based on DNA molecules self‐assembly through specific hydrogen‐bond base pairing. The second part focuses the attention on how polypeptides and proteins structural properties could be used to engineer organized networks templating the formation of multifunctional materials. The structural organization of all examples is discussed as revealed by scanning probe microscopy or transmission electron microscopy imaging techniques.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Chemistry
Publisher: Wiley
ISSN: 0947-6539
Date of First Compliant Deposit: 24 October 2019
Date of Acceptance: 3 September 2019
Last Modified: 12 Nov 2024 16:45
URI: https://orca.cardiff.ac.uk/id/eprint/126287

Citation Data

Cited 2 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics