Block Copolymer Self-Assembly for Biological and Chemical Sensing

Biological and chemical (BCh) sensing relying on the self-assembly of block copolymers (BCPs) has become ubiquitous in addressing a wide range of challenges across diverse technological fields. In this Review, we highlight recent advancements in utilizing the unique properties of BCPs (e.g., their tunable nanostructures, ability to form highly ordered arrangements, nanoscale domains, and versatile chemical functionalities) in BCh sensing technologies to enhance their respective performance. The discussed sensing approaches encompass surface-enhanced Raman spectroscopy (SERS), electrochemistry, and optics, where BCPs have been demonstrated to improve the sensitivity, selectivity, and stability of the BCh sensing devices. The Review particularly emphasizes the role of BCPs in the development of nanostructured surfaces for enhanced signal transduction and in creating porous matrices with a large active area. Furthermore, the self-assembly of BCPs in solution and their role in aiding the self-organization of other sensing materials such as plasmonic nanoparticles are also explored. Importantly, we further discuss the potential of BCPs in future sensing applications, identifying key research directions that could drive further innovation in the field. This Review aims to serve as a valuable resource for researchers interested in the application of self-assembled BCPs in BCh sensing.

Authors

Institutions

Publication Details

Journal
ACS Applied Polymer Materials
Published
2024-12-12
DOI
https://doi.org/10.1021/acsapm.4c03286
Citations
13
Primary Topic
Block Copolymer Self-Assembly
Type
article
Field-Weighted Citation Impact
1.52
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Block Copolymer Self-Assembly for Biological and Chemical Sensing

Brian Yuliarto, M. Kogelschatz, Chandra Wulandari, Hutomo Suryo Wasisto et al.
13 citations
ACS Applied Polymer Materials
Block Copolymer Self-Assembly
1.52
article

Block Copolymer Self-Assembly for Biological and Chemical Sensing

Brian Yuliarto, M. Kogelschatz, Chandra Wulandari, Hutomo Suryo Wasisto, Achmad Fajar Putranto, Guillaume Fleury, M. Zelsmann, Ferry Anggoro Ardy Nugroho, Atqiya Muslihati, Yudhistira Tirtayasri Amrillah
article en
13 citations

Abstract

Biological and chemical (BCh) sensing relying on the self-assembly of block copolymers (BCPs) has become ubiquitous in addressing a wide range of challenges across diverse technological fields. In this Review, we highlight recent advancements in utilizing the unique properties of BCPs (e.g., their tunable nanostructures, ability to form highly ordered arrangements, nanoscale domains, and versatile chemical functionalities) in BCh sensing technologies to enhance their respective performance. The discussed sensing approaches encompass surface-enhanced Raman spectroscopy (SERS), electrochemistry, and optics, where BCPs have been demonstrated to improve the sensitivity, selectivity, and stability of the BCh sensing devices. The Review particularly emphasizes the role of BCPs in the development of nanostructured surfaces for enhanced signal transduction and in creating porous matrices with a large active area. Furthermore, the self-assembly of BCPs in solution and their role in aiding the self-organization of other sensing materials such as plasmonic nanoparticles are also explored. Importantly, we further discuss the potential of BCPs in future sensing applications, identifying key research directions that could drive further innovation in the field. This Review aims to serve as a valuable resource for researchers interested in the application of self-assembled BCPs in BCh sensing.

ACS Applied Polymer MaterialsVol. 6(24)
Institut polytechnique de Grenoble (FR), Centre National de la Recherche Scientifique (FR), Bandung Institute of Technology (ID), Université de Bordeaux (FR), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), University of Indonesia (ID), CEA Grenoble (FR), Laboratoire des Technologies de la Microélectronique (FR), Laboratoire de Chimie des Polymères Organiques (FR), Laboratoire d'Électronique des Technologies de l'Information (FR), Institut Polytechnique de Bordeaux (FR), Ab Analitica (Italy) (IT), Université Grenoble Alpes (FR)
Openalex Percentile: Top 13%
Block Copolymer Self-Assembly
1.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.