4.6 Article

Enzymatically Polymerized Organic Conductors on Model Lipid Membranes

期刊

LANGMUIR
卷 39, 期 23, 页码 8196-8204

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.langmuir.3c00654

关键词

-

向作者/读者索取更多资源

Seamless integration between biological systems and electrical components is essential for understanding and combating neurological disorders. By employing bioelectronic systems made up of conjugated polymers, which can transport electronic and ionic charges, it is possible to achieve this integration. The enzyme-mediated polymerization of thiophene-based monomers on a synthetic lipid bilayer provides insights into their interactions with a cell membrane model, suggesting their potential for in vivo neural therapeutics.
Seamless integration between biological systems and electricalcomponents is essential for enabling a twinned biochemical-electricalrecording and therapy approach to understand and combat neurologicaldisorders. Employing bioelectronic systems made up of conjugated polymers,which have an innate ability to transport both electronic and ioniccharges, provides the possibility of such integration. In particular,translating enzymatically polymerized conductive wires, recently demonstratedin plants and simple organism systems, into mammalian models, is ofparticular interest for the development of next-generation devicesthat can monitor and modulate neural signals. As a first step towardachieving this goal, enzyme-mediated polymerization of two thiophene-basedmonomers is demonstrated on a synthetic lipid bilayer supported ona Au surface. Microgravimetric studies of conducting films polymerizedin situ provide insights into their interactions with a lipid bilayermodel that mimics the cell membrane. Moreover, the resulting electricaland viscoelastic properties of these self-organizing conducting polymerssuggest their potential as materials to form the basis for novel approachesto in vivo neural therapeutics.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据