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Polythiophene derivatives as chemical sensors: a DFT study on the influence of side groups.
Barboza, Bruno Hori; Gomes, Orisson Ponce; Batagin-Neto, Augusto.
Affiliation
  • Barboza BH; Department of Physics, School of Sciences, São Paulo State University (UNESP), Bauru, SP, 17033-360, Brazil.
  • Gomes OP; School of Sciences, POSMAT, São Paulo State University (UNESP), Bauru, SP, 17033-360, Brazil.
  • Batagin-Neto A; Campus of Itapeva, São Paulo State University (UNESP), Itapeva, SP, 18409-010, Brazil. a.batagin@unesp.br.
J Mol Model ; 27(1): 17, 2021 Jan 07.
Article in En | MEDLINE | ID: mdl-33409576
Conjugated polymers have been considered promising candidates for applications in chemical sensors, mainly due to their high versatility of synthesis, low cost, light weight, and suitable optoelectronic properties. In this context, polythiophene (PT) derivatives have been successfully employed. However, at the same time that the versatility of the synthesis allows the production of varied derivatives, the complexity of interactions with analytes hinders an efficient design of compounds with improved sensing properties. In the present report, electronic structure calculations were employed to identify promising PT derivatives for chemical sensor applications. Structural, optoelectronic, and reactivity properties of a set of branched PT derivatives were evaluated. Adsorption studies considering different gaseous compounds were conducted for selected systems. The results suggest that an appropriate choice of the side groups can lead to derivatives with improved sensorial properties. In particular, PT-CN derivative was identified as the most promising compound for high sensitive chemical sensors towards SO2 and NH3 analytes.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Polymers / Thiophenes Language: En Journal: J Mol Model Journal subject: BIOLOGIA MOLECULAR Year: 2021 Document type: Article Affiliation country: Brazil Country of publication: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Polymers / Thiophenes Language: En Journal: J Mol Model Journal subject: BIOLOGIA MOLECULAR Year: 2021 Document type: Article Affiliation country: Brazil Country of publication: Germany