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Rational Design of Peptide Biorecognition Elements on Carbon Nanotubes for Sensing Volatile Organic Compounds

  • Daniel Sim
  • , Zhifeng Kuang
  • , Gustavo Sant'Anna
  • , Rachel M. Krabacher
  • , Michael C. Brothers
  • , Jorge L. Chávez
  • , Jennifer A. Martin
  • , Ahmad E. Islam
  • , Benji Maruyama
  • , Rajesh R. Naik
  • , Nicholas M. Bedford
  • , Steve S. Kim

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Carbon nanotube (CNT) chemiresistors have emerged as miniaturized platforms for wearable volatile organic compound (VOC) sensors. As a promising biorecognition element (BRE), a short peptide can functionalize CNT to be sensitive and selective to target VOCs. However, unveiling the VOC-optimized peptide-CNT pair for gas-phase sensing remains unclear. Here, a novel multimodal molecular toolset for designing, building, and probing suitable BRE-CNT sensors using machine learning, molecular dynamics, and near-edge X-ray absorption fine structure spectroscopy is presented. This computational and experimental suite predicts the peptide conformation on the CNT surface and probes how the peptide–CNT interfaces affect the VOC sensing. Then, peptide-functionalized CNT chemiresistors are tested against various VOCs to confirm the efficacy of the toolkit. The results show that the vertically oriented peptide on the CNT surface hinders VOC access to the peptide–CNT interface, resulting in a significantly lower sensor signal than the CNT chemiresistor with the horizontally oriented peptide. The interactive computational and experimental results strongly indicate that a peptide conformation plays an important role in VOC sensing sensitivity.

Original languageEnglish
Article number2201707
JournalAdvanced Materials Interfaces
Volume10
Issue number2
Early online dateNov 15 2022
DOIs
StatePublished - Jan 17 2023
Externally publishedYes

Keywords

  • carbon nanotube chemiresistors
  • human performance-indicative biomarkers
  • peptide biorecognition elements
  • peptide conformation prediction
  • volatile organic compounds

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