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

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 15, 2022
Source ID
10.1002/admi.202201707

Entities

People

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

Organizations

  • 711th Human Performance Wing
  • Air Force Office of Scientific Research
  • Air Force Research Laboratory
  • National Academy of Sciences
  • University of New South Wales

Tags

Readers

  • Nanocomposite Materials Science
  • Nanoscale Plasmonic Nanotechnology
  • Systems Analysis and Design

Technology Areas

  • AI & ML