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Probing peptide nanowire conductivity by THz nanoscopy.

Armin SolemanifarXiao GuoBogdan C DonoseKarl BertlingBronwyn LaycockAleksandar D Rakić
Published in: Nanotechnology (2021)
Significant efforts have recently been invested in assessing the physical and chemical properties of microbial nanowires for their promising role in developing alternative renewable sources of electricity, bioelectronic materials and implantable sensors. One of their outstanding properties, the ever-desirable conductivity has been the focus of numerous studies. However, the lack of a straightforward and reliable method for measuring it seems to be responsible for the broad variability of the reported data. Routinely employed methods tend to underestimate or overestimate conductivity by several orders of magnitude. In this work, synthetic peptide nanowires conductivity is interrogated employing a non-destructive measurement technique developed on a terahertz scanning near-field microscope to test if peptide aromaticity leads to higher electrical conductivity. Our novel peptide conductivity measurement technique, based on triple standards calibration method, shows that in the case of two biopolymer mimicking peptides, the sample incorporating aromatic residues (W6) is about six times more conductive than the negative control (L6). To the best of our knowledge, this is the first report of a quantitative nano-scale terahertz s-SNOM investigation of peptides. These results prove the suitability of the terahertz radiation-based non-destructive approach in tandem with the designer peptides choice as model test subjects. This approach requires only simple sample preparation, avoids many of the pitfalls of typical contact-based conductivity measurement techniques and could help understanding fundamental aspects of nature's design of electron transfer in biopolymers.
Keyphrases
  • room temperature
  • amino acid
  • electron transfer
  • machine learning
  • single molecule
  • molecular dynamics simulations
  • low cost
  • molecularly imprinted
  • electron microscopy
  • data analysis
  • simultaneous determination