Objective
Monitoring the DNA and protein composition of cells is key to understanding most biological processes, including the molecular origins of specific diseases. To this end, the emerging field of molecular electronics offers unique opportunities for label-free single-biomolecule sensing. In particular, tunnelling current modulations caused by trapping an individual molecule in a nanoscopic gap between two electrodes can be used to discriminate species based on their electronic structure. The junction conductance is highly sensitive not only to the structure of the molecule, but also to the gap size, the voltage applied, the bonding arrangement inside the gap and the immediate molecular environment. Mechanically controlled break junctions (MCBJs) that allow the formation of closely-spaced electrodes with picometer resolution, can exert a degree of control over each of these parameters and therefore represent an ideal platform for in-situ studies at single-molecule level.
In BioGraphING, I will develop the first graphene MCBJ, a unique device that will be both a model system for studying charge transport in molecular junctions at room temperature, and a sensing platform for biomolacular fingerprinting. Graphene’s atomic thinness, chemical inertness and strong in-plane bonds will lead to a device architecture with superior mechanical stability and measurement resolution. Given that a robust and reliable contact to single molecules is crucial for high junction conductance, various anchoring modes of the molecules to the graphene electrodes will be investigated (e.g. covalent bonding, π-π stacking). I will monitor the molecular conductance as a function of electrode distance and bias voltage in air, vacuum and in liquid. Combined with quantum transport simulations and statistical data analysis my final goal is to establish molecular fingerprints for amino acids and peptides with specific biological functions, an important challenge in single-molecule biophysics.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesdata science
- engineering and technologynanotechnologynano-materialstwo-dimensional nanostructuresgraphene
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- natural sciencesbiological sciencesbiophysics
- natural scienceschemical sciencesorganic chemistryamines
Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
2628 CN Delft
Netherlands