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Mid- and far-infrared plasmonic biosensing with graphene


This project's main idea is to develop a new spectroscopic technique based on tunable plasmonics in graphene,by exploring the polarization dependent interaction of small biomolecules with terahertz (THz) radiation. Graphene iswidely recognized as an ideal platform for strong light matter interactions due to its excellent plasmonic response in themid to far infrared spectral range. In addition, the plasmonic response of graphene is highly tunable in real time usingelectrostatic gating. Fundamental structural features of peptides that are critically important for their functions can,in principle, be probed by polarization dependent spectroscopy in the THz range, as described in a recent simulation study, which also explicitly noted that THz chiro-optical spectroscopy has not yet been demonstrated experimentally. The innovative aspect of this project is, therefore, to develop devices that realize this predicted technique for molecular analysis using spectroscopic plasmonics. Two different architectures will be developed for implementing strong light matter interaction between graphene and biomolecules. In one approach, micrometer-wide ribbons of graphene, patterned by optical lithography, act as the active plasmonic medium. The second approach consists of transferring a continuous graphene sheet onto a grating of high dielectric contrast provided by alternating lines of SiO2 and Al2O3 on a high resistivity silicon wafer. Both architectures are based on theoretical simulations developed and performed by the team members, who have recently published their studies in a book about graphene plasmonics. Specifically, the two device architectures are modeled using full electrodynamics calculations, which are faster and perform better than the conventional time domain integration of Maxwells equations. The high sensitivity of surface based detection methods, including conventional noble metal plasmonics, makes them particularly advantageous for analyzing small quantities of biomolecules. Being a 2D material, graphene is a natural choice for implementing surface based sensors. Furthermore, the unique properties of the electromagnetic coupling of molecular excitations to surface plasmons in graphene open possibilities for extending the analytical capabilities of these sensors beyond the current state of the artfor label free measurements. Realtime tuning of plasmon resonances in graphene will enable spectroscopic, i.e.,more specific, detection of biomolecules in presence of solvent and other background signals. This specificity will be enhanced by structural, e.g., chiral, signatures enabled by polarization dependent THz measurements. The specificityand information content of these measurements will be further enhanced by taking advantage of the high intensitytunable broadband THz excitation produced by the two color air plasma method and of the time resolved pump probecapabilities of the THz source and spectrometer to be developed in this project. (AU)

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Scientific publications (4)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
BAHAMON, DARIO A.; GOMEZ-SANTOS, G.; STAUBER, T. Emergent magnetic texture in driven twisted bilayer graphene. NANOSCALE, v. 12, n. 28, p. 15383-15392, JUL 28 2020. Web of Science Citations: 6.
BARCELOS, INGRID D.; BECHTEL, HANS A.; DE MATOS, CHRISTIANO J. S.; BAHAMON, DARIO A.; KAESTNER, BERND; MAIA, FRANCISCO C. B.; FREITAS, RAUL O. Probing Polaritons in 2D Materials with Synchrotron Infrared Nanospectroscopy. ADVANCED OPTICAL MATERIALS, v. 8, n. 5, SI DEC 2019. Web of Science Citations: 1.
FERES, FLAVIO H.; BARCELOS, INGRID D.; MAYER, RAFAEL A.; DOS SANTOS, THIAGO M.; FREITAS, RAUL O.; RASCHKE, MARKUS B.; BAHAMON, DARIO A.; MAIA, FRANCISCO C. B. Dipole modelling for a robust description of subdiffractional polariton waves. NANOSCALE, v. 11, n. 44, p. 21218-21226, NOV 28 2019. Web of Science Citations: 0.
TORRES, V; SILVA, P.; DE SOUZA, E. A. T.; SILVA, L. A.; BAHAMON, D. A. Valley notch filter in a graphene strain superlattice: Green's function and machine learning approach. Physical Review B, v. 100, n. 20 NOV 11 2019. Web of Science Citations: 0.

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