Sahika Inal

King Abdullah University of Science and Technology, Saudi Arabia
Presenter Bio

Sahika Inal is an Associate Professor of Bioengineering with affiliations in Electrical Engineering and Materials Science and Engineering at King Abdullah University of Science and Technology (KAUST). She has a B.Sc. degree in Textile Engineering from Istanbul Technical University (Turkey), an M.Sc. in Polymer Science, and a Ph.D. in Experimental Physics, both from the University of Potsdam (Germany). She completed her postdoctoral training at the Center of Microelectronics of Provence of the Ecole Nationale Supérieure des Mines de Saint-Étienne (France). Her expertise is in polymer science and bioelectronic devices, particularly in the photophysics of conjugated polymers, characterization of polymer films and the design of biosensors and actuators. Inal lab exploits the functionalities of organic electronic materials, investigates ionic/electronic charge transport, and designs electronic devices that record/stimulate biological signals.

Abstract: Conjugated Polymer based Electronics for Diagnostics in Physiological Media
1Organic Bioelectronics Lab, Biological and Environmental Science and Engineering Division, King Abdullah University   Conjugated polymers provide a unique toolbox for establishing electrical communication with biological systems. I will show how modulating the chemistry of these materials can lead to interfaces that maximize interactions with biological systems while maintaining electronic transport properties. These materials are then used in organic electrochemical transistors (OECTs) to detect biological species in physiological media. I will introduce two types of OECT based sensors; one that detects metabolites with performance exceeding the state-of-the-art, and the other that detects coronavirus spike proteins at the physical limit. Having challenged these sensors with patient samples and cellular media, I will discuss areas where proof-of-concept platforms may fail and how to prolong the operation in biological environments. By tackling each of these problems, we improve device performance to a level that marks a considerable step toward label-free diagnostics.

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