In this research, we proposed a highly tunable hybrid plasmonic biosensor for identifying molecule fingerprints of proteins in the infrared range. The device is composed of a photonic band-gap structure and a cavity. The plasmonic energy is confined inside the cavity to enhance the light-analyte interactions. A layer of graphene is placed on the bottom surface of the cavity that is filled with analytes for detection. Our device has a high value of effective sensitivity that is defined as the ratio of the resonant frequency shift to the change of effective refractive index when the cavity is loaded with an analyte. The effective refractive index takes into account the effects of both the cavity structure and the optical property of the analyte. Another feature of our device is that a wide-ranging electrical tunability can be realized by applying various values of bias voltage to the graphene. The resonant frequency can be tuned for sensing different analytes without redesigning and refabricating the device. In addition, the graphene tunability can improve the sensitivity in detecting the non-targeted analytes. A prototype was designed based on photonic theory and fabricated via bottom-up lithography techniques. The research results are expected to be beneficial for nanometer-range bio-identifications and infrared optical sensors.

In this study, we propose a biochemical sensor that features a photonic cavity integrated with graphene. The tunable hybrid plasmonic-photonic sensor can detect the molecular fingerprints of biochemicals with a small sample volume. The stacking sequence of the device is “ITO grating/graphene/TiO₂/Au/Si substrate”, which composes a photonic band gap structure. A defect is created within the ITO gratings to form a resonant cavity. The plasmonic-photonic energy can be confined in the cavity to enhance the interaction between light and the analyte deposited in the cavity. The finite element simulation results indicated that the current sensor exhibits very high values in resonance shift and sensitivity. Moreover, the resonance spectrum with a broad resonance linewidth can identify the molecular vibration bands, which was exemplified by the fingerprint detections of protein and the chemical compound CBP. The sensor possesses an electrical tunability by including a graphene layer, which allowed us to tune the effective refractive index of the cavity to increase the sensor’s sensing performance. In addition, our device admits a phononic bandgap as well, which was exploited to sense the mechanical properties of two particular dried proteins based on the simplified elastic material model instead of using the more realistic viscoelastic model. The dual examinations of the optical and mechanical properties of analytes from a phoxonic sensor can improve the selectivity in analyte detections.