Microemitter-Based IR Spectroscopy and Imaging with Multilayer Graphene Thermal Emission.

IR analyses such as Fourier transform infrared spectroscopy (FTIR) are widely used in many fields; however, the performance of FTIR is limited by the slow speed (∼10 Hz), large footprint (∼ millimeter), and glass bulb structure of IR light sources. Herein, we present IR spectroscopy and imaging based on multilayer-graphene microemitters, which have distinct features: a planar structure, bright intensity, a small footprint (sub-µm2), and high modulation speed of >50 kHz. We developed an IR analysis system based on the multilayer-graphene microemitter and performed IR absorption spectroscopy. We show two-dimensional IR chemical imaging that visualizes the distribution of the chemical information. In addition, we present high-spatial-resolution IR imaging with a spatial resolution of ∼1 µm, far higher than the diffraction limit. The graphene-based IR spectroscopy and imaging can open new routes for IR applications in chemistry, material science, medicine, biology, electronics, and physics.

Predicting anxiety state using smartphone-based passive sensing.

This study predicts the change of stress levels using real-world and online behavioral features extracted from smartphone log information. Previous studies of stress detection using smartphone data focused on a single feature and did not consider all features simultaneously. We propose a method to extract a co-occurring combination of a user's real-world and online behavioral features by converting raw sensor data into categorical features. We conducted an experiment in which the State Trait Anxiety Inventory (STAI) was used to assess the anxiety-related stress levels of 20 healthy participants. The participants installed a log-collecting application on their smartphones and answered the STAI questions once a day for one month. The proposed method showed an F-score of 74.2%, which is 4.0% higher than the F-score of previous studies (70.2%) that used single non-combined features. The results demonstrate that anxiety-related stress levels can be predicted using combined features extracted from smartphone log data.

High-speed and on-chip graphene blackbody emitters for optical communications by remote heat transfer.

High-speed light emitters integrated on silicon chips can enable novel architectures for silicon-based optoelectronics, such as on-chip optical interconnects, and silicon photonics. However, conventional light sources based on compound semiconductors face major challenges for their integration with a silicon-based platform because of their difficulty of direct growth on a silicon substrate. Here we report ultra-high-speed (100-ps response time), highly integrated graphene-based on-silicon-chip blackbody emitters in the near-infrared region including telecommunication wavelength. Their emission responses are strongly affected by the graphene contact with the substrate depending on the number of graphene layers. The ultra-high-speed emission can be understood by remote quantum thermal transport via surface polar phonons of the substrates. We demonstrated real-time optical communications, integrated two-dimensional array emitters, capped emitters operable in air, and the direct coupling of optical fibers to the emitters. These emitters can open new routes to on-Si-chip, small footprint, and high-speed emitters for highly integrated optoelectronics and silicon photonics.