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-μm), and high modulation speed of >50 kHz. We developed an IR analysis system based on the multilayer-graphene microemitter and performed IR absorption spectroscopy.

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.

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.