In-plane anisotropic layered materials such as black phosphorus (BP) have emerged as an important class of two-dimensional (2D) materials that bring a new dimension to the properties of 2D materials, hence providing a wide range of opportunities for developing conceptually new device applications. However, all of recently reported anisotropic 2D materials are relatively narrow-bandgap semiconductors (<2 eV), and there has been no report about this type of materials with wide bandgap, restricting the relevant applications such as polarization-sensitive photodetection in short wave region. Here we present a new member of the family, germanium diselenide (GeSe) with a wide bandgap of 2.74 eV, and systematically investigate the in-plane anisotropic structural, vibrational, electrical, and optical properties from theory to experiment. Photodetectors based on GeSe exhibit a highly polarization-sensitive photoresponse in short wave region due to the optical absorption anisotropy induced by in-plane anisotropy in crystal structure. Furthermore, exfoliated GeSe flakes show an outstanding stability in ambient air which originates from the high activation energy of oxygen chemisorption on GeSe (2.12 eV) through our theoretical calculations, about three times higher than that of BP (0.71 eV). Such unique in-plane anisotropy and wide bandgap, together with high air stability, make GeSe a promising candidate for future 2D optoelectronic applications in short wave region.

Modulating lasing wavelength flexibly and repeatedly on a single rod is essential to the practical applications of micro/nanorod lasers. In this paper, a structure that decouples the gain medium and optical cavity is proposed, where the corresponding mechanism for the lasing wavelength shift is explained. Based on the above structure, one kind of wavelength continuously variable lasers is achieved on a single GaN/InGaN core-shell microrod without modifying the geometry of the resonant cavity or cutting the microrod. By using this method, lasing wavelength can be modulated from 372 to 408 nm flexibly and repeatedly in a 10 μm facilely synthesized microrod. This approach demonstrates a big application potential in numerous fields consisting of optical telecommunication and environmental monitoring.

Feature extraction of electroencephalography (EEG) signals plays a significant role in the wearable computing field. Due to the practical applications of EEG emotion calculation, researchers often use edge calculation to reduce data transmission times, however, as EEG involves a large amount of data, determining how to effectively extract features and reduce the amount of calculation is still the focus of abundant research. Researchers have proposed many EEG feature extraction methods. However, these methods have problems such as high time complexity and insufficient precision. The main purpose of this paper is to introduce an innovative method for obtaining reliable distinguishing features from EEG signals. This feature extraction method combines differential entropy with Linear Discriminant Analysis (LDA) that can be applied in feature extraction of emotional EEG signals. We use a three-category sentiment EEG dataset to conduct experiments. The experimental results show that the proposed feature extraction method can significantly improve the performance of the EEG classification: Compared with the result of the original dataset, the average accuracy increases by 68%, which is 7% higher than the result obtained when only using differential entropy in feature extraction. The total execution time shows that the proposed method has a lower time complexity.

The steady progress in medical diagnosis and treatment of diseases largely hinges on the steady development and improvement of modern imaging modalities. Raman spectroscopy has attracted increasing attention for clinical applications as it is label-free, non-invasive, and delivers molecular fingerprinting information of a sample. In combination with fiber optic probes, it also allows easy access to different body parts of a patient. However, image acquisition with fiber optic probes is currently not possible. Here, we introduce a fiber optic probe-based Raman imaging system for the real-time molecular virtual reality data visualization of chemical boundaries on a computer screen and the physical world. The approach is developed around a computer vision-based positional tracking system in conjunction with photometric stereo and augmented and mixed chemical reality, enabling molecular imaging and direct visualization of molecular boundaries of three-dimensional surfaces. The proposed approach achieves a spatial resolution of 0.5 mm in the transverse plane and a topology resolution of 0.6 mm, with a spectral sampling frequency of 10 Hz, and can be used to image large tissue areas in a few minutes, making it highly suitable for clinical tissue-boundary demarcation. A variety of applications on biological samples, i.e., distribution of pharmaceutical compounds, brain-tumor phantom, and various types of sarcoma have been characterized, showing that the system enables rapid and intuitive assessment of molecular boundaries.

We propose an ultra-compact optical 90° hybrid with the smallest length of 107μm, consisting of a wedge-shaped 2 × 4 MMI coupler connected with a 2 × 2 MMI coupler using silicon nanowaveguide technology. Neither cascaded phase shifters nor waveguide crossings are attached to the proposed 90° hybrid in coherent receiving system. The proposed device is demonstrated on silicon-on-insulator (SOI) with 220nm thick top-silicon layer and 2μm thick buried oxide layer. A high performance of the proposed 90° hybrid is exhibited experimentally with a high extinction ratio larger than 20dB, an excess loss mostly less than 0.5dB, a common mode rejection ratio better than -20dB and phase deviation within the range of 5° over C-band spectral range.

Raman spectroscopy using fiber optic probe combines non‐contacted and label‐free molecular fingerprinting with high mechanical flexibility for biomedical, clinical and industrial applications. Inherently, fiber optic Raman probes provide information from a single point only, and the acquisition of images is not straightforward. For many applications, it is highly crucial to determine the molecular distribution and provide imaging information of the sample. Here, we propose an approach for Raman imaging using a handheld fiber optic probe, which is built around computer vision–based assessment of positional information and simultaneous acquisition of spectroscopic information. By combining this implementation with real‐time data processing and analysis, it is possible to create not only fiber‐based Raman imaging but also an augmented chemical reality image of the molecular distribution of the sample surface in real‐time. We experimentally demonstrated that using our approach, it is possible to determine and to distinguish borders of different bimolecular compounds in a short time. Because the method can be transferred to other optical probes and other spectroscopic techniques, it is expected that the implementation will have a large impact for clinical, biomedical and industrial applications.

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