Epitaxial Growth of Uniform Single-Layer and Bilayer Graphene with Assistance of Nitrogen Plasma

Unsupervised learning of spatially-resolved ARPES spectra for epitaxially grown graphene via non-negative matrix factorization

This study proposed an unsupervised machine-learning approach for analyzing spatially-resolved ARPES. A combination of non-negative matrix factorization (NMF) and k-means clustering was applied to spatially-resolved ARPES spectra of the graphene epitaxially grown on a SiC substrate. The Dirac cones of graphene were decomposed and reproduced fairly well using NMF. The base and activation matrices obtained from the NMF results reflected the detailed spectral features derived from the number of graphene layers and growth directions. The spatial distribution of graphene thickness on the substrate was clearly visualized by the clustering using the activation matrices acquired via NMF. Integration with k-means clustering enables clear visualization of spatial variations. Our method efficiently handles large datasets, extracting spectral features without manual inspection. It offers broad applicability beyond graphene studies to analyze ARPES spectra in various materials.

Electrostatic Tuning of Bilayer Graphene Edge Modes

We study the effect of a local potential shift induced by a side electrode on the edge modes at the boundary between gapped and ungapped bilayer graphene. A potential shift close to the gapped-ungapped boundary causes the emergence of unprotected edge modes, propagating in both directions along the boundary. These counterpropagating edge modes allow edge backscattering, as opposed to the case of valley-momentum-locked edge modes. We then calculate the conductance of a bilayer graphene wire in presence of finger-gate electrodes, finding strong asymmetries with energy inversion and deviations from conductance quantization that can be understood with the gate-induced unprotected edge modes.

Recent Advances in Graphene-Based Nanocomposites for Ammonia Detection

The increasing demand to mitigate the alarming effects of the emission of ammonia (NH3) on human health and the environment has highlighted the growing attention to the design of reliable and effective sensing technologies using novel materials and unique nanocomposites with tunable functionalities. Among the state-of-the-art ammonia detection materials, graphene-based polymeric nanocomposites have gained significant attention. Despite the ever-increasing number of publications on graphene-based polymeric nanocomposites for ammonia detection, various understandings and information regarding the process, mechanisms, and new material components have not been fully explored. Therefore, this review summarises the recent progress of graphene-based polymeric nanocomposites for ammonia detection. A comprehensive discussion is provided on the various gas sensor designs, including chemiresistive, Quartz Crystal Microbalance (QCM), and Field-Effect Transistor (FET), as well as gas sensors utilising the graphene-based polymer nanocomposites, in addition to highlighting the pros and cons of graphene to enhance the performance of gas sensors. Moreover, the various techniques used to fabricate graphene-based nanocomposites and the numerous polymer electrolytes (e.g., conductive polymeric electrolytes), the ion transport models, and the fabrication and detection mechanisms of ammonia are critically addressed. Finally, a brief outlook on the significant progress, future opportunities, and challenges of graphene-based polymer nanocomposites for the application of ammonia detection are presented.

Optical Biosensor Based on Graphene and Its Derivatives for Detecting Biomolecules

Graphene and its derivatives show great potential for biosensing due to their extraordinary optical, electrical and physical properties. In particular, graphene and its derivatives have excellent optical properties such as broadband and tunable absorption, fluorescence bursts, and strong polarization-related effects. Optical biosensors based on graphene and its derivatives make nondestructive detection of biomolecules possible. The focus of this paper is to review the preparation of graphene and its derivatives, as well as recent advances in optical biosensors based on graphene and its derivatives. The working principle of face plasmon resonance (SPR), surface-enhanced Raman spectroscopy (SERS), fluorescence resonance energy transfer (FRET) and colorimetric sensors are summarized, and the advantages and disadvantages of graphene and its derivatives applicable to various types of sensors are analyzed, and the methods of surface functionalization of graphene and its derivatives are introduced; these optical biosensors can be used for the detection of a range of biomolecules such as single cells, cellular secretions, proteins, nucleic acids, and antigen-antibodies; these new high-performance optical sensors are capable of detecting changes in surface structure and biomolecular interactions with the advantages of ultra-fast detection, high sensitivity, label-free, specific recognition, and the ability to respond in real-time. Problems in the current stage of application are discussed, as well as future prospects for graphene and its biosensors. Achieving the applicability, reusability and low cost of novel optical biosensors for a variety of complex environments and achieving scale-up production, which still faces serious challenges.