A review on synthesis, properties, and biomedical applications of graphene quantum dots (GQDs).

A new type of 0-dimensional carbon-based materials called graphene quantum dots (GQDs) is gaining significant attention as a non-toxic and eco-friendly nanomaterial. GQDs are nanomaterials composed of sp2hybridized carbon domains and functional groups, with their lateral size less than 10 nm. The unique and exceptional physical, chemical, and optical properties arising from the combination of graphene structure and quantum confinement effect due to their nano-size make GQDs more intriguing than other nanomaterials. Particularly, the low toxicity and high solubility derived from the carbon core and abundant edge functional groups offer significant advantages for the application of GQDs in the biomedical field. In this review, we summarize various synthetic methods for preparing GQDs and important factors influencing the physical, chemical, optical, and biological properties of GQDs. Furthermore, the recent application of GQDs in the biomedical field, including biosensor, bioimaging, drug delivery, and therapeutics are discussed. Through this, we provide a brief insight on the tremendous potential of GQDs in biomedical applications and the challenges that need to be overcome in the future.

Engineering functionalization and properties of graphene quantum dots (GQDs) with controllable synthesis for energy and display applications.

Graphene quantum dots (GQDs), a new type of 0D nanomaterial, are composed of a graphene lattice with sp2 bonding carbon core and characterized by their abundant edges and wide surface area. This unique structure imparts excellent electrical properties and exceptional physicochemical adsorption capabilities to GQDs. Additionally, the reduction in dimensionality of graphene leads to an open band gap in GQDs, resulting in their unique optical properties. The functional groups and dopants in GQDs are key factors that allow the modulation of these characteristics. So, controlling the functionalization level of GQDs is crucial for understanding their characteristics and further application. This review provides an overview of the properties and structure of GQDs and summarizes recent developments in research that focus on their controllable synthesis, involving functional groups and doping. Additionally, we provide a comprehensive and focused explanation of how GQDs have been advantageously applied in recent years, particularly in the fields of energy storage devices and displays.

Effective pseudo-labeling based on heatmap for unsupervised domain adaptation in cell detection.

Cell detection is an important task in biomedical research. Recently, deep learning methods have made it possible to improve the performance of cell detection. However, a detection network trained with training data under a specific condition (source domain) may not work well on data under other conditions (target domains), which is called the domain shift problem. In particular, cells are cultured under different conditions depending on the purpose of the research. Characteristics, e.g., the shapes and density of the cells, change depending on the conditions, and such changes may cause domain shift problems. Here, we propose an unsupervised domain adaptation method for cell detection using a pseudo-cell-position heatmap, where the cell centroid is at the peak of a Gaussian distribution in the map and selective pseudo-labeling. In the prediction result for the target domain, even if the peak location is correct, the signal distribution around the peak often has a non-Gaussian shape. The pseudo-cell-position heatmap is thus re-generated using the peak positions in the predicted heatmap to have a clear Gaussian shape. Our method selects confident pseudo-cell-position heatmaps based on uncertainty and curriculum learning. We conducted numerous experiments showing that, compared with the existing methods, our method improved detection performance under different conditions.