Over the past few decades, researchers have established artificial enzymes as highly stable and low-cost alternatives to natural enzymes in a wide range of applications. A variety of materials including cyclodextrins, metal complexes, porphyrins, polymers, dendrimers and biomolecules have been extensively explored to mimic the structures and functions of naturally occurring enzymes. Recently, some nanomaterials have been found to exhibit unexpected enzyme-like activities, and great advances have been made in this area due to the tremendous progress in nano-research and the unique characteristics of nanomaterials. To highlight the progress in the field of nanomaterial-based artificial enzymes (nanozymes), this review discusses various nanomaterials that have been explored to mimic different kinds of enzymes. We cover their kinetics, mechanisms and applications in numerous fields, from biosensing and immunoassays, to stem cell growth and pollutant removal. We also summarize several approaches to tune the activities of nanozymes. Finally, we make comparisons between nanozymes and other catalytic materials (other artificial enzymes, natural enzymes, organic catalysts and nanomaterial-based catalysts) and address the current challenges and future directions (302 references).

One-pot fabrication of fluorescent carbon dots was facilely developed by directly heating ascorbic acid aqueous solution at 90 °C. The resulting carbon dots possess excitation, pH and polarity-dependent luminescence and upconversion fluorescence properties.

We developed a theoretical framework to prove the existence and quantify the Waddington landscape as well as chreode-biological paths for development and differentiation. The cells can have states with the higher probability ones giving the different cell types. Different cell types correspond to different basins of attractions of the probability landscape. We study how the cells develop from undifferentiated cells to differentiated cells from landscape perspectives. We quantified the Waddington landscape through construction of underlying probability landscape for cell development. We show the developmental process proceeds as moving from undifferentiated to the differentiated basins of attractions. The barrier height of the basins of attractions correlates with the escape time that determines the stability of cell types. We show that the developmental process can be quantitatively described and uncovered by the biological paths on the quantified Waddington landscape from undifferentiated to the differentiated cells. We found the dynamics of the developmental process is controlled by a combination of the gradient and curl force on the landscape. The biological paths often do not follow the steepest descent path on the landscape. The landscape framework also quantifies the possibility of reverse differentiation process such as cell reprogramming from differentiated cells back to the original stem cell. We show that the biological path of reverse differentiation is irreversible and different from the one for differentiation process. We found that the developmental process described by the underlying landscape and the associated biological paths is relatively stable and robust against the influences of environmental perturbations.