Deep learning in two-dimensional materials: Characterization, prediction, and design
Xinqin Meng,
Chengbing Qin,
Xilong Liang
et al.
Abstract:Since the isolation of graphene, two-dimensional (2D) materials have attracted increasing interest because of their excellent chemical and physical properties, as well as promising applications. Nonetheless, particular challenges persist in their further development, particularly in the effective identification of diverse 2D materials, the domains of large-scale and high-precision characterization, also intelligent function prediction and design. These issues are mainly solved by computational techniques, such… Show more
The exploration and functionalization of two-dimensional (2D) materials have opened new horizons in the fields of catalysis and materials science. Therein, 2D non-metallic nitrides have attracted significant attention due to...
The exploration and functionalization of two-dimensional (2D) materials have opened new horizons in the fields of catalysis and materials science. Therein, 2D non-metallic nitrides have attracted significant attention due to...
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