Nonlinear optics of graphitic carbon allotropes: from 0D to 3D.

The dimensionality of materials fundamentally influences their electronic and optical properties, presenting a complex interplay with nonlinear optical (NLO) characteristics that remains largely unexplored. In this review, we focus on the influence of dimensionality on the NLO properties of graphitic allotropes, ranging from 0D fullerenes, 1D carbon nanotubes, and 2D graphene, to 3D graphite, all of which share a consistent sp hybridized chemical bonding structure. We examine the distinct physical and NLO properties across these dimensions, underscoring the profound impact of dimensionality.

Detection Method for Three-Phase Electricity Theft Based on Multi-Dimensional Feature Extraction.

The advent of smart grids has facilitated data-driven methods for detecting electricity theft, with a preponderance of research efforts focused on user electricity consumption data. The multi-dimensional power state data captured by Advanced Metering Infrastructure (AMI) encompasses rich information, the exploration of which, in relation to electricity usage behaviors, holds immense potential for enhancing the efficiency of theft detection. In light of this, we propose the Catch22-Conv-Transformer method, a multi-dimensional feature extraction-based approach tailored for the detection of anomalous electricity usage patterns.