Aerospace Airflow and Transient Elastodynamic Responses of the Smart Composite Structures: Verification of the results via a machine learning algorithm

Aerospace Science and Technology, Journal Year: 2025, Volume and Issue: unknown, P. 110293 - 110293

Published: May 1, 2025

Language: Английский

Machine Learning-Assisted Optical Characterization and Growth Modulation of Two-Dimensional Materials

Chemistry, Journal Year: 2025, Volume and Issue: 7(3), P. 80 - 80

Published: May 13, 2025

This review focuses on research machine learning-enabled two-dimensional (2D) materials, exploring the progress and prospects of this interdisciplinary field. At a fundamental level, learning algorithms incorporate imaging systems to build highly accurate viewing frameworks for material analysis. Two-dimensional materials have rich set optical properties, including light absorption emission, anisotropy, photoluminescence, nonlinear effects, which can accurately understand through image characterization, spectral fusion, quantitative Meanwhile, preparation process post-processing are key aspects in growth regulation 2D helps optimize experiments by analyzing kinetics fine control. Related has spawned many academic achievements, gradually penetrating electronics, energy, other industrial applications. The innovation technology deepening multidisciplinary integration expected unlock more emerging applications expand application boundaries materials.

Language: Английский

Carrera Unified Formulation for intelligent vibration control in hybrid nanocomposite structures: Verification of the results via a hybrid machine learning algorithm

Mechanics of Advanced Materials and Structures, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 19

Published: May 14, 2025

Language: Английский