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Modeling and simulations for 2D materials: a ReaxFF perspective
Recent advancements in the field of two-dimensional (2D) materials have led to the
discovery of a wide range of 2D materials with intriguing properties. Atomistic-scale …
discovery of a wide range of 2D materials with intriguing properties. Atomistic-scale …
Deep learning in two-dimensional materials: Characterization, prediction, and design
X Meng, C Qin, X Liang, G Zhang, R Chen, J Hu… - Frontiers of …, 2024 - Springer
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 …
interest because of their excellent chemical and physical properties, as well as promising …
[HTML][HTML] An adaptive machine learning-based optimization method in the aerodynamic analysis of a finite wing under various cruise conditions
Conventional wing aerodynamic optimization processes can be time-consuming and
imprecise due to the complexity of versatile flight missions. Plenty of existing literature has …
imprecise due to the complexity of versatile flight missions. Plenty of existing literature has …
Decoding the origins of strength anisotropy in two-dimensional materials
Defects are inevitable in two-dimensional (2D) materials, which is widely recognized to
affect the strength of 2D materials. It is known the uniaxial tension strength is significantly …
affect the strength of 2D materials. It is known the uniaxial tension strength is significantly …
Machine learning enabled optimization of showerhead design for semiconductor deposition process
In semiconductor fabrication, the deposition process generates layers of materials to realize
insulating and conducting functionality. The uniformity of the deposited thin film layers' …
insulating and conducting functionality. The uniformity of the deposited thin film layers' …
Fracture strength of Graphene at high temperatures: data driven investigations supported by MD and analytical approaches
The extraordinary opto-electronic and mechanical properties of Graphene makes it a
popular material for several applications. However, defects like: cracks, and voids are …
popular material for several applications. However, defects like: cracks, and voids are …
[HTML][HTML] Leveraging graph neural networks and neural operator techniques for high-fidelity mesh-based physics simulations
Develo** fast and accurate computational models to simulate intricate physical
phenomena has been a persistent research challenge. Recent studies have demonstrated …
phenomena has been a persistent research challenge. Recent studies have demonstrated …
[HTML][HTML] Residual Pyramidal GAN (RP-GAN) for crack detection and prediction of crack growth in engineered cementitious composites
Crack detection has recently gained credence in the field of engineering automation.
Engineered cementitious composites (ECC) are a durable, and environmentally friendly …
Engineered cementitious composites (ECC) are a durable, and environmentally friendly …
Fracture at the two-dimensional limit
More than a century ago, AA Griffith published the seminal paper establishing the
foundational framework for fracture mechanics. The elegant theory creatively introduced the …
foundational framework for fracture mechanics. The elegant theory creatively introduced the …
Machine learning and experiments: A synergy for the development of functional materials
With machine learning (ML) and artificial intelligence (AI) becoming increasingly refined and
accessible, computer engineers and materials scientists are utilizing these data-driven …
accessible, computer engineers and materials scientists are utilizing these data-driven …