Despite the advancements, predicting materials properties at the nanoscale presents several challenges:
Complexity: The behavior of nanomaterials can be highly complex due to quantum effects and surface phenomena. Scale: The transition from nanoscale to macroscale properties is not always straightforward. Data Availability: High-quality data for training ML models can be scarce or difficult to obtain. Computational Resources: First-principles calculations and MD simulations can be computationally intensive.
