Computational models can complement experimental work by:
Simulating Experiments: Running simulations to predict outcomes and compare with experimental results. Understanding Mechanisms: Providing insights into the mechanisms at play at the nanoscale. Optimizing Conditions: Helping to optimize experimental conditions and parameters for better results.
