What Are the Future Trends in Molecular Modeling for Catalysis?
The future of molecular modeling in catalysis is promising, with several trends shaping the field:
Machine Learning: Integration of machine learning algorithms with molecular modeling can enhance the prediction accuracy and reduce computational costs. Multiscale Modeling: Combining different modeling approaches, such as QM/MM (Quantum Mechanics/Molecular Mechanics), to study catalytic processes at different scales. High-Throughput Screening: Automation and high-throughput computational screening of catalytic materials to identify promising candidates rapidly. Collaborative Platforms: Development of collaborative platforms that allow researchers to share data, tools, and results to accelerate discovery.
