The discovery of new material combinations for catalysis involves a combination of experimental and computational approaches. Key methodologies include:
1. High-Throughput Screening: This involves the rapid synthesis and testing of a large number of material combinations to identify promising candidates. 2. Computational Modeling: Advanced computational techniques such as density functional theory (DFT) and machine learning can predict the catalytic properties of new material combinations before they are synthesized. 3. Combinatorial Chemistry: This technique involves the systematic mixing and matching of different elements to create a library of potential catalysts. 4. In Situ Characterization: Techniques like X-ray diffraction and electron microscopy are used to analyze the structure and composition of catalysts under operating conditions.
