Reaction Design & Optimization
Chemical reaction design and optimization is vital in organic synthesis research. By altering the reaction parameters (catalyst, pH, solvent, temperature, or time), certain outputs (cost savings, purity, selectivity, or yield) can be achieved. In optimizing chemical reactions, flexibility, precision and reproducibility are required of the synthesis tools with which the experiments are carried out. In designing chemical reactions, focus is placed on building a synthetic pathway to a target molecule from commercially available starting materials.
A “disconnected approach” is typically taken, where focus is placed on the construction of key bonds. The process is broken down into simple steps, working backwards from the target molecule rather than forwards from the starting material. While many chemists resort to their extensive reaction knowledge to make these synthetic routes, there are now many software tools, such as SYNTHIA™, which allow users to easily analyze custom pathways for known and novel molecules against search criteria.
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Buchwald Catalysts and Ligands enable versatile cross-coupling reactions for C-C, C-N, and other bond formations.
Buchwald Catalysts and Ligands enable versatile cross-coupling reactions for C-C, C-N, and other bond formations.
Photocatalysis utilizes visible light to activate a chemical reaction. Our extensive portfolio of catalysts and photoreactors enable consistent reactions in photoredox catalysis.
Explore a wide array of phosphine ligands for cross-coupling reactions and diverse applications.
Several experimental methodologies can be employed in reaction optimization. In a trial and error, or one variable at a time, approach, all experimental inputs are kept constant, except one, to record a certain output. A series of reactions are performed until an optimum is determined. Another variable is then chosen, and the process repeats itself until all inputs have been probed and a set of optimal inputs have been established.
A multi-parameter, or “design of experiments”, approach varies factors simultaneously from their lowest to highest value to find optimal conditions more efficiently. The different combinations are executed in the same set of experiments. Additional experiments are run between low and high factors to determine intrinsic variability. The values can be represented in a cube to illustrate the relations between the factors and the responses. For this optimization process to be successful, attention must be paid to reproducibility by performing the reactions in a systematic manner and controlled framework.
After a viable synthetic pathway to synthesize the target molecule is found countless additional hours are put in to optimize each chemical reaction to make the product better, faster, or more efficient. Utilizing chemical reaction design optimization can lead to scientific breakthroughs more rapidly.
Figure 1.Reaction Optimization Table
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