Catalysts enable the quick and accurate synthesis of new molecules. They can be optimized for turnover frequency, selectivity, efficiency, and stability. High-quality catalysts enable the high-volume production of commodity chemicals and the efficient synthesis of specialty chemicals and drugs at high purities.
Optimizing existing catalysts and developing novel catalysts can be a laborious process with vast resources needed to efficiently screen potential catalysts. The traditional process of catalysis design is slow and cumbersome, with large quantities of failed experiments and mountains of waste produced in the process. In the lab, it can be difficult to gain insights as to what is happening at the molecular level, and without such insight, experimentalists are often in the dark about which steps to take to improve their catalyst.
Insight into the mechanism of the catalysts provided by computations can immediately unveil how steric and electronic substitutions can help or hinder the catalyst in the quest to improve turnover frequency, selectivity, and efficiency. Knowing which step is rate- or selectivity-determining can help focus design efforts on optimizing the catalyst for that specific step. Being able to screen possible compounds in a high-throughput manner allows experimentalists to narrow down a list from hundreds or thousands of candidates to the ten best that they should try in the lab.
Computational tools accelerate the traditional catalyst optimization process, providing high-quality candidates and insight into the mechanism of the reactions involved. Rowan’s workflows can provide insight into your current catalysts, and helps model you potential new catalysts, decreasing the time from ideation to high-purity products.
Rowan puts the power of computational tools into the hands of traditional lab chemists. With Rowan, it is easy for those without modeling experience to quickly obtain answers to their chemical questions.
Rowan's Fukui index workflow can quickly identify which sites on a molecule are most reactive to nucleophiles, electrophiles, and radicals. This workflow work on organic and inorganic molecules, and runs many times faster than a traditional transition state search, putting insights immediately into the hands of experimental chemists, allowing them to asses the affects of R-groups or other substitutions on reaction rates. These insights can also be used to guide computations for mechanistic determination, indicating where the initial reaction is likely to take place on a molecule.
When precise answers are needed, Rowan's transition state optimization tools allow users to determine the energy barrier to their reaction and gain insight into how to improve their catalyst. The lowest energy conformer for reactants, products, and transition states can be determined with Rowan's conformational search workflow. Conformational searches also provide entropic corrections, which are often neglected in traditional computational chemistry calculations.
Reduction potentials can be screened quickly with our custom workflow, giving unprecedented insight into how substitutions will affect the operating voltage of electrocatalysts. When coupled with a complete mapping of the catalytic pathway with Rowans TS tools, one can determine how increasing the overpotential will affect the reaction rate when there are multiple pathways available. Similarly, pKa computations can be performed to determine the charge of the molecule at different pHs (see our preprint) and thus the effect of pH on the reaction pathway and rate.
Talk with a member of our team to learn how Rowan can accelerate materials science research and help you develop next-generation materials.
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