Simon R. Bare

Abstract Machine learning (ML) is rapidly emerging as a catalyst discovery method, whose success depends on curated experimental datasets with defined uncertainties. Despite this need, uncertainty in catalyst performance is rarely quantified across datasets generated using multiple reactors.

Abstract Dilute-metal-alloy nanoparticles exhibit enhanced catalytic performance compared with monometallic nanoparticles for many reactions. Anecdotal reports indicate that very dilute alloying can also slow the sintering rates of supported nanoparticles, although this has not been rigorously assessed and cannot be explained using bulk descriptors such as metal melting temperature.

Abstract Transitioning to a circular plastics economy will require use of renewable feedstocks, energy-efficient processes, and closed-loop recyclable polymers, such as polyesters. A key challenge lies in sustainably sourcing monomers used to make recyclable polyesters.