Hillhouse Research Group
Recent News Highlights
Dr. Tim Siegler and Dr. Wiley Dunlap-Shohl report the discovery of a previously unknown degradation pathway for hybrid perovskites (which happens to be the the dominant degradation pathway in the presence of oxygen, humidity, and light) and report the first-ever kinetic rate equation for perovskite degradation. See pre-print in ChemRxiv
Optical absorbance is used to study the kinetics of methylammonium lead iodide (MAPbI3) thin film degradation in response to combinations of moisture, oxygen, and illumination over a range of temperatures. 105 degradations were conducted over 41 unique environmental conditions. We discover that water acts synergistically with oxygen in a water-accelerated photo-oxidation (WPO) pathway. This pathway is the dominant pathway at 25 °C and is 10, 100, 1000, and >1000 times faster than dry photooxidation (DPO), degradation via hydrate formation, thermal degradation, and blue light degradation, respectively. We find that the rate determining step for DPO is proton abstraction from methylammonium while for WPO it is proton abstraction from water, which occurs at a faster rate and results in water acting as an accelerant for photooxidation of MAPbI3. A full kinetic rate equation is derived and fitted to the data to determine activation energies and rate constants. Find the preprint here.
Dr. Ryan Stoddard and Dr. Wiley Dunlap-Shohl's paper on machine learning to forecast degradation of perovskite thin films and devices to appear in ACS Energy Letters
In ACS Energy Letters, we report that use of linear machine learning models can be used to accurately forecast degradation-based evolution of PV device-relevant properties in perovskite thin films for a range of temperature, humidity, and illumination intensity. We also show these predictive models can be extended to devices by use of dark field microscope imaging. Link to Ryan and Wiley's paper.