Halide Perovskites Application Toolkit

Halide perovskites have firmly established themselves as the forerunners in next generation photovoltaics and light-emitting devices. Underpinning this spectacular rise are their exceptional properties such as large absorption cross-sections, defect tolerance, large spin-orbit coupling, long balanced charge diffusion lengths, slow hot carrier cooling, ion migration, radiation tolerance etc. Hence, there has been a rapid proliferation of their applications beyond conventional optoelectronics to fields such as spintronics, radiation detectors, memristors, bioimaging <i>etc</i>. Cutting across the boundaries of these emerging perovskite applications, artificial intelligence (AI) and machine learning are key enablers advancing the state-of-the-art in perovskite materials discovery optimized for each niche area. In this talk, I will examine some of our studies in these unconventional applications ranging from advanced photovoltaics concepts of hot carriers (Li et al., 2017) and multiple exciton generation (Li et al., 2018); high order multi-photon spectroscopy(Chen et al., 2017); spintronics (Giovanni et al., 2019); strain engineering and structural dynamics(Fu et al., 2022); as well as our latest foray into perovskite materials design and discovery leveraging fresh Mathematical AI methods based on topology and geometry (Anand et al., 2022). <br/> <br/> <br/>Anand, D. V., Xu, Q., Wee, J., Xia, K., & Sum, T. C. (2022). Topological feature engineering for machine learning based halide perovskite materials design. <i>npj Computational Materials</i>,<i> 8</i>(1), 203. https://doi.org/10.1038/s41524-022-00883-8<br/>Chen, W., Bhaumik, S., Veldhuis, S. A., Xing, G., Xu, Q., Grätzel, M., Mhaisalkar, S., Mathews, N., & Sum, T. C. (2017). Giant five-photon absorption from multidimensional core-shell halide perovskite colloidal nanocrystals. <i>Nature Communications</i>,<i> 8</i>(1), 15198. https://doi.org/10.1038/ncomms15198<br/>Fu, J., Xu, Q., Abdelwahab, I., Cai, R., Febriansyah, B., Yin, T., Loh, K. P., Mathews, N., Sun, H., & Sum, T. C. (2022). Strain propagation in layered two-dimensional halide perovskites. <i>Science Advances</i>,<i> 8</i>(37), eabq1971. https://doi.org/doi:10.1126/sciadv.abq1971<br/>Giovanni, D., Lim, J. W. M., Yuan, Z., Lim, S. S., Righetto, M., Qing, J., Zhang, Q., Dewi, H. A., Gao, F., Mhaisalkar, S. G., Mathews, N., & Sum, T. C. (2019). Ultrafast long-range spin-funneling in solution-processed Ruddlesden–Popper halide perovskites. <i>Nature Communications</i>,<i> 10</i>(1), 3456. https://doi.org/10.1038/s41467-019-11251-4<br/>Li, M., Bhaumik, S., Goh, T. W., Kumar, M. S., Yantara, N., Grätzel, M., Mhaisalkar, S., Mathews, N., & Sum, T. C. (2017). Slow cooling and highly efficient extraction of hot carriers in colloidal perovskite nanocrystals. <i>Nature Communications</i>,<i> 8</i>(1), 14350. https://doi.org/10.1038/ncomms14350<br/>Li, M. J., Begum, R., Fu, J. H., Xu, Q., Koh, T. M., Veldhuis, S. A., Gratzel, M., Mathews, N., Mhaisalkar, S., & Sum, T. C. (2018). Low threshold and efficient multiple exciton generation in halide perovskite nanocrystals. <i>Nature Communications</i>,<i> 9</i>, Article 4197. https://doi.org/10.1038/s41467-018-06596-1