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Hartono, Noor Putri

Publications and source records attributed to Hartono, Noor Putri.

Cage Molecules Stabilize Lead Halide Perovskite Thin Films

The environmental stability of hybrid organic-inorganic perovskite (HOIP) materials needs to increase to enable their widespread adoption in thin-film solar and optoelectronic devices. Molecular additives have recently emerged as an effective strategy for regulating HOIP crystal growth and passivating defects. However, to date the choice of additives is largely limited to a dozen or so materials under the design philosophy that high crystallinity is a prerequisite for stable HOIP thin films. Here, in this study, we incorporate porous organic cages (POCs) as functional additives into perovskite thin films for the first time and investigate the HOIP-POC interaction via a combined experimental and computational approach. POCs are significantly larger than the small-molecule additives explored for HOIP synthesis to date but much smaller than polymeric sealants. Partially amorphized composites of MAPbI 3 (methylammonium lead iodide, HOIP) and RCC3 (an amine POC) form a network-like surface topography and lead to an increase in the optical bandgap from 1.60 to 1.63 eV. Further in situ optical imaging suggests that RCC3 can delay the MAPbI 3 film degradation onset up to 50x under heat and humidity stresses, showing promise for improving reliability in HOIP-based solar-cell and light-emitting applications. Furthermore, there is evidence of molecular interactions between RCC3 and MAPbI 3 , as fingerprinted by the suppressed N-H stretching mode in MA + from Fourier transform infrared (FTIR) spectra and density functional theory (DFT) simulations that suggest strong hydrogen bonding between MA + and RCC3. Given the diversity of POCs and HOIPs, our work opens a new avenue to stabilize HOIPs via tailored molecular interactions with functional organic materials.

36 MATERIALS SCIENCE↗

How machine learning can help select capping layers to suppress perovskite degradation

Environmental stability of perovskite solar cells (PSCs) has been improved by trial-and-error exploration of thin low-dimensional (LD) perovskite deposited on top of the perovskite absorber, called the capping layer. In this study, a machine-learning framework is presented to optimize this layer. We featurize 21 organic halide salts, apply them as capping layers onto methylammonium lead iodide (MAPbI 3 ) films, age them under accelerated conditions, and determine features governing stability using supervised machine learning and Shapley values. We find that organic molecules’ low number of hydrogen-bonding donors and small topological polar surface area correlate with increased MAPbI 3 film stability. The top performing organic halide, phenyltriethylammonium iodide (PTEAI), successfully extends the MAPbI3 stability lifetime by 4 ± 2 times over bare MAPbI 3 and 1.3 ± 0.3 times over state-of-the-art octylammonium bromide (OABr). Through characterization, we find that this capping layer stabilizes the photoactive layer by changing the surface chemistry and suppressing methylammonium loss.

36 MATERIALS SCIENCE↗