Zhao, Yicheng | Search NASA

DOE OSTI2023

Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells

Abstract Simultaneously optimizing the processing parameters of functional thin films remains a challenge. The design and utilization of a fully automated platform called SPINBOT is presented for the engineering of solution‐processed functional thin films. The SPINBOT is capable of performing experiments with high sampling variability through the unsupervised processing of hundreds of substrates with exceptional experimental control. Through the iterative optimization process enabled by the Bayesian optimization (BO) algorithm, the SPINBOT explores an intricate parameter space, continuously improving the quality and reproducibility of the produced thin films. This machine learning (ML)‐guided reliable SPINBOT platform enables the acceleration of the optimization process of perovskite solar cells via a simple photoluminescence characterization of films. As a result, this study arrives at an optimal film that, when processed into a solar cell in an ambient atmosphere, immediately yields a champion power conversion efficiency (PCE) of 21.6% with satisfactory performance reproducibility. The unsealed devices retain 90% of their initial efficiency after 1100 h of continuous operation at 60–65 °C under metal‐halide lamps. It is anticipated that the integration of robotic platforms with the intelligent algorithm will facilitate the widespread adoption of effective autonomous experimentation to address the evolving needs and constraints within the materials science research community.

14 SOLAR ENERGY↗

DOE OSTI2022

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↗