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US researchers have applied robotics and automation to the discovery of perovskite materials for use in tandem perovskite solar cell technologies. The robotic platform is multifunctional, capable of mixing precursors, spin coating, annealing, and characterization of optoelectronic thin films.
Researchers at the University of California, San Diego have developed an automated materials discovery and testing platform for tandem perovskite solar cell technologies. The robotic platform is multifunctional, capable of mixing precursors, spin coating, annealing, and characterization of optoelectronic thin films.
Initially focused on perovskite technology, it is called the Perovskite Automated Spin Coat Assembly Line (PASCAL). It is suitable for composition engineering to improve the durability of perovskite absorbers for tandem solar cell applications, and screening for triple cation and triple halide compositions.
“We believe that having a robot perform repetitive tasks is resource-efficient, as it frees up well-trained researchers for the higher-level tasks of hypothesis generation and testing,” David P. Fenning, corresponding author of the research, told pv magazine . “It also reduces noise in the experimental data, which increases the statistical power of the experiments.”
The novel platform reportedly allows for a rate of up to 430 sample depositions or measurements per day. “PASCAL automates thin film fabrication using standard spin-coating procedures used in manual processes, but with greater accuracy, control and record keeping than human operators,” the researchers say.
PASCAL allows for a wide selection of compositions and the ability to analyze 58 “unique compositions” within the complex realm of triple halide and triple cation compositions. It also favors coating reproducibility, as demonstrated by the team’s work.
"With this screening dataset, we leveraged machine learning to develop a long-lasting composition that shows near-zero shifting of photoluminescence peaks at both 85 C and photoexposure of approximately 4 sols," the academics explain.
The composition was then transformed into single-junction prototype devices. On the characterization line there are cameras, LED and laser excitation sources, a halogen lamp and a spectrometer. It can generate a standard set of darkfield, brightfield, photoluminescence and transmittance data, stored for each sample.
The entire system is controlled from a single computer using a custom Python library.
Looking at the results, the research affirmed the efficacy of PASCAL specifically for automating solution-processed optoelectronic thin film research. The approach, hardware, and data are “proof that automated platforms are an opportunity to accelerate the identification and discovery of new thin film materials.” The accessibility of low-cost robotics and open-source communities for automation were an enabling factor, Fenning noted.
The platform was presented in the study « PASCAL: the perovskite automated spin coat assembly line accelerates composition screening in triple-halide perovskite alloys », published in Digital Discovery .
Feedback from industry and the research community has been positive. “We have received a lot of encouragement and enthusiasm from researchers, from early career to senior, in both industry and academia. I think our most significant contribution to them may be that it is not as difficult or as expensive as it once was, given the advances in robotics and the open source platforms available,” says Fenning.
Looking ahead, Fenning says, “Operational stability is the name of the game for perovskites. We are working on studies that relate durability to chemical and process variations using the low-noise experimental foundation that PASCAL provides.”
He added that the PASCAL platform is supporting research to “scale up perovskite processing” at a new research center led by the Massachusetts Institute of Technology (MIT), which received funding from the U.S. Department of Energy’s Solar Energy Technologies Office (SETO). It’s called Accelerated Co-Design of Durable, Reproducible, and Efficient Perovskite Tandems, nicknamed ADDEPT, a national center that includes university research teams from the University of California San Diego, Princeton, and MIT, as well as industrial partners CubicPV and Verde Technologies. |
