The researchers have demonstrated that RoboMapper can rapidly identify new perovskite materials with improved stability and solar cell efficiency. The team’s findings have been published in Matter.
“RoboMapper allows us to conduct materials testing more quickly, while also reducing both cost and energy overhead – making the entire process more sustainable,” said Aram Amassian, corresponding author of a paper on the work and a professor of materials science and engineering at North Carolina State University (NC State).
Conventional materials research requires a researcher to prepare a sample and undertake multiple steps to test each sample using different instruments. This involves placing, aligning and calibrating samples as needed to collect the data.
Previous efforts to automate this process have relied largely on automating the assembly line with one sample per chip moving through the data collection process. According to NC State, this improves speed, but each of the steps is done with one sample at a time.
“RoboMapper also automates this process, but places dozens of samples on each chip by miniaturising the material samples with the help of modern printing,” Amassian said in a statement. “It still performs each step of the data collection process, but it does so for multiple materials in parallel, saving time and energy.”
“This makes searching for new materials far more efficient, more cost effective, and more sustainable in terms of our carbon footprint,” said Tonghui Wang, lead author of the paper and a Ph.D. student at NC State. “It’s nearly 10 times faster than previous automated techniques.”
The team evaluated the environmental impact of traditional materials research and data collection and compared it with the RoboMapper.
“It was remarkable to find that characterisation is the major source of greenhouse gas emissions in materials research,” said environmental economist Lucía Serrano-Luján, co-author of the paper and a researcher at Rey Juan Carlos University and the Technical University of Cartagena. “The RoboMapper’s ability to streamline the data collection process by placing dozens of materials on the same chip reduced greenhouse gas emissions tenfold.”
To demonstrate RoboMapper, the researchers focused first on perovskite materials, which are defined by their crystalline structure and are better than silicon at absorbing light. Perovskite solar cells can be thinner and lighter than silicon solar cells without sacrificing the cell’s ability to convert light into electricity. These favourable properties are offset by the material’s stability.
“The challenge is that perovskite materials tend to degrade when exposed to light, losing the properties that made them desirable in the first place,” said Amassian. “We’re looking for ways to engineer these materials so that they are stable,”
The researchers had their first significant finding with RoboMapper during the technology’s proof-of-concept demonstration.
The researchers tasked RoboMapper with making alloys using a defined set of elements. RoboMapper then made samples with 150 different alloy compositions and conducted optical spectroscopy and X-ray structural assessments and stability tests of those samples.
RoboMapper’s tests were designed to identify whether an alloy was suitable for tandem solar cells. This meant assessing whether it had the crystalline structure of a perovskite; whether it had a desirable set of optical characteristics, and whether it was stable when exposed to intense light. This experimental data was used to construct a computational model that identified a specific alloy composition that it predicted would have the best combination of desired attributes.
The researchers then replicated the desired alloy with RoboMapper and conventional laboratory techniques, both of which were tested.
“We are able to quickly identify the most stable composition from a possible set of perovskite alloys at a target band gap using the specific suite of elements we confined ourselves to for this proof-of-concept work,” said Amassian. “The material we identified using RoboMapper also turned out to be more efficient at converting light into electricity in solar cell devices. Our conventional techniques validated the results from RoboMapper.
Amassian said the next steps for this work include expanding the range of potential alloys for testing in RoboMapper.
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