A Wiki for Perovskite Solar Cell Research

An international team of experts has collected data on metal halide perovskite solar cells from more than 15,000 publications and developed a database with visualisation options and analysis tools. The database is open source and provides an overview of the rapidly growing knowledge as well as the open questions in this exciting class of materials. The study was initiated by HZB scientist Dr. Eva Unger and implemented and coordinated by her postdoc Jesper Jacobsson.


Halide perovskites have huge potential for solar cells and other optoelectronic applications. Solar cells based on metal-organic perovskites achieve efficiencies of more than 25 percent, they can be produced cheaply and with minimal energy consumption, but still require improvements in terms of stability and reliability. In recent years, research on this class of materials has boomed, producing a flood of results that is almost impossible to keep track of by traditional means. Under the keyword "perovskite solar", more than 19,000 publications had already been entered in the Web of Science (spring 2021).

FAIR data

Now 95 experts from more than 30 international research institutions have designed a database to systematically record findings on perovskite semiconductors. The data are prepared according to the FAIR principles, i.e. they are findable, accessible, interoperable and reusable. By reading the existing literature, the experts have collected more than 42,000 individual data sets, in which the data can be filtered and displayed according to various criteria such as material compositions or component type. Researchers from several teams at HZB were involved in this Herculean task.

New insights by AI

"Data has always been the basis of empirical science, but when data is collected in sufficiently large quantities and in a coherent way, it can be searched with modern algorithms and artificial intelligence and can provide completely new insights," says Jesper Jacobsson, coordinator of this project.

Interactive tools, easy uploads

The database provides analysis tools and graphical data visualizations that enable easy and interactive exploration, and also offers the option to easily upload new data from new peer-reviewed publications. "It's a wiki for perovskite solar cell research," says Eva Unger, counting on the participation of the research community: "In the future, this type of research data platform will offer us the opportunity to make our research data public according to FAIR principles in addition to established publication formats."

Not only science, but also industry will benefit: The database provides an overview of the current state of knowledge, while also uncovering gaps in knowledge from which new productive research questions can arise.

arö

  • Copy link

You might also be interested in

  • Michael Naguib is visiting HZB as a Humboldt Research Awardee
    News
    16.06.2025
    Michael Naguib is visiting HZB as a Humboldt Research Awardee
    Professor Michael Naguib, from Tulane University in the USA, is one of the discoverers of a new class of 2D materials: MXenes are characterised by a puff pastry-like structure and have many applications, such as in the production of green hydrogen or as storage media for electrical energy. During his Humboldt Research Award in 2025, Professor Naguib is working with Prof Volker Presser at the Leibniz Institute for New Materials in Saarbrücken and with Dr Tristan Petit at HZB.
  • Tage des offenen Reallabors - Das HZB lädt ein!
    Nachricht
    11.06.2025
    Tage des offenen Reallabors - Das HZB lädt ein!
    Photovoltaik trifft Architektur.
  • AI in Chemistry: Study Highlights Strengths and Weaknesses
    News
    04.06.2025
    AI in Chemistry: Study Highlights Strengths and Weaknesses
    How well does artificial intelligence perform compared to human experts? A research team at HIPOLE Jena set out to answer this question in the field of chemistry. Using a newly developed evaluation method called “ChemBench,” the researchers compared the performance of modern language models such as GPT-4 with that of experienced chemists.