The Perovskite Database Project

as published in nature energy magazine

The Perovskite Database Project (PDP) aims at making all perovskite device data, both past and future, available in a form adherent to the FAIR data principles, i.e. Findable, Accessible, Interoperable, and Reusable.

A 10 minute lecture by Prof. Eva Unger about PDP and FAIR data principles:

As published in Nature Energy magazine the project team went through over 16,000 perovskite papers and recorded data for over 42,000 researched perovskite solar cells. Anyone can upload more data to the database and anyone can register to access the data. Please use the form on this page to gain access to this database on MaterialsZone's platform.

Perovskite Solar Cells (PSC) are predicted to be a disruptive technology in the PV industry as they are able to achieve a very high PCE increasing from 3.8% in 2009 to 25.7% in 2022.

High efficiency, combined with the lightweight, flexible nature (having 1/10th of the weight per square meter as silicon) makes PSCs very attractive. Rethink Energy predicts PSCs can achieve 7% of global photovoltaic market share by 2025, increasing to >29% by 2030 (assuming predicted efficiency will increase by 30% and costs reduced by up to 50%). Allied Market Research estimates that global Perovskite solar cell market size will reach $6.6 billion by 2030, growing at a CAGR of 32.4% from 2021 to 2030.

An illustration of the standard research cycle and of how the Perovskite Database Project expands it and contributes to research and public knowledge is demonstrated in figure 1:

Figure 1. (credit: https://www.nature.com/articles/s41560-021-00941-3)

The project is based on an open database and open-sourced tools enabling anyone, without any programming experience, to interactively explore, search, filter, analyze, and visualize the data. The core of those tools are a set of interactive graphics that can be reached from the web page.

An example of one of the dashboards showing the progress of PCE of perovskite cells along the years is demonstrated in figure 2.

Figure 2: A plot generated using one of the dashboards showing the progress of PCE of perovskite cells along the years. (credit: https://www.nature.com/articles/s41560-021-00941-3)

Available Apps

The apps are accessible through MaterialsZone’s platform. Before signing up to the platform, make sure to:

  1. Fill-out the application form on the this page. (The email you enter in the form will be the one for accessing the platform and will be verified along the sign up process)
  2. Receive an invitation by email from MaterialsZone.

There are now 9 apps focusing on different aspects, with more to come.

Figures generated by the interactive graphics are free to be used in any way.

List of Apps:

  • General development - Focuses on the development of general device performance and enables filtering within the entire dataset.
  • Record evolution - Sorts out the record cells given any number of specified constraints, e.g. for transparent cells, or inverted cells, or cells based on CsPbI3, or cells fulfilling any combination of constraints.
  • Band gap analysis - Focusing on comparing device metrics as a function of perovskite band gap.
  • Scaling - Specifically focusing on illustrating the development in device scaling.
  • Modules - Focusing on perovskite modules.
  • Stability - Enables filtering and visualization of all devices with reported stability data.
  • Outdoor testing - Enables filtering and visualization of all devices with data from outdoor measurements. This is still a rather limited dataset, but we expect more of this in the future.
  • Downloading data - Enables downloading the entire dataset or any possible subset thereof.
  • Uploading data - For uploading new data to the database.

For additional information about the project, the contributors, the partners, the content within the database, and how to extract or contribute to the database, please visit the project's official website.

While you can extract value from the current database, its current structure is not AI/ML ready. Thus, it is limited in providing AI/ML insights and you may find it difficult to converge it with your own data.

Figure 3 shows a small glimpse of the type of insights you might obtain from the data using Materials Zone when subscribing to more advanced features of the platform.

Figure 3: Showing the PCE distribution in a given dataset (subset) while coloring the records by the perovskite material class. (credit: MaterialsZone's platform)

These valuable insights and much more were obtained by upgrading a subset of the data with our more advanced features. We’ll be happy to show you what great insights emerged from the data.

As a next step, the raw data, combined with your own private data, has the potential to provide you with rapid insights and accelerate your research, development and time-to-market.

You can “stand on the shoulders of giants” (the authors and researchers behind these 16,000 papers) and make your next technology leap, much faster, with shorter and fewer ‘trial and error’ cycles.

If you would like to learn more, please send us an email to: contact@materials.zone