Tag: Perowskit

  • EPFL researchers improve efficiency of solar cells with rubidium

    EPFL researchers improve efficiency of solar cells with rubidium

    Researchers at EPFL have discovered a method for reducing the energy loss of perovskite solar cells, according to a press release. Perovskite solar cells are based on semiconductors with a wide bandgap, but they often suffer from phase separation, which causes a drop in performance over time. The integration of rubidium (Rb) is intended to stabilise the semiconductor material and at the same time improve the energy efficiency of the solar cell. By utilising the lattice voltage of the perovskite film, the researchers were also able to ensure that the Rb ions are fixed in the right place.

    The researchers led by Lukas Pfeifer and Likai Zheng from Michael Grätzel’s group at EPFL also used the X-ray diffraction method to verify and analyse this effect. They discovered that, in addition to the lattice stress, the introduction of chloride ions also makes a decisive contribution to the stabilisation of the material. The chloride ions equalise the size differences between the incorporated elements and thus ensure a more uniform ion distribution. The result is a more uniform material with fewer defects and a more stable electronic structure.

    The new perovskite composition reached 93.5 per cent of its theoretical limit with an open circuit voltage of 1.30 volts. This is one of the lowest energy losses ever measured in perovskite semiconductors. An improved photoluminescence quantum yield also indicates a more efficient conversion of sunlight into electricity.

    Increasing the efficiency of perovskite solar cells could lead to more efficient and cost-effective solar modules and thus reduce dependence on fossil fuels. Perovskites could also be used for LEDs, sensors and other optoelectronic applications. The EPFL’s findings could therefore also accelerate the commercialisation of these technologies.

  • AI accelerates perovskite solar cells for the mass market

    AI accelerates perovskite solar cells for the mass market

    Perovskite solar cells already achieve efficiencies of over 26% and are light, flexible and inexpensive to produce. They are considered a promising alternative to conventional silicon modules. However, challenges such as long-term stability and scalability still stand in the way of industrial utilisation.

    AI as the key to optimising production
    The Karlsruhe Institute of Technology (KIT) is researching how machine learning can improve the manufacturing process for perovskite cells. Deep learning models analyse material properties in real time and optimise the parameters for maximum efficiency.

    Detecting errors before they occur
    AI uses in-situ imaging techniques to monitor thin-film formation and detect errors at an early stage. This allows process deviations to be corrected immediately and expensive rejects to be avoided.

    Simulations for maximum efficiency
    AI-supported simulations allow production conditions to be precisely adapted. The control of the vacuum quenching time in particular plays a decisive role. AI optimises this process to ensure the best possible material structure.

    The path to market maturity
    The KIT study shows that AI is a key driver for the further development of perovskite photovoltaics. The technology could revolutionise the solar energy market and become industrially usable faster than ever with AI.