• Predicting solar cell performance from t

    From ScienceDaily@1:317/3 to All on Fri Mar 4 21:30:34 2022
    Predicting solar cell performance from terahertz and microwave
    spectroscopy

    Date:
    March 4, 2022
    Source:
    Helmholtz-Zentrum Berlin fu"r Materialien und Energie
    Summary:
    Many semiconducting materials are possible candidates for solar
    cells. In recent years, perovskite semiconductors in particular
    have attracted attention, as they are both inexpensive and easy
    to process and enable high efficiencies. Now a new study shows how
    terahertz (TRTS) and microwave spectroscopy (TRMC) can be used to
    reliably determine the mobility and lifetime of the charge carriers
    in new semiconducting materials. Using these measurement data it
    is possible to predict the potential efficiency of the solar cell
    in advance and to classify the losses in the finished cell.



    FULL STORY ==========================================================================
    Many semiconducting materials are possible candidates for solar cells. In recent years, perovskite semiconductors in particular have attracted
    attention, as they are both inexpensive and easy to process and enable
    high efficiencies.

    Now a new study shows how terahertz (TRTS) and microwave spectroscopy
    (TRMC) can be used to reliably determine the mobility and lifetime of the charge carriers in new semiconducting materials. Using these measurement
    data it is possible to predict the potential efficiency of the solar
    cell in advance and to classify the losses in the finished cell.


    ==========================================================================
    The most important properties of a semiconductor to be used as a solar
    cell include the mobility and lifetime of electrons and "holes." Both quantities can be measured without contacts with spectroscopic methods
    using terahertz or microwave radiation. However, measurement data found
    in literature often differ by orders of magnitude. This has made it
    difficult to use them for reliable assessments of material quality.

    Reference samples measured "We wanted to get to the bottom of these differences, and contacted experts from a total of 15 international laboratories to analyse typical sources of error and problems with the measurements," says Dr. Hannes Hempel from the HZB team led by Dr. Thomas Unold. The HZB physicists sent reference samples produced by the team
    of Dr. Martin Stolterfoht at University Potsdam to each laboratory with
    the perovskite semiconductor compound (Cs,FA,MA)Pb(I,Br)3) optimised
    for stability.

    Better data for better prediction One result of the joint work is the significantly more precise determination of the transport properties with terahertz or microwave spectroscopy. "We could identify some neuralgic
    points that have to be considered before the actual measurements takes
    place, which allows us to arrive at significantly better agreement of
    the results," Hempel emphasises.

    Another result of the study: With reliable measurement data and a more
    advanced analysis, the characteristics of the solar cell can also be
    calculated more precisely. "We believe that this analysis is of great
    interest for photovoltaic research, because it predicts the maximum
    possible efficiency of the material in a solar cell and reveals the
    influence of various loss mechanisms, such as transport barriers,"
    says Unold. This applies not only to the material class of perovskite semiconductors, but also to other new semiconducting materials, which
    can thus be tested more quickly for their potential suitability.

    ========================================================================== Story Source: Materials provided by Helmholtz-Zentrum_Berlin_fu"r_Materialien_und_Energie.

    Note: Content may be edited for style and length.


    ========================================================================== Journal Reference:
    1. Hannes Hempel, Tom J. Savenjie, Martin Stolterfoht, Jens Neu,
    Michele
    Failla, Vaisakh C. Paingad, Petr Kužel, Edwin J. Heilweil,
    Jacob A.

    Spies, Markus Schleuning, Jiashang Zhao, Dennis Friedrich, Klaus
    Schwarzburg, Laurens D.A. Siebbeles, Patrick Do"rflinger, Vladimir
    Dyakonov, Ryuzi Katoh, Min Ji Hong, John G. Labram, Maurizio Monti,
    Edward Butler‐Caddle, James Lloyd‐Hughes, Mohammad
    M. Taheri, Jason B. Baxter, Timothy J. Magnanelli, Simon Luo,
    Joseph M. Cardon, Shane Ardo, Thomas Unold. Predicting Solar Cell
    Performance from Terahertz and Microwave Spectroscopy. Advanced
    Energy Materials, 2022; 2102776 DOI: 10.1002/aenm.202102776 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2022/03/220304100955.htm

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