journal article·2019-02Open access

Design‐to‐Device Approach Affords Panchromatic Co‐Sensitized Solar Cells

Christopher B. Cooper, Edward J. Beard, Álvaro Vázquez‐Mayagoitia, Liliana Stan, Gavin B. G. Stenning, Daniel W. Nye, Julian A. Vigil, Tina Tomar, Jingwen Jia, Govardhana B. Bodedla, Song Chen, Lucía Gallego, Santiago Franco, Antonio Carella, K. R. Justin Thomas, Song Xue, Xunjin Zhu, Jacqueline M. Cole

Advanced Energy Materials· Volume 9· Issue 5

Abstract

Abstract Data‐driven materials discovery has become increasingly important in identifying materials that exhibit specific, desirable properties from a vast chemical search space. Synergic prediction and experimental validation are needed to accelerate scientific advances related to critical societal applications. A design‐to‐device study that uses high‐throughput screens with algorithmic encodings of structure–property relationships is reported to identify new materials with panchromatic optical absorption, whose photovoltaic device applications are then experimentally verified. The data‐mining methods source 9431 dye candidates, which are auto‐generated from the literature using a custom text‐mining tool. These candidates are sifted via a data‐mining workflow that is tailored to identify optimal combinations of organic dyes that have complementary optical absorption properties such that they can harvest all available sunlight when acting as co‐sensitizers for dye‐sensitized solar cells (DSSCs). Six promising dye combinations are shortlisted for device testing, whereupon one dye combination yields co‐sensitized DSSCs with power conversion efficiencies comparable to those of the high‐performance, organometallic dye, N719. These results demonstrate how data‐driven molecular engineering can accelerate materials discovery for panchromatic photovoltaic or other applications.
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Research context

OpenAlex topics: Machine Learning in Materials Science · Quantum Dots Synthesis And Properties · Advanced Photocatalysis Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Cavendish Laboratory Department of Physics University of Cambridge J. J. Thomson Avenue Cambridge CB3 0HE UK

Department of Chemical Engineering and Biotechnology University of Cambridge West Cambridge Site Philippa Fawcett Drive Cambridge CB3 0AS UK

Research Complex at Harwell Rutherford Appleton Laboratory Harwell Oxford Didcot Oxon OX11 0FA UK

Argonne National Laboratory 9700 South Cass Avenue Argonne IL 60439 USA

ISIS Neutron and Muon Facility STFC Rutherford Appleton Laboratory Harwell Science and Innovation Campus Didcot OX11 0QX UK

Department of Chemistry University of Cambridge Lensfield Rd Cambridge CB2 1EW UK

Organic Materials Laboratory Department of Chemistry Indian Institute of Technology Roorkee Roorkee 247667 India

Tianjin Key Laboratory of Organic Solar Cells and Photochemical Conversion School of Chemistry & Chemical Engineering Tianjin University of Technology 391 Binshui Xidao Xiqing District Tianjin 300384 P. R. China

Department of Chemistry and Institute of Molecular Functional Materials Hong Kong Baptist University Kowloon Tong Hong Kong P. R. China

Department of Organic Chemistry and Aragon Materials Science Institute ICMA University of Zaragoza‐CSIC Zaragoza 50009 Spain

Department of Chemical Sciences University of Naples Federico II Via Cintia 21 Naples 80126 Italy

Funding

Winston Churchill Foundation of the United States · Ministerio de Economía y Competitividad · Gobierno de Aragón · Research Grants Council, University Grants Committee · Hong Kong Baptist University · U.S. Department of Energy

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