Design-to-Device Approach Affords Panchromatic Co-sensitized Solar Cells

Cooper, Christopher B.; Beard, Edward J.; Vazquez-Mayagoitia, Alvaro; Stan, Liliana; Stenning, Gavin B. G.; Nye, Daniel W.; Vigil, Julian A.; Tomar, Tina; Jia, Jingwen; Bodedla, Govardhana Babu; Chen, Song; Aibar, Lucia Gallego; Ontaneda, Santiago Franco; Carella, Antonio; Thomas, K. R. Justin; Xue, Song; Zhu, Xunjin; Cole, Jacqueline M.

doi:10.1002/aenm.201802820

Title: Design-to-Device Approach Affords Panchromatic Co-sensitized Solar Cells

Journal Article · 06 December 2018 · Advanced Energy Materials

DOI: https://doi.org/10.1002/aenm.201802820 · OSTI ID:1494584

^[1]; Beard, Edward J. ^[2]; Vazquez-Mayagoitia, Alvaro ^[3]; Stan, Liliana ^[3]; Stenning, Gavin B. G. ^[4]; Nye, Daniel W. ^[4]; Vigil, Julian A. ^[2]; Tomar, Tina ^[5]; Jia, Jingwen ^[6]; Bodedla, Govardhana Babu ^[7]; Chen, Song ^[7]; Aibar, Lucia Gallego ^[8]; Ontaneda, Santiago Franco ^[8]; Carella, Antonio ^[9]; Thomas, K. R. Justin ^[10]; Xue, Song ^[6]; Zhu, Xunjin ^[7]; Cole, Jacqueline M. ^[11]

Univ. of Cambridge, Cambridge (United Kingdom); Rutherford Appleton Lab, Oxon (United Kingdom)
Univ. of Cambridge, Cambridge (United Kingdom)
Argonne National Lab. (ANL), Argonne, IL (United States)
STFC Rutherford Appleton Lab, Didcot (United Kingdom)
Indian Inst. of Technology Roorkee, Roorkee (India)
Tianjin Univ. of Technology, Tianjin (People's Republic of China)
Hong Kong Baptist Univ., Hong Kong (People's Republic of China)
Univ. of Zaragoza-CSIC, Zaragoza (Spain)
Univ. of Naples Federico II, Naples (Italy)
Indian Inst. of Technology, Roorkee, Roorkee (India)
Univ. of Cambridge, Cambridge (United Kingdom); Rutherford Appleton Lab, Oxon (United Kingdom); Argonne National Lab. (ANL), Argonne, IL (United States); STFC Rutherford Appleton Lab, Didcot (United Kingdom)

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. Here, these results demonstrate how data–driven molecular engineering can accelerate materials discovery for panchromatic photovoltaic or other applications.

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Research Organization:: Argonne National Lab. (ANL), Argonne, IL (United States)

Sponsoring Organization:: Spanish Ministerio de Economia y Competitividad (MINECO); Research Grants Council (RGC) of Hong Kong; USDOE

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1494584

Journal Information:: Advanced Energy Materials, Journal Name: Advanced Energy Materials Journal Issue: 5 Vol. 9; ISSN 1614-6832

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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