Chemometric modeling of power conversion efficiency of organic dyes in dye sensitized solar cells for the future renewable energy

Krishna, Jillella Gopala; Ojha, Probir Kumar; Kar, Supratik; Roy, Kunal; Leszczynski, Jerzy

doi:10.1016/j.nanoen.2020.104537

Title: Chemometric modeling of power conversion efficiency of organic dyes in dye sensitized solar cells for the future renewable energy

Journal Article · Tue Jan 28 00:00:00 EST 2020 · Nano Energy

DOI:https://doi.org/10.1016/j.nanoen.2020.104537· OSTI ID:1598518

Krishna, Jillella Gopala ^[1]; Ojha, Probir Kumar ^[2]; Kar, Supratik ^[3]; Roy, Kunal ^[2]; Leszczynski, Jerzy ^[3]

National Inst. of Pharmaceutical Educational and Research (NIPER), Kolkata (India)
Jadavpur Univ. Kolkata (India)
Jackson State Univ., Jackson, MS (United States)

The present study reports chemometric modeling of power conversion efficiency (PCE) of dye sensitized solar cells (DSSCs) using the biggest available data set till date which comprises around 1200 dyes covering 7 chemical classes. To extract the best structural features required for higher PCE, we have developed multiple partial least squares (PLS) quantitative structure-property relationship (QSPR) models for the Triphenylamine, Phenothiazine, Indoline, Porphyrin, Coumarin, Carbazole and Diphenylamine chemical classes using descriptors derived from the best subset selection method followed by selection of best five models in each dataset based on the Mean Absolute Error (MAE) values. The models were validated both internally and externally followed by the consensus predictions employing “Intelligent Consensus Predictor” tool to examine whether the quality of predictions can be improved with the “intelligent” selection of multiple PLS models. The quality of predictions for the respective external sets showed that the consensus models (CM) are better than the individual models (IM) in most of the cases. From the insights of the developed models, we concluded that attributes like a packed structure toward higher conductivity of electrons, auxiliary donor fragment of aromatic tertiary amines, number of thiophenes inducing the bathochromic shift and augmenting the absorption, presence of additional electron donors, enhancement of electron-donating abilities, number of non-aromatic conjugated C(sp²) which helps as conjugation extension units to broaden the absorption and highly conjugated $$π$$-systems exert positive contributions to the PCE. On the contrary, features negatively contributing to PCE are the followings: fragments which lower the tendency of localized $π–π*$ transition, fragments related to larger volume and surface area of dyes along with hydrophobicity resulting in poor adhesion, fragment RC = N causing dye hydrolysis, steric hindrance for π electronic mobility, fragments enhancing polarity, etc. Finally, the identified features from the best QSPR model of the coumarin dataset was employed in designing of ten more efficient coumarin dyes (predicted %PCE ranging from 8.93 to 10.62) than the existing ones.

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Research Organization:: Jackson State Univ., Jackson, MS (United States)

Sponsoring Organization:: USDOE Office of Science (SC); Government of India; National Institute of Pharmaceutical Education and Research Kolkata (NIPER-Kolkata); University Grants Commission (UGC), New Delhi; National Science Foundation (NSF); Council of Scientific & Industrial Research (CSIR)

Grant/Contract Number:: SC0018322; OIA-1757220

OSTI ID:: 1598518

Alternate ID(s):: OSTI ID: 1597533

Journal Information:: Nano Energy, Vol. 70, Issue C; ISSN 2211-2855

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 24 works

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Title: Chemometric modeling of power conversion efficiency of organic dyes in dye sensitized solar cells for the future renewable energy

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