2024-03-28T15:19:23Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/2394292021-08-18T09:39:12Zcom_10261_46com_10261_3col_10261_299
Accelerating organic solar cell material’s discovery: high-throughput screening and big data
Rodríguez Martínez, Xabier
Pascual San José, Enrique
Campoy Quiles, Mariano
Ministerio de Ciencia e Innovación (España)
European Research Council
CSIC - Unidad de Recursos de Información Científica para la Investigación (URICI)
The discovery of novel high-performing materials such as non-fullerene acceptors and low band gap donor polymers underlines the steady increase of record efficiencies in organic solar cells witnessed during the last years. Nowadays, the resulting catalogue of organic photovoltaic materials is becoming unaffordably vast to be evaluated following classical experimentation methodologies: their requirements in terms of human workforce time and resources are prohibitively high, which rest momentum to the evolution of the organic photovoltaic technology. As a result, high-throughput experimental and computational methodologies are fostered to leverage their inherently high exploratory paces and accelerate novel material’s discovery. In this review, we present some of the computational (pre)screening approaches performed prior to experimentation to select the most promising molecular candidates from the available materials libraries or, alternatively, generate molecules beyond human intuition. Then, we outline the main high-throuhgput experimental screening and characterization approaches with application in organic solar cells, namely those based on lateral parametric gradients (measuring-intensive) and on automated device prototyping (fabrication-intensive). In both cases, experimental datasets are generated at unbeatable paces, which notably enhance big data readiness. Herein, machine-learning algorithms find a rewarding application niche to retrieve quantitative structure-activity relationships and extract molecular design rationale, which are expected to keep the material’s discovery pace up in organic photovoltaics.
This work was supported by the Spanish Ministry of Science and
Innovation through the “Severo Ochoa” Programme for Centers
of Excellence in R&D (FUNFUTURE, CEX2019-000917-S) and
project reference PGC2018-095411-B-I00. The authors
acknowledge financial support from the European Research through project ERC CoG 648901, and support of the
publication fee by the CSIC Open Access Publication Support
Initiative through its Unit of Information Resources for Research
(URICI). The authors thank Prof. C. Brabec and Dr. J. Hauch for
fruitful discussions on the topics of this review. The table of
contents image and Figure 10 in the manuscript have been
designed using freely available resources from Flaticon.com.
Peer reviewed
2021-04-28T08:56:07Z
2021-04-28T08:56:07Z
2021-04-23
artículo
http://purl.org/coar/resource_type/c_6501
Energy and Environmental Science: 10.1039/D1EE00559F (2021)
1754-5692
http://hdl.handle.net/10261/239429
1754-5706
http://dx.doi.org/10.13039/501100000781
http://dx.doi.org/10.13039/501100004837
en
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/CEX2019-000917-S
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-095411-B-I00
info:eu-repo/grantAgreement/EC/H2020/648901
Publisher's version
http://dx.doi.org/10.1039/D1EE00559F
Sí
open
Royal Society of Chemistry (UK)