2020
DOI: 10.1016/j.trechm.2020.03.006
|View full text |Cite
|
Sign up to set email alerts
|

Organic Photovoltaics: Relating Chemical Structure, Local Morphology, and Electronic Properties

Abstract: Substantial enhancements in the efficiencies of bulk-heterojunction (BHJ) organic solar cells (OSCs) have come from largely trial-and-error-based optimizations of the morphology of the active layers. Further improvements, however, require a detailed understanding of the relationships among chemical structure, morphology, electronic properties, and device performance. On the experimental side, characterization of the local (i.e., nanoscale) morphology remains challenging, which has called for the development of… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
5

Citation Types

0
46
0

Year Published

2020
2020
2022
2022

Publication Types

Select...
6
1

Relationship

1
6

Authors

Journals

citations
Cited by 54 publications
(46 citation statements)
references
References 124 publications
(245 reference statements)
0
46
0
Order By: Relevance
“…In general, such advanced materials are developed based on inspiration from past research and extensive trial‐and‐error experiments; however, a complete survey of target materials including the never‐explored molecular space is difficult due to the high risks involved and limited resources. Recently, the meteoric rise of machine learning (ML) technology has attracted the attention of the organic electronics community, [ 1–5 ] as it allows rapid virtual screening and is much faster than quantum mechanical (QM) calculations. Moreover, ML algorithms can instantaneously give an answer by considering big data, which is impossible for human brains.…”
Section: Introductionmentioning
confidence: 99%
“…In general, such advanced materials are developed based on inspiration from past research and extensive trial‐and‐error experiments; however, a complete survey of target materials including the never‐explored molecular space is difficult due to the high risks involved and limited resources. Recently, the meteoric rise of machine learning (ML) technology has attracted the attention of the organic electronics community, [ 1–5 ] as it allows rapid virtual screening and is much faster than quantum mechanical (QM) calculations. Moreover, ML algorithms can instantaneously give an answer by considering big data, which is impossible for human brains.…”
Section: Introductionmentioning
confidence: 99%
“…[ 1–5 ] However, a further improvement of the materials science and device engineering of organic solar cells is required to employ them in portable, lightweight, and semitransparent energy‐harvesting solutions. [ 6–8 ]…”
Section: Introductionmentioning
confidence: 99%
“…The efficiency of an organic photovoltaic device is sensitively dependent on the active layer morphology, whose structure can be divided into three sections in a polymer:fullerene bulk heterojunction: (1) a pure polymer region, (2) a pure fullerene region, and (3) donor:acceptor interface one [ 15 ]. The latter has a crucial role in the light absorption, electron-hole recombination, and exciton dissociation, and therefore determines the PCE.…”
Section: Introductionmentioning
confidence: 99%