From Perylene Diimide Polymers to <scp>Fused‐Ring</scp> Electron Acceptors: A <scp>15‐Year</scp> Exploration Journey of Nonfullerene Acceptors
Bibliographic record
Abstract
Comprehensive Summary Fullerene derivatives are classic electron acceptor materials for organic solar cells (OSCs) but possess some intrinsic drawbacks such as weak visible light absorption, limited optoelectronic property tunability, difficult purification and photochemical/morphological instability. Fullerene acceptors are a bottleneck restricting further development of this field. Our group pioneered the exploration of novel nonfullerene acceptors in China in 2006, and initiated the research of two representative acceptor systems, rylene diimide polymer and fused‐ring electron acceptor (FREA). FREA breaks the theoretical efficiency limit of fullerene‐based OSCs (~13%) and promotes the whole field to an unprecedented prosperity with efficiency of 20%, heralding a nonfullerene era for OSCs. In this review, we revisit 15‐year nonfullerene exploration journey, summarize the design principles, molecular engineering strategies, physical mechanisms and device applications of these two nonfullerene acceptor systems, and propose some possible research topics in the near future. What is the most favorite and original chemistry developed in your research group? Fused‐ring electron acceptor for photovoltaics. How do you get into this specific field? Could you please share some experiences with our readers? In 2006 when I came back to ICCAS from USA and started my independent academic career, I was interested in organic photovoltaics (OPV) which I had never touched before since I believed it is useful and should have a bright future. OPV converts renewable solar energy to clean electricity through photovoltaic effect. The active layer in OPV device consists of electron donor and electron acceptor. Although fullerenes were prevailing acceptor materials in OPV at that time, I doubted if this choice is correct considering their fatal flaws such as weak absorption. I was curious about why no research groups in China explored fullerene alternatives before 2006. In 2006 our group initiated the nonfullerene OPV research of China. In 2015 we invented the milestone molecule ITIC and pioneered fused‐ring electron acceptor (FREA). Around 300 research groups in >20 countries have utilized the FREA to fabricate high‐efficiency OPV devices with champion efficiency of >20%. The FREA has subverted previously predominant fullerenes, and is inaugurating a new era of the OPV field. How do you supervise your students? I expect that my students should have some essential personalities such as curiosity, creativity, devotion, persistence and diligence. I encourage them to do original, unique and leading research. I endow them with cheerful academic atmosphere such as self‐motivation, open‐mindedness and cross‐cooperation. I would like to provide them with warm human solicitude when they need help or suffer from bitterness. What is the most important personality for scientific research? Curiosity; uniqueness; persistence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".