DFT-assisted design of curcumin-based donor-π-bridge-acceptor molecular structures: Advancing nonlinear optical materials and sustainable organic solar cells
Bibliographic record
Abstract
This study explores the theoretical design of novel curcumin-based structures with enhanced nonlinear optical (NLO) characteristics. By systematically substituting hydroxyl (OH) functionalities in bisdemethoxycurcumin (BdMC) with various donor and acceptor functionalities at the edges of the π-bridge backbone, we constructed 12 different derivatives. Density-functional theory (DFT) and time-dependent DFT (TD-DFT) calculations were performed at the B3LYP/6-311++G(d,p) and CAM-B3LYP/6-311++G(d,p) levels to analyze the optoelectronic properties. The introduction of donors and acceptors significantly improved NLO characteristics. Notably, BdMC-1 (N(C 2 H 5 ) 2 -π-bridge-NO 2 ) exhibited a remarkable enhancement in NLO responses, with the average polarizability (<α>) and the first hyperpolarizability (β tot ) increasing from 465.3 to 660.9 (a.u.) and 14254.4 to 143487.6 (a.u.), respectively. UV–Vis spectroscopy showed BdMC-1 as the most red-shifted compound, with a maximum wavelength (λ max ) of 431.1 nm, the lowest optical bandgap of 2.88 eV, and an ultrahigh light harvesting efficiency (LHE) of 97.4%. The designed compounds exhibited narrower HOMO-LUMO electronic bandgaps (as low as 2.08 eV) compared to BdMC (3.32 eV), contributing to the improved NLO responses. Natural bond orbital (NBO) analysis confirmed the formation of a charge separation state, facilitating effective electron migration from donors to acceptors through the π-bridge. Additionally, using BdMC-based materials as acceptors in organic solar cells (OSCs) yielded open-circuit voltages (Voc) from 1.62 to 2.23 V, fill factors (FF) above 90%, and low exciton binding energies (E e−b ) in the range of 0.08 to 0.80 eV.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".