Deuteration Effects on the Physical and Optoelectronic Properties of Donor–Acceptor Conjugated Polymers
Bibliographic record
Abstract
The significant differences in scattering cross sections between deuterium and protium are unique to neutron scattering techniques and have been a long-standing area of interest within the neutron scattering community. Researchers have explored selective deuteration to manipulate scattering contrast in soft matter systems, leading to the widespread use of deuterium labeling in materials development. As deuteration changes the atomic mass, it alters physical properties such as molecular volume, polarizability, and polarity, which in turn may affect noncovalent interactions and crystal ordering. Despite previous studies, there remains a limited understanding of how deuteration impacts donor-acceptor (DA) conjugated polymers. To address this, we synthesized deuterated DPP polymers and systematically investigated the effects of side-chain deuteration on their thermal stability, crystal packing, morphology, and optoelectronic properties. We found that deuteration increased the melting and crystallization temperatures of DPP polymers, although it did not significantly alter their morphology, molecular packing, or charge mobility. These properties were assessed by using atomic force microscopy (AFM), X-ray scattering, and thin-film transistor device measurements, respectively, for DPP polymers. Our work shows that deuterium labeling could be a powerful method for controlling scattering length density, enabling neutrons to study the structure and dynamics of conjugated polymers without impacting their electronic performance.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".