UV-vis, MCD, and computational studies of the electronic structures of core-modified porphyrins and phthalocyanines
Bibliographic record
Abstract
The electronic structures and optical properties of a large variety of core-modified porphyrins, phthalocyanines (Pcs), naphthalocyanines (Ncs), and anthracocyanines (Acs) were investigated using UV-vis and magnetic circular dichroism (MCD) methods. In some cases, electrochemistry and spectroelectrochemistry were used to further probe the electronic structures of these compounds. In addition, Density Functional Theory (DFT), and Time Dependent DFT (TDDFT) approaches were also employed to correlate experimental properties with the electronic structures of the target compounds. Several types of ligands (bulky, electronwithdrawing, and electron-donating) were incorporated onto the respective macrocyclic peripheries to determine trends and the best macrocycle-substituent combination for its suitable application. The most prominent applications of the molecules studied in this thesis are photochemotherapeutics for photodynamic cancer therapy (PDT), light-harvesting, and optical materials. Speaking directly to their PDT and near infra-red (NIR) solar cell applications, the compounds that had the strongest and furthest red-shifted absorptions in the NIR region of the optical absorption spectrum were macrocycles with greatly extended π-systems (the Ncs and Acs) which also featured bulky, electron-donating ligands.
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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) | 0.002 | 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".