Dimensionality-engineered electron channels for directional acceleration of 1,4-NADH-dependent photoenzymatic CO2-to-liquid fuels
Bibliographic record
Abstract
Efficient and selective regeneration of enzymatically active 1,4-NADH from NAD + is pivotal for accelerating photoenzymatic CO 2 conversion. However, constructing photocatalysts that sustain continuous electron flow and provide sufficient hydride supply remains a major challenge. Herein, we report a rhodium-coordinated three-dimensional conjugated polymer (3D-Bpy-Rh) photocatalyst featuring multiple electron channels, designed through dimensionality engineering and incorporation of hydride-forming active centers. Such a 3D structure promotes rapid charge separation and multidimensional electron migration, while facilitating trapped-electron release to Rh centers for accelerated electron transfer. As a result, 3D-Bpy-Rh achieves a visible-light driven NADH regeneration efficiency of 90.8 % with 99.2 % selectivity toward 1,4-NADH, surpassing state-of-the-art photocatalysts. Furthermore, the mechanism between the electron reduction capability of the photocatalyst and the selective formation of 1,4-NADH was elucidated, combining transient absorption spectroscopy analysis and DFT calculations. When integrated into photoenzymatic systems, this photocatalyst enhances CO 2 conversion, boosting methanol and ethanol yields by 5.2- and 2.0-fold, respectively. These results highlighted the potential of dimensionality-engineered photocatalysts for selective 1,4-NADH regeneration and efficient photoenzymatic fuel synthesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".