Hybrid Photo- and Thermal Catalyst System for Continuous CO<sub>2</sub> Reduction
Bibliographic record
Abstract
Heterogeneous thermal catalytic processes are vital for industrial production of fuels, fertilizers, and other chemicals necessary for sustaining human life. However, these processes are highly energy-intensive, requiring a vast consumption of fossil fuels. An emerging class of heterogeneous catalysts that are thermally driven but also exhibit a photochemically enhanced rate can potentially reduce process energy intensity by partially substituting conventional heat (where fossil fuels are needed) with solar energy. Such catalyst systems have yet to be practically utilized. Here, we demonstrate a compact electrically heated photo- and thermal annular reactor module to reduce CO2 to CO, via the reverse water gas shift reaction. A first-principles-based design approach was taken in developing a SiO2 on an Al photo- and thermal catalyst system for the model photo- and thermal indium oxide hydroxide (In2O3–x(OH)y) catalysts. A 5-fold light enhancement in the CO production rate and over 70 h of stable CO production were achieved. This represents the highest light enhancement effect reported for this model photocatalyst to date. The reactor presented herein allows continuous operation and a significant reduction of 31% in heater power consumption when provided with an additional 2 suns of irradiation, demonstrating the strong photo- and thermal-harvesting performances of the catalyst system developed in this work.
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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) | 0.001 | 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".