Dynamic Cu<sup>(I)</sup>/Cu<sup>(II)</sup> Redox Shuttle for Maltose and Lactose Isomerization under Pulsed Electric Field
Bibliographic record
Abstract
Due to their prebiotic effects, lactulose and maltulose have garnered increasing interest from the food and pharmaceutical industries. Pulsed electric field (PEF) technology can enhance energy use efficiency, particularly in electroactivation, offering a potential means to convert reducing sugars. A specialized PEF-treated design has been developed to facilitate alternative catalyst-driven production of lactulose and maltulose by manipulating the morphology and oxidation states of copper catalysts. Under optimal conditions (4 kV/cm, 50 Hz, and 10 μs for 30 min), remarkable yields of lactulose (55.75%) and maltulose (43.27%) were achieved. Higher conversion rates were observed with an increased PEF treatment electric field strength and pulse width. The yields and selectivities of lactulose and maltulose were not significantly influenced by the frequency. Intriguingly, structural monosaccharides, including glucose, galactose, xylose, and arabinose, were also detected in the isomerization reaction. These findings suggest that PEF, utilizing CuO plates, induces glycoside bond hydrolysis and the conversion of aldose to pentose. Microscopic measurements (high-resolution transmission electron microscopy (HRTEM), high-energy X-ray diffraction (XRD), in situ Raman, and X-ray photoelectron spectroscopy (XPS)) revealed that transient Lewis acid–base pairs formed by the Cu + /Cu 2+ shuttle could serve as active sites for reducing sugar isomerization, and DFT simulation further confirmed that the presence of active Cu species could promote the isomerization of lactose and maltose via a lower energy barrier. The PEF process proves to be an economical method for transforming low-value sugars into high-value carbon materials.
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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".