Synergistic Lewis Acid-Base pair electrolyte Configuration enables reversible zinc anode via multiple electrostatic interactions
Bibliographic record
Abstract
A synergistic Lewis acid-base pair additive, combining citric acid and caffeine, enhances electrochemical performance in aqueous zinc-ion batteries. The tailored additive reconfigures hydrogen bonding for improved Zn 2+ de-solvation, restricts active water, meanwhile co-adsorbs on the zinc anode, suppressing side reactions and promoting uniform Zn 2+ deposition, offering a cost-effective solution to the limitations of single additive. • An innovative Lewis acid-base pair (LABP) additive strategy was first proposed. • Strengthened hydrogen bonds between LABP and active water facilities Zn 2+ dynamics. • LABP adsorbs synergistically onto the zinc surface, forming an LABP-anode interface. • Electrostatic interactions among LABP components, H 2 O, and zinc ensure performance. Aqueous zinc batteries hold significant promise for grid-level energy storage due to low cost and high safety, but dendrite growth and water-induced side reactions limit widespread adoption. Electrolyte additives have emerged as a feasible solution, yet commonly used Lewis-acids, Lewis-bases or zwitterions often lack cost-effectiveness and rational design. Here, we introduce a synergic Lewis acid-base pair (LABP) additive, combining citric acid and caffeine, to address these challenges. While citric acid and caffeine individually causes corrosion and precipitation, together they leverage electrostatic interactions to stabilize the electrolyte by reconfiguring hydrogen bonding to impede proton transport, different from prior additives with first-shell coordination features. Additionally, the additive enhances the LABP co-chemisorbed anode interphase and improves zinc deposition via multiple H 2 O-shielded nucleation sites, as evidenced by experiments and computational simulations. Consequently, the LABP achieves 99.80 % coulombic efficiency in half cells and enables stable operation for 2,800 h at 1.0 mA cm −2 in symmetric cells. In practical zinc-iodine full cells, the LABP extends cycle life to over 680 cycles with high-loading cathodes (13 mg cm −2 ), low N/P ratio (2.6), and lean electrolyte, significantly outperforming cells without the additive. This LABP approach provides new avenues for electrolyte design in zinc-ion and other battery systems.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".