An in-Depth Study of How Zinc Metal Surface Morphology Determines Aqueous Zinc-Ion Battery Stability
Bibliographic record
Abstract
In order to achieve the net-zero world initiative and combat the climate crisis, a global consensus of marching towards a sustainable energy structure has been built, where developing reliable, affordable, and sustainable energy storage devices, the medium of storing intermittent surplus electricity from clean and inexhaustible renewable energy sources, such as wind power and solar energy, and transferring to the smart electric grid system, is of great significance [1]. Besides lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs), the two dominant technologies having been developed substantially in the energy storage industry, researchers started pioneering studies on multivalent-ion systems of Ca [2, 3], Mg [4], Al [5, 6], and Zn [7-9] with competitive advantages, especially the ones as non-flammable economic substitutes, to ease manufacturing burden and enrich practical solutions for widespread application scenarios [10]. Especially, zinc metal with benefits of aqueous compatibility, commensurate capacity (820 mAh/g), and crust abundance, a resurgence of rechargeable zinc-ion batteries (ZIBs) is happening. This battery system with water-based electrolyte chemistries is born with eye-catching benefits of safety and affordability; Zn/MnO2 with an improved energy density of 409 Wh/kg at 1.9 V is considered a promising candidate for grid-scale energy storage [11]. This revolutionary cheap and safe solution empowers the global energy structural transformation and enriches the public’s awareness of sustainable development. However, like most reactive metals, zinc exposed in the air naturally evolves a dense passivation layer of Zn5(CO3)2(OH)6 to discontinue the corrosion by oxygen and humidity, which, in batteries, can passivate the molecular dynamics at the interface between zinc and the electrolyte and demonstrate enormous electron transfer resistance due to the inferior conductivity [12]. Thus, wearing off this passivation layer is considered a facile approach to revitalize the frozen kinetics of zinc ions [13]. Exposing fresh zinc to the electrolyte is also conductive of forming a functional solid-electrolyte interphase (SEI). Studies present that ZnF2-rich SEI plays a pivotal role in elongating the cycling life of zinc symmetric cells by effectively screening zinc from electrolyte solvents and reducing their sequence of side reactions [14]. Additionally, a tactful change of zinc’s surface roughness before electrochemical operations should impact electron distribution, zinc nucleation and growth, and SEI formation. Especially, dendrites are often considered guilty of internal short-circuiting of batteries; similar to lithium, the far-end of zinc dendrites can become dead zinc, whose accumulation brings in issues of electrolyte depletion, anodic capacity loss, internal resistance growth, and cell polarization [15]. In this work, a simple method was developed to change the surface of Zn anode to create more nucleation sites with lowered energy barriers (nucleation over-potentials), thus alleviating their dendrite growth. The cycling programs for zinc symmetric cells are standardized by fixing either the depth of cycling (DOC) or the areal current density in accordance with the constant energy or constant power supply in full batteries. In order to enunciate the battery degradation mechanism and shed light on the gas emission problems, we operate a careful electrochemical analysis cooperated with the differential electrochemical mass spectrometry (DEMS) technique. The preliminary data demonstrate an evident impact of initial zinc surface morphology on sequential zinc plating/stripping profiles and eventual lifespans at serial DOCs and current densities.
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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 | 0.001 |
| 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".