3D Vertically Aligned Li Metal Anodes with Ultrahigh Cycling Currents and Capacities of 10 mA cm<sup>−2</sup>/20 mAh cm<sup>−2</sup> Realized by Selective Nucleation within Microchannel Walls
Bibliographic record
Abstract
Abstract Although metallic lithium is regarded as the “Holy Grail” for next‐generation rechargeable batteries due to its high theoretical capacity and low overpotential, the uncontrollable Li dendrite growth, especially under high current densities and deep plating/striping, has inhibited its practical application. Herein, a 3D‐printed, vertically aligned Li anode (3DP‐VALi) is shown to efficiently guide Li deposition via a “nucleation within microchannel walls” process, enabling a high‐performance, dendrite‐free Li anode. Moreover, the microchannels within the microwalls are beneficial for promoting fast Li + diffusion, supplying large space for the accommodation of Li during the plating/stripping process. The high‐surface‐area 3D anode design enables high operating current densities and high areal capacities. As a result, the Li–Li symmetric cells using 3DP‐VALi demonstrate excellent electrochemical performances as high as 10 mA cm −2 /10 mAh cm −2 for 1500 h and 5 mA cm −2 /20 mAh cm −2 for 400 h, respectively. Additionally, the Li–S and Li–LiFePO 4 cells using 3DP‐VALi anodes present excellent cycling stability up to 250 and 800 cycles at a rate of 1 C, respectively. It is believed that these new findings could open a new window for dendrite‐free metal anode design and pave the way toward energy storage devices with high energy/power density.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".