Synergistic Cathode Design for High‐Performance Dual‐Salt Magnesium/Lithium‐Ion Batteries Using 2D/2D 1T/2H‐MoS<sub>2</sub>@Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene Nanocomposite
Bibliographic record
Abstract
Abstract Magnesium‐ion batteries (MIBs) and dual‐salt magnesium/lithium‐ion batteries (MLIBs) have emerged as promising contenders for next‐generation energy storage. In contrast to lithium metal anode in lithium metal batteries, magnesium metal anode in MIBs and MLIBs presents a safer alternative due to the limited dendrite growth and higher volumetric capacity, along with higher natural abundance. This study explores a MLIB configuration with a novel cathode design by employing a 2D/2D nanocomposite of 1T/2H mixed phase MoS2 and delaminated Ti3C2Tx MXene (1T/2H‐MoS2@MXene) to address challenges associated with slow kinetics of magnesium ions during cathode interactions. This cathode design takes advantage of the high electrical conductivity of Ti3C2Tx MXene and the expanded interlayer spacing with enhanced conductivity of the 1T metallic phase in 1T/2H mixed phase MoS2. Through a designed synthesis method, the resulting nanocomposite cathode maintains structural integrity, enabling the stable and reversible storage of dual Mg2+ and Li+ ions. The nanocomposite cathode demonstrates superior performance in MLIBs compared to individual components (253 mAh g−1 at 50 mA g−1, and 36% of capacity retention at 1,000 mA g−1), showcasing short ion transport paths and fast ion storage kinetics. This work represents a significant advancement in cathode material design for cost‐effective and safe MLIBs.
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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".