Stabilizing Ni<sup>2+</sup> in Hollow Nano MOF/Polymetallic Phosphides Composites for Enhanced Electrochemical Performance in 3D‐Printed Micro‐Supercapacitors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Polymetallic phosphides exhibit favorable conductivities. A reasonable design of nano‐metal–organic frame (MOF) composite morphologies and in situ introduction of polymetallic phosphides into the framework can effectively improve electrolyte penetration and rapid electron transfer. To address existing challenges, Ni, with a strong coordination ability with N, is introduced to partially replace Co in nano‐Co–MOF composite. The hollow nanostructure is stabilized through CoNi bimetallic coordination and low‐temperature controllable polymetallic phosphide generation rate. The Ni, Co, and P atoms, generated during reduction, effectively enhance electron transfer rate within the framework. X‐ray absorption fine structure (XAFS) characterization results further confirm the existence of Ni–N, Ni–Ni, and Co–Co structures in the nanocomposite. The changes in each component during the charge–discharge process of the electrochemical reactions are investigated using in situ X‐ray diffraction (XRD). Theoretical calculations further confirm that P can effectively improve conductivity. VZNPGC//MXene MSCs, constructed with active materials derived from the hollow nano MOF composites synthesized through the Ni 2+ stabilization strategy, demonstrate a specific capacitance of 1184 mF cm −2 , along with an energy density of 236.75 µWh cm −2 (power density of 0.14 mW cm −2 ). This approach introduces a new direction for the synthesis of highly conductive nano‐MOF composites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 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 it