Promoting Electromagnetic Wave Absorption Performance by Integrating MoS<sub>2</sub>@Gd<sub>2</sub>O<sub>3</sub>/MXene Multiple Hetero‐Interfaces in Wood‐Derived Carbon Aerogels
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 Multi‐component composite materials with a magnetic‐dielectric synergistic effect exhibit satisfactory electromagnetic wave absorption performance. However, the effective construction of the structure for these multi‐component materials to fully exploit the advantages of each component remains a challenge. Inspired by natural biomass, this study utilizes wood as the raw material and successfully prepares high‐performance MoS 2 @Gd 2 O 3 /Mxene loaded porous carbon aerogel (MGMCA) composite material through a one‐pot hydrothermal method and carbonization treatment process. With a delicate structural design, the MGMCA is endowed with abundant heterogeneous interface structures, favorable impedance matching characteristics, and a magnetic‐dielectric synergistic system, thus demonstrating multiple electromagnetic wave loss mechanisms. Benefiting from these advantages, the obtained MGMCA exhibits outstanding electromagnetic wave absorption performance, with a minimum reflection loss of −57.5 dB at an ultra‐thin thickness of only 1.9 mm. This research proposes a reliable strategy for the design of multi‐component composite materials, providing valuable insight for the design of biomass‐based materials as electromagnetic wave absorbers.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it