Neighbors Matter: Leveraging Collective Thermoplasmonic Effects for Smart Soft Actuators
Bibliographic record
Abstract
In this work, we are exploring the collective thermoplasmonic properties of small spherical gold nanoparticles embedded into poly( N -isopropylacrylamide) (pNIPAM) films, with a focus on their application as efficient light-driven nanoheaters for smart soft actuation systems. Uniform Au-pNIPAM hybrid films with adjustable thickness in the micrometer range (1–22 μm) and distinct concentrations of gold nanoparticles were fabricated by using a photopolymerizable pNIPAM-based resin containing Au-pNIPAM core–shell microgels as building blocks (15 nm diameter gold cores). Upon 520 nm light excitation, the Au-pNIPAM films exhibit a significant temperature increase of up to 75 °C above room temperature at a light irradiance of 116 mW/mm 2, as determined by thermal imaging. These results compare well with those obtained with an analytical model describing the rise in temperature produced by neighboring particles in a three-dimensional (3D) matrix under continuous illumination, with a relative margin of error of less than 7% for nearly all cases studied. Finally, light-guided swimming robots were fabricated by leveraging the collective photothermal properties of gold nanoparticles in the Au-pNIPAM films. Under light exposure, the trajectory and rotation of swimming robots floating at the air/water interface can be precisely controlled due to the light-induced Marangoni effect, with average speeds of up to 2.5 mm/s for triangular-shaped robots.
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.
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) | 0.000 | 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 | 0.001 |
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 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".