Remote distance prinitng by direct sound printing and its applications
Bibliographic record
Abstract
Direct Sound Printing (DSP) is an emerging additive manufacturing modality that utilizes focused or patterned ultrasound to induce localized chemical reactions for polymerization of monomeric or prepolymer solutions. This method enables volumetric feature formation beyond the line-of-sight of conventional optical or mechanical deposition systems, allowing fabrication through optically opaque barriers and within sealed or inaccessible domains. In this study, we investigate DSP for Remote Distance Printing (RDP) at operational ranges up to several centimeters from the acoustic source, with spatial control achieved via acoustic beam shaping and dynamic focal steering. The effects of ultrasound frequency, peak negative pressure, and exposure time on polymerization rate, voxel resolution, and mechanical integrity of the printed features are quantified. Material systems compatible with DSP, including PEGDA- and GelMA-based hydrogels and sonosensitive polymers, are examined for biocompatibility and structural fidelity. Demonstrations include deep-tissue scaffold fabrication within surrogate tissue phantoms and structural reinforcement in enclosed components. These results establish DSP as a promising approach for non-invasive biomanufacturing and on-demand repair in sealed environments where common 3-D printing approaches are impractical.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".