Piezodynamic Behavior of HA-BT Osteoconductive Coatings Under LIPUS Stimulation in Lab-on-a-Chip Model: A Promising Strategy for Bone Regeneration
Bibliographic record
Abstract
Bone regeneration demands biomaterials capable of supporting tissue integration and mimicking the native piezodynamic properties of bone. In this study, hydroxyapatite–barium titanate (HA-BT) composite coatings with varying BT content (10, 30, and 50 wt%) were developed to enhance the piezoelectric response and corrosion resistance of Ti6Al4V implants. The coatings were synthesized via high-energy ball milling and atmospheric plasma spraying (APS). XRD analysis with Rietveld refinement confirmed the presence of HA along with secondary phases (TTCP, β-TCP, CaO). Electrochemical tests revealed lower corrosion current densities for the coatings containing ≤30% BT, indicating improved stability in physiological environments. Cytotoxicity assays (MTT) demonstrated biocompatibility across all formulations. Piezoresponse force microscopy (DART-SS-PFM) confirmed enhanced d33-eff values for the 50% BT coating (>15 pm/V); however, biological assays under low-intensity pulsed ultrasound (LIPUS) stimulation showed increased osteocalcin expression for ≤30% BT, while 50% BT induced cellular stress. Overall, HA-BT coatings with up to 30% BT exhibited optimal electrochemical stability, favorable piezoelectric performance, and enhanced biological response, underscoring their potential for orthopedic implant applications and regenerative tissue engineering.
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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) | 0.000 | 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 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".