Multifunctional cerium-tetracycline coating for titanium implants: A dual approach to antibacterial and corrosion resistance
Bibliographic record
Abstract
Titanium implants, such as Ti6Al4V, are widely used in dentistry and orthopedics due to their excellent biocompatibility and mechanical properties. However, bacterial infections following implantation remain a significant challenge. In this study, we modified the surface of Ti6Al4V with a cerium titanate layer loaded with tetracycline (Tetra), to enhance its bioactivity and antibacterial properties. Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and Fourier Transform Infrared microscopy (FT-IR) confirmed the successful modification and uniform drug distribution. The tetracycline adsorbed on the surface was released within 3 h, likely through Ce 3+ ion exchange or dissolution of Ce 3+ - Tetracycline complex. Potentiodynamic polarization and Electrochemical Impedance Spectroscopy (EIS) indicated increased corrosion resistance. The modified coatings (Ce-Tit-Tetra) exhibited significant antibacterial activity against Staphylococcus aureus , attributed to controlled tetracycline release. Neither this coating nor the cerium only variant (Ce-Tit) showed any activity against Escherichia coli , highlighting challenges in addressing antibiotic resistance. Additionally, the modified material demonstrated greater protein adsorption, indicating improved bioactivity compared to bare Ti6Al4V. These findings suggest that cerium-tetracycline-modified titanium coatings hold promise for enhancing implant performance, but further research is needed to expand their antimicrobial spectrum. • Cerium titanate layer was prepared on the surface of the Ti6Al4V and used as a carrier for the antibiotic tetracycline. • FT-IR microscopy confirmed the uniform distribution of the active substance. • The material exhibited significantly improved corrosion resistance. • Antibacterial studies demonstrated a substantial ability to inhibit the growth of S . aureus bacterial strain.
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) | 0.000 | 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".