Laser‐Patterned Diamond Electrodes for Adhesion and Proliferation of Human Mesenchymal Stem Cells
Bibliographic record
Abstract
The ability to form diamond electrodes on insulating polycrystalline diamond substrates using single‐step laser patterning and the use of these electrodes as a substrate that supports the adhesion and proliferation of human mesenchymal stem cells (hMSCs) are demonstrated. Laser‐induced graphitization results in a conductive amorphous carbon surface, rich in oxygen‐ and nitrogen‐terminated groups. This leads to an electrode with a high specific capacitance of 182 μF cm 2 , a wide water window of 3.25 V, and a low electrochemical impedance of 129 Ω cm 2 at 1 kHz—essential attributes for effective bioelectronic cell interfaces. The electrode's surface exhibits no cytotoxic responses with hMSCs, supporting cell adhesion and proliferation. Cells cultured on the electrode display significant elongation and alignment along the direction of the laser‐patterned microgrooves—an additional modality for cellular modulation. The combination of favorable electrochemical performance and effective cellular control makes laser‐patterned diamond electrodes a versatile platform in stem cell therapeutics. This direct fabrication approach paves the way for the integration of diamond electrodes in bioelectronic devices, offering new opportunities for tissue engineering and electroactive biomaterial applications.
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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 | 0.000 |
| 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 | 0.000 |
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".