Label‐Free and Low‐Power Driven Cancer Biomarker Detection Enabled by 2D Hexagonal Titanium Oxide
Bibliographic record
Abstract
Abstract 2D nanomaterials have shown significant advances in next‐generation biosensor development. However, current 2D‐enabled electronic biosensors rarely achieve a detection limit down to pico‐gram level, possibly due to their intrinsic low carrier mobilities, biocompatibility or instability. TiO 2 , a biocompatible material, has been widely adopted in bio‐applications. Recently, 2D TiO 2 with a unique planar hexagonal phase exhibits a reduced bandgap of 2 eV and high p‐type mobility. A small perturbation could stimulate an observable electronic swing, enabling a high‐performance biosensor in a label‐free manner. Here, 2D h‐TiO 2 is fabricated into a liquid‐gated field‐effect transistor, while a wide spectrum, nonspecific biomarker carcinoembryonic antigen (CEA) is selected as the target molecule. The h‐TiO 2 surface is first functionalized with 3‐aminopropyltriethoxysilane and subsequently decorated with anti‐CEA, creating an affinity probe toward CEA molecules. The real‐time response to different concentrations of CEA is tested from 1 pg mL −1 to 10 ng mL −1 under a low working voltage of 0.05 V, and an ultralow detection limit of 0.22 pg mL −1 is achieved. Meanwhile, the selectivity of the devices is demonstrated using cytokeratin‐19‐fragment and neuron‐specific enolase. The results highlight the potential of layered hexagonal metal oxides for high‐performance biosensors, enabling future low‐power portable devices for disease diagnosis.
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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".