Transparent Anodic TiO<SUB>2</SUB> Nanotube Arrays on Plastic Substrates for Disposable Biosensors and Flexible Electronics
Why this work is in the frame
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Bibliographic record
Abstract
Exploitation of anodically formed self-organized TiO2 nanotube arrays in mass-manufactured, disposable biosensors, rollable electrochromic displays and flexible large-area solar cells would greatly benefit from integration with transparent and flexible polymeric substrates. Such integration requires the vacuum deposition of a thin film of titanium on the desired substrate, which is then anodized in suitable media to generate TiO2 nanotube arrays. However the challenges associated with control of Ti film morphology, nanotube array synthesis conditions, and film adhesion and transparency, have necessitated the use of substrate heating during deposition to temperatures of at least 300 degrees C and as high as 500 degrees C to generate highly ordered open-pore nanotube arrays, thus preventing the use of polymeric substrates. We report on a film growth technique that exploits atomic peening to achieve high quality transparent TiO2 nanotube arrays with lengths up to 5.1 microm at room temperature on polyimide substrates without the need for substrate heating or substrate biasing or a Kauffman ion source. The superior optical quality and uniformity of the nanotube arrays was evidenced by the high specular reflectivity and the smooth pattern of periodic interferometric fringes in the transmission spectra of the nanotube arrays, from which the wavelength-dependent effective refractive index was extracted for the air-TiO2 composite medium. A fluorescent immunoassay biosensor constructed using 5.1 microm-long transparent titania nanotube arrays (TTNAs) grown on Kapton substrates detected human cardiac troponin I at a concentration of 0.1 microg ml(-1).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it