Development of nano- and microdevices for the next generation of biotechnology, wearables and miniaturized instrumentation
Bibliographic record
Abstract
This is a short communication based on recent high-impact publications related to how various chemical materials and substrate modifications could be tuned for nano- and microdevices, where their application for high point-of-care bioanalysis and further applications in life science is discussed. Hence, they have allowed different high-impact research topics in a variety of fields, from the control of nanoscale to functional microarchitectures embedded in various support materials to obtain a device for a given application or use. Thus, their incorporation in standard instrumentation is shown, as well as in new optical setups to record different classical and non-classical light, signaling, and energy modes at a variety of wavelengths and energy levels. Moreover, the development of miniaturized instrumentation was also contemplated. In order to develop these different levels of technology, the chemistry, physics and engineering of materials were discussed. In this manner, a number of subjects that allowed the design and manufacture of devices could be found. The following could be mentioned by way of example: (i) nanophotonics; (ii) design, synthesis and tuning of advanced nanomaterials; (iii) classical and non-classical light generation within the near field; (iv) microfluidics and nanofluidics; (v) signal waveguiding; (vi) quantum-, nano- and microcircuits; (vii) materials for nano- and microplatforms, and support substrates and their respective modifications for targeted functionalities. Moreover, nano-optics in in-flow devices and chips for biosensing were discussed, and perspectives on biosensing and single molecule detection (SMD) applications. In this perspective, new insights about precision nanomedicine based on genomics and drug delivery systems were obtained, incorporating new advanced diagnosis methods based on lab-on-particles, labs-on-a-chip, gene therapies, implantable devices, portable miniaturized instrumentation, single molecule detection for biophotonics, and neurophotonics. In this manner, this communication intends to highlight recent reports and developments of nano- and microdevices and further approaches towards the incorporation of developments in nanophotonics and biophotonics in the design of new materials based on different strategies and enhanced techniques and methods. Recent proofs of concept are discussed that could allow new substrates for device manufacturing. Thus, physical phenomena and materials chemistry with accurate control within the nanoscale were introduced into the discussion. In this manner, new potential sources of ideas and strategies for the next generation of technology in many research and development fields are showcased.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".