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Record W4392927348 · doi:10.32920/25412728.v1

One-step Non-uniform Photolithography System for Three-dimensional Conically Shaped Microwell Fabrication

2024· preprint· en· W4392927348 on OpenAlexaff
Ahmad Ali Manzoor

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPhotolithographyOpacityMaterials scienceConical surfaceFabricationCurvaturePhotopolymerNanotechnologyMicrofluidicsLight intensitySubstrate (aquarium)OpticsOptoelectronicsPolymerGeometryPhysicsComposite material

Abstract

fetched live from OpenAlex

Conical microwells are utilized in a wide range of biological applications such as cell spheroid formation, drug screening, cancer diagnostics, and three-dimensional oncology models. The shape of a microwell is an important parameter that defines its applicability. Currently, there exists no facile fabrication method for the creation of such conically shaped microwells. In this study, we develop a new platform based on non-uniform photopolymerization that effectively facilitates the synthesis of three-dimensional (3D) polymer-based conical microwells on a glass substrate in a simple 2D microfluidic channel. We also numerically investigate the parabolic curvature formation of microwells using non-uniform photolithography (NUPL) via incorporation of spatiotemporal free-radical diffusion into the modeling of photopolymerization to gain insights into its key mechanisms. We also perform numerical simulations to model the 3D-shape tuning ability of NUPL for the microwell synthesis through a variation of UV light intensity induced by the presence of opaque materials. The result of this study leads to characterize the morphological microwell shape change experimentally through a variation of UV light intensity and fluid opacity. Simply by manipulating the non-uniformity of the incident UV light, we are able to fabricate 3D V-shaped microwells with various bottom shape features. Notably, our method allows one to optimize and design polymeric microwells with shape features tuned to their application.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.025
GPT teacher head0.278
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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