Zenodo (CERN)
open access
HIGH-THROUGHPUT FABRICATION AND DEFECT SORTING OF BIOMEDICAL MICRO/NANOROBOTS AT THE LIMIT High-Throughput Fabrication x Automated Sorting x Defect Identification This 770-page Research Working Edition develops a falsification-oriented, nonclinical architecture for high-throughput fabrication and defect sorting of biomedical micro/nanorobots. It asks whether production can accelerate while complete material accounting, class-specific defect evidence, rare-hazard detection, rejection burden and independent terminal function remain directly measurable on the entire unselected population. Gross line speed, a visually well-formed unit or selected best specimens are not accepted as qualified capacity. The monograph contains 30 distinct mathematical research plates, 82 chapters, 410 single-page investigations, 200 detailed Research Gates and 33 genuinely distinguishable Phoenix Answer Embryos. Model families include qualified output rate, Little's law, physical material balance, stagewise joint yield, OEE, Poisson and overdispersed defect counts, beta-binomial clustering, confusion matrices, precision-recall, hazardous-miss bounds, sequential likelihood evidence, cost-sensitive thresholds, reject options, multimodal likelihood and covariance fusion, gauge R&R, drift, conformal anomaly detection, selective risk, queue stability, data reconciliation, capture-recapture prevalence and noncompensable release logic. The minimum demonstrator uniquely tracks 100,000 units and blindly injects five defect classes, including rare hazardous defects and one clustered carrier-level failure. Multimodal sorting competes with sampling microscopy and single-channel sorting under identical material, live-time, station, compute, retest and labor budgets. Every unit receives an auditable branch and stratified independent terminal verification. Hazardous escape above the frozen ceiling, unexplained material imbalance, forced classification of unsupported evidence, omitted rejects or qualified-capacity gain purchased solely by higher rejection is a hard veto. This is a prospective scientific architecture, not an executed clinical study. It does not claim in-body safety, therapeutic efficacy, regulatory approval or clinical benefit. DOI-linked publications support component methods and boundary conditions; they do not validate the integrated F23 manufacturing and sorting system. Technical profile: 770 pages; approximately 164,365 English words by machine count; 30 distinct formula families; 82 chapters; 410 single-page research studies; 200 Research Gates; 33 Phoenix Answer Embryos; 22 DOI evidence records; navigable bookmarks; sixfold QA. Author: Feng Cheng-en (33) x Starli STARLI Research Institute XXXIV / Flagship 23 Join the STARLI Research Community Explore more than 100 interdisciplinary research themes and follow the evolving STARLI Research Gate community: https://zenodo.org/communities/starli-research-gate/
HIGH-THROUGHPUT FABRICATION AND DEFECT SORTING OF BIOMEDICAL MICRO/NANOROBOTS AT THE LIMIT High-Throughput Fabrication x Automated Sorting x Defect Identification This 770-page Research Working Edition develops a falsification-oriented, nonclinical architecture for high-throughput f
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Magnetic medical microrobots with memory-capable genetic circuits.#182530
- Editorial: Intelligent micro- and nanorobotic systems for enhanced medical procedures.#351462
- Next-generation biomedical nanorobots: active design, intelligent control, and translational opportunities in regenerative and minimally invasive medicine.#479521
- TRANSLATABLE BY DESIGN: EXPERIMENTAL CONTROL, DATA PIPELINES, AND MODEL EVALUATION IN BIOMEDICINE#929124
- Convergence of Nanotechnology and Artificial Intelligence: Revolutionizing Healthcare and Beyond#718361
Record · ID 1482791
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive