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Published on: August 23, 2012
Open-source robotic chip-to-plate interface for high-throughput microfluidic generation of materials libraries
Isabel B Navarro1, Gregory Datto1,2, Lameck Beni1
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104.
Biorxiv : the Preprint Server for Biology
|May 25, 2026
Summary
LMNOP-bot automates the generation and collection of micro- and nanomaterial libraries from microfluidic devices, significantly increasing throughput. This open-source platform enables rapid, reproducible, and accessible materials development for diverse applications.
Area of Science:
- Materials Science
- Robotics
- Chemical Engineering
Background:
- Data-driven materials development necessitates large, well-characterized formulation libraries.
- Microfluidic platforms offer precise material control but face throughput limitations due to output interfacing challenges.
- Manual transfers or non-microfluidic methods hinder throughput and reproducibility in microfluidic library generation.
Purpose of the Study:
- To develop an open-source robotic platform for automated micro- and nanomaterial library generation and collection.
- To overcome the bottleneck of interfacing microfluidic device outputs with standard well plates.
- To enhance the throughput, reproducibility, and accessibility of data-driven materials development.
Main Methods:
- Introduction of LMNOP-bot (Libraries of Micro- and Nano-materials, OPen-source bot), a low-cost, open-source robotic platform.
- Utilizing synchronized, pressure-driven flow for continuous formulation and direct deposition into well plates.
- Demonstrating compatibility with PDMS/glass and polycarbonate microfluidic devices and 96-/384-well plates.
Main Results:
- LMNOP-bot achieves a throughput of one sample every four seconds, a ~50x increase over existing serial microfluidic workflows.
- The system collects ≥30 µL per formulation and operates robustly for over 10,000 runs without maintenance.
- High precision and reproducibility were confirmed through repeated sampling, with seamless interfacing to standard well plates.
Conclusions:
- LMNOP-bot effectively removes a key bottleneck in microfluidic library generation.
- The platform enables rapid, scalable, and accessible exploration of material design spaces.
- This open-source solution promotes broader adoption of automated microfluidic material synthesis for research and development.
