ArticlebioRxiv : the preprint server for biology2026
Open-source robotic chip-to-plate interface for high-throughput microfluidic generation of materials libraries.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Data-driven materials development requires large, well-characterized libraries of precisely defined formulations. While microfluidic platforms excel at generating highly controlled materials, their throughput is often limited by the challenge of efficiently interfacing device outputs with standard well plates. This bottleneck frequently necessitates manual transfer or non-microfluidic workflows, constraining both throughput and reproducibility. Here, we present LMNOP-bot (Libraries of Micro- and Nano-materials, OPen-source bot), an open-source robotic platform for the automated generation and collection of micro- and nanomaterial libraries from serial microfluidic outputs. Using synchronized, pressure-driven flow, LMNOP-bot enables continuous formulation and direct deposition into standard well plates. The system is low-cost (<$700, excluding pressure regulators), constructed from readily available or easily fabricated components, and designed for broad accessibility. LMNOP-bot collects ≥30 μL per formulation at a rate of one sample every four seconds, representing an approximately 50× increase in throughput over existing serial microfluidic workflows, and operates robustly for over 10,000 runs without maintenance. We demonstrate compatibility with both PDMS/glass and commercial polycarbonate devices, with seamless interfacing to 96- and 384-well plates. Repeated sampling confirms high precision and reproducibility. By removing a key bottleneck in microfluidic library generation, LMNOP-bot enables rapid, scalable, and accessible exploration of material design spaces.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.