Evidence map›Paper›PMID 40428703›Full record

ArticleMicromachines2025

SlimPort: Port-Driven High-Level Synthesis for Continuous-Flow Microfluidic Biochips.

Youlin Pan, Yanbo Xu, Ziyang Chen, Xing Huang, Genggeng Liu

Abstract read
In one paragraph

Article in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Youlin PanCollege of Computer and Data Science, Fuzhou University, Fuzhou 350116, China.
Yanbo XuCollege of Computer and Data Science, Fuzhou University, Fuzhou 350116, China.ORCID 0009-0004-0115-886X
Ziyang ChenCollege of Computer and Data Science, Fuzhou University, Fuzhou 350116, China.
Xing HuangSchool of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China.ORCID 0000-0002-5396-110X
Genggeng LiuCollege of Computer and Data Science, Fuzhou University, Fuzhou 350116, China.ORCID 0000-0002-3099-4371

Funding

Fujian Natural Science Funds 2023J06017National Natural Science Foundation of China 62372109
6 · The paper itself

Abstract

Continuous-flow microfluidic biochips (CFMBs) automatically execute various bioassays by precisely controlling the transport of fluid samples, which is driven by pressure delivered through fluidic ports. High-level synthesis, as an important stage in the design flow of CFMBs, generates binding and scheduling solutions whose quality directly affects the efficiency of the execution of bioassays. Existing high-level synthesis methods perform numerous transport tasks concurrently to increase efficiency. However, fluidic ports cannot be shared between concurrently executing transport tasks, resulting in a large number of fluidic ports introduced by existing methods. Increasing the number of fluidic ports undermines the integration, reduces the reliability, and increases the manufacturing cost. In this paper, we propose a port-driven high-level synthesis method based on integer linear programming (ILP) called SlimPort, integrating the optimization of fluidic port number into high-level synthesis, which has never been considered in prior work. Meanwhile, to ensure bioassay correctness, volume management between devices with a non-fixed input/output ratio is realized. Additionally, two acceleration strategies for ILP, scheduling constraint reduction and upper boundary estimation of fluidic port number, are proposed to improve the efficiency of SlimPort. Experimental results from multiple benchmarks demonstrate that SlimPort leads to high assay execution efficiency and a low number of fluidic ports.

Indexed as

fluidic porthigh-level synthesismicrofluidic biochipsvolume management

Identifiers

PMID40428703
PMCPMC12114398

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