Evidence map›Paper›PMID 37938589›Full record

ArticleNature communications2023

Real-time signal processing via chemical reactions for a microfluidic molecular communication system.

Vivien Walter, Dadi Bi, Ali Salehi-Reyhani, Yansha Deng

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

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

4 authors.

Vivien Walter *Department of Engineering, King's College London, London, WC2R 2LS, UK.ORCID http://orcid.org/0000-0003-3203-9543
Dadi Bi *Department of Engineering, King's College London, London, WC2R 2LS, UK.ORCID http://orcid.org/0000-0002-4743-3685
Ali Salehi-ReyhaniDepartment of Surgery and Cancer, Imperial College London, London, W12 0HS, UK.ORCID http://orcid.org/0000-0002-1084-2012
Yansha DengDepartment of Engineering, King's College London, London, WC2R 2LS, UK. yansha.deng@kcl.ac.uk.ORCID http://orcid.org/0000-0003-1001-7036

Funding

RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/S001603/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/T000937/1
6 · The paper itself

Abstract

Signal processing over the molecular domain is critical for analysing, modifying, and synthesising chemical signals in molecular communication systems. However, the lack of chemical signal processing blocks and the wide use of electronic devices to process electrical signals in existing molecular communication platforms can hardly meet the biocompatible, non-invasive, and size-miniaturised requirements of applications in various fields, e.g., medicine, biology, and environment sciences. To tackle this, here we design and construct a liquid-based microfluidic molecular communication platform for performing chemical concentration signal processing and digital signal transmission over distances. By specifically designing chemical reactions and microfluidic geometry, the transmitter of our platform is capable of shaping the emitted signals, and the receiver is able to threshold, amplify, and detect the chemical signals after propagation. By encoding bit information into the concentration of sodium hydroxide, we demonstrate that our platform can achieve molecular signal modulation and demodulation functionalities, and reliably transmit text messages over long distances. This platform is further optimised to maximise data rate while minimising communication error. The presented methodology for real-time chemical signal processing can enable the implementation of signal processing units in biological settings and then unleash its potential for interdisciplinary applications.

Identifiers

PMID37938589
PMCPMC10632502

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Registered trials

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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 OpenQuestion graph.