2018
DOI: 10.1371/journal.pone.0192202
|View full text |Cite
|
Sign up to set email alerts
|

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things

Abstract: We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g., finite element analysis (FEA). However, analytical models are key for the information and communication te… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
36
0

Year Published

2018
2018
2022
2022

Publication Types

Select...
6
1
1

Relationship

1
7

Authors

Journals

citations
Cited by 36 publications
(36 citation statements)
references
References 32 publications
0
36
0
Order By: Relevance
“…The molecular-to-electrical transduction properties of the bioFET are reflected to the output current of the receiver through modeling the capacitive effects arising from the liquid-semiconductor interface and the 1/f noise resulting from the defects of the SiNW transducer channel. Kuscu and Akan [258] considered a 2-D convectional RD system that does not lend itself to closed-form analytical expressions for the received signal. The authors develop a heuristic model using a two-compartmental modeling approach, which divides the channel into compartments, in each of which either transport or reaction occurs, and derive an analytical expression for the time course of the number of bound receptors over a planar receiver surface placed at the bottom of the channel.…”
Section: ) Received Signal Modelsmentioning
confidence: 99%
See 1 more Smart Citation
“…The molecular-to-electrical transduction properties of the bioFET are reflected to the output current of the receiver through modeling the capacitive effects arising from the liquid-semiconductor interface and the 1/f noise resulting from the defects of the SiNW transducer channel. Kuscu and Akan [258] considered a 2-D convectional RD system that does not lend itself to closed-form analytical expressions for the received signal. The authors develop a heuristic model using a two-compartmental modeling approach, which divides the channel into compartments, in each of which either transport or reaction occurs, and derive an analytical expression for the time course of the number of bound receptors over a planar receiver surface placed at the bottom of the channel.…”
Section: ) Received Signal Modelsmentioning
confidence: 99%
“…However, for practical systems, the physical properties of the realistic receiver architectures and their impact on the molecular propagation in the MC channel should be taken into consideration to the most possible extent. Finite element simulations on microfluidic MC channel with bioFET receivers and macroscale MC experiments with alcohol sensors clearly reveal the effect of the coupling between the MC-Rx and the channel [258], [268]. The coupling is highly nonlinear, and in most of the cases, it is not analytically tractable; therefore, beyond the available analytical tools, researchers may need to focus on stochastic simulations and experiments to validate the performance of the proposed detection techniques in realistic scenarios.…”
Section: E Challenges For Developing MC Detection Techniquesmentioning
confidence: 99%
“…1) One-shot Detection: We use the slope s of the linear ramp-up region as the decision variable. From the bacteria response y approximated for the linear ramp-up region in (12), s is obtained as…”
Section: Decision Variablementioning
confidence: 99%
“…Microfluidics are divided into four groups including 1) convection, 2) laminar flow diffusion, 3) static diffusion, and 4) geometric metering with respect to their principles of gradient generation. [55][56][57][58] Microfluidic gradient devices are usually portable, inexpensive, quick gradient device, require low power, and enable Macromol. Biosci.…”
Section: Microfluidic Devicementioning
confidence: 99%