TY - GEN
T1 - Modeling Diffusion and Chemical Reactions to Analyze Redox-Based Molecular-Electrical Communication
AU - Gorla, Karthik Reddy
AU - Barker, Tyler
AU - Pierobon, Massimiliano
N1 - Funding Information:
This paper is based upon work supported by the Semiconductor Research Corporation (SRC) through Task No. 2843.001 and the National Science Foundation (NSF) through Grant No. ECCS-1807604. The authors also acknowledge support and experimental setup knowledge from Dr. Gregory F. Payne and Dr. Eunkyoung Kim of Institute for Bioscience and Biotechnology Research (IBBR), University of Maryland.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - For more than a decade, Molecular Communication (MC), inspired by the natural way biological cells communicate, has been studied in engineering as the key paradigm for realizing computing and information systems increasingly integrated with biology. Broad application scenarios range from medical diagnostics and treatment, to biocompatible device and systems engineering. This paper focuses on a recently proposed technology able to transduce information from the MC domain to the electrical domain of classical circuits and systems. In particular, this is based on redox reactions, i. e., chemical processes where molecules exchange electrons, which play an important role in living systems. Based on these processes and a proof-of-concept prototype realized by our research collaborators, this paper addresses the computational modeling necessary to derive the design principles of such system. In particular, a stochastic simulation framework is developed to reproduce the transduction of information signals from the MC (input molecule concentration) to the electrical domain (output current). Numerical results from this framework, realized in MATLAB, are presented to evaluate the Signal-toNoise Ratio (SNR), the Limit of Detection (LOD), and the Limit of Quantification (LOQ) of this transduction process as a function of the input concentration value. While at its preliminary stage, this framework has the potential to be foundational towards the engineering of a complete redox-based bio-hybrid electronics.
AB - For more than a decade, Molecular Communication (MC), inspired by the natural way biological cells communicate, has been studied in engineering as the key paradigm for realizing computing and information systems increasingly integrated with biology. Broad application scenarios range from medical diagnostics and treatment, to biocompatible device and systems engineering. This paper focuses on a recently proposed technology able to transduce information from the MC domain to the electrical domain of classical circuits and systems. In particular, this is based on redox reactions, i. e., chemical processes where molecules exchange electrons, which play an important role in living systems. Based on these processes and a proof-of-concept prototype realized by our research collaborators, this paper addresses the computational modeling necessary to derive the design principles of such system. In particular, a stochastic simulation framework is developed to reproduce the transduction of information signals from the MC (input molecule concentration) to the electrical domain (output current). Numerical results from this framework, realized in MATLAB, are presented to evaluate the Signal-toNoise Ratio (SNR), the Limit of Detection (LOD), and the Limit of Quantification (LOQ) of this transduction process as a function of the input concentration value. While at its preliminary stage, this framework has the potential to be foundational towards the engineering of a complete redox-based bio-hybrid electronics.
KW - Chemical noise
KW - Cyclic voltammetry
KW - Diffusion noise
KW - Molecular communication
KW - Redox channel
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U2 - 10.1109/ICC40277.2020.9148750
DO - 10.1109/ICC40277.2020.9148750
M3 - Conference contribution
AN - SCOPUS:85089436041
T3 - IEEE International Conference on Communications
BT - 2020 IEEE International Conference on Communications, ICC 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Communications, ICC 2020
Y2 - 7 June 2020 through 11 June 2020
ER -