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      Development of Novel Bioreactor Control Systems Based on Smart Sensors and Actuators

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          Abstract

          Bioreactors of various forms have been widely used in environmental protection, healthcare, industrial biotechnology, and space exploration. Robust demand in the field stimulated the development of novel designs of bioreactor geometries and process control strategies and the evolution of the physical structure of the control system. After the introduction of digital computers to bioreactor process control, a hierarchical structure control system (HSCS) for bioreactors has become the dominant physical structure, having high efficiency and robustness. However, inherent drawbacks of the HSCS for bioreactors have produced a need for a more consolidated solution of the control system. With the fast progress in sensors, machinery, and information technology, the development of a flat organizational control system (FOCS) for bioreactors based on parallel distributed smart sensors and actuators may provide a more concise solution for process control in bioreactors. Here, we review the evolution of the physical structure of bioreactor control systems and discuss the properties of the novel FOCS for bioreactors and related smart sensors and actuators and their application circumstances, with the hope of further improving the efficiency, robustness, and economics of bioprocess control.

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          Precise, automated control of conditions for high-throughput growth of yeast and bacteria with eVOLVER

          Precise control over microbial cell growth conditions could enable detection of minute phenotypic changes, which would improve our understanding of how genotypes are shaped by adaptive selection. Although automated cell-culture systems such as bioreactors offer strict control over liquid culture conditions, they often do not scale to high-throughput or require cumbersome redesign to alter growth conditions. We report the design and validation of eVOLVER, a scalable DIY framework that can be configured to carry out high-throughput growth experiments in molecular evolution, systems biology, and microbiology. We perform high-throughput evolution of yeast across systematically varied population density niches to show how eVOLVER can precisely characterize adaptive niches. We describe growth selection using time-varying temperature programs on a genome-wide yeast knockout library to identify strains with altered sensitivity to changes in temperature magnitude or frequency. Inspired by large-scale integration of electronics and microfluidics, we also demonstrate millifluidic multiplexing modules that enable multiplexed media routing, cleaning, vial-to-vial transfers and automated yeast mating.
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            Networked Control System: Overview and Research Trends

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              Printable Fabrication of a Fully Integrated and Self-Powered Sensor System on Plastic Substrates

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                Author and article information

                Contributors
                Journal
                Front Bioeng Biotechnol
                Front Bioeng Biotechnol
                Front. Bioeng. Biotechnol.
                Frontiers in Bioengineering and Biotechnology
                Frontiers Media S.A.
                2296-4185
                04 February 2020
                2020
                : 8
                : 7
                Affiliations
                [1] 1Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University , Tianjin, China
                [2] 2SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin) , Tianjin, China
                [3] 3Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), School of Chemical Engineering and Technology, Tianjin University , Tianjin, China
                Author notes

                Edited by: Eduardo Jacob-Lopes, Universidade Federal de Santa Maria, Brazil

                Reviewed by: Peter Neubauer, Technische Universität Berlin, Germany; Tonci Rezic, University of Zagreb, Croatia

                *Correspondence: Tao Chen, chentao@ 123456tju.edu.cn

                This article was submitted to Bioprocess Engineering, a section of the journal Frontiers in Bioengineering and Biotechnology

                Article
                10.3389/fbioe.2020.00007
                7011095
                ec22dc6d-9079-4149-81c8-e1e86fd49693
                Copyright © 2020 Wang, Wang, Chen and Zhao.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 August 2019
                : 07 January 2020
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 104, Pages: 15, Words: 0
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 21776208
                Award ID: 21621004
                Award ID: 21390201
                Categories
                Bioengineering and Biotechnology
                Review

                flat organizational control systems,knowledge-based control systems,bioreactors,smart sensors,actuators

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