We present an approach to the schematic design and time-dependent simulation of microfluidic systems that are composed of basic components, such as pumps, channels, mixing junctions, and valves. For the schematic capture and the simulation, the Cadence Virtuoso design framework is employed, with the components modeled by Verilog-AMS. The pressures and flow rates are calculated with the help of the hydraulic analogy between electronics and fluidics. Signal flow quantities are used to express the flow of chemical concentration. Our focus is on systems employing chemofluidic transistors, i.e., hydrogel-based microvalves that facilitate autonomous flow control without the need for an external control unit. Our approach also covers layout editing by the use of programmed cells. The utility of the approach is exemplified by the successful top-down design of a chemofluidic oscillator circuit and by the functionally correct simulation of a chemofluidic SR flip-flop.

The unbelievable properties of our information processing capabilities regarding the processing of big data, resilience, and energy efficiency are inspiration sources for the optimization and the rethinking of the principles of electronic information processing. Here, we present an approach of integrated circuits intended to solve chemical problems by active processing of chemical information.

Operating industrial plants at their maximum energy and resources efficiency often means to operate them close at their design limits. Due to strict safety and process parameter constraints, it is challenging to control them close to the optimal setpoints. Currently process performance improvement projects are realized by application of PC based model predictive controllers as add-ons. Applications of up-to-date optimizing control algorithms are characterized by high requirements on software architecture, numerical computing power and realtime behavior. These requirements are not accomplishable running optimizing control algorithms on Programmable Logic Controllers (PLCs) by current available software architectures. Therefore the aim of the Embedded Energy Efficiency Industrial Controller Platform (E3ICP) project is the development of an infrastructure for running state-of-the-art model predictive controllers on industrial embedded PLCs.