Speaker
Description
From a broader perspective, our objective is to investigate the kinetic and thermodynamic features associated with chemical computation, an emerging and highly significant area of current research. The central motivation is to examine whether chemical computational schemes can offer benefits compared to conventional computing approaches. Our study focuses on systematically exploring different parameter regimes and identifying the conditions that produce efficient, stable, and reliable reaction dynamics.
Since chemical computation is often associated with reaction networks containing autocatalytic processes, we consider the Schlögl reaction model as a representative system. This model includes an autocatalytic reaction step that generates bistability in the concentration of the autocatalytic species through nonlinear feedback effects. To drive the system externally, we introduce a periodically varying pumping rate of another chemical species.
The delayed response of the autocatalytic species concentration relative to the external modulation leads to the emergence of hysteresis loops. The enhancement of the system response under suitable conditions is analyzed through the area enclosed by these hysteresis loops. Importantly, the loop area approaches zero in the quasi-static limit, highlighting the inherently dynamic origin of the hysteresis phenomenon. We further observe a turnover behavior of this quantity as various control parameters are changed.
Our findings may serve as an initial step toward understanding kinetic mechanisms relevant to chemical computation. In addition, the present work provides an early investigation of dynamic hysteresis in chemical reaction systems where the concentration of chemical species acts as the governing variable. We also perform stochastic thermodynamic analyses using Shannon entropy and relate this measure to the hysteretic response of the system, thereby exploring the possible connection between hysteresis and information loss in chemical processes.
