Incorporating cutting-edge research and training in scientific thinking into undergraduate education plays a crucial role in enhancing students' abilities. This paper uses pressure as an example to progressively outline the derivation of pressure in equilibrium thermodynamic systems. It then discusses the unique properties of pressure in non-equilibrium active systems, drawing on the latest research in the field of soft condensed matter. Unlike in equilibrium systems, pressure in these non-equilibrium systems is not a state function determined by a single system parameter but depends on the microscopic details of interactions and dynamics. This paper aims to deepen students' understanding of pressure from different perspectives, strengthen their fundamental knowledge in physics, and introduce them to cutting-edge research developments. It is hoped that this work will inspire and provide insights for fellow educators.

When the particle's velocity or squeezing among particles is increased, the flow rate of discrete particles passing through the bottleneck is significantly reduced, which is called the “more haste, less speed” effect. In this paper, molecular dynamics simulation is used to study the effects of self-propelled force on the bottleneck clogging of active particles driven by different external velocity fields. With the increase of self-propelled force, the flow rate of active particles decreases. Based on the power-law exponent of complementary cumulative distribution function and clogging probability, it is explained that although the self-propelled force can effectively enhance the particle motility, it also causes the increase of the clogging probability, consequently leading to the decrease of the flow rate. On the pedagogical side, as a typical complex system, bottleneck flow of active particle can assist students in understanding the physical thought that optimal individual does not necessarily bring global optimum. Besides, it is beneficial to the development of academic ability and scientific literacy for undergraduates, by the rigorous training of data processing and statistical analysis.