Scaling variation in the pinch-off of colloid-polymer mixtures.

HYPOTHESIS: The scaling laws of drop pinch-off are known to be affected by drop compositions including dissolved polymers and non-Brownian particles. When the size of the particles is comparable to the characteristic length scale of the polymer network, these particles may interact strongly with the polymer environment, leading to new types of scaling behaviors not reported before. EXPERIMENTS: Using high-speed imaging, we experimentally studied the time evolution of the neck diameter hmin of drops composed of silica nanoparticles dispersed in PEO solution when extruded from a nozzle. FINDINGS: After initial Newtonian necking with hmin âˆ¼ t2/3, the subsequent stage may exhibit scaling variation, characterized by either exponential or power-law decay, depending on the nanoparticle volume fraction ϕ. The exponential decay hmin âˆ¼ e-t/τ signifies the coil-stretch transition in typical viscoelastic suspensions. We conducted an analysis of the power-law scenario hmin âˆ¼ tα at high ϕ, categorizing the entire process into three distinct regimes based on the exponents α. The dependences of critical thicknesses at transition points and exponents on polymer concentration offer initial insights into the potential transition from heterogeneous to homogeneous thinning in the mixture. This novel scaling variation bears implications for accurately predicting and controlling droplet fragmentation in industrial applications.

Chemotaxis of an elastic flagellated microrobot.

Machine learning algorithms offer a tool to boost mobility and flexibility of a synthetic microswimmer, hence may help us design truly smart microrobots. In this work, we design a two-gait microrobot swimming in circular or helical trajectory. It utilizes the coupling between flagellum elasticity and resistive force to change the characteristics of swimming trajectory. Leveraging a deep reinforcement learning (DRL) approach, we show that the microrobot can self-learn chemotactic motion autonomously (without heuristics) using only several current and historical chemoattractant concentration and curvature information. The learned strategy is more efficient than a human-devised shortsighted strategy and can be further greatly improved in a stochastic environment. Furthermore, in the helical trajectory case, if additional heuristic information of direction is supplemented to evaluate the strategy during the learning process, then a highly efficient strategy can be discovered by the DRL. The microrobot can quickly align the helix vector to the gradient direction using just several smart sequential gait switchings. The success for the efficient strategies depends on how much historical information is provided and also the steering angle step size of the microrobot. Our results provide useful guidance for the design and smart maneuver of synthetic spermlike microswimmers.

Molecular Dynamics Simulation of a Jet in a Binary System at Supercritical Environment.

With the development of large-thrust liquid rocket engines, the behavior of liquid in supercritical conditions arouses increasing public interest. Due to the high pressure and temperature of the combustion chamber, fuel reaches its critical point much more easily, and enters supercritical conditions. Due to the drastic changes in the physical properties of the fluid near the critical point, it is usually difficult to simulate the fluid motion using traditional computational fluid dynamic methods; but molecular dynamics (MD) can simulate fluid motion at the molecular level. In view of the engineering application, the physical properties of a binary system consisting of argon and nitrogen, and the stability of subcritical jets sprayed into supercritical environment, has been studied here using the MD method. First, the molecular dynamic simulation of the equation of state (EOS) of the mixture was put forward. Four conditions, with different mixing ratios of nitrogen, were designed. The results showed that the mixing ratio of nitrogen noticeably affected the results; these results were compared with the Soave-Redich-Kwong (SRK) EOS. Second, a simulation was conducted of subcritical nitrogen jet sprayed into a supercritical argon environment. After analyzing the results, the jet density and temperature distributions were obtained and the disturbance growth rate of the shear layer was analyzed.