Cleaning effects due to shape oscillation of bubbles over a rigid boundary

Recent experiments have revealed the interesting cleaning effects that take place due to the shape mode oscillation of bubbles over a rigid boundary. While a microbubble was undertaking shape oscillation moving over a bacterial biofilm, it removed the contaminants from the boundary and created a clean path through the biofilm. This demonstrated much higher cleaning efficiency than that associated with the volume oscillation of cavitation bubbles; however, the mechanism is unknown. Here, we study this phenomenon using the boundary integral method with the viscous effects modeled using the viscous potential flow theory and the compressible effects using the weakly compressible theory. The viscous stress at the rigid boundary is approximated using the boundary layer theory. We observed that the natural frequencies of shape mode oscillation decrease significantly due to the presence of the boundary. The shear stress at the boundary due to the shape oscillation of a nearby bubble is at least 20 times higher than that due to volume oscillation with the same energy and is significant only within the area directly beneath the bubble. This is explained by the notably faster decay for higher shape modes of the kinetic energy in the fluid as the distance to the center of the bubble r increases with the induced velocity of mode k decaying at a rate of O(r-(k+ 2)) away from the bubble. These results achieve excellent agreement with the intriguing cleaning effects first observed in the experiment and explain the mechanism behind this new highly efficient method of cleaning

Penetration of hydroxyl radicals in the aqueous phase surrounding a cavitation bubble

In the sonochemical degradation of nonvolatile compounds, the free radicals must be delivered into the aqueous solution from the cavitation bubble to initiate reduction–oxidation reactions. The penetration depth in the liquid becomes an important parameter that influences the radical delivery efficiency and eventual treatment performance. However, the transport of radicals in the liquid phase is not well understood yet. In this paper, we focus on the most reactive OH radical and numerically simulate its penetration behavior. This is realized by solving the coupled equations of bubble dynamics, intracavity chemistry, and radical dispersion in the aqueous phase. The results present both the local and global penetration patterns for the OH radicals. By performing simulations over a wide range of acoustic parameters, we find an undesirable phenomenon that the penetration can be adversely suppressed when strengthening the radical production. A mechanistic analysis attributes this to the excessively vigorous recombination reactions associated with high radical concentrations near the bubble interface. In this circumstance, the radicals are massively consumed and converted into molecular species before they can appreciably diffuse away. Our study sheds light on the interplay between radical production inside the bubble and dispersion in the outside liquid. The derived conclusions provide guides for sonochemical applications from a new perspective

A fully-mapped and energy-efficient FPGA accelerator for dual-function AI-based analysis of ECG

In this paper, a fully-mapped field programmable gate array (FPGA) accelerator is proposed for artificial intelligence (AI)-based analysis of electrocardiogram (ECG). It consists of a fully-mapped 1-D convolutional neural network (CNN) and a fully-mapped heart rate estimator, which constitute a complementary dual-function analysis. The fully-mapped design projects each layer of the 1-D CNN to a hardware module on an Intel Cyclone V FPGA, and a virtual flatten layer is proposed to effectively bridge the feature extraction layers and fully-connected layer. Also, the fully-mapped design maximizes computational parallelism to accelerate CNN inference. For the fully-mapped heart rate estimator, it performs pipelined transformations, self-adaptive threshold calculation, and heartbeat count on the FPGA, without multiplexed usage of hardware resources. Furthermore, heart rate calculation is elaborately analyzed and optimized to remove division and acceleration, resulting in an efficient method suitable for hardware implementation. According to our experiments on 1-D CNN, the accelerator can achieve 43.08× and 8.38× speedup compared with the software implementations on ARM-Cortex A53 quad-core processor and Intel Core i7-8700 CPU, respectively. For the heart rate estimator, the hardware implementations are 25.48× and 1.55× faster than the software implementations on the two aforementioned platforms. Surprisingly, the accelerator achieves an energy efficiency of 63.48 GOPS/W, which obviously surpasses existing studies. Considering its power consumption is only 67.74 mW, it may be more suitable for resource-limited applications, such as wearable and portable devices for ECG monitoring