An Experimental Study of Copper Extraction Characteristics in a T-Junction Microchannel

Deep learning-augmented T-junction droplet generation

Droplet generation technology has become increasingly important in a wide range of applications, including biotechnology and chemical synthesis. T-junction channels are commonly used for droplet generation due to their integration capability of a larger number of droplet generators in a compact space. In this study, a finite element analysis (FEA) approach is employed to simulate droplet production and its dynamic regimes in a T-junction configuration and collect data for post-processing analysis. Next, image analysis was performed to calculate the droplet length and determine the droplet generation regime. Furthermore, machine learning (ML) and deep learning (DL) algorithms were applied to estimate outputs through examination of input parameters within the simulation range. At the end, a graphical user interface (GUI) was developed for estimation of the droplet characteristics based on inputs, enabling the users to preselect their designs with comparable microfluidic configurations within the studied range.

Process intensification for sustainable extraction of metals from e-waste: challenges and opportunities

The electrical and electronic waste is expected to increase up to 74.7 million metric tons by 2030 due to the unparalleled replacement rate of electronic devices, depleting the conventional sources of valuable metals such as rare earth elements, platinum group metals, Co, Sb, Mo, Li, Ni, Cu, Ag, Sn, Au, and Cr. Most of the current techniques for recycling, recovering, and disposing of e-waste are inappropriate and therefore contaminate the land, air, and water due to the release of hazardous compounds into the environment. Hydrometallurgy and pyrometallurgy are two such conventional methods used extensively for metal recovery from waste electrical and electronic equipment (WEEE). However, environmental repercussions and higher energy requirements are the key drawbacks that prevent their widespread application. Thus, to ensure the environment and elemental sustainability, novel processes and technologies must be developed for e-waste management with enhanced recovery and reuse of the valued elements. Therefore, the goal of the current work is to examine the batch and continuous processes of metal extraction from e-waste. In addition to the conventional devices, microfluidic devices have been also analyzed for microflow metal extraction. In microfluidic devices, it has been observed that the large specific surface area and short diffusion distance of microfluidic devices are advantageous for the efficient extraction of metals. Additionally, cutting-edge technologies have been proposed to enhance the recovery, reusability, and recycling of e-waste. The current study may support decision-making by researchers in deciding the direction of future research and moving toward sustainable development.

New Concept for the Study of the Fluid Dynamics of Lithium Extraction Using Calix[4]arene Derivatives in T-Type Microreactor Systems

Lithium extraction remains a challenge in the hydrometallurgy process due to its economic value and maldistribution sources. Employing calix[4]arene derivatives in solvent extraction techniques results in high selectivity and extraction capability, but a slow extraction rate. The slow kinetics of batch-wise extraction can be drastically accelerated by using a T-type microreactor system. Therefore, a combination of calix[4]arene and a microreactor system serves as an ideal platform for efficient lithium extraction. In this work, the fluid dynamics of lithium extraction using a monoacetic acid calix[4]arene derivative in a T-type microreactor system were studied. Increasing the O/A ratio increases the average length, surface area, and volume of the organic droplets, but decreases the specific surface area. In contrast, increasing the Reynolds number decreases the average length, surface area, and volume of the organic droplets, but increases the specific surface area. It was found that shorter diffusion distance, larger specific surface area, and faster vortex velocity were the factors that play the most pivotal roles in achieving great extraction rate enhancement in T-type microreactor systems compared to batch-wise systems. These findings represent an important new concept in the study of the fluid dynamics of lithium extraction using monoacetic acid calix[4]arene derivatives in T-type microreactor systems.

Experimental Studies of Droplet Formation Process and Length for Liquid–Liquid Two-Phase Flows in a Microchannel

In this study, changes in the droplet formation mechanism and the law of droplet length in a two-phase liquid–liquid system in 400 × 400 μm standard T-junction microchannels were experimentally studied using a high-speed camera. The study investigated the effects of various dispersed phase viscosities, various continuous phase viscosities, and two-phase flow parameters on droplet length. Two basic flow patterns were observed: slug flow dominated by the squeezing mechanism, and droplet flow dominated by the shear mechanism. The dispersed phase viscosity had almost no effect on droplet length. However, the droplet length decreased with increasing continuous phase viscosity, increasing volume flow rate in the continuous phase, and the continuous-phase capillary number Cac. Droplet length also increased with increasing volume flow rate in the dispersed phase and with the volume flow rate ratio. Based on the droplet formation mechanism, a scaling law governing slug and droplet length was proposed and achieved a good fit with experimental data.

Safety assessment in development and operation of modular continuous-flow processes

Improved safety is one of the main drivers for microreactor application in chemical process development and small-scale production.