CFD simulation of anaerobic granular sludge reactors: A review

Roles of entrapped bubbles in methanogenic granules under oscillating pressure: Respiration and embolization for intra-granular transport

Anaerobic granular sludge plays a pivotal role in the treatment of concentrated organic wastewater. However, previous studies on intra- granular transport have generally overlooked lung-like respiration that expedites transport in response to fluctuating pressure. This study explored the activities of calcified and normal granules under simulated hydrostatic pressure oscillations. The results revealed a significant enhancement in the bioactivity of calcified granules under oscillating pressure, contrasting with the comparatively lower bioactivity observed in normal granules. The hypothesis posited that the gas pockets in calcified granules facilitated respiration as the functional structure. The presence of tiny bubbles exhibited a propensity for inducing clogging, thereby diminishing the capillary connectivity essential for substrate diffusion. The proposed respiration and embolization concepts decipher the distinct roles of entrapped bubbles in the granular bioactivity across diverse fluid states. This study offers valuable insights into the impact of fluidization on microscopic transport within granule-based bed reactors.

Simulation and Optimization: A New Direction in Supercritical Technology Based Nanomedicine

In recent years, nanomedicines prepared using supercritical technology have garnered widespread research attention due to their inherent attributes, including structural stability, high bioavailability, and commendable safety profiles. The preparation of these nanomedicines relies upon drug solubility and mixing efficiency within supercritical fluids (SCFs). Solubility is closely intertwined with operational parameters such as temperature and pressure while mixing efficiency is influenced not only by operational conditions but also by the shape and dimensions of the nozzle. Due to the special conditions of supercriticality, these parameters are difficult to measure directly, thus presenting significant challenges for the preparation and optimization of nanomedicines. Mathematical models can, to a certain extent, prognosticate solubility, while simulation models can visualize mixing efficiency during experimental procedures, offering novel avenues for advancing supercritical nanomedicines. Consequently, within the framework of this endeavor, we embark on an extensive review encompassing the application of mathematical models, artificial intelligence (AI) methodologies, and computational fluid dynamics (CFD) techniques within the medical domain of supercritical technology. We undertake the synthesis and discourse of methodologies for calculating drug solubility in SCFs, as well as the influence of operational conditions and experimental apparatus upon the outcomes of nanomedicine preparation using supercritical technology. Through this comprehensive review, we elucidate the implementation procedures and commonly employed models of diverse methodologies, juxtaposing the merits and demerits of these models. Furthermore, we assert the dependability of employing models to compute drug solubility in SCFs and simulate the experimental processes, with the capability to serve as valuable tools for aiding and optimizing experiments, as well as providing guidance in the selection of appropriate operational conditions. This, in turn, fosters innovative avenues for the development of supercritical pharmaceuticals.