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Inertial microfluidics is essential for separating particles and cells, enabling numerous biomedical applications. Despite the simplicity of spiral microchannels, the lack of predictive models hampers real‐world applications, highlighting the need for cost‐effective computational tools. In this study, four novel data fitting models are developed using linear and power regression analyses to investigate how flow conditions influence particle behaviors within spiral microchannels. These models are rigorously tested under two different flow rates, focusing on a smaller particle representing Salmonella Typhimurium and a larger particle representing bacterial aggregates, aiming for effective separation and detection. A critical parameter, the sheath‐to‐sample flow rate ratio, is either interpolated or extrapolated using the microchannel's aspect ratios to predict particle separation. The models show strong agreement with experimental data, underscoring their predictability and efficiency. These insights suggest that further refinement of these models can significantly reduce research and development costs for advanced inertial microfluidic devices in biomedical applications. This work represents a crucial step towards establishing a robust computational framework, advancing inertial microfluidics towards practical biomedical applications. [ABSTRACT FROM AUTHOR]

Microfluidic‐assisted synthesis of nanoparticles has generated significant interest for its precise control and high throughput capabilities. Among various nanomaterials, gold nanoparticles (AuNPs) have shown remarkable potential in numerous applications, such as disease detection, photothermotherapy, drug delivery, and even defense applications. Recent synthesis strategy of peptide‐mediated method has sparked greater interest by offering unique chiroptical properties and their applications in biomedical applications. In this study, the use of droplet microfluidics is explored for the synthesis of peptide‐mediated AuNPs, aiming to accelerate automated production via flow chemistry. This method leads to the formation of anisotropic gold particles, with sizes ranging from hundreds of nanometers to the micron scale. The interfacial energy is identified at the water/oil interface as a critical factor influencing this outcome, with L‐glutathione (L‐GSH) playing a significant role in the development of hyper‐branched structures. These results demonstrate the capability of droplet microfluidics in producing anisotropic gold particles at micron scales, presenting new possibilities for the advancement of nanoparticle synthesis techniques. [ABSTRACT FROM AUTHOR]

The spectacular physical phenomenon of surface plasmon resonance (SPR) is the essence of present‐day plasmonic sensors. Meanwhile, the unique properties of the interaction between light and matter have been carved out into the development of modern‐day diagnostic biosensors. Plasmons, in simple terms, are oscillating free electrons in metallic nano‐structures triggered by an incoming electromagnetic (EM) wave. With the advantages of real‐time and label‐free bio‐sensing, plasmonic sensors are being utilized in multiple diverse areas of food technology, the bio‐medical diagnostic sector, and even the chemical industry. Although this review will be brief, readers can gain a comprehensive picture of the essential elements by taking a broader look into the exploration of SPR sensor design via simulated studies and representative experimental plasmonic schemes developed for bio‐sensing. In short, the various SPR sensing schemes that researchers have explored to realize enhanced SPR sensitivity are reviewed and summarized. Different experimental plasmonic sensors are also examined in which new SPR excitation schemes have been adopted. These "unconventional" designs, specifically those involving hybrid localized surface plasmon resonance (LSPR)‐SPR excitation, may inspire those in the plasmonic field. [ABSTRACT FROM AUTHOR]