Mixing, homogenization, separation, and filtration are crucial processes in miniaturized analytical systems employed for in-vitro biological, environmental, and food analysis. However, in microfluidic systems achieving homogenization becomes more challenging due to the laminar flow conditions, which lack the turbulent flows typically used for mixing in traditional analytical systems. Here, we introduce an acoustofluidic platform that leverages an acoustic transducer to generate microvortex streaming, enabling effective homogenizing of food samples. To reduce reliance on external equipment, tubing, and pump, which is desirable for Point-of-Need testing, our pumpless platform employs a hydrophilic yarn capable of continuous wicking for sample perfusion. Following the homogenization process, the platform incorporates an array of micropillars for filtering out large particles from the samples. Additionally, the porous structure of the yarn provides a secondary screening mechanism. The resulting system is compact, and reliable, and was successfully applied to the detection of Escherichia coli (E. coli) in two different types of berries using quantitative polymerase chain reaction (qPCR). The platform demonstrated a detection limit of 5 CFU g ⁻¹, showcasing its effectiveness in rapid and sensitive pathogen detection.

Malodor is regarded as a very significant nuisance, 2nd only to noise pollution, in the developed world. It directly impacts people's health and wellbeing. The prevention of odor build-up is a key property for both interior textiles and active sportswear. Traditional approaches for odor elimination rely on textile surface treatment. However, the role of intrinsic morphology and chemical composition of fibers in odor elimination has not been taken into account. In this study, the adsorption characteristics and mechanisms of three common types of fibers (wool, cotton and nylon) for two typical odors of acetic acid and ammonia were systematically investigated through kinetic modelling, the inverse gas chromatography (IGC) technique, and density functional theory (DFT) calculations. Both acetic acid and ammonia adsorption onto fibers followed a pseudo-second-order kinetic model. Among all the tested fibers, wool showed the highest adsorption ability towards both acetic acid and ammonia. The adsorption behaviors of cotton and nylon were explored based on quantitative measurement of surface Lewis acid-base properties using the IGC technique. These findings were further corroborated by DFT calculations via the interactions between fibers and the adsorbed odor. This study provides a new insight into odor adsorption onto commonly used fibers and their interactions, which is a key step in developing fibrous materials for odor control, including body odor and indoor air pollutants.