Crack patterns of drying dense bacterial suspensions

Suppression of cracking in drying colloidal suspensions with chain-like particles

The prevention of drying-induced cracking is crucial in maintaining the mechanical integrity and functionality of colloidal deposits and coatings. Despite exploring various approaches, controlling drying-induced cracking remains a subject of great scientific interest and practical importance. By introducing chain-like particles composed of the same material and with comparable size into commonly used colloidal suspensions of spherical silica nanoparticles, we can significantly reduce the cracks formed in dried particle deposits and achieve a fivefold increase in the critical cracking thickness of colloidal silica coatings. The mechanism underlying the crack suppression is attributed to the increased porosity and pore sizes in dried particle deposits containing chain-like particle, which essentially leads to reduction in internal stresses developed during the drying process. Meanwhile, the nanoindentation measurements reveal that colloidal deposits with chain-like particles exhibit a smaller reduction in hardness compared to those reported using other cracking suppression approaches. This work demonstrates a promising technique for preparing colloidal coatings with enhanced crack resistance while maintaining desirable mechanical properties.

Drying of bio-colloidal sessile droplets: Advances, applications, and perspectives

Drying of biologically-relevant sessile droplets, including passive systems such as DNA, proteins, plasma, and blood, as well as active microbial systems comprising bacterial and algal dispersions, has garnered considerable attention over the last decades. Distinct morphological patterns emerge when bio-colloids undergo evaporative drying, with significant potential in a wide range of biomedical applications, spanning bio-sensing, medical diagnostics, drug delivery, and antimicrobial resistance. Consequently, the prospects of novel and thrifty bio-medical toolkits based on drying bio-colloids have driven tremendous progress in the science of morphological patterns and advanced quantitative image-based analysis. This review presents a comprehensive overview of bio-colloidal droplets drying on solid substrates, focusing on the experimental progress during the last ten years. We provide a summary of the physical and material properties of relevant bio-colloids and link their native composition (constituent particles, solvent, and concentrations) to the patterns emerging due to drying. We specifically examined the drying patterns generated by passive bio-colloids (e.g., DNA, globular, fibrous, composite proteins, plasma, serum, blood, urine, tears, and saliva). This article highlights how the emerging morphological patterns are influenced by the nature of the biological entities and the solvent, micro- and global environmental conditions (temperature and relative humidity), and substrate attributes like wettability. Crucially, correlations between emergent patterns and the initial droplet compositions enable the detection of potential clinical abnormalities when compared with the patterns of drying droplets of healthy control samples, offering a blueprint for the diagnosis of the type and stage of a specific disease (or disorder). Recent experimental investigations of pattern formation in the bio-mimetic and salivary drying droplets in the context of COVID-19 are also presented. We further summarized the role of biologically active agents in the drying process, including bacteria, algae, spermatozoa, and nematodes, and discussed the coupling between self-propulsion and hydrodynamics during the drying process. We wrap up the review by highlighting the role of cross-scale in situ experimental techniques for quantifying sub-micron to micro-scale features and the critical role of cross-disciplinary approaches (e.g., experimental and image processing techniques with machine learning algorithms) to quantify and predict the drying-induced features. We conclude the review with a perspective on the next generation of research and applications based on drying droplets, ultimately enabling innovative solutions and quantitative tools to investigate this exciting interface of physics, biology, data sciences, and machine learning.