A simple capillary viscometer based on the ideal gas law

Go with the flow: deep learning methods for autonomous viscosity estimations

Closed-loop experiments can accelerate material discovery by automating both experimental manipulations and decisions that have traditionally been made by researchers. Fast and non-invasive measurements are particularly attractive for closed-loop strategies. Viscosity is a physical property for fluids that is important in many applications. It is fundamental in application areas such as coatings; also, even if viscosity is not the key property of interest, it can impact our ability to do closed-loop experimentation. For example, unexpected increases in viscosity can cause liquid-handling robots to fail. Traditional viscosity measurements are manual, invasive, and slow. Here we use convolutional neural networks (CNNs) as an alternative to traditional viscometry by non-invasively extracting the spatiotemporal features of fluid motion under flow. To do this, we built a workflow using a dual-armed collaborative robot that collects video data of fluid motion autonomously. This dataset was then used to train a 3-dimensional convolutional neural network (3D-CNN) for viscosity estimation, either by classification or by regression. We also used these models to identify unknown laboratory solvents, again based on differences in fluid motion. The 3D-CNN model performance was compared with the performance of a panel of human participants for the same classification tasks. Our models strongly outperformed human classification in both cases. For example, even with training on fewer than 50 videos for each liquid, the 3D-CNN model gave an average accuracy of 88% for predicting the identity of five different laboratory solvents, compared to an average accuracy of 32% for human observation. For comparison, random category selection would give an average accuracy of 20%. Our method offers an alternative to traditional viscosity measurements for autonomous chemistry workflows that might be used both for process control (e.g., choosing not to pipette liquids that are too viscous) or for materials discovery (e.g., identifying new polymerization catalysts on the basis of viscosification).

Probing mutual interactions between Pseudomonas aeruginosa and Candida albicans in a biofabricated membrane-based microfluidic platform

Microbes are typically found in multi-species (polymicrobial) communities. Cooperative and competitive interactions between species, mediated by diffusible factors and physical contact, leads to highly dynamic communities that undergo changes in composition diversity and size. Infections can be more severe or more difficult to treat when caused by multiple species. Interactions between species can improve the ability of one or more species to tolerate anti-microbial treatments and host defenses. Pseudomonas aeruginosa (Pa), a ubiquitous bacterium, and the opportunistic pathogenic yeast, Candida albicans (Ca), are frequently found together in cystic fibrosis lung infections and wound infections. While significant progress has been made in determining interactions between Pa and Ca, there are still important questions that remain unanswered. Here, we probe the mutual interactions between Pa and Ca in a custom-made microfluidic device using biopolymer chitosan membranes that support cross-species communication. By assembling microbes in physically separated, chemically communicating populations or bringing into direct interactions in a mixed culture, in situ polymicrobial growth and biofilm morphology were qualitatively characterized and quantified. Our work reveals new dynamic details of their mutual interactions including cooperation, competition, invasion, and biofilm formation. The membrane-based microfluidic platform can be further developed to understand the polymicrobial interactions within a controlled interactive microenvironment to improve microbial infection prevention and treatment.

A Review of Microfluidic Devices for Rheological Characterisation

The rheological characterisation of liquids finds application in several fields ranging from industrial production to the medical practice. Conventional rheometers are the gold standard for the rheological characterisation; however, they are affected by several limitations, including high costs, large volumes required and difficult integration to other systems. By contrast, microfluidic devices emerged as inexpensive platforms, requiring a little sample to operate and fashioning a very easy integration into other systems. Such advantages have prompted the development of microfluidic devices to measure rheological properties such as viscosity and longest relaxation time, using a finger-prick of volumes. This review highlights some of the microfluidic platforms introduced so far, describing their advantages and limitations, while also offering some prospective for future works.

Flow-assembled chitosan membranes in microfluidics: recent advances and applications

The integration of membranes in microfluidic devices has been extensively exploited for various chemical engineering and bioengineering applications over the past few decades. To augment the applicability of membrane-integrated microfluidic platforms for biomedical and tissue engineering studies, a biologically friendly fabrication process with naturally occurring materials is highly desired. The in situ preparation of membranes involving interfacial reactions between parallel laminar flows in microfluidic networks, known as the flow-assembly technique, is one of the most biocompatible approaches. Membranes of many types with flexible geometries have been successfully assembled inside complex microchannels using this facile and versatile flow-assembly approach. Chitosan is a naturally abundant polysaccharide known for its pronounced biocompatibility, biodegradability, good mechanical stability, ease of modification and processing, and film-forming ability under near-physiological conditions. Chitosan membranes assembled by flows in microfluidics are freestanding, robust, semipermeable, and well-aligned in microstructure, and show high affinity to bioactive reagents and biological components (e.g. biomolecules, nanoparticles, or cells) that provide facile biological functionalization of microdevices. Here, we discuss the recent developments and optimizations in the flow-assembly of chitosan membranes and chitosan-based membranes in microfluidics. Furthermore, we recapitulate the applications of the chitosan membrane-integrated microfluidic platforms dedicated to biology, biochemistry, and drug release fields, and envision the future developments of this important platform with versatile functions.

Modulating the properties of flow-assembled chitosan membranes in microfluidics with glutaraldehyde crosslinking

Glutaraldehyde crosslinking significantly enhances the mechanical robustness of the originally compromised flow-assembled chitosan membranes after Pluronic passivation in microfluidics.