Hyperspectral imaging for dynamic thin film interferometry

Absolute thickness field measurement on curved axisymmetric thin free films with monochromatic light

The thickness of thin films is a key parameter to understand their thinning dynamics and stability. Thickness measurements are commonly performed using interferometry. White light illumination allows us to measure the absolute thickness, but is limited to small thicknesses (<2μm) or is restricted to a point with a spectrometer. Monochromatic light gives access to a broader range of thicknesses but solely in a relative manner unless a reference thickness is known. These methods are extensively used to quantify the thickness profiles of flat soap films. In contrast, they are applied to curved interfaces (bubbles) only in a few specific cases, mainly due to the complexity arising from the curvature as the optical path depends on the position. In this paper, we elucidate the influence of the curvature and show that it can be used to measure the entire and absolute thickness profiles using monochromatic light. We demonstrate the validity of the method on soap bubbles, antibubbles, and catenoid soap films. This cost-effective technique is adapted to quantitatively study the thin film dynamics in these geometries.

Spatiotemporal mapping of nanotopography and thickness transitions of ultrathin foam films

Freshly formed soap films, soap bubbles, or foam films display iridescent colors due to thin film interference that changes as squeeze flow drives drainage and a progressive decrease in film thickness. Ultrathin (thickness <100 nm) freestanding films of soft matter containing micelles, particles, polyelectrolyte-surfactant complexes, or other supramolecular structures or liquid crystalline phases display drainage via stratification. A fascinating array of thickness variations and transitions, including stepwise thinning and coexistence of thick-thin flat regions, arise in micellar foam films that undergo drainage via stratification. In this tutorial, we describe the IDIOM (interferometry digital imaging optical microscopy) protocols that combine the conventional interferometry principle with digital filtration and image analysis to obtain nanometer accuracy for thickness determination while having high spatial and temporal resolution. We provide fully executable image analysis codes and algorithms for the analysis of nanotopography and summarize some of the unique insights obtained for stratified micellar foam films.

Nonaqueous foam stabilization mechanisms in the presence of volatile solvents

Hypothesis Nonaqueous foams are found in a variety of applications, many of which contain volatile components that need to be removed during processing. Sparging air bubbles into the liquid can be used to aid in their removal, but the resulting foam can be stabilized or destabilized by several different mechanisms, the relative importance of which are not yet fully understood. Investigating the dynamics of thin film drainage, four competing mechanisms can be observed, such as solvent evaporation, film viscosification, and thermal and solutocapillary Marangoni flows. Experiments Experimental studies with isolated bubbles and/or bulk foams are needed to strengthen the fundamental knowledge of these systems. This paper presents interferometric measurements of the dynamic evolution of a film formed by a bubble rising to an air-liquid interface to shed light on this situation. Two different solvents with different degrees of volatility were investigated to reveal both qualitative and quantitative details on thin film drainage mechanisms in polymer-volatile mixtures. Findings Using interferometry, we found evidence that solvent evaporation and film viscosification both strongly influence the stability of interface. These findings were corroborated by comparison with bulk foam measurements, revealing a strong correlation between these two systems.

Measuring cryo-TEM sample thickness using reflected light microscopy and machine learning

In cryo-transmission electron microscopy (cryo-TEM), sample thickness is one of the most important parameters that governs image quality. When combining cryo-TEM with other imaging methods, such as light microscopy, measuring and controlling the sample thickness to ensure suitability of samples becomes even more critical due to the low throughput of such correlated imaging experiments. Here, we present a method to assess the sample thickness using reflected light microscopy and machine learning that can be used prior to TEM imaging of a sample. The method makes use of the thin-film interference effect that is observed when imaging narrow-band LED light sources reflected by thin samples. By training a neural network to translate such reflection images into maps of the underlying sample thickness, we are able to accurately predict the thickness of cryo-TEM samples using a light microscope. We exemplify our approach using mammalian cells grown on TEM grids, and demonstrate that the thickness predictions are highly similar to the measured sample thickness. The open-source software described herein, including the neural network and algorithms to generate training datasets, is freely available at github.com/bionanopatterning/thicknessprediction. With the recent development of in situ cellular structural biology using cryo-TEM, there is a need for fast and accurate assessment of sample thickness prior to high-resolution imaging. We anticipate that our method will improve the throughput of this assessment by providing an alternative method to screening using cryo-TEM. Furthermore, we demonstrate that our method can be incorporated into correlative imaging workflows to locate intracellular proteins at sites ideal for high-resolution cryo-TEM imaging.

Diagnostic Approaches For COVID-19: Lessons Learned and the Path Forward

Coronavirus disease 2019 (COVID-19) is a transmitted respiratory disease caused by the infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although humankind has experienced several outbreaks of infectious diseases, the COVID-19 pandemic has the highest rate of infection and has had high levels of social and economic repercussions. The current COVID-19 pandemic has highlighted the limitations of existing virological tests, which have failed to be adopted at a rate to properly slow the rapid spread of SARS-CoV-2. Pandemic preparedness has developed as a focus of many governments around the world in the event of a future outbreak. Despite the largely widespread availability of vaccines, the importance of testing has not diminished to monitor the evolution of the virus and the resulting stages of the pandemic. Therefore, developing diagnostic technology that serves as a line of defense has become imperative. In particular, that test should satisfy three criteria to be widely adopted: simplicity, economic feasibility, and accessibility. At the heart of it all, it must enable early diagnosis in the course of infection to reduce spread. However, diagnostic manufacturers need guidance on the optimal characteristics of a virological test to ensure pandemic preparedness and to aid in the effective treatment of viral infections. Nanomaterials are a decisive element in developing COVID-19 diagnostic kits as well as a key contributor to enhance the performance of existing tests. Our objective is to develop a profile of the criteria that should be available in a platform as the target product. In this work, virus detection tests were evaluated from the perspective of the COVID-19 pandemic, and then we generalized the requirements to develop a target product profile for a platform for virus detection.

Tear Film Stability as a Function of Tunable Mucin Concentration Attached to Supported Lipid Bilayers

In this work, we describe the development of a tunable, acellular in vitro model of the mucin layer of the human tear film. First, supported lipid bilayers (SLBs) comprised of the phospholipid DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine) and biotinyl cap PE (1,2-dioleoyl-sn-glycero-3-phosphoethanolamine-N-(cap biotinyl)) are created on the surface of a glass dome with radius of curvature comparable to the human eye. Next, biotinylated bovine submaxillary mucins (BSM) are tethered onto the SLB using streptavidin protein. The mucin presentation can be tuned by altering the concentration of biotinylated BSM, which we confirm using fluorescence microscopy. Due to the optically smooth surface that results, this model is compatible with interferometry for monitoring film thickness. Below a certain level of mucin coverage, we observe short model tear film breakup times, mimicking a deficiency in membrane-associated mucins. In contrast, the breakup time is significantly delayed for SLBs with high mucin coverage. Because no differences in mobility or wettability were observed, we hypothesize that higher mucin coverage provides a thicker hydrated layer that can protect against external disturbances to thin film stability. This advance paves the way for a more physiological, interferometry-based in vitro model for investigating tear film breakup.

Use of Hyperspectral Imaging for the Quantification of Organic Contaminants on Copper Surfaces for Electronic Applications

To correctly assess the cleanliness of technical surfaces in a production process, corresponding online monitoring systems must provide sufficient data. A promising method for fast, large-area, and non-contact monitoring is hyperspectral imaging (HSI), which was used in this paper for the detection and quantification of organic surface contaminations. Depending on the cleaning parameter constellation, different levels of organic residues remained on the surface. Afterwards, the cleanliness was determined by the carbon content in the atom percent on the sample surfaces, characterized by XPS and AES. The HSI data and the XPS measurements were correlated, using machine learning methods, to generate a predictive model for the carbon content of the surface. The regression algorithms elastic net, random forest regression, and support vector machine regression were used. Overall, the developed method was able to quantify organic contaminations on technical surfaces. The best regression model found was a random forest model, which achieved an R² of 0.7 and an RMSE of 7.65 At.-% C. Due to the easy-to-use measurement and the fast evaluation by machine learning, the method seems suitable for an online monitoring system. However, the results also show that further experiments are necessary to improve the quality of the prediction models.

Single bubble and drop techniques for characterizing foams and emulsions

The physics of foams and emulsions has traditionally been studied using bulk foam/emulsion tests and single film platforms such as the Scheludko cell. Recently there has been a renewed interest in a third class of techniques that we term as single bubble/drop tests, which employ isolated whole bubbles and drops to probe the characteristics of foams and emulsions. Single bubble and drop techniques provide a convenient framework for investigating a number of important characteristics of foams and emulsions, including the rheology, stabilization mechanisms, and rupture dynamics. In this review we provide a comprehensive discussion of the various single bubble/drop platforms and the associated experimental measurement protocols including the construction of coalescence time distributions, visualization of the thin film profiles and characterization of the interfacial rheological properties. Subsequently, we summarize the recent developments in foam and emulsion science with a focus on the results obtained through single bubble/drop techniques. We conclude the review by presenting important venues for future research.

Bubble Coalescence at Wormlike Micellar Solution-Air Interfaces

Surfactants in aqueous solutions self-assemble in the presence of salt, to form long, flexible, wormlike micelles (WLM). WLM solutions exhibit viscoelastic properties and are used in many applications, such as for cosmetic products, drag reduction, and hydraulic fracturing. Understanding the coalescence stability of bubbles in WLM solutions is important for the development of WLM based products that require a stable dispersion of bubbles. In this paper, we investigate the thin film drainage dynamics leading up to the coalescence of bubbles at flat WLM solution-air interfaces. The salts and surfactant type and concentrations were chosen so as to have the viscoelastic properties of the tested WLM solutions span over 2 orders of magnitude in moduli and relaxation times. The various stages in drainage and coalescence, the formation of a thick region at the apex (a dimple), the thinning and washout of this dimple, and the final stages of drainage before rupture, are modified by the viscoelasticity of the wormlike micellar solutions. As a result of the unique viscoelastic properties of the WLM solutions, we also observe a number of interesting fluid dynamic phenomena during the drainage processes including elastic recoil, thin film ripping, and single-step terminal drainage.