Desiccation cracks in clay composites unveil intricate physicochemical dynamics, yet their control is pivotal for geotechnical and environmental engineering. This study investigates the influence of cation valency and ionic size on desiccation crack patterns in bentonite–chloride salt slurries. Controlled drying experiments were performed using monovalent (NaCl, KCl), divalent (MgCl _2 , CaCl _2 ) and trivalent (FeCl _3 ) cations. Crack development was monitored by high-resolution imaging and quantitatively analysed using Python-based image processing. Complementary aggregate size distribution, zeta potential, X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) measurements were used to elucidate the physicochemical mechanisms controlling crack morphology. Results show that both cation valency and ionic radius substantially affect water retention and aggregation in the slurry and consequently determine crack network characteristics (node and ped counts, growth rates and temporal regimes). Notably, the influence of inner orbital electron screening in Fe ^3+ —manifest as reduced effective ionic radius and altered swelling — was experimentally evident via crack statistics. Observed trends are interpreted using an integrated framework that couples DLVO interactions, capillary-driven hydro–mechanical stresses and fracture mechanics. The findings provide mechanistic insight into salt–clay interactions with implications for designing crack-resistant bentonite-based barriers.

Desiccation cracks in clay composites unveil intricate physicochemical dynamics, yet their control is pivotal for geotechnical and environmental engineering. In this work the role of cation valency and size on desiccation crack pattern in bentonite-salt chloride slurry is examined. Experiments with monovalent (NaCl, KCl), divalent (MgCl2, CaCl2), and trivalent (FeCl3) cations under controlled drying were performed. Crack evolution was tracked and quantified by high-resolution imaging and PYTHON analytics. Aggregate size, zeta potential, X-Ray Diffraction (XRD), and Fourier transform Infrared Spectroscopy (FTIR) analyses illuminated the mechanisms shaping crack morphology. Studies revealed that the valency and ionic radius of the cation are both important factors that influence the water retention capacity of the composite slurry, and hence control the final crack patterns. The screening effect of inner orbital electrons in the case of large sized cations like Fe+3 is experimentally demonstrated for the first time via desiccation crack patterns. Three distinct time zones of cracking emerge that is more pronounced in higher-valency cations. KCl makes stable cracks by delaying crack formation and forms needle-like crystals by supersaturation; while CaCl2 accelerates the fracturing process due to dense formation of aggregates reducing water retention capacity. These insights advance the mechanistic understanding of salt-clay interactions, offering strategies for crafting crack-resistant materials for engineered barriers and soil stabilization.

Surface roughness plays a critical role in determining the physical and functional performance of materials across biomedical, industrial, and chemical engineering. This study investigates the use of deep learning techniques to approximate surface roughness and quantify stochasticity from microscopic images of polydimethylsiloxane (PDMS) polymers treated with sandpaper of varying grit levels. Building on a dataset of scanning electron microscopy (SEM) and confocal microscopy images from a surface wetting study, we developed supervised deep learning models, aimed at predicting roughness parameters and identifying latent texture features. Unique preprocessing pipelines were designed for each image modality to account for their distinct imaging characteristics. Our results highlight an inverse relationship between sandpaper grit level and visual surface roughness, while also uncovering nonlinearities introduced by specific grit-substrate interactions. This approach demonstrates the viability of visual deep learning as a low-cost, scalable alternative to traditional surface characterization, particularly for chemically flexible, lightweight polymers like PDMS. This study provide a foundation for future applications in microfluidics, biomedical device design, and surface engineering where rapid, image-based surface analysis is beneficial and cost-effective.

The present manuscript examines the dried patterns of sodium chloride (NaCl salt) crystals on the basis of a biopolymer complex fluid drop. The study focuses on the effects of varying relative humidity of the room on the crystal formation and stability. The findings reveal that the morphology of the crystal changes from a cross-crystal pattern to a dendritic pattern with changing humidity, even after initial crystal formation. The same observation was made for drops on a hydrophobic polymer surface. The study provides insight into the morphological changes of NaCl crystals with changing humidity and highlights the importance of considering humidity as a key factor in controlling crystal formation and stability. The findings have the potential to be applied in various fields such as material science, pharmaceuticals, and biomedicine, where controlling crystal formation and stability is essential.

Fluid mixing process under direct current (DC) voltage stress is a complex phenomenon when the physical and chemical properties of the two streams are different. We experimentally investigate two streams of fluid flow one with added ink, changing its density and electro-chemical properties, followed by the application of different DC voltage levels. In this experiment, we found that as the applied voltage increases, volumes of the two fluids - with and without ink keep oscillating. Using the state-of-the-art image segmentation methods based on k-means clustering on the transformed La*b* colour image space, we carry out the pixel counting based volume calculation in the voltage induced fluid mixing experiments. Here, each frame of the video is considered as a separate image, undergoing segmentation process yielding estimated pixel numbers in each cluster. Repeating this frame-by-frame clustering-based image segmentation process on the whole video data yields a fluctuating time-series data, showing the ratio of the two fluids within the closed chamber. Due to the high complexity of the noisy fluctuating time series data, we then apply the autoregressive fractionally integrated moving average (ARFIMA) model to quantify the two-fluid volumetric ratio fluctuation data in compact and simple discrete time models. The hyperparameter tuning of the ARFIMA models have also been demonstrated. The efficacy of the fractional order discrete time models or estimators change with the length of data being modelled which may be useful in getting better insights into the stability of fluid mixing process using the volumetric ratio data analysis, irrespective of the timescale of the experiments.

Desiccation patterns left by micro-droplets of water impregnated with particles on hydrophobic substrates have been analyzed with respect to variations in the elastic stiffness of the substrates, particle size and relative humidity. The complex and unique patterns obtained, have been analyzed and explained in terms of the time scales of moving Triple Phase Line (TPL) on substrate and substrate relaxation rate. The rate of TPL movement is found to depend on the relative humidity and substrate stiffness. In turn, this affects the contact angle hysteresis. Particle movement is a result of viscous drag and inertia apart from electrostatic interactions. We have successfully explained the myriad patterns obtained from drying droplets via systematic rheological measurements along with an understanding of the role of all the effective forces and their time scales of action.

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Golda Khullar, Moutushi Dutta Choudhury; A study on drop impact on soft surfaces. AIP Conference Proceedings 3 February 2023; 2558 (1): 020036. https://doi.org/10.1063/5.0121322 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search

This paper studies various wetting characteristics on different surfaces of Polydimethylsiloxane (PDMS) polymer. The random roughness of the surface is engineered by using sandpapers to introduce different order of hydrophobic properties to understand the temporal evolution of drying droplets. We develop statistical models to predict temporal evolution of the base diameter, height, surface, and contact angle of drying droplets with varying grit size or surface roughness. Five different robust polynomial regression models have been compared for the prediction of three dependent variables - base diameter, height, and surface of drying droplets for random rough surfaces. In a nutshell, we here identify the best statistical model to capture the dynamics of drying droplets on hydrophobic surfaces of random roughness characteristics.

A short note on observations of dried patterns of a bi-dispersive colloidal drop on a relatively soft polymer-surface is presented here. The patterns have huge applications in the field of medical diagnosis, fertilization and drug delivery industry and improvement of coating/printing technology. The features in the dried drop involve self-organized open systems. The pattern analysis initiates the predicted mechanism of drying. Drops of liquid containing suspended particles are assumed to be drying on a horizontal semi-solid substrate of a polymer. Study of the fractal geometry of a pattern characterizes the system’s overall behavior and predicts the system’s basic wetting properties.

In this paper, we propose a mathematical picture of flow in a drying multiphase droplet. The system studied consists of a suspension of microscopic polystyrene beads in water. The time development of the drying process is described by defining the “Euler characteristic surface,” which provides a multiscale topological map of this dynamical system. A novel method is adopted to analyze the images extracted from experimental video sequences. Experimental image data are converted to binary data through appropriate Gaussian filters and optimal thresholding and analyzed using the Euler characteristic determined on a hexagonal lattice. In order to do a multiscale analysis of the extracted image, we introduce the concept of Euler characteristic at a specific scale r > 0. This multiscale time evolution of the connectivity information on aggregates of polysterene beads in water is summarized in a Euler characteristic surface and, subsequently, in a Euler characteristic level curve plot. We introduce a metric between Euler characteristic surfaces as a possible similarity measure between two flow situations. The constructions proposed by us are used to interpret flow patterns (and their stability) generated on the upper surface of the drying droplet interface. The philosophy behind the topological tools developed in this work is to produce low-dimensional signatures of dynamical systems, which may be used to efficiently summarize and distinguish topological information in various types of flow situations.

A simple colloidal drop generally forms ring like patterns after drying. The deposition morphology of the dried drop changes significantly when such a drop dries in the vicinity of another similar drop. Here we present an observational study and statistical analysis of the patterns formed inside an isolated as well as interacting drops of gelatin containing sodium sulfate (Na2SO4). In all the cases, multiple concentric regions of solute particles combined with the polymer gel appear as the drops dry up. Needle crystals of sulfur and coacervates of salt and gelatin are visible in some regions. The outer region becomes non-uniform, so does the size distribution of the needle crystals and coacervates. The non-uniformity increases with proximity of the drops. Here we propose a novel mechanism of growing patterns inside the single drop during drying and correlate that with the results obtained for interacting drops. This study and the proposed mechanism provide insights into the future studies of drying drops under different physical conditions. Further we explore the statistical characteristics of the single and interacting drops using the field emission scanning electron microscopy (FESEM) images. Next, we report fractal and image texture analyses along with object shape statistics of the drop FESEM images, under various experimental conditions. Several statistical hypothesis tests have been carried out to identify the most significant features.

Evaporation of a drop, though a simple everyday observation, provides a fascinating subject for study. Various issues interact here, such as dynamics of the contact line, evaporation-induced phase transitions, and formation of patterns. The explanation of the rich variety of patterns formed is not only an academic challenge, but also a problem of practical importance, as applications are growing in medical diagnosis and improvement of coating/printing technology. The multi-scale aspect of the problem is emphasized in this review. The specific fundamental problem to be solved, related to the system is the investigation of the mass transfer processes, the formation and evolution of phase fronts and the identification of mechanisms of pattern formation. To understand these problems, we introduce the important forces and interactions involved in these processes, and highlight the evaporation-driven phase transitions and flows in the drop. We focus on how the deposited patterns are related to and tuned by important factors, for instance substrate properties and contents of the drop. In addition, the formation of crust and crack patterns are discussed. The simulation and modeling methods, which are often utilized in this topic, are also reviewed. Finally, we summarize the applications of drop evaporation and suggest several potential directions for future research in this area. Exploiting the full potential of this topic in basic science research and applications needs involvement and interaction between scientists and engineers from disciplines of physics, chemistry, biology, medicine and other related fields.

The dynamics of evaporating water droplets on heated graphene-poly(dimethylsiloxane) (PDMS) composites is investigated experimentally and theoretically. By inserting graphene nucleates in PDMS, we report the effect of change in thermal resistance on the evaporation process of water droplets on the heated graphene-PDMS composite surface. By dispersing graphene within the PDMS matrix, the evaporation of water droplets is enhanced. The graphene nucleate density over the surface was controlled by varying graphene wt % from 0 to 2%, which in turn controls the thermal resistance and hence the evaporation rate. Experimentally, the maximum evaporation rate of 0.0044 μL/s was observed for the sample of 2 wt % graphene-PDMS composite. The evaporation rate on a 2 wt % graphene-PDMS composite surface is about 1.5 times higher compared to that of plain PDMS without graphene. A theoretical model confirms that the initial contact angle and the presence of thermal coupling between liquid droplets and the substrate play an important role in evaporation dynamics. Thermal conductance increases 3 times with the increase in graphene wt % from 0.1 to 2.0 wt % in PDMS. The heat-storing capacity of graphene is responsible for the enhanced evaporation. The experimental findings are in good agreement with theoretical results. These samples were found insensitive to degradation and may find potential applications where high efficiency and high heat flux are needed.

We report the formation of crack patterns in drying films of Laponite-NaCl solution. Crack patterns that develop upon drying aqueous Laponite-NaCl solution change drastically as the amount of NaCl is varied in the solution. In this work, we have investigated the effect of NaCl on drying films of aqueous solution of Laponite under two conditions: (i) when the film is bounded by a wall, as in Petri dish experiments and (ii) when the film does not have any boundary, as in experiments with droplets. In order to obtain insights into the effect of the substrate, the experiments have been done with two different substrates of different hydrophobicities, polypropylene and glass. The formation of crack patterns has been explained on the basis of the wetting and spreading properties of the solution on these substrates and the effect of salt on colloidal aggregation. In this work, we have shown that the presence of salt in aqueous Laponite solution can induce crack patterns depending on the nature of the substrate. Another important aspect of this work is the role of NaCl in crack inhibition in desiccating films of aqueous Laponite, in the presence of static electric field. This effect can be utilized to suppress undesirable crack formation in many applications.

This review is devoted to the simple process of drying a multicomponent droplet of a complex fluid which may contain salt or other inclusions. These processes provide a fascinating subject for study. The explanation of the rich variety of patterns formed is not only an academic challenge but also a problem of practical importance, as applications are growing in medical diagnosis and improvement of coating/printing technology. The fundamental scientific problem is the study of the mechanism of micro- and nanoparticle self-organization in open systems. The specific fundamental problems to be solved, related to this system, are the investigation of the mass transfer processes, the formation and evolution of phase fronts, and the identification of mechanisms of pattern formation. The drops of liquid containing dissolved substances and suspended particles are assumed to be drying on a horizontal solid insoluble smooth substrate. The chemical composition and macroscopic properties of the complex fluid, the concentration and nature of the salt, the surface energy of the substrate, and the interaction between the fluid and substrate which determines the wetting all affect the final morphology of the dried film. The range of our study encompasses the fully wetting case with zero contact angle between the fluid and substrate to the case where the drop is levitated in space, so there is no contact with a substrate and angle of contact can be considered as 180°.

Evaporation of droplets is an interesting problem which has aroused a keen interest in the scientific community. The behavior of a drying droplet on solid substrates produces everyday phenomena like the coffee stain effect, deposition of lime scales on walls etc. It is also very important in many scientific and industrial procedures. Among several varieties of systems, a droplet of colloidal gel containing an inorganic salt presents a very interesting class. In this work we study a rich variety of self-assembled patterns generated by the evaporation of a droplet of colloidal copper sulphate (CuSO 4 .5H 2 O) solution, having different concentrations, on a glass surface. Our results show that the patterns are dendritic in nature having multiple branches. A simple aqueous solution of copper sulphate does not produce the same morphology. The pattern formation process may be controlled by several parameters such as the particle size, structure of the crystalline salt, droplet size, ambient temperature and humidity.