The Exploration of Ink Formulations in Binder Jet 3D Printing Drugs.

The application of binder jet 3D printing technology in the pharmaceutical field is developing rapidly. The properties of the ink are very important, affecting the stability of the ejection and the precision of the finished product, but there is a great lack of research on pharmaceutical inks. This study used solvents and excipients commonly used in pharmaceuticals to quantify the printability of inks using printability Z value theory, while using an ink-jet printing and observation platform to analyze the droplet ejection state of different composition inks from microscopic level. Studies have shown that compared to ethanol, the ejection effect of droplets was better when isopropanol was added to the ink, and the proportion added should not be greater than 40%; as the molecular weight of polyvinylpyrrolidone (PVP) increased, the concentration of PVP tolerated by the ink decreased; glycerin has a high ejection efficiency when the proportion is within 10%. In summary, a superior ink formulation of 40% aqueous isopropanol plus 0.1% PVP K30 and 4% glycerin was obtained. With this ink, levetiracetam dispersible tablets were prepared with a smooth printing process and the tablets had good appearance, good mechanical properties, and rapid release. This study provides a mutual validation of the Z value theory and the results of droplet ejection and tablet printing, while providing good ideas.

Design & automation of a small-scale towing tank for flow visualization.

Although the towing tank is a standard piece of equipment used to investigate fluid phenomena, it primarily exists as custom-built hardware that takes up a significant footprint. The size, cost, and custom-built nature have heretofore inhibited the production of this equipment in the authors' context, an African university. This paper presents a small-scale (1000 mm x 200 mm x 200 mm), low-cost (<$1,000) towing tank made using readily available components and basic digital fabrication tools. Other universities on the continent and beyond can hence create this foundational platform for fluid mechanics-related teaching and research. Leveraging an Arduino microcontroller loaded with the GRBL firmware, G-code is sent from the computer to stepper motors to execute movements in two axes. This allows for automation capabilities, controlled towing speeds, and consistent experimental conditions. Validation tests revealed motion accuracy within 1 %. A glitter-based flow visualization approach to measuring surface phenomena is demonstrated here. Experiments conducted successfully visualized relevant flow characteristics generated by bluff bodies being towed in the tank. As the Reynolds number increased within the operating range, wider wakes and larger, more distinct vortices were generated, as expected. This platform can be replicated widely in institutions that may otherwise forego experimentation in fluid mechanics.

Exergy Flow as a Unifying Physical Quantity in Applying Dissipative Lagrangian Fluid Mechanics to Integrated Energy Systems.

Highly integrated energy systems are on the rise due to increasing global demand. To capture the underlying physics of such interdisciplinary systems, we need a modern framework that unifies all forms of energy. Here, we apply modified Lagrangian mechanics to the description of multi-energy systems. Based on the minimum entropy production principle, we revisit fluid mechanics in the presence of both mechanical and thermal dissipations and propose using exergy flow as the unifying Lagrangian across different forms of energy. We illustrate our theoretical framework by modeling a one-dimensional system with coupled electricity and heat. We map the exergy loss rate in real space and obtain the total exergy changes. Under steady-state conditions, our theory agrees with the traditional formula but incorporates more physical considerations such as viscous dissipation. The integral form of our theory also allows us to go beyond steady-state calculations and visualize the local, time-dependent exergy flow density everywhere in the system. Expandable to a wide range of applications, our theoretical framework provides the basis for developing versatile models in integrated energy systems.

Encoding spatiotemporal asymmetry in artificial cilia with a ctenophore-inspired soft-robotic platform.

A remarkable variety of organisms use metachronal coordination (i.e. numerous neighboring appendages beating sequentially with a fixed phase lag) to swim or pump fluid. This coordination strategy is used by microorganisms to break symmetry at small scales where viscous effects dominate and flow is time-reversible. Some larger organisms use this swimming strategy at intermediate scales, where viscosity and inertia both play important roles. However, the role of individual propulsor kinematics-especially across hydrodynamic scales-is not well-understood, though the details of propulsor motion can be crucial for the efficient generation of flow. To investigate this behavior, we developed a new soft robotic platform using magnetoactive silicone elastomers to mimic the metachronally coordinated propulsors found in swimming organisms. Furthermore, we present a method to passively encode spatially asymmetric beating patterns in our artificial propulsors. We investigated the kinematics and hydrodynamics of three propulsor types, with varying degrees of asymmetry, using Particle Image Velocimetry and high-speed videography. We find that asymmetric beating patterns can move considerably more fluid relative to symmetric beating at the same frequency and phase lag, and that asymmetry can be passively encoded into propulsors via the interplay between elastic and magnetic torques. Our results demonstrate that nuanced differences in propulsor kinematics can substantially impact fluid pumping performance. Our soft robotic platform also provides an avenue to explore metachronal coordination at the meso-scale, which in turn can inform the design of future bioinspired pumping devices and swimming robots.

Physics-informed neural networks for high-resolution weather reconstruction from sparse weather stations.

Background: The accurate provision of weather information holds immense significance to many disciplines. One example corresponds to the field of air traffic management, in which one basis for weather detection is set upon recordings from sparse weather stations on ground. The scarcity of data and their lack of precision poses significant challenges to achieve a detailed description of the atmosphere state at a certain moment in time. Methods: In this article, we foster the use of physics-informed neural networks (PINNs), a type of machine learning (ML) architecture which embeds mathematically accurate physics models, to generate high-quality weather information subject to the regularization provided by the Navier-Stokes equations. Results: The application of PINNs is oriented to the reconstruction of dense and precise wind and pressure fields in areas where only a few local measurements provided by weather stations are available. Our model does not only disclose and regularize such data, which are potentially corrupted by noise, but is also able to precisely compute wind and pressure in target areas. Conclusions: The effect of time and spatial resolution over the capability of the PINN to accurately reconstruct fluid phenomena is thoroughly discussed through a parametric study, concluding that a proper tuning of the neural network's loss function during training is of utmost importance.

There is currently a great interest in the many uses of artificial intelligence (AI) and how it is affecting our daily lives. From the robotics field to the use of language recognition to interact with different users, we are experiencing how machine intelligence is increasing day by day. In this article, we delve into one of the many applications of artificial intelligence: weather reconstruction. The ability to accurately determine weather conditions is believed to have an impact on various disciplines, e.g. reducing costs at airports due to delays, cancellations and associated compensations. In this particular example, a precise description of the status of the atmosphere is therefore necessary if countermeasures are to be executed. However, conventional weather recording with on-ground stations is often limited to a few sparse locations. Following that line of thought, it is not only necessary to estimate the weather in areas surrounding stations, but also on other target areas which may be subject to lack of weather information. Our strategy is based on the application of neural networks, a type of AI architecture, to infer data based on the underlying physics that drive the measured weather phenomena. For that purpose, we make use of neural networks which are consistent with physics laws, the so-called physics-informed neural networks (PINNs). This article deals with their adoption to weather pattern reconstruction, with the objective of further increasing the precision and availability of information given scarce reference measurements.

Hemodynamic influence of mild stenosis morphology in different coronary arteries: a computational fluid dynamic modelling study.

Introduction: Mild stenosis [degree of stenosis (DS) < 50%] is commonly labeled as nonobstructive lesion. Some lesions remain stable for several years, while others precipitate acute coronary syndromes (ACS) rapidly. The causes of ACS and the factors leading to diverse clinical outcomes remain unclear. Method: This study aimed to investigate the hemodynamic influence of mild stenosis morphologies in different coronary arteries. The stenoses were modeled with different morphologies based on a healthy individual data. Computational fluid dynamics analysis was used to obtain hemodynamic characteristics, including flow waveforms, fractional flow reserve (FFR), flow streamlines, time-average wall shear stress (TAWSS), and oscillatory shear index (OSI). Results: Numerical simulation indicated significant hemodynamic differences among different DS and locations. In the 20%-30% range, significant large, low-velocity vortexes resulted in low TAWSS (<4 dyne/cm2) around stenoses. In the 30%-50% range, high flow velocity due to lumen area reduction resulted in high TAWSS (>40 dyne/cm2), rapidly expanding the high TAWSS area (averagely increased by 0.46 cm2) in left main artery and left anterior descending artery (LAD), where high OSI areas remained extensive (>0.19 cm2). Discussion: While mild stenosis does not pose any immediate ischemic risk due to a FFR > 0.95, 20%-50% stenosis requires attention and further subdivision based on location is essential. Rapid progression is a danger for lesions with 20%-30% DS near the stenoses and in the proximal LAD, while lesions with 30%-50% DS can cause plaque injury and rupture. These findings support clinical practice in early assessment, monitoring, and preventive treatment.

Pathogenesis of Pachyvein Formation in Central Serous Chorioretinopathy: A Hydrodynamic Analysis.

Objectives: To attain an understanding of pachyvein formation seen with central serous chorioretinopathy (CSC) by measuring the choroidal blood flow (CBF) velocity and to apply the findings to existing hydrodynamic theorems. Methods: Nineteen subjects with monocular CSC (mean age 51.8 ± 12.7 years) were included. Laser speckle flowgraphy measured the mean blur rate (MBR) in the foveal and perifoveal regions, and the findings were applied to the Equation of Continuity (Q = AV) and Bernoulli's theorem (1/2V2 + P/ρ = constant). Results: The mean foveal/perifoveal MBRs in the CSC eyes were 6.4 ± 3.2/9.6 ± 3.2 (p < 0.001). The mean MBRs in the non-CSC eyes were 8.3 ± 3.2/7.9 ± 2.4 (p = 0.37). The significant foveal CBF velocity decrease in CSC eyes occurs because of exudation from the hyperpermeable choriocapillaris. The subsequent decrease in blood volume due to the exudation elicits a decrease in the blood flow velocity in the inferior venules in accordance with the Equation of Continuity. The decrease in the blood flow velocity may result in an elevated blood flow pressure in the inferior venules and veins at the exudation site, in accordance with Bernoulli's theorem. Conclusion: A significant decrease in the foveal MBR may result from exudation from the hyperpermeable macular choriocapillaris. This decreased velocity may elicit a blood pressure elevation that can expand the inferior venules and veins at the exudation site, so-called pachyvein and pachychoroid formation. The application of hydrodynamic theorems to the measurement of ocular blood flow can provide new insights into the understanding of the pathogenesis of chorioretinal disease.

Network Topology of Wing Veins in Hawaiian Flies Mitigates Allometric Dilemma.

Specific Hawaiian fruit flies have an extra crossvein (ECV) in the wing vein network which connects contiguously with another crossvein and forms a unique cruciform topology. These flies are distinguished by their large wings and their allometrically small vein diameters compared to those of typical fruit flies. Small vein diameters may increase frictional energy loss during internal blood transport, although they lead to an improvement in the wing's moment of inertia. Our hypothesis was that the ECV's presence would reduce the hydraulic resistance of the entire vein network. To investigate the hemodynamic effects of its presence, the flow rate of blood and frictional pressure loss within the vein networks was simulated by modeling them as hydraulic circuits. The results showed a 3.1% reduction in pressure loss owing to the network topology created by the presence of the ECV. This vein and its contiguous crossvein diverted part of the blood from the wing veins topologically parallel to them, reducing the pressure loss in these bypassed veins. The contiguity of the ECV to the other crossvein provided the shortest blood transfer route and lowest pressure drop between these crossveins. The results suggest that the presence of the ECV may counterbalance the heightened resistance caused by constricted veins.

Twisted fibers enable drop flow control and enhance fog capture.

Drop-fiber interactions are fundamental to the operation of technologies such as atmospheric fog capture, oil filtration, refrigeration, and dehumidification. We demonstrate that by twisting together two fibers, a sliding drop's flow path can be controlled by tuning the ratio between its size and the twist wavelength. We find both experimentally and numerically that twisted fiber systems are able to asymmetrically stabilize drops, both enhancing drop transport speeds and creating a rich array of new flow patterns. We show that the passive flow control generated by twisting fibers allows for woven nets that can be "programmed" with junctions that predetermine drop interactions and can be anticlogging. Furthermore, it is shown that twisted fiber structures are significantly more effective at capturing atmospheric fog compared to straight fibers.

Elucidating the roles of electrolytes and hydrogen bonding in the dewetting dynamics of the tear film.

This study explores the impact of electrostatic interactions and hydrogen bonding on tear film stability, a crucial factor for ocular surface health. While mucosal and meibomian layers have been extensively studied, the role of electrolytes in the aqueous phase remains unclear. Dry eye syndrome, characterized by insufficient tear quantity or quality, is associated with hyperosmolality, making electrolyte composition an important factor that might impact tear stability. Using a model buffer solution on a silica glass dome, we simulated physiologically relevant tear film conditions. Sodium chloride alone induced premature dewetting through salt crystal nucleation. In contrast, trace amounts of solutes with hydroxyl groups (sodium phosphate dibasic, potassium phosphate monobasic, and glucose) exhibited intriguing phenomena: quasi-stable films, solutal Marangoni-driven fluid influx increasing film thickness, and viscous fingering due to Saffman-Taylor instability. These observations are rationalized by the association of salt solutions with increased surface tension and the propensity of hydroxyl-group-containing solutes to engage in significant hydrogen bonding, altering local viscosity. This creates a viscosity contrast between the bulk buffer solution and the film region. Moreover, these solutes shield the glass dome, counteracting sodium chloride crystallization. These insights not only advance our understanding of tear film mechanics but also pave the way for predictive diagnostics in dry eye syndrome, offering a robust platform for personalized medical interventions based on individual tear film composition.

The Role of Fluid Mechanics in Coronary Atherosclerotic Plaques: An Up-to-Date Review.

Most acute coronary syndromes are due to a sudden luminal embolism caused by the rupturing or erosion of atherosclerotic plaques. Prevention and treatment of plaque development have become an effective strategy to reduce mortality and morbidity from coronary heart disease. It is now generally accepted that plaques with thin-cap fibroatheroma (TCFA) are precursors to rupturing and that larger plaques and high-risk plaque features (including low-attenuation plaque, positive remodeling, napkin-ring sign, and spotty calcification) constitute unstable plaque morphologies. However, plaque vulnerability or rupturing is a complex evolutionary process caused by a combination of multiple factors. Using a combination of medicine, engineering mechanics, and computer software, researchers have turned their attention to computational fluid mechanics. The importance of fluid mechanics in pathological states for promoting plaque progression, inducing plaque tendency to vulnerability, or even rupture, as well as the high value of functional evaluation of myocardial ischemia has become a new area of research. This article reviews recent research advances in coronary plaque fluid mechanics, aiming to describe the concept, research implications, current status of clinical studies, and limitations of fluid mechanic's characteristic parameters: wall shear stress (WSS), axial plaque shear (APS), and fractional flow reserve (FFR). Previously, most computational fluid dynamics were obtained using invasive methods, such as intravascular ultrasound (IVUS) or optical coherence tomography (OCT). In recent years, the image quality and spatial resolution of coronary computed tomography angiography (CCTA) have greatly improved, making it possible to compute fluid dynamics by noninvasive methods. In the future, the combination of CCTA-based anatomical stenosis, plaque high-risk features, and fluid mechanics can further improve the prediction of plaque development, vulnerability, and risk of rupturing, as well as enabling noninvasive means to assess the degree of myocardial ischemia, thereby providing an important aid to guide clinical decision-making and optimize treatment.

Flow modeling and structural characterization in fungal pellets.

Fungal pellets are hierarchical systems that can be found in an ample variety of applications. Modeling transport phenomena in this type of systems is a challenging but necessary task to provide knowledge-based processes that improve the outcome of their biotechnological applications. In this work, an upscaled model for total mass and momentum transport in fungal pellets is implemented and analyzed, using elements of the volume averaging and adjoint homogenization methods departing from the governing equations at the microscale in the intracellular and extracellular phases. The biomass is assumed to be composed of a non-Newtonian fluid and the organelles impervious to momentum transport are modeled as a rigid solid phase. The upscaled equations contain effective-medium coefficients, which are predicted from the solution of adjoint closure problems in a three-dimensional periodic domains representative of the microstructure. The construction of these domains was performed for Laccaria trichodermophora based on observations of actual biological structures. The upscaled model was validated with direct numerical simulations in homogeneous portions of the pellets core. It is shown that no significant differences are observed when the dolipores are open or closed to fluid flow. By comparing the predictions of the average velocity in the extracellular phase resulting from the upscaled model with those from the classical Darcy equation (i.e., assuming that the biomass is a solid phase) the contribution of the intracellular fluid phase was evidenced. This work sets the foundations for further studies dedicated to transport phenomena in this type of systems.

Micro-Scale Particle Tracking: From Conventional to Data-Driven Methods.

Micro-scale positioning techniques have become essential in numerous engineering systems. In the field of fluid mechanics, particle tracking velocimetry (PTV) stands out as a key method for tracking individual particles and reconstructing flow fields. Here, we present an overview of the micro-scale particle tracking methodologies that are predominantly employed for particle detection and flow field reconstruction. It covers various methods, including conventional and data-driven techniques. The advanced techniques, which combine developments in microscopy, photography, image processing, computer vision, and artificial intelligence, are making significant strides and will greatly benefit a wide range of scientific and engineering fields.

A finite element analysis of periodontal ligament fluid mechanics response to occlusal loading based on hydro-mechanical coupling model.

OBJECTIVE: Considering fluid stimulation is one of the essential biomechanical signals for periodontal tissues, this study aims to characterizing fluid mechanics response during occlusal loading by a hydro-mechanical coupling model for periodontal ligament. DESIGN: Models simulating periodontium with normal bone height and with intraosseous defects were built with three mechanical modules: tooth, periodontal ligament and alveolar bone. Tooth was modeled as linear elastic, and periodontal ligament and alveolar bone as a hydro-mechanical coupling model. Transient analyses under dynamic occlusal loading were performed. Fluid dynamics within periodontal ligament space was simulated and visualized by post-processing module. RESULTS: Reciprocating oscillatory flow occurred within the periodontal ligament under occlusal loading. Higher pore pressure and fluid velocity were observed in furcation and apical regions compared to mid-root and cervical regions. Intraosseous defects increased pore pressure and fluid velocity within the periodontal ligament, most significantly near the defect. CONCLUSION: Based on the results of the hydro-mechanical coupling model, significant oscillatory fluid motion is observed within the periodontal ligament under occlusal loading. Particularly, higher fluid velocity is evident in the furcation and apical areas. Additionally, Intraosseous defects significantly enhance fluid motion within the periodontal ligament.

Applying the Kolmogorov-Zurbenko filter followed by random forest models to 7Be observations in Spain (2006-2021).

In this study, we analysed 7Be weekly surface measurements from six Spanish laboratories from 2006 to 2021. The Kolmogorov-Zurbenko filter was applied to the six 7Be time series, and following an iterative process, the original data were divided into two fractions: one related to variations characterized by periods above 33 days (including, among others, the seasonal cycle) and the second noisier fraction related to mechanisms originating from variations with periods below 33 days. Both fractions were independent at the six locations. The second machine-based step using random forest models was applied with the aim of identifying the most influential inputs to the observed 7Be concentrations, and machine learning-inspired regression models were fitted. With respect to seasonal components, the results indicated that the memory of the system was the most influential input, as expected by the large fraction of variance explained by the seasonal cycle, followed by that of humidity and wind-related variables. For the fraction corresponding to periods below 33 d, precipitation-, humidity-, and radiation-related variables were the most influential. This methodology has made it possible to successfully describe the major mechanisms known to be involved in the generation of the surface 7Be concentrations observed in Spain.

Predicting buoyant jet characteristics: a machine learning approach.

We study positively buoyant miscible jets through high-speed imaging and planar laser-induced fluorescence methods, and we rely on supervised machine learning techniques to predict jet characteristics. These include, in particular, predictions to the laminar length and spread angle, over a wide range of Reynolds and Archimedes numbers. To make these predictions, we use linear regression, support vector regression, random forests, K-nearest neighbour, and artificial neural network algorithms. We evaluate the performance of the aforementioned models using various standard metrics, finding that the random forest algorithm is the best for predicting our jet characteristics. We also discover that this algorithm outperforms a recent empirical correlation, resulting in a significant increase in accuracy, especially for predicting the laminar length.

A two-phase thin-film model for cell-induced gel contraction incorporating osmotic effects.

We present a mathematical model of an experiment in which cells are cultured within a gel, which in turn floats freely within a liquid nutrient medium. Traction forces exerted by the cells on the gel cause it to contract over time, giving a measure of the strength of these forces. Building upon our previous work (Reoch et al. in J Math Biol 84(5):31, 2022), we exploit the fact that the gels used frequently have a thin geometry to obtain a reduced model for the behaviour of a thin, two-dimensional cell-seeded gel. We find that steady-state solutions of the reduced model require the cell density and volume fraction of polymer in the gel to be spatially uniform, while the gel height may vary spatially. If we further assume that all three of these variables are initially spatially uniform, this continues for all time and the thin film model can be further reduced to solving a single, non-linear ODE for gel height as a function of time. The thin film model is further investigated for both spatially-uniform and varying initial conditions, using a combination of analytical techniques and numerical simulations. We show that a number of qualitatively different behaviours are possible, depending on the composition of the gel (i.e., the chemical potentials) and the strength of the cell traction forces. However, unlike in the earlier one-dimensional model, we do not observe cases where the gel oscillates between swelling and contraction. For the case of initially uniform cell and gel density, our model predicts that the relative change in the gels' height and length are equal, which justifies an assumption previously used in the work of Stevenson et al. (Biophys J 99(1):19-28, 2010). Conversely, however, even for non-uniform initial conditions, we do not observe cases where the length of the gel changes whilst its height remains constant, which have been reported in another model of osmotic swelling by Trinschek et al. (AIMS Mater Sci 3(3):1138-1159, 2016; Phys Rev Lett 119:078003, 2017).

Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantom.

Purpose: Validation of quantitative imaging biomarkers is a challenging task, due to the difficulty in measuring the ground truth of the target biological process. A digital phantom-based framework is established to systematically validate the quantitative characterization of tumor-associated vascular morphology and hemodynamics based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Approach: A digital phantom is employed to provide a ground-truth vascular system within which 45 synthetic tumors are simulated. Morphological analysis is performed on high-spatial resolution DCE-MRI data (spatial/temporal resolution = 30 to 300 µm/60 s) to determine the accuracy of locating the arterial inputs of tumor-associated vessels (TAVs). Hemodynamic analysis is then performed on the combination of high-spatial resolution and high-temporal resolution (spatial/temporal resolution = 60 to 300 µm/1 to 10 s) DCE-MRI data, determining the accuracy of estimating tumor-associated blood pressure, vascular extraction rate, interstitial pressure, and interstitial flow velocity. Results: The observed effects of acquisition settings demonstrate that, when optimizing the DCE-MRI protocol for the morphological analysis, increasing the spatial resolution is helpful but not necessary, as the location and arterial input of TAVs can be recovered with high accuracy even with the lowest investigated spatial resolution. When optimizing the DCE-MRI protocol for hemodynamic analysis, increasing the spatial resolution of the images used for vessel segmentation is essential, and the spatial and temporal resolutions of the images used for the kinetic parameter fitting require simultaneous optimization. Conclusion: An in silico validation framework was generated to systematically quantify the effects of image acquisition settings on the ability to accurately estimate tumor-associated characteristics.

Functional bio-inspired hybrid fliers with separated ring and leading edge vortices.

Recent advances in passive flying systems inspired by wind-dispersed seeds contribute to increasing interest in their use for remote sensing applications across large spatial domains in the Lagrangian frame of reference. These concepts create possibilities for developing and studying structures with performance characteristics and operating mechanisms that lie beyond those found in nature. Here, we demonstrate a hybrid flier system, fabricated through a process of controlled buckling, to yield unusual geometries optimized for flight. Specifically, these constructs simultaneously exploit distinct fluid phenomena, including separated vortex rings from features that resemble those of dandelion seeds and the leading-edge vortices derived from behaviors of maple seeds. Advanced experimental measurements and computational simulations of the aerodynamics and induced flow physics of these hybrid fliers establish a concise, scalable analytical framework for understanding their flight mechanisms. Demonstrations with functional payloads in various forms, including bioresorbable, colorimetric, gas-sensing, and light-emitting platforms, illustrate examples with diverse capabilities in sensing and tracking.

Immiscible Rayleigh-Taylor turbulence: Implications for bacterial degradation in oil spills.

An unstable density stratification between two fluids mixes spontaneously under the effect of gravity, a phenomenon known as Rayleigh-Taylor (RT) turbulence. If the two fluids are immiscible, for example, oil and water, surface tension prevents intermixing at the molecular level. However, turbulence fragments one fluid into the other, generating an emulsion in which the typical droplet size decreases over time as a result of the competition between the rising kinetic energy and the surface energy density. Even though the first phenomenological theory describing this emulsification process was derived many years ago, it has remained elusive to experimental verification, hampering our ability to predict the fate of oil in applications such as deep-water spills. Here, we provide the first experimental and numerical verification of the immiscible RT turbulence theory, unveiling a unique turbulent state that originates at the oil-water interface due to the interaction of multiple capillary waves. We show that a single, non-dimensional, and time-independent parameter controls the range of validity of the theory. Our findings have wide-ranging implications for the understanding of the mixing of immiscible fluids. This includes in particular oil spills, where our work enables the prediction of the oil-water interface dynamics that ultimately determine the rate of oil biodegradation by marine bacteria.