Images Of Droplets Research Articles

65 kHz picosecond digital off-axis holographic imaging of 3D droplet trajectory in a kerosene swirl spray flame

It is difficult to track fuel droplets in a swirl spray combustion field due to three-dimensional (3D) movement and turbulent flame influence. The present work carries out an experimental study to investigate and track the dispersed kerosene droplets in a swirl spray combustion field. RP-3 kerosene and air are mixed and burned in open space under different mixture ratios. Pulsed high-speed (65 kHz) digital off-axis holography with an equivalent pixel size of 9.3 μm is adopted to visualize and quantify the droplet size, 3D position and velocity. The measurement uncertainty of the technique is calibrated and discussed. The turbulent flame of hydrocarbon fuel causes some darker speckles in the morphology view, but droplet images are clear and the initial droplet size distribution at 1 mm downstream of the swirler is obtained. A particle tracking algorithm considering x, y and z with different locating errors and droplet diameter is proposed and applied to obtain droplet trajectory. Smoothed droplet trajectories are obtained through multi-frame tracking and trajectory regressing methods. From the perspective of the Lagrangian view, droplet momentum and size oscillation are also observed and discussed.

Effect of interfacial activity of quaternary ammonium cation on kinetics of epoxidation of allyl chloride with hydrogen peroxide

A series of quaternary ammonium phosphotungstic heteropoly acid catalysts with different carbon chain lengths [(CnH2n+1)2(CH3)2N]3{PO4[W(O)(O2)2]4} (n = 8, 10, 12, 14, 16) were synthesized for the epoxidation of allyl chloride with H2O2. The hydrophilic and hydrophobic structure of the catalysts were regulated to optimize the interfacial activity by changing the carbon chain lengths of the quaternary ammonium cations. The reaction system using catalyst [(C10H21)2(CH3)2N]3{PO4[W(O)(O2)2]4} showed the lowest interfacial tension between oil and water, the smallest particle size of emulsion droplets and the largest interfacial area, which resulted in the highest catalytic performance. The reaction kinetics and interface properties studies, including the activation energy, interfacial tension, and microscopic imaging of droplets, were conducted to provide strong proof. The epoxidation reaction rates were significantly associated with the surface activity of different carbon chain length catalysts and their effects on the allyl chloride-H2O2 interfacial properties.

In Situ Characterization of Carbonate/Oil/Water Interfacial Layers Using Advanced EM Techniques for Enhanced Oil Recovery

The visualization and characterization of the interactions between injection brine, oil, and carbonate rock play a major role in understanding the causative mechanisms behind wettability alteration and enhanced oil recovery. However, conventional imaging methods fail to provide such important analysis due to limited resolution and visualization capabilities. To address this gap, a cryogenic electron microscope (EM) and liquid-cell holder have been utilized in this study. The results from each of these techniques are discussed and compared. The liquid-cell transmission electron microscope (TEM) holder with an encapsulation function feature successfully enabled the direct observation and analysis of the liquid sample close to its native conditions. Energy-dispersive spectroscopy (EDS) analyses have been simultaneously utilized to provide the chemical mapping of the rock–fluid interfaces. These results provide, for the first time, nanoscale images of oil droplets, calcite nanoparticles, and dissolved salt ions in their native environment. The compositional distribution of multiple elements and elemental mapping of the structures in solution are also presented. The presented novel nanoscale characterization provides a new insight into the rock–oil–brine interactions, and this understanding can be critical to optimize the salinity and injection water compositions used for enhanced oil recovery in carbonate reservoirs.

A near-infrared AIE probe and its applications for specific in vitro and in vivo two-photon imaging of lipid droplets

A near-infrared AIE probe and its applications for specific in vitro and in vivo two-photon imaging of lipid droplets

Structure Rigidification Promoted Ultrabright Solvatochromic Fluorescent Probes for Super-Resolution Imaging of Cytosolic and Nuclear Lipid Droplets.

Lipid droplets (LDs) containing cytosolic and nuclear LDs have recently received increasing attention because of their diverse biological roles in living systems. However, developing fluorescent probes for super-resolution visualization of these subcellular LDs still remains challenging due to insufficient fluorescence brightness and poor nuclear membrane permeability. Herein, we rationally synthesized a series of ultrabright solvatochromic fluorescent probes based on benzoboranils (BBAs) for LD-specific super-resolution imaging using structured illumination microscopy (SIM). The rigidly structured probes exhibit ultrahigh fluorescence quantum yields of up to 99.9% in low-polar solvents. They also show more significant fluorescence enhancements in lipid environments than commercial LD probes. Owing to these excellent merits, our lipophilic fluorescent probes can specifically light up subcellular LDs at ultralow concentrations down to 10 nM. Further use of BBA-CF3 for super-resolution SIM imaging of cytosolic and nuclear LDs and their fusion process was successfully achieved. The unprecedented spatial resolution for nuclear LDs with an FWHM value of 142 nm was also acquired. Collectively, our ultrabright fluorescent probes hold tremendous potential to unveil the mysterious roles of cytosolic and nuclear LDs in biological research using SIM.

Effect of Image Segmentation Thresholding on Droplet Size Measurement

Droplet size spectrum is a key factor in pesticide application because it affects the biological efficacy of a treatment in terms of target coverage, environmental impact in terms of evaporation, drift and run-off, and operator’s safety in terms of inhalation and dermal exposure. Droplet measurement methods based upon image analysis have to face the “binarization” or “segmentation” process, by which the objects of interest (the droplets) are extracted from the background. Segmentation is carried out by choosing appropriate threshold values, mostly based on the operator’s experience. In this study, images of droplets of an air induction nozzle TVI 8002 at four pressures (0.3, 0.5, 1.0, and 1.5 MPa) were obtained using the liquid immersion method. Each image was processed multiple times, firstly by using a “reference” threshold value based on the operator’s experience and then by using 11 different threshold values, chosen in the range of around ±5% of the reference threshold and based upon the average gray level of the image. For each threshold value, the corresponding spray parameters (volumetric diameters, mean diameters, Sauter diameters, and numeric diameters) were analyzed. The results showed that spray parameters had a statistically significant linear trend with respect to the threshold values in most cases. However, in absolute terms, variations were almost always less than 1.0% of reference values. This result allows considering the image acquisition system used in the present study as an automatic tool able to select the threshold according to the gray level of the image, making the whole segmentation process faster, more objective, and less dependent on the operator’s experience.

Yellow-Emitting Carbon Dots for Selective Fluorescence Imaging of Lipid Droplets in Living Cells.

This study shows a one-pot preparation of carbon dots by a solvothermal method in ethylene glycol. The carbon dots show yellow-colored fluorescence emission in water. The carbon dots showed distinct preference to be present in the hydrophobic environment which was evident from their efficient transfer from aqueous phase to organic phase. They were also found to locate themselves in the vesicle bilayer and micelle core. This inherent lipophilic character of these carbon dots has been successfully utilized for the selective imaging of lipid droplets inside the living cells. The selective imaging of lipid droplets was confirmed by similar staining patterns with other staining dyes and the starvation study.

An Edge Detection Method Based on Local Gradient Estimation: Application to High-Temperature Metallic Droplet Images

Edge detection is a fundamental step in many computer vision systems, particularly in image segmentation and feature detection. There are a lot of algorithms for detecting edges of objects in images. This paper proposes a method based on local gradient estimation to detect metallic droplet image edges and compare the results to a contour line obtained from the active contour model of the same images, and to results from crowdsourcing to identify droplet edges at specific points. The studied images were taken at high temperatures, which makes the segmentation process particularly difficult. The comparison between the three methods shows that the proposed method is more accurate than the active contour method, especially at the point of contact between the droplet and the base. It is also shown that the reliability of the data from the crowdsourcing is as good as the edge points obtained from the local gradient estimation method.

Three-dimensional measurement of the droplets out of focus in shadowgraphy systems via deep learning-based image-processing method

For the shadowgraphy techniques with a single camera, it is difficult to accurately obtain the shape, size, and depth location of the droplets out of focus due to the defocus blur. This paper proposed a deep learning-based method to recover the sharp images and infer the depth information from the defocused blur droplets images. The proposed model comprising of a defocus map estimation subnetwork and a defocus deblur subnetwork is optimized with a two-stage strategy. To train the networks, the synthetic blur data generated by the Gauss kernel method are utilized as the input data, which mimic the defocused images of droplets. The proposed approach has been assessed based on synthetic images and real sphere blur images. The results demonstrate that our method has satisfactory performance both in terms of depth location estimation and droplet size measurement, e.g., the diameter relative error is less than 5% and the location error is less than 1 mm for the sphere with a diameter of more than 1 mm. Moreover, the present model also exhibits considerable generalization and robustness against the transparent ellipsoid and the random background noise. A further application of the present model to the measurement of transparent water droplets generated by an injector is also explored and illustrates the practicability of the present model in real experiments. The present study indicates that the proposed learning-based method is promising for the three-dimensional (3D) measurement of spray droplets via a combination of shadowgraphy techniques using a single camera, which will greatly reduce experimental costs and complexity.

GÖRÜNTÜ İŞLEME YÖNTEMİ İLE SİNÜZOİDAL ATALET KUVVETLERİ ALTINDA BENZİN ATOMİZASYON KALİTESİNİN BELİRLENMESİ

The atomization quality has gained importance with the used of injection systems in internal combustion engines. The atomization quality has been increased by raising spray pressures by the way advances in the production technologies of high-pressure pumps and injectors. In the current situation, the spray pressures in Gasoline Direct Injection (GDI) technology have been reached bar levels between 200 and 800. When the pressure level is raised higher than the specified pressure value, it is understood from studies in the literature that the atomization quality is not provided a significant improvement and the production cost increase due to the technology required for high pressure. In this paper, the fuel has been atomized by using Sinusoidal Intertidal Forces (SIF) as another method to improve the atomization quality. In the literature, there is no any study regarding the suitability of using by atomized under SIF of the gasoline fuel used in internal combustion engines. In the application study, the gasoline fuel has been atomized without the pressure by manufactured SIF generator and the droplet images obtained analysis result has been examined by using the image processing method. According to analysis results, it has been observed that the droplets sizes produced with SIF method were similar results to the droplet sizes founded using the GDI method. It has been determined that the smaller droplet sizes can be obtained with lower costs without using pressure thanks to this method and the method can be applied efficiently in internal combustion engines.

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size, velocity, and shape. These droplet characteristics, in turn, determine the functional quality of the printed parts. Hence, to ensure repeatable and reliable part quality it is necessary to monitor and control the droplet characteristics. Existing approaches for in-situ monitoring of droplet behavior in DoD-LMJ rely on high-speed imaging sensors. The resulting high volume of droplet images acquired is computationally demanding to analyze and hinders real-time control of the process. To overcome this challenge, the objective of this work is to use time series data acquired from an in-process millimeter-wave sensor for predicting the size, velocity, and shape characteristics of droplets in DoD-LMJ process. As opposed to high-speed imaging, this sensor produces data-efficient time series signatures that allows rapid, real-time process monitoring. We devise machine learning models that use the millimeter-wave sensor data to predict the droplet characteristics. Specifically, we developed multilayer perceptron-based non-linear autoregressive models to predict the size and velocity of droplets. Likewise, a supervised machine learning model was trained to classify the droplet shape using the frequency spectrum information contained in the millimeter-wave sensor signatures. High-speed imaging data served as ground truth for model training and validation. These models captured the droplet characteristics with a statistical fidelity exceeding 90%, and vastly outperformed conventional statistical modeling approaches. Thus, this work achieves a practically viable sensing approach for real-time quality monitoring of the DoD-LMJ process, in lieu of the existing data-intensive image-based techniques.

Highly lipophilic coumarin fluorophore with excimer-monomer transition property for lipid droplet imaging

Lipid droplet (LD) fluorescent imaging plays an important role in the detection of lipid-related diseases. Due to their poor photostability and low hydrophobicity of currently available LD imaging fluorophores, LD imaging is limited by its short imaging period and low imaging contrast. Herein, we reasonably designed a highly lipophilic compound Cou-Flu with excellent photostability and excimer-monomer transition property. It exhibited weak excimer emission in cytoplasm, but strong monomer emission in LDs, enabling high contrast LD imaging and LD movement tracing in cells. Zebrafish imaging study demonstrated that Cou-Flu was also suitable for in vivo LD detection with excellent sensitivity. We anticipate that Cou-Flu could be widely applied to understand LD-related intracellular activities and even LD-related diseases in the future.

Low-cost, open-source contact angle analyzer using a mobile phone, commercial tripods and 3D printed parts

Measurement of contact angle is important in many areas of science and engineering research. Contact angle analyzers are however not easily accessible due to their expensive cost, which hinders their use in research and also in education. In this study we propose a low-cost contact angle analyzer that can be assembled with 3D printed parts. Mobile phone is used for imaging, and the image is analyzed using an open-source ImageJ plugin. Commercial camera tripods are used as platform that provides movement in many degrees of freedom, which are important in leveling of the substrate and proper imaging of droplets. We utilize the tripods to build imaging modules, sample plate module and volume metering module, each of which perform distinct tasks. Especially, we characterize the usefulness of the volume metering module, which helps users dispense same volume of liquid to reduce human error during measurement. The cost of an analyzer is $255.10, which is an order of magnitude lower compared to commercial products. With the advancement in open source software and upgrades in the hardware modules, we expect that the proposed contact angle analyzer to have a positive impact in resource limited research labs and educational environments.

Label-Free Imaging of Lipid Droplets in Prostate Cells Using Stimulated Raman Scattering Microscopy and Multivariate Analysis.

Hyperspectral stimulated Raman scattering (SRS) microscopy is a powerful imaging modality for the analysis of biological systems. Here, we report the application of k-means cluster analysis (KMCA) of multi-wavelength SRS images in the high-wavenumber region of the Raman spectrum as a robust and reliable method for the segmentation of cellular organelles based on the intrinsic SRS spectrum. KMCA has been applied to the study of the endogenous lipid biochemistry of prostate cancer and prostate healthy cell models, while the corresponding SRS spectrum of the lipid droplet (LD) cluster enabled direct comparison of their composition. The application of KMCA in visualizing the LD content of prostate cell models following the inhibition of de novo lipid synthesis (DNL) using the acetyl-coA carboxylase inhibitor, 5-(tetradecyloxy)-2-furoic acid (TOFA), is demonstrated. This method identified a reliance of prostate cancer cell models upon DNL for metabolic requirements, with a significant reduction in the cellular LD content after treatment with TOFA, which was not observed in normal prostate cell models. SRS imaging combined with KMCA is a robust method for investigating drug–cell interactions in a label-free manner.

The assessment of average cell number inside in-flight 3D printed droplets in microvalve-based bioprinting

3D cell bioprinting is an innovative and time-saving additive manufacturing technology; it precisely generates complex cell-laden constructs to overcome the limitations of 2D cell culture and conventional tissue engineering scaffold technology. Many efforts have been made to evaluate the bioprinter performance by considering printed cell number and the consistency of printed cell number. In this paper, a modified droplet imaging system is used to study the printing performance for a micro-valve-based 3D bioprinter using fluorescence MCF-7 cells. The effects of droplet dispensing physics (dosing energy Ed), ink properties (Z number—the inverse of the Ohnesorge number and particle sedimentation velocity), and input cell concentration are considered. The droplet imaging system demonstrates a strong capability and accuracy in analyzing bioprinting performance for printed cell density less than 300 cells/droplet. The average printed cell number is positively correlated with the increasing input cell concentration, dosing energy, and printing time. Printing ink, with Z number ranging from 4 to 7.41 and cell sedimentation velocity at 9.45×10−8 m/s, can provide the estimated printed cell number and consistent cell printing results within 2 min printing time. Printing inks with higher Z number or cell sedimentation velocity should be ejected under dosing energy below 2.1 La and printed right after filling the reservoir to achieve reliable and stable printing results.

Specific lipid droplet imaging of atherosclerotic plaques and fatty liver using an imidazole-based fluorescence probe

Selective labelling and high-fidelity tracking of intracellular lipid droplets (LDs) can provide direct insight into pathological processes associated with abnormal lipid metabolism and therefore are of great value. We herein present a novel imidazole-based probe, TITM, which shows the aggregation-induced emission property and a remarkable fluorescence increase in sunflower oil than in water. With the advantages of good lipophilicity, biocompatibility, and LDs-targeted specificity, TITM allows the real-time and long-term tracking of dynamic LDs in living cells with high-resolution imaging performance. By establishment of LDs-related atherosclerosis (AS) and fatty liver mouse model, the imaging performance of TITM at pathological tissue level is well studied to show impressive selectivity and resolution.

Beyond Fresnel’s approximation: Luneburg’s kernel to simulate the interferometric images of droplets or irregular rough particles

Interferometric particle imaging is generally interpreted in the framework of Fresnel conditions. We develop here a new formalism based on Luneburg’s kernel. It enables to predict the interferometric images of droplets or rough particles when Fresnel conditions are not respected. It is compared to previous experimental results, and then used to understand possible sources of noise when analyzing interferometric particle images.

Droplet deposition characteristics detection method based on deep learning

Accurate acquisition of spraying quality parameters of plant protection Unmanned Aerial Vehicle (UAV) is helpful to analyze the deposition and distribution of pesticides in field crops. It is of great significance for pest control. UAV spray quality detection system was used to collect droplets, the droplet deposition parameters can be detected by processing the droplet images. However, the spots and the adhesion of the droplets led to large data errors. In order to solve this problem, this paper developed a recognition method of adhesive droplets based on Deeplab V3 + deep learning network, and a concave point matching segmentation algorithm based on convolutional neural network was designed to segment adhesion droplets. Used water instead of pesticides to spray to verify the detection effect of the above method. The test results showed that this method was accurate in the identification and extraction of droplets in the detection of droplet coverage. Compared with the droplet coverage measured by Deposit scan, the average relative error is 3.81%. Compared with the manual counting method, the detection error of the droplet deposition density was 3.17%. It was better for the segmentation of adhesion droplets. In terms of droplet size detection, compared with volume middle diameter measured by laser particle sizer, the detection error was 5.48%. This method improves the accuracy of UAV spray quality detection, so as to ensure the correctness of plant protection UAV spraying decisions.

Polarization-dependent LIF/Mie ratio for sizing of micrometric ethanol droplets doped with Nile red.

The present study deals with droplet sizing based on laser-induced fluorescence (LIF) and Mie scattering for varied polarization of the utilized laser (parallel or perpendicular). The polarization-dependent LIF/Mie ratio is studied for micrometric droplets (25-60 µm) produced with a droplet generator. The investigations were carried out with the dye Nile red dissolved in ethanol and ethanol/iso-octane mixtures. A spectral absorption and fluorescence characterization at various dye and ethanol concentrations is carried out in a cuvette in order to identify reabsorption effects. The LIF|| droplet images (index ||: parallel polarization) show a more homogeneous intensity distribution in the droplets and slightly stronger morphology-dependent resonances (MDRs) in comparison to LIF⊥ (index ⊥: perpendicular polarization). The spectral LIF emissions reveal a dependence of the MDR on the ethanol admixture. The larger the ethanol content, the lower the MDR peak, which is also shifted further to the red part of the spectrum. The Mie droplet signal images are mainly characterized by two distinct glare points, one at the entrance of the laser light (reflection) and one at the exit (first-order refraction). The Mie⊥ images show a more pronounced entrance glare point, in comparison to Mie||, where the exit glare point is more pronounced. These observations are in accordance with the theory. The calibration curve of the micro droplet signals revealed a volumetric trend of the LIF signals and a slightly higher LIF⊥ signal and sensitivity in comparison to LIF||. The signal Mie⊥ follows roughly a quadratic trend on average, while Mie|| follows a linear trend. Consequently, the calculated LIF⊥/Mie⊥ ratio shows a linear trend, whereas the LIF||/Mie|| ratio shows a quadratic trend, which confirms theoretical calculations. A numerical simulation of the Mie signal at various detection angles shows a good agreement with the experimental data at large apertures.

Lipophilic neutral iridium(III) complexes for phosphorescence imaging of lipid droplets and potential photodynamic therapy

Compared with the recently reported large number of fluorescent lipid droplet (LD) probes based on organic fluorophores, phosphorescent LD probes based on transition metal complexes are much less reported. In addition, LDs are rarely studied as targets for photodynamic therapy (PDT). In this work, two lipophilic neutral iridium(III) complexes, namely [Ir(bt)2(hpd)] (denoted as LDIr1) and [Ir(piq)2(hpd)] (denoted as LDIr2) (where Hbt = 2-phenylbenzothiazole, Hpiq = 1-penylisoquinoline, Hhpd = 3,5-heptanedione), have been synthesized and characterized. These complexes exhibit long-lived orange to red phosphorescence emission and large Stokes shifts (ca. 160 nm). They can specifically stain LDs in living A549 and HepG2 cells, showing excellent biocompatibility and favourable photostability. Complex LDIr1 has been successfully applied for monitoring of oleic acid-induced LDs accumulation in living A549 cells and in vivo imaging of larval zebrafish. Moreover, these two iridium(III) complexes can efficiently generate singlet oxygen upon visible light (425 nm) irradiation to kill cancer cells effectively by means of PDT. They display impressive high phototoxicity index (PI) values of 1087 and 263 for complexes LDIr1 and LDIr2, respectively. This study provides useful insights into rational design of new metal complex-based LD-targeted phosphorescent probes and PDT agents.