Computer vision-assisted investigation of boiling heat transfer on segmented nanowires with vertical wettability.

The boiling efficacy is intrinsically tethered to trade-offs between the desire for bubble nucleation and necessity of vapor removal. The solution to these competing demands requires the separation of bubble activity and liquid delivery, often achieved through surface engineering. In this study, we independently engineer bubble nucleation and departure mechanisms through the design of heterogeneous and segmented nanowires with dual wettability with the aim of pushing the limit of structure-enhanced boiling heat transfer performances. The demonstration of separating liquid and vapor pathways outperforms state-of-the-art hierarchical nanowires, in particular, at low heat flux regimes while maintaining equal performances at high heat fluxes. A deep-learning based computer vision framework realized the autonomous curation and extraction of hidden big data along with digitalized bubbles. The combined efforts of materials design, deep learning techniques, and data-driven approach shed light on the mechanistic relationship between vapor/liquid pathways, bubble statistics, and phase change performance.

A Deep Learning Perspective on Dropwise Condensation.

Condensation is ubiquitous in nature and industry. Heterogeneous condensation on surfaces is typified by the continuous cycle of droplet nucleation, growth, and departure. Central to the mechanistic understanding of the thermofluidic processes governing condensation is the rapid and high-fidelity extraction of interpretable physical descriptors from the highly transient droplet population. However, extracting quantifiable measures out of dynamic objects with conventional imaging technologies poses a challenge to researchers. Here, an intelligent vision-based framework is demonstrated that unites classical thermofluidic imaging techniques with deep learning to fundamentally address this challenge. The deep learning framework can autonomously harness physical descriptors and quantify thermal performance at extreme spatio-temporal resolutions of 300 nm and 200 ms, respectively. The data-centric analysis conclusively shows that contrary to classical understanding, the overall condensation performance is governed by a key tradeoff between heat transfer rate per individual droplet and droplet population density. The vision-based approach presents a powerful tool for the study of not only phase-change processes but also any nucleation-based process within and beyond the thermal science community through the harnessing of big data.

Deep learning predicts boiling heat transfer.

Boiling is arguably Nature's most effective thermal management mechanism that cools submersed matter through bubble-induced advective transport. Central to the boiling process is the development of bubbles. Connecting boiling physics with bubble dynamics is an important, yet daunting challenge because of the intrinsically complex and high dimensional of bubble dynamics. Here, we introduce a data-driven learning framework that correlates high-quality imaging on dynamic bubbles with associated boiling curves. The framework leverages cutting-edge deep learning models including convolutional neural networks and object detection algorithms to automatically extract both hierarchical and physics-based features. By training on these features, our model learns physical boiling laws that statistically describe the manner in which bubbles nucleate, coalesce, and depart under boiling conditions, enabling in situ boiling curve prediction with a mean error of 6%. Our framework offers an automated, learning-based, alternative to conventional boiling heat transfer metrology.

In situ investigation of particle clustering dynamics in colloidal assemblies using fluorescence microscopy.

Colloidal self-assembly is a process in which dispersed matter spontaneously form higher-order structures without external intervention. During self-assembly, packed particles are subject to solvent-evaporation induced dynamic structuring phases, which leads to microscale defects called the grain boundaries. While it is imperative to precisely control detailed grain boundaries to fabricate well-defined self-assembled crystals, the understanding of the colloidal physics that govern grain boundaries remains a challenge due to limited resolutions of current visualization approaches. In this work, we experimentally report in situ particle clustering dynamics during evaporative colloidal assembly by studying a novel microscale laser induced fluorescence technique. The fluorescence microscopy measures the saturation levels with high fidelity to identify distinct colloidal structuring regimes during self-assembly as well as cracking mechanics. The techniques discussed in this work not only enables unprecedented levels of colloidal self-assembly analysis but also have potential to be used for various sensing applications with microscopic resolutions.

The Control of Colloidal Grain Boundaries through Evaporative Vertical Self-Assembly.

Self-assembly continuously gains attention as an excellent method to create novel nanoscale structures with a wide range of applications in photonics, optoelectronics, biomedical engineering, and heat transfer applications. However, self-assembly is governed by a diversity of complex interparticle forces that cause fabricating defectless large scale (>1 cm) colloidal crystals, or opals, to be a daunting challenge. Despite numerous efforts to find an optimal method that offers the perfect colloidal crystal by minimizing defects, it has been difficult to provide physical interpretations that govern the development of defects such as grain boundaries. This study reports the control over grain domains and intentional defect characteristics that develop during evaporative vertical deposition. The degree of particle crystallinity and evaporation conditions is shown to govern the grain domain characteristics, such as shapes and sizes. In particular, the grains fabricated with 300 and 600 nm sphere diameters can be tuned into single-column structures exceeding ≈1 mm by elevating heating temperature up to 93 °C. The understanding of self-assembly physics presented in this work will enable the fabrication of novel self-assembled structures with high periodicity and offer fundamental groundworks for developing large-scale crack-free structures.

Capillary Wicking in Hierarchically Textured Copper Nanowire Arrays.

Capillary wicking through homogeneous porous media remains challenging to simultaneously optimize due to the unique transport phenomena that occur at different length scales. This challenge may be overcome by introducing hierarchical porous media, which combine tailored morphologies across multiple length scales to design for the individual transport mechanisms. Here, we fabricate hierarchical nanowire arrays consisting of vertically aligned copper nanowires (∼100 to 1000 nm length scale) decorated with dense copper oxide nanostructures (∼10 to 100 nm length scale) to create unique property sets that include a large specific surface area, high rates of fluid delivery, and the structural flexibility of vertical arrays. These hierarchical nanowire arrays possess enhanced capillary wicking ( K/ Reff = 0.004-0.023 µm) by utilizing hemispreading and are advantageous as evaporation surfaces. With the advent and acceleration of flexible electronics technologies, we measure the capillary properties of our freestanding hierarchical nanowire arrays installed on curved surfaces and observe comparable fluid delivery to flat arrays, showing the difference of 10-20%. The degree of effective inter-nanowire pore and porosity is shown to govern the capillary performance parameters, thereby this study provides the design strategy for capillary wicking materials with unique and tailored combinations of thermofluidic properties.

A Paired Bead and Magnet Array for Molding Microwells with Variable Concave Geometries.

A spheroid culture is a useful tool for understanding cellular behavior in that it provides an in vivo-like three-dimensional environment. Various spheroid production methods such as non-adhesive surfaces, spinner flasks, hanging drops, and microwells have been used in studies of cell-to-cell interaction, immune-activation, drug screening, stem cell differentiation, and organoid generation. Among these methods, microwells with a three-dimensional concave geometry have gained the attention of scientists and engineers, given their advantages of uniform-sized spheroid generation and the ease with which the responses of individual spheroids can be monitored. Even though cost-effective methods such as the use of flexible membranes and ice lithography have been proposed, these techniques incur serious drawbacks such as difficulty in controlling the pattern sizes, achievement of high aspect ratios, and production of larger areas of microwells. To overcome these problems, we propose a robust method for fabricating concave microwells without the need for complex high-cost facilities. This method utilizes a 30 x 30 through-hole array, several hundred micrometer-order steel beads, and magnetic force to fabricate 900 microwells in a 3 cm x 3 cm polydimethylsiloxane (PDMS) substrate. To demonstrate the applicability of our method to cell biological applications, we cultured adipose stem cells for 3 days and successfully produced spheroids using our microwell platform. In addition, we performed a magnetostatic simulation to investigate the mechanism, whereby magnetic force was used to trap the steel beads in the through-holes. We believe that the proposed microwell fabrication method could be applied to many spheroid-based cellular studies such as drug screening, tissue regeneration, stem cell differentiation, and cancer metastasis.

Effect of off-plane bifurcation angles of primary bronchi on expiratory flows in the human trachea.

BACKGROUND: The human airway is exposed to the development of diverse flow patterns based on differences in its morphological/geometrical parameters across individuals. Although effects of the asymmetry between the right and left main bronchi on airway flows have been investigated in the past, there exists a paucity in terms of studies that focus on the role of stronger physiological asymmetric features, such as off-plane bifurcation angles of primary bronchi, in expiratory flows. METHOD: Computational fluid dynamic techniques have been used to demonstrate presence of Dean-type secondary flows and vortices in the bifurcation region. Formation of a distinctive pattern was observed corresponding to an increase in the off-plane branching angle. An experiment involving 3D printed airways and smoke was also performed to visualize flow patterns and verify simulation results. RESULTS: Good agreement was observed between computational and experimental results. Furthermore, it was revealed that the predicted wall shear stress distribution demonstrated significant changes (with a maximum shear stress increase of 30.7%) compared to conventional airway models that adopt symmetric bifurcation angles. The overall flow demonstrated a swerving motion, which was characterized by tracking the vortex cores (maximum accumulated radial movement of 72.6°) when they ascended towards the trachea inlet in off-plane airway models. CONCLUSIONS: It was confirmed that off-plane bifurcations in human trachea significantly alter the flow characteristics in expiratory flows. It is expected that the results of this study will provide useful information regarding increasingly advanced patient-specific treatments for respiratory diseases in the trachea.

Degradation of a thin Ag layer induced by poly(3,4-ethylenedioxythiophene):polystyrene sulfonate in a transmission electron microscopy specimen of an inverted polymer solar cell.

It was found that the Ag electrode layer in a transmission electron microscopy (TEM) specimen of an inverted polymer solar cell structure of Ag/PEDOT:PSS/P3HT:PCBM/TiO(2)/ITO/glass (where PEDOT is poly(3,4-ethylenedioxythiophene), PSS is polystyrene sulfonate, and ITO is indium tin oxide) was broken down into particles as time passed. In order to investigate the cause of Ag particle formation and the effect of the degradation on the performance of solar cells, the temporal change of the cross-sectional TEM micrographs was examined together with energy-dispersive X-ray spectroscopy (EDS) analysis and electron tomography. Temporal degradation of Ag/Si and Ag/1 nm-Ti/PEDOT:PSS/ITO/glass structures was also studied. Absorption of water by the PEDOT:PSS layer followed by corrosion of the grain boundaries of the Ag layer by the corrosive water was thought to be the reason of Ag particle formation and fast performance lowering of the device.