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1. The Effect of the Stiffness of Soft Materials on Hemiwicking Performance

   https://doi.org/10.1109/ITherm45881.2020.9190180  

   Germain, Thomas ; Putnam, Shawn A. ( July 2020 , 2020 19th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm))

   Fabricating micro and nanosized structures to induce hemiwicking on a heated surface has risen in popularity due to the higher heat flux the surface can experience. Recent studies have focused on the effects on the pillar geometry and spacing on the wicking velocity and the critical heat flux. As a result, a majority of the models that have been derived focus on the fluid properties and the wicking structure geometry and spacing. This study presents changes to the wicking performance when the stiffness of a soft material is taken into effect. Multiple similar wicking structures were fabricated using a negative mold method utilizing an in-house stamping apparatus. Using the mold, multiple polydimethylsiloxane (PDMS) samples were created, where the stiffness of the samples was varied by altering the mixing ratio and the curing time. The wicking velocity of ethanol, isopropyl alcohol, and isooctane did not vary for the samples that had a Young's Modulus greater than 1 MPa, but a notable decrease in the wicking velocity for all three fluids were observed for samples with a Young's Modulus less than 1 MPa. This study provides insight to the importance of the stiffness of the material is for hemiwicking on soft materials and that deformation effects have to be taken into account for Young's Moduli less than 1 MPa. 

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2. A simple analytic model for predicting the wicking velocity in micropillar arrays

   https://doi.org/10.1038/s41598-019-56361-7  

   Krishnan, Siva Rama ; Bal, John ; Putnam, Shawn A. ( December 2019 , Scientific Reports)

   Hemiwicking is the phenomena where a liquid wets a textured surface beyond its intrinsic wetting length due to capillary action and imbibition. In this work, we derive a simple analytical model for hemiwicking in micropillar arrays. The model is based on the combined effects of capillary action dictated by interfacial and intermolecular pressures gradients within the curved liquid meniscus and fluid drag from the pillars at ultra-low Reynolds numbers$${\boldsymbol{(}}{{\bf{10}}}^{{\boldsymbol{-}}{\bf{7}}}{\boldsymbol{\lesssim }}{\bf{Re}}{\boldsymbol{\lesssim }}{{\bf{10}}}^{{\boldsymbol{-}}{\bf{3}}}{\boldsymbol{)}}$$$\left({10}^{-7}\lesssim \mathrm{Re}\lesssim {10}^{-3}\right)$. Fluid drag is conceptualized via a critical Reynolds number:$${\bf{Re}}{\boldsymbol{=}}\frac{{{\bf{v}}}_{{\bf{0}}}{{\bf{x}}}_{{\bf{0}}}}{{\boldsymbol{\nu }}}$$$\mathrm{Re}=\frac{v_0{x}_0}{\nu }$, wherev₀corresponds to the maximum wetting speed on a flat, dry surface andx₀is the extension length of the liquid meniscus that drives the bulk fluid toward the adsorbed thin-film region. The model is validated with wicking experiments on different hemiwicking surfaces in conjunction withv₀andx₀measurements using Water$${\boldsymbol{(}}{{\bf{v}}}_{{\bf{0}}}{\boldsymbol{\approx }}{\bf{2}}\,{\bf{m}}{\boldsymbol{/}}{\bf{s}}{\boldsymbol{,}}\,{\bf{25}}\,{\boldsymbol{\mu }}{\bf{m}}{\boldsymbol{\lesssim }}{{\bf{x}}}_{{\bf{0}}}{\boldsymbol{\lesssim }}{\bf{28}}\,{\boldsymbol{\mu }}{\bf{m}}{\boldsymbol{)}}$$$\left(v_0\approx 2m/s,25\mu m\lesssim x_0\lesssim 28\mu m\right)$, viscous FC-70$${\boldsymbol{(}}{{\boldsymbol{v}}}_{{\bf{0}}}{\boldsymbol{\approx }}{\bf{0.3}}\,{\bf{m}}{\boldsymbol{/}}{\bf{s}}{\boldsymbol{,}}\,{\bf{18.6}}\,{\boldsymbol{\mu }}{\bf{m}}{\boldsymbol{\lesssim }}{{\boldsymbol{x}}}_{{\bf{0}}}{\boldsymbol{\lesssim }}{\bf{38.6}}\,{\boldsymbol{\mu }}{\bf{m}}{\boldsymbol{)}}$$$\left(v_0\approx 0.3m/s,18.6\mu m\lesssim x_0\lesssim 38.6\mu m\right)$and lower viscosity Ethanol$${\boldsymbol{(}}{{\boldsymbol{v}}}_{{\bf{0}}}{\boldsymbol{\approx }}{\bf{1.2}}\,{\bf{m}}{\boldsymbol{/}}{\bf{s}}{\boldsymbol{,}}\,{\bf{11.8}}\,{\boldsymbol{\mu }}{\bf{m}}{\boldsymbol{\lesssim }}{{\bf{x}}}_{{\bf{0}}}{\boldsymbol{\lesssim }}{\bf{33.3}}\,{\boldsymbol{\mu }}{\bf{m}}{\boldsymbol{)}}$$$\left(v_0\approx 1.2m/s,11.8\mu m\lesssim x_0\lesssim 33.3\mu m\right)$.

    

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3. Decrypting the mechanisms of wicking and evaporation heat transfer on micro-pillars during the pool boiling of water using high-resolution infrared thermometry

   https://doi.org/10.1063/5.0135110  

   Wang, Chi ; Rahman, Md Mahamudur ; Bucci, Matteo ( March 2023 , Physics of Fluids)

   Surfaces with micrometer-scale pillars have shown great potential in delaying the boiling crisis and enhancing the critical heat flux (CHF). However, physical mechanisms enabling this enhancement remain unclear. This knowledge gap is due to a lack of diagnostics that allow elucidating how micro-pillars affect thermal transport phenomena on the engineered surface. In this study, for the first time, we are able to measure time-dependent temperature and heat flux distributions on a boiling surface with engineered micro-pillars using infrared thermometry. Using these data, we reveal the presence of an intra-pillar liquid layer, created by the nucleation of bubbles and partially refilled by capillary effects. However, contrarily to conventional wisdom, the energy removed by the evaporation of this liquid cannot explain the observed CHF enhancement. Yet, predicting its dry out is the key to delaying the boiling crisis. We achieve this goal using simple analytic models and demonstrate that this process is driven by conduction effects in the boiling substrates and, importantly, in the intra-pillar liquid layer itself. Importantly, these effects also control the wicking flow rate and its penetration length. The boiling crisis occurs when, by coalescing, the size of the intra-pillar liquid layer becomes too large for the wicking flow to reach its innermost region. Our study reveals and quantifies unidentified physical aspects, key to the performance optimization of boiling surfaces for cooling applications.

    

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4. Multi-Objective Optimization of Predicted Magnetic Properties From Multifield Processing Conditions in Polymer Matrix Particle Composites

   https://doi.org/10.1115/SMASIS2022-91175  

   Widdowson, Denise ; Erol, Anil ; Papula, Dashiell ; Ounaies, Zoubeida ; von Lockette, Paris ( September 2022 , Proceedings of the ASME 2022 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASME 2022 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Dearborn, Michigan, USA. September 12–14, 2022. V001T02A008. ASME.)

   Additive manufacturing, no longer reserved exclusively for prototyping components, can create parts with complex geometries and locally tailored properties. For example, multiple homogenous material sources can be used in different regions of a print or be mixed during printing to define properties locally. Additionally, heterogeneous composites provide an opportunity for another level of tuning properties through processing. For example, within particulate-filled polymer matrix composites before curing, the presence of an applied electric and/or magnetic fields can reorient filler particles and form hierarchical structures depending on the fields applied. Control of particle organization is important because effective material properties are highly dependent on the distribution of filler material within composites once cured. While previous work in homogenization and effective medium theories have determined properties based upon ideal analytic distributions of particle orientations and spatial location, this work expands upon these methods generating discrete distributions from quasi-Monte Carlo simulations of the electromagnetic processing event. Results of simulations provide predicted microarchitectures from which effective properties are determined via computational homogenization.

   These particle dynamics simulations account for dielectric and magnetic forces and torques in addition to hydrodynamic forces and hard particle separation. As such, the distributions generated are processing field dependent. The effective properties for a composite represented by this distribution are determined via computational homogenization using finite element analysis (FEA). This provides a path from constituents, through processing parameters to effective material properties. In this work, we use these simulations in conjunction with a multi-objective optimization scheme to resolve the relationships between processing conditions and effective properties, to inform field-assisted additive manufacturing processes.

   The constituent set providing the largest range of properties can be found using optimization techniques applied to the aforementioned simulation framework. This key information provides a recipe for tailoring properties for additive manufacturing design and production. For example, our simulation results show that stiffness for a 10% filler volume fraction can increase by 34% when aligned by an electric field as compared to a randomly distributed composite. The stiffness of this aligned sample is also 29% higher in the direction of the alignment than perpendicular to it, which only differs by 5% from the random case [1]. Understanding this behavior and accurately predicting composite properties is key to producing field processed composites and prints. Material property predictions compare favorably to effective medium theory and experimentation with trends in elastic and magnetic effective properties demonstrating the same anisotropic behavior as a result of applied field processing. This work will address the high computational expense of physics simulation based objective functions by using efficient algorithms and data structures. We will present an optimization framework using nested gradient searches for micro barium hexaferrite particles in a PDMS matrix, optimizing on composite magnetization to determine the volume fraction of filler that will provide the largest range of properties by varying the applied electric and magnetic fields.

    

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5. Manipulation and statistical analysis of the fluid flow of polymer semiconductor solutions during meniscus-guided coating

   https://doi.org/10.1557/mrs.2020.306  

   Shaw, Leo ; Diao, Ying ; Martin-Noble, Geoffrey C. ; Yan, Hongping ; Hayoz, Pascal ; Weitz, R. Thomas ; Kaelblein, Daniel ; Toney, Michael F. ; Bao, Zhenan ( December 2020 , MRS Bulletin)

   null (Ed.)

   Recent work in structure–processing relationships of polymer semiconductors have demonstrated the versatility and control of thin-film microstructure offered by meniscus-guided coating (MGC) techniques. Here, we analyze the qualitative and quantitative aspects of solution shearing, a model MGC method, using coating blades augmented with arrays of pillars. The pillars induce local regions of high strain rates—both shear and extensional—not otherwise possible with unmodified blades, and we use fluid mechanical simulations to model and study a variety of pillar spacings and densities. We then perform a statistical analysis of 130 simulation variables to find correlations with three dependent variables of interest: thin-film degree of crystallinity and transistor field-effect mobilities for charge-transport parallel (μ para ) and perpendicular (μ perp ) to the coating direction. Our study suggests that simple fluid mechanical models can reproduce substantive correlations between the induced fluid flow and important performance metrics, providing a methodology for optimizing blade design. 

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