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Dive into the research topics where Andres A. Aguirre-Pablo is active.

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Featured researches published by Andres A. Aguirre-Pablo.


RSC Advances | 2016

A simple and low-cost fully 3D-printed non-planar emulsion generator

Jia Ming Zhang; Er Qiang Li; Andres A. Aguirre-Pablo; Sigurdur T. Thoroddsen

Droplet-based microfluidic devices provide a powerful platform for material, chemical and biological applications based on droplet templates. The technique traditionally utilized to fabricate microfluidic emulsion generators, i.e. soft-lithography, is complex and expensive for producing three-dimensional (3D) structures. The emergent 3D printing technology provides an attractive alternative due to its simplicity and low-cost. Recently a handful of studies have already demonstrated droplet production through 3D-printed microfluidic devices. However, these devices invariably use purely two-dimensional (2D) flow structures. Herein we apply 3D printing technology to fabricate simple and low-cost 3D miniaturized fluidic devices for droplet generation (single emulsion) and droplet-in-droplet (double emulsion) without need for surface treatment of the channel walls. This is accomplished by varying the channel diameters at the junction, so the inner liquid does not touch the outer walls. This 3D-printed emulsion generator has been successfully tested over a range of conditions. We also formulate and demonstrate, for the first time, uniform scaling laws for the emulsion drop sizes generated in different regimes, by incorporating the dynamic contact angle effects during the drop formation. Magnetically responsive microspheres are also produced with our emulsion templates, demonstrating the potential applications of this 3D emulsion generator in chemical and material engineering.


RSC Advances | 2016

Droplet generation in cross-flow for cost-effective 3D-printed “plug-and-play” microfluidic devices

Jia Ming Zhang; Andres A. Aguirre-Pablo; Er Qiang Li; Ulrich Buttner; Sigurdur T. Thoroddsen

Droplet-based microfluidics is a rapidly growing field of research and involves various applications from chemistry to biology. Droplet generation techniques become the pre-requisite focus. Additive manufacturing (3D printing) technology has recently been exploited in microfluidics due to its simplicity and low cost. However, only relatively large droplets can be produced in current 3D-printed droplet generators, due to the channel dimension limitations on how fine a channel can be 3D-printed. Here we report a novel design of a 3D-printed “plug-and-play” device for the generation of monodisperse microdroplets with sizes down to ∼50 μm. This device combines a 3D-printed generator, a commercial tubing and a fingertight fitting, which can be easily assembled and disassembled. Different emulsions, water-in-oil and oil-in-water, can be generated in the same device. Scaling laws for droplet sizes generated in our device have been successfully proposed and verified. Furthermore, the feasibility of 3D printing technology used in droplet-based engineering applications has been demonstrated by two novel 3D-printed devices, as well as by using the device for producing magnetically responsive microparticles.


Science Advances | 2017

Self-determined shapes and velocities of giant near-zero drag gas cavities

Ivan U. Vakarelski; Evert Klaseboer; Aditya Jetly; Mohammad Mansoor; Andres A. Aguirre-Pablo; Derek Y. C. Chan; Sigurdur T. Thoroddsen

A gas cavity can reduce the hydrodynamic drag on a falling sphere in liquid to near zero by providing perfect slip conditions. Minimizing the retarding force on a solid moving in liquid is the canonical problem in the quest for energy saving by friction and drag reduction. For an ideal object that cannot sustain any shear stress on its surface, theory predicts that drag force will fall to zero as its speed becomes large. However, experimental verification of this prediction has been challenging. We report the construction of a class of self-determined streamlined structures with this free-slip surface, made up of a teardrop-shaped giant gas cavity that completely encloses a metal sphere. This stable gas cavity is formed around the sphere as it plunges at a sufficiently high speed into the liquid in a deep tank, provided that the sphere is either heated initially to above the Leidenfrost temperature of the liquid or rendered superhydrophobic in water at room temperature. These sphere-in-cavity structures have residual drag coefficients that are typically less than 110 those of solid objects of the same dimensions, which indicates that they experienced very small drag forces. The self-determined shapes of the gas cavities are shown to be consistent with the Bernoulli equation of potential flow applied on the cavity surface. The cavity fall velocity is not arbitrary but is uniquely predicted by the sphere density and cavity volume, so larger cavities have higher characteristic velocities.


Scientific Reports | 2017

Tomographic Particle Image Velocimetry using Smartphones and Colored Shadows

Andres A. Aguirre-Pablo; Meshal K. Alarfaj; Er Qiang Li; J.F. Hernández-Sánchez; Sigurdur T. Thoroddsen

We demonstrate the viability of using four low-cost smartphone cameras to perform Tomographic PIV. We use colored shadows to imprint two or three different time-steps on the same image. The back-lighting is accomplished with three sets of differently-colored pulsed LEDs. Each set of Red, Green & Blue LEDs is shone on a diffuser screen facing each of the cameras. We thereby record the RGB-colored shadows of opaque suspended particles, rather than the conventionally used scattered light. We subsequently separate the RGB color channels, to represent the separate times, with preprocessing to minimize noise and cross-talk. We use commercially available Tomo-PIV software for the calibration, 3-D particle reconstruction and particle-field correlations, to obtain all three velocity components in a volume. Acceleration estimations can be done thanks to the triple pulse illumination. Our test flow is a vortex ring produced by forcing flow through a circular orifice, using a flexible membrane, which is driven by a pressurized air pulse. Our system is compared to a commercial stereoscopic PIV system for error estimations. We believe this proof of concept experiment will make this technique available for education, industry and scientists for a fraction of the hardware cost needed for traditional Tomo-PIV.


Advanced materials and technologies | 2017

Recyclable Nonfunctionalized Paper‐Based Ultralow‐Cost Wearable Health Monitoring System

Joanna M. Nassar; Kush Mishra; Kirklann Lau; Andres A. Aguirre-Pablo; Muhammad Mustafa Hussain


ACM Transactions on Graphics | 2017

Rainbow particle imaging velocimetry for dense 3D fluid velocity imaging

Jinhui Xiong; Ramzi Idoughi; Andres A. Aguirre-Pablo; Abdulrahman B. Aljedaani; Xiong Dun; Qiang Fu; Sigurdur T. Thoroddsen; Wolfgang Heidrich


Bulletin of the American Physical Society | 2017

3D Rainbow Particle Tracking Velocimetry.

Andres A. Aguirre-Pablo; Jinhui Xiong; Ramzi Idoughi; Abdulrahman B. Aljedaani; Xiong Dun; Qiang Fu; Sigurdur T. Thoroddsen; Wolfgang Heidrich


Bulletin of the American Physical Society | 2017

Near-Zero-Drag Objects

Sigurdur T. Thoroddsen; Ivan U. Vakarelski; E. Klaseboer; Aditya Jetly; Mohammad Mansoor; Andres A. Aguirre-Pablo; Derek Y. C. Chan


Advanced materials and technologies | 2017

Wearable Sensors: Recyclable Nonfunctionalized Paper‐Based Ultralow‐Cost Wearable Health Monitoring System (Adv. Mater. Technol. 4/2017)

Joanna M. Nassar; Kush Mishra; Kirklann Lau; Andres A. Aguirre-Pablo; Muhammad Mustafa Hussain


Bulletin of the American Physical Society | 2016

Smartphone based Tomographic PIV using colored shadows

Andres A. Aguirre-Pablo; Meshal K. Alarfaj; Er Qiang Li; Sigurdur T. Thoroddsen

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Sigurdur T. Thoroddsen

King Abdullah University of Science and Technology

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Er Qiang Li

King Abdullah University of Science and Technology

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Abdulrahman B. Aljedaani

King Abdullah University of Science and Technology

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Aditya Jetly

King Abdullah University of Science and Technology

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Erqiang Li

King Abdullah University of Science and Technology

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Ivan U. Vakarelski

King Abdullah University of Science and Technology

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Jia Ming Zhang

King Abdullah University of Science and Technology

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Jinhui Xiong

King Abdullah University of Science and Technology

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Joanna M. Nassar

King Abdullah University of Science and Technology

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Kirklann Lau

King Abdullah University of Science and Technology

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