Impact of Fiber Orientation in Electrospun PLA Scaffolds on Fluid Dynamics in a Custom Microfluidic Device

Abstract

Organ-on-Chip (OoC) systems are evolving as vital tools in biomedical research, proposing advanced platforms to replicate human tissue microenvironments for drug testing and disease modeling. This study examines how the orientation of polylactic acid (PLA) fibers influences fluid movement in a custom OoC setup. PLA scaffolds are fabricated via electrospinning with either random or aligned fiber orientations. Scanning electron microscopy (SEM) reveals that random scaffolds are 70 µm thick with fibers measuring 1.12 µm, while aligned scaffolds are thinner at 35 µm with fibers of 1.02 µm. Porosity and matrix structure are analyzed to understand the impact of fiber arrangement. Liquid water permeability is tested using a custom three dimensional (3D)-printed device conforming to ISO 7198:2016 standards. Computational fluid dynamics (CFD) simulations, employing the Porous Media Flow Module and Brinkman's equations, predict flow behavior based on scaffold morphology. A dual-chamber microfluidic chip integrated with pressure sensors allows real-time measurements to validate the simulations. Results demonstrate that fiber alignment significantly alters scaffold permeability and flow dynamics. These insights are valuable for tissue engineering, offering a validated framework to design microfluidic devices with tailored fluidic environments optimized for specific scaffold architectures.

Keywords: Organ‐on‐Chip; computational fluid dynamics (CFD); electrospinning; fiber alignment; liquid permeability; microfluidic devices.

Figure 1

SEM images of electrospun PLA scaffold with: A) fibers with aligned orientation (A‐PLA, left); and B) fibers with randomized orientation (R‐PLA, right). Scale bars: 20 µm.

Figure 2

Design and conceptualization of the microfluidic device: A) Exploded view of the microfluidic device showing the seven stacked layers with varying thicknesses (0.5 and 2 mm); B) the assembled device includes dedicated inlet and outlet ports for both microfluidic chambers; C) Cross‐sectional view of the device highlighting the spatial organization of the upper and lower chambers, with the scaffold positioned as a barrier between compartments.

Figure 3

Simulation results at the macroscopic scale for random and aligned scaffolds when v_U = v_L (corresponding to a flow rate of ≈1 mL day⁻¹) and v_U > v_L (corresponding to a flow rate of ≈10 and 1 mL day⁻¹): A) velocity along five yz planes when v_U = v_L; B) velocity along five yz planes when v_U > v_L; C) pressure distribution when v_U = v_L, D) pressure distribution when v_U > v_L; E) velocity profile along z for both flow configurations (blue curve refers to v_U = v_L, orange curve refers to v_U > v_L applied along the secondary y‐axis); F) pressure profile along z for both flow configurations (blue curve refers to v_U = v_L, orange curve refers to v_U > v_L applied along the secondary y‐axis). v_U and v_L indicate the flow velocity in the upper and lower chambers, respectively. Arc length indicates the distance along the z‐axis of the device, measured in millimeters, where 0 mm represents the bottom and 2 mm the top, and along which the velocity and pressure profiles were measured.

Figure 4

Streamlines across the scaffold obtained from simulations at the macroscopic scale for random and aligned scaffolds integrated into the double‐chamber OoC. Three flow configurations concerning different velocity values in the upper (v_U) and lower (v_L) chambers were analyzed: v_U = v_L, v_U = 10 × v_L, and v_L = 10 × v_U. Distinct flow profiles were observed for the two fiber arrangements when the velocities in the upper and lower chambers differed.

Figure 5

Steps to obtain the geometry for the micro‐scale simulation: A) SEM image of a random PLA scaffold, B) 3D reconstruction of the arrangement of the random fibers, C) coupling of the random fibers with two fluid volumes in the upper and lower regions, along with a porous solid volume between the fibers (total thickness of the scaffold = 70 µm); D) SEM image of an aligned PLA scaffold, E) 3D reconstruction of the arrangement of the aligned fibers, F) coupling of the aligned fibers with two fluid volumes in the upper and lower regions, along with a porous solid volume between the fibers (total thickness of the scaffold = 35 µm).

Figure 6

Simulation results at the microscopic scale for random and aligned scaffolds: A) velocity distribution when v_U = v_L; B) velocity distribution when v_U > v_L; C) pressure distribution when v_U = v_L, D) pressure distribution when v_U > v_L; E) velocity profile along z for both flow configurations (blue curve refers to v_U = v_L, orange curve refers to v_U > v_L applied to the secondary y‐axis); F) pressure profile along z for both flow configurations (blue curve refers to v_U = v_L, orange curve refers to v_U > v_L applied to the secondary y‐axis). v_U and v_L indicate the flow velocity in the upper and lower chambers, respectively. Arc length indicates the distance along the z‐axis of the domain, measured in microns, where 0 mm represents the bottom and 270 µm the top, and along which the velocity and pressure profiles were measured.

Figure 7

Shear stress on the fibers when v_U = v_L: A) upper surface of the random scaffold, B) lower surface of the random scaffold, C) upper surface of the aligned scaffold with fibers aligned to the direction of flow, D) lower surface of the aligned scaffold with fibers aligned to the direction of flow, E), upper surface of the aligned scaffold with fibers perpendicular to the direction of flow, F) lower surface of the aligned scaffold with fibers aligned to the direction of flow.

Figure 8

Shear stress on the fibers when v_U = 10 × v_L: A) upper surface of the random scaffold, B) lower surface of the random scaffold, C) upper surface of the aligned scaffold with fibers aligned to the direction of flow, D) lower surface of the aligned scaffold with fibers aligned to the direction of flow, E), upper surface of the aligned scaffold with fibers perpendicular to the direction of flow, F) lower surface of the aligned scaffold with fibers aligned to the direction of flow.

Figure 9

Streamline (red lines) plots obtained from simulations at the microscopic scale for random and aligned scaffolds. For each configuration, two plots were examined: one considering streamlines across the membranes and another with uniform density, indicating the direction and relative intensity of fluid flow. For the aligned scaffold, both flow configurations—fibers aligned with the flow direction and perpendicular to it—were considered. The three flow configurations analyzed involved different values of velocities in the upper (v_U) and lower (v_L) chambers. The blue arrows in the first figure (top‐left) represent the inlet direction of the flow for both streamline plots and can be extended to all other images.

Figure 10

Experimental (exp) and simulated (sim) flow rates across the scaffold (Q_{L –} Q_U) under three different flow conditions (color‐coded). The solid lines represent experimental data, while the dashed lines indicate simulation results. The secondary y‐axis is used for v_U = v_L because its values are an order of magnitude smaller, making them otherwise unreadable on the primary axis.

Figure 11

CAD and images of the system designed for permeability measurement: A) Disassembled view of the system, illustrating the fluid inflow and outflow, along with Teflon components and a porous scaffold. B) Dimensions of the main component, with side and top views. C) Photographs of the assembled device, showing top, isometric, and side views.

Figure 12

Zoomed‐in view of the fluid domain used for the simulations at the microscopic scale. The selected volume includes the electrospun PLA scaffold, characterized by its porous structure, allowing for a detailed analysis of fluid flow dynamics at the microscale.