3D-printed microfluidic automation

Abstract

Microfluidic automation - the automated routing, dispensing, mixing, and/or separation of fluids through microchannels - generally remains a slowly-spreading technology because device fabrication requires sophisticated facilities and the technology's use demands expert operators. Integrating microfluidic automation in devices has involved specialized multi-layering and bonding approaches. Stereolithography is an assembly-free, 3D-printing technique that is emerging as an efficient alternative for rapid prototyping of biomedical devices. Here we describe fluidic valves and pumps that can be stereolithographically printed in optically-clear, biocompatible plastic and integrated within microfluidic devices at low cost. User-friendly fluid automation devices can be printed and used by non-engineers as replacement for costly robotic pipettors or tedious manual pipetting. Engineers can manipulate the designs as digital modules into new devices of expanded functionality. Printing these devices only requires the digital file and electronic access to a printer.

Fig. 1. Basic valve design

(a) Photograph of the single-valve device. (b, c) Schematics of a valve unit in its open (b) and closed (c) states. (d, e) Micrographs of a valve unit in its open (d) and closed (e) states.

Fig. 2. Membrane deflection simulation

COMSOL simulations of the deflection of the valve membrane at (a) 0 psi, (b) 2.9 psi and (c) 5.8 psi respectively. The color heat map shows the von Mises stress on the membrane at these pressures. The nozzle is positioned 200 μm away from the membrane at rest.

Fig. 3. microCT imaging of membrane

(a) Cross-sectional image of the nozzle and membrane portion of the device obtained by microCT. (b) Color heat map plot of the thickness of the membrane obtained from cross-sectional microCT images, viewed orthogonally. The major irregularities are “phantom features” (arrows) due to out-of-the plane features artifactually introduced by the tomography algorithm. (c) Histogram plot of the membrane thickness (114.62 ± 15.31 µm; mean ± SD). Filtering out the out-of-plane artifacts only changes the average by ~1 µm.

Fig. 4. Single valve characterization

(a) Electrical current crossing the valve at three valve actuation frequencies. The fully open and fully closed states of the valve are indicated by black and white arrows, respectively. (b) Flow rate as a function of the control pressure applied to the valve. (c) The control pressure needed to fully close a valve over 20 opening/closing cycles, showing reproducibility of valve closure.

Fig. 5. 3D-printed switch

(a) Circuit diagram and (b) photograph of the two-valve switch. (c-e) Photographs of a dye-filled switch in three different actuation states.

Fig. 6. 3D-printed pump

(a) Circuit diagram and (b) photograph of the peristaltic pump. (c-e) Photographs of a dye-filled pump in three different phases of a peristaltic actuation sequence. (f) Pump rate as a function of pump actuation frequency.

Fig. 7. Valve control of the 3D-printed cell perfusion system

(a) Circuit diagram and (b) photograph of the four-valve switch. (c) Photograph of a dye-filled switch connected to a cell culture chamber (fluorescent micrographs of indicated regions shown as inset). (d) Fluorescence plots showing the concentration profiles in the switch and chamber during fluid-switching events. The red and blue curves correspond to the fluorescence intensity in the cell chamber and the switching device regions, respectively (within the switch, fluorescence was measured within the yellow-boxed region). The top green and black timelines indicate the valve actuation events.

Fig. 8. Calcium imaging with the 3D-printed perfusion system

(a) CHO-K1 cells loaded with calcium indicator dye, Fluo-4, were perfused with a series of 20 s exposures to 3 concentrations (5, 25 and 125 µM) of ATP. Six examples of the 947 cells that responded to ATP are shown in (b) at the time points indicated. A yellow box indicates the central region used to determine average fluorescence. (c) Graphs of calcium responses from the top half of the fluorescent images in (a). The bottom graph depicts the fluorescence traces from 488 individual ATPresponsive cells. The top graph depicts their averaged fluorescence. Arrowheads indicate the times at which the images in (b) were taken. The black bar shows the time frame depicted in Movie S5. (d) The average response (± SEM) to each application for all 947 ATP-responsive cells from the full field of view in (a). (e) The distribution of the responses to the first round of ATP for all 947 ATP-responsive cells. (f) Relative timing and repeatability of stimulus delivery 24compared to cellular calcium response. After calcium responses to 5 repeats of 5, 15, and 45 μM ATP were recorded in the green fluorescence channel (only responses to 45 μM shown for clarity), 6 applications of Alexa 594 dye mixed in with the ATP solutions were recorded in the red fluorescence channel using the same perfusion protocol.