Design, modeling and characterization of microfluidic architectures for high flow rate, small footprint microfluidic systems

Abstract

We propose a strategy for optimizing distribution of flow in a microfluidic chamber for microreactor, lateral flow assay and immunocapture applications. It is aimed at maximizing flow throughput, while keeping footprint, cell thickness, and shear stress in the distribution channels at a minimum, and offering a uniform flow field along the whole analysis chamber. In order to minimize footprint, the traditional tree-like or "rhombus" design, in which distribution microchannels undergo a series of splittings into two subchannels with equal lengths and widths, was replaced by a design in which subchannel lengths are unequal, and widths are analytically adapted within the Hele-Shaw approximation, in order to keep the flow resistance uniform along all flow paths. The design was validated by hydrodynamic flow simulation using COMSOL finite element software. Simulations show that, if the channel is too narrow, the Hele-Shaw approximation loses accuracy, and the flow velocity in the chamber can fluctuate by up to 20%. We thus used COMSOL simulation to fine-tune the channel parameters, and obtained a fluctuation of flow velocity across the whole chamber below 10%. The design was then implemented into a PDMS device, and flow profiles were measured experimentally using particle tracking. Finally, we show that this system can be applied to cell sorting in self-assembling magnetic arrays, increasing flow throughput by a factor 100 as compared to earlier reported designs.

PEGylation of magnetic poly(glycidyl methacrylate) microparticles for microfluidic bioassays

“…1) with a rectangular cross-section was fabricated using soft lithography 44 according to a procedure previously described 45 . The inner dimensions of each channel were (w x h x l): 200 µm x 50 µm x 30 mm.…”

Modeling of cell sorting and rare cell capture with microfabricated biodevices

“…The probability of successful cell capture was calculated from the percentage of the channel width where 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 the velocity vectors flow into the trap. Also, in the work of Saias et al, a single-phase model with the same physical characteristics as water was used for optimizing the flow distribution in a microfluidic chamber [28].…”

Design and modeling of microfluidic systems for multiple chromatographic separations

“…Toepke et al determined the velocity and concentration profiles in a microfluidic flow-flash system [9]. Others used COMSOL simulations to fine-tune the channel parameters and to validate the designed channel pattern [10]. Haroun et al made simulations to find the ideal channel pattern providing the efficient synthesis of a PET radiotracer compound [11].…”