Thermodynamic Analysis of Irreversibility in Microfluidic Mixing Devices
DOI:
https://doi.org/10.5281/zenodo.22698603Keywords:
microfluidic mixing, entropy generation minimization, viscous dissipation, herringbone micromixer, irreversibility, Peclet number, mixing index, second-law analysisAbstract
Microfluidic mixing devices must generate species-concentration uniformity within channel lengths of only a few
millimeters, and doing so under laminar, low-Reynolds-number flow necessarily relies on chaotic advection
structures that dissipate mechanical energy and generate entropy through both viscous friction and irreversible
mass diffusion, yet the relative size of these two irreversibility sources across realistic operating conditions is not
always reported quantitatively for a given mixer geometry. We performed a second-law (entropy generation
minimization) analysis of a staggered-herringbone passive micromixer combining computational fluid dynamics with
a scalar transport solver across 40 operating conditions spanning flow rates from 5 to 200 muL/min (Reynolds
number 0.02-0.9, Peclet number 1.2 x 10^3-4.8 x 10^4). Total volumetric entropy generation rate increased from 3.1
x 10^-3 W/(m^3 K) at the lowest flow rate to 2.86 W/(m^3 K) at the highest, a roughly 920-fold increase, with the
balance between viscous and diffusive (concentration-gradient) contributions shifting systematically across this
range: diffusive entropy generation dominated at low flow rate (81% of total at 5 muL/min) while viscous entropy
generation dominated at high flow rate (76% of total at 200 muL/min), crossing over at an intermediate flow rate of
approximately 42 muL/min. The mixing index, defined from the coefficient of variation of outlet concentration,
improved from 0.61 at the lowest flow rate to 0.94 at 80 muL/min but then plateaued, reaching only 0.96 at the
highest flow rate tested, while total entropy generation over the same interval more than quadrupled, indicating
strongly diminishing thermodynamic returns on mixing quality beyond roughly 80 muL/min. A dimensionless Bejan
number, the ratio of diffusive to total entropy generation, decreased monotonically from 0.81 to 0.24 across the
tested flow range (R^2 = 0.97 for a power-law fit against Peclet number), and a geometric parameter sweep varying
herringbone groove depth by ±25% shifted the crossover flow rate by up to 18% while changing peak mixing index
by less than 2 percentage points. These results identify an operating window, approximately 60-90 muL/min for this
geometry, in which near-complete mixing is achieved without incurring the steep entropy-generation penalty of
substantially higher flow rates, providing a quantitative second-law basis for selecting operating conditions in
passive microfluidic mixer design.
References
Landauer R (1961) Irreversibility and heat generation in the computing process. IBM Journal of Research and Development 5(3):183-191. https://doi.org/10.1147/rd.53.0183
Bennett CH (1982) The thermodynamics of computation-a review. International Journal of Theoretical Physics 21(12):905-940. https://doi.org/10.1007/BF02084158
Jarzynski C (1997) Nonequilibrium equality for free energy differences. Physical Review Letters 78(14):2690-2693. https://doi.org/10.1103/PhysRevLett.78.2690
Crooks GE (1999) Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences. Physical Review E 60(3):2721-2726. https://doi.org/10.1103/PhysRevE.60.2721
Seifert U (2012) Stochastic thermodynamics, fluctuation theorems and molecular machines. Reports on Progress in Physics 75(12):126001. https://doi.org/10.1088/0034-4885/75/12/126001
Parrondo JMR, Horowitz JM, Sagawa T (2015) Thermodynamics of information. Nature Physics 11(2):131-139. https://doi.org/10.1038/nphys3230
Bekenstein JD (1973) Black holes and entropy. Physical Review D 7(8):2333-2346. https://doi.org/10.1103/PhysRevD.7.2333
Onsager L (1931) Reciprocal relations in irreversible processes. I. Physical Review 37(4):405-426. https://doi.org/10.1103/PhysRev.37.405
Tsallis C (1988) Possible generalization of Boltzmann-Gibbs statistics. Journal of Statistical Physics 52(1-2):479-487. https://doi.org/10.1007/BF01016429
Berut A, Arakelyan A, Petrosyan A, Ciliberto S, Dillenschneider R, Lutz E (2012) Experimental verification of Landauer's principle linking information and thermodynamics. Nature 483(7388):187-189. https://doi.org/10.1038/nature10872
Lloyd S (2000) Ultimate physical limits to computation. Nature 406(6799):1047-1054. https://doi.org/10.1038/35023282
Esposito M, Van den Broeck C (2010) Three faces of the second law. I. Master equation formulation. Physical Review E 82(1):011143. https://doi.org/10.1103/PhysRevE.82.011143
Sagawa T, Ueda M (2010) Generalized Jarzynski equality under nonequilibrium feedback control. Physical Review Letters 104(9):090602. https://doi.org/10.1103/PhysRevLett.104.090602
Toyabe S, Sagawa T, Ueda M, Muneyuki E, Sano M (2010) Experimental demonstration of information-to-energy conversion and validation of the generalized Jarzynski equality. Nature Physics 6(12):988-992. https://doi.org/10.1038/nphys1821
Verlinde E (2011) On the origin of gravity and the laws of Newton. Journal of High Energy Physics 2011(4):029. https://doi.org/10.1007/JHEP04(2011)029
Vopson MM (2019) The mass-energy-information equivalence principle. AIP Advances 9(9):095206. https://doi.org/10.1063/1.5123794
Szilard L (1929) Uber die Entropieverminderung in einem thermodynamischen System bei Eingriffen intelligenter Wesen. Zeitschrift fur Physik 53(11-12):840-856. https://doi.org/10.1007/BF01341281
Prigogine I (1978) Time, structure, and fluctuations. Science 201(4358):777-785. https://doi.org/10.1126/science.201.4358.777
Hawking SW (1975) Particle creation by black holes. Communications in Mathematical Physics 43(3):199-220. https://doi.org/10.1007/BF02345020
Wolpert DH (2019) The stochastic thermodynamics of computation. Journal of Physics A: Mathematical and Theoretical 52(19):193001. https://doi.org/10.1088/1751-8121/ab0850
Still S, Sivak DA, Bell AJ, Crooks GE (2012) Thermodynamics of prediction. Physical Review Letters 109(12):120604. https://doi.org/10.1103/PhysRevLett.109.120604
Shannon CE (1948) A mathematical theory of communication. Bell System Technical Journal 27(3):379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
Jaynes ET (1957) Information theory and statistical mechanics. Physical Review 106(4):620-630. https://doi.org/10.1103/PhysRev.106.620
Landauer R (1961) Irreversibility and heat generation in the computing process. IBM Journal of Research and Development 5(3):183-191. https://doi.org/10.1147/rd.53.0183
Bennett CH (1982) The thermodynamics of computation-a review. International Journal of Theoretical Physics 21(12):905-940. https://doi.org/10.1007/BF02084158
Jarzynski C (1997) Nonequilibrium equality for free energy differences. Physical Review Letters 78(14):2690-2693. https://doi.org/10.1103/PhysRevLett.78.2690
