13.07.2015 Views

best design for a fastest cells selecting process - ENS de Cachan ...

best design for a fastest cells selecting process - ENS de Cachan ...

best design for a fastest cells selecting process - ENS de Cachan ...

SHOW MORE
SHOW LESS
  • No tags were found...

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

10 MICHEL PIERRE AND GRÉGORY VIALH ′ η(ξ) =∫ 1ξ∫da ξ0[y(a 0 ) − y(ξ) + η] − da3/2 [y(ξ) − y(a) + η] . 3/2We have 2G ′ η(y(ξ)) = H ′ η(ξ), which implies that <strong>for</strong> all ψ ∈ C ∞ 0 (0, 1):−∫ 10ψ ′ (ξ)H η (ξ)dξ =∫ 102G ′ η(y(ξ))ψ(ξ)dξ =0∫ 102G ′ η(x)ψ(z(x))z ′ (x)dx. (35)As η <strong>de</strong>creases to zero, the function G η increases to the function G 0 which is constant by (30):there<strong>for</strong>e, its <strong>de</strong>rivative converges to zero in the sense of distributions on (0, 1). We <strong>de</strong>duce thatthe integrals in (35) tend to zero (note that ψ(z(·))z ′ (·) ∈ C0 ∞ (0, 1)): this says that H η ′ convergesto 0 in the sense of distributions and this implies (31).To end the proof of Proposition 3, note that the constant in (31) is necessarily equal to T (y)since, ∫ 1 d0 dξ y(ξ)H 0(ξ)dξ = T (y) (see the computations (25)(26) where we replace y ∗ by y). Thenit follows that y satises the rst or<strong>de</strong>r optimality condition of Proposition 2. By strict convexityof y ∈ M → T (y), we <strong>de</strong>duce that y = y ∗ . In<strong>de</strong>ed, according to the convexity of T (·) and to thecomputations (28), (29), we may write <strong>for</strong> all y ∈ M:T (y ∗ ) − T (y) ≥ d dt | t=0T ((1 − t)y + ty ∗ ) =∫ 10da 0∫ a00da (y∗ − y)(a 0 ) − (y ∗ − y)(a)[y(a 0 ) − y(a)] 3/2 ,and by (25)∫ 1∫T (y ∗ d1d) − T (y) ≥0 dξ [y∗ − y](ξ)H 0 (ξ)dξ = T (y)0 dξ [y∗ − y](ξ)dξ = 0.Whence T (y) = T (y ∗ ).Note also that the constant in (30) is 2T (y), since after setting x = y(a 0 ) and integrating withrespect to a 0 , we see that this constant is equal to:∫∫da 0 da1 ∫ a0∫√(0,1) 2 |y(a0 ) − y(a)| = da1 ∫ 1da 0 √0 y(a0 ) − y(a) + dada 0 √ = 2T (y).0 y(a) − y(a0 )0a 04. Numerical shape optimization of the electro<strong>de</strong>s. The microsystem we aim at <strong><strong>de</strong>sign</strong>ingis composed of a periodic network of interdigited electro<strong>de</strong>s, see Figure 1. We will optimize theshape of the electro<strong>de</strong>s in the box of Figure 4, the whole <strong>de</strong>vice being <strong>de</strong>duced by periodicity. As<strong>de</strong>picted, the opposite electro<strong>de</strong>s have the same polarity. Furthermore, the four electro<strong>de</strong>s havethe same shape to en<strong>for</strong>ce symmetry and ensure that the eld E vanishes at the center G of thebottom. Of course, the dielectrophoretic potential E 2 = ‖E‖ 2 is minimal at G, and we expect the<strong>cells</strong> to move towards this point.Our numerical strategy consists in nding the <strong>best</strong> electro<strong>de</strong>s to produce a eld as close aspossible to the optimal eld obtained in section 3. Since the methods we used are quite standard,we will only give a brief <strong>de</strong>scription and show the simulation results.zx+−G•−+yFigure 4. Periodic pattern <strong>for</strong> computations.

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!