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AWESOME LECTURE#2 Microfluidics + integrated circuit can control cells and chemical compounds.

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Presentation on theme: "AWESOME LECTURE#2 Microfluidics + integrated circuit can control cells and chemical compounds."— Presentation transcript:

1

2 AWESOME LECTURE#2

3 Microfluidics + integrated circuit can control cells and chemical compounds.

4 MICROFLUID + INTEGRATED CIRCUIT =

5  Overview…

6  What are microfluids?

7  Overview…  What are microfluids?  Lab on a Chip (control)

8  Overview…  What are microfluids?  Lab on a Chip (control)  Tests & Applications

9

10  SMALL FLUIDS!

11  Channel < 1 mm in length

12  SMALL FLUIDS!  Channel < 1 mm in length  Examples:

13  SMALL FLUIDS!  Channel < 1 mm in length  Examples:

14  SMALL FLUIDS!  Channel < 1 mm in length  Examples:

15  SMALL FLUIDS!  Channel < 1 mm in length  Examples:

16  SMALL FLUIDS!  Channel < 1 mm in length  Examples:

17  Interesting properties…

18  Reynolds Number (flow)

19  Interesting properties…  Reynolds Number (flow)  Re = L V avg ρ/μ

20  Interesting properties…  Reynolds Number (flow)  Re = L V avg ρ/μ ▪ L = most relevant length

21  Interesting properties…  Reynolds Number (flow)  Re = L V avg ρ/μ ▪ L = most relevant length ▪ ρ = fluid density

22  Interesting properties…  Reynolds Number (flow)  Re = L V avg ρ/μ ▪ L = most relevant length ▪ ρ = fluid density ▪ μ = viscosity

23  Interesting properties…  Reynolds Number (flow)  Re = L V avg ρ/μ ▪ L = most relevant length ▪ ρ = fluid density ▪ μ = viscosity  Re < 100

24  Interesting properties…  Reynolds Number (flow)  Re = L V avg ρ/μ ▪ L = most relevant length ▪ ρ = fluid density ▪ μ = viscosity  Re < 100  Re > 2000

25  Types of Flow

26  Pressure Driven Flow

27  Types of Flow  Pressure Driven Flow  http://faculty.washington.edu/yagerp/microfluidicstutorial/tutorialhome.htm http://faculty.washington.edu/yagerp/microfluidicstutorial/tutorialhome.htm

28  Types of Flow  Electrokinetic Flow

29  Types of Flow  Electrokinetic Flow  http://faculty.washington.edu/yagerp/microfluidicstutorial/tutorialhome.htm http://faculty.washington.edu/yagerp/microfluidicstutorial/tutorialhome.htm

30

31  What is it?

32  Programmable chip + microfluidics chamber

33  What is it?  Programmable chip + microfluidics chamber  Why do we need it?

34  What is it?  Programmable chip + microfluidics chamber  Why do we need it?  Larger quantities

35  What is it?  Programmable chip + microfluidics chamber  Why do we need it?  Larger quantities  Smaller objects

36  What is it?  Programmable chip + microfluidics chamber  Why do we need it?  Larger quantities  Smaller objects  DNA, living cells, droplets of chemical compounds

37  But how does it work?

38  DIELECTROPHORESIS (DEP)

39  But how does it work?  DIELECTROPHORESIS (DEP)  Non-uniform field  induced dipole

40  But how does it work?  DIELECTROPHORESIS (DEP)  Non-uniform field  induced dipole  Apply local e-field

41  But how does it work?  DIELECTROPHORESIS (DEP)  Non-uniform field  induced dipole  Apply local e-field  Different dielectric constant  force

42  F DEP = 2πε m a 3 CM(ω) Grad(E rms 2 )

43  Clausius-Mossoti factor

44  F DEP = 2πε m a 3 CM(ω) Grad(E rms 2 )  Clausius-Mossoti factor  CM(ω) = Re [ (ε p - ε m ) / (ε p + 2 ε m )]

45  F DEP = 2πε m a 3 CM(ω) Grad(E rms 2 )  Clausius-Mossoti factor  CM(ω) = Re [ (ε p - ε m ) / (ε p + 2 ε m )] ▪ CM(ω) < 0  nDEP

46  F DEP = 2πε m a 3 CM(ω) Grad(E rms 2 )  Clausius-Mossoti factor  CM(ω) = Re [ (ε p - ε m ) / (ε p + 2 ε m )] ▪ CM(ω) < 0  nDEP ▪ CM(ω) > 0  pDEP

47 http://www.blazelabs.com/pics/emep.gif

48

49  Voltage…

50  AC fields

51  Voltage…  AC fields  No ion shielding

52  Voltage…  AC fields  No ion shielding  Less harmful

53  Voltage…  AC fields  No ion shielding  Less harmful  5V CMOS process

54  Voltage…  AC fields  No ion shielding  Less harmful  5V CMOS process  Lower noise

55  Voltage…  AC fields  No ion shielding  Less harmful  5V CMOS process  Lower noise  Less heat

56  Yeast

57

58  Programming of large numbers of cells

59  Yeast  Programming of large numbers of cells  Assembly of tissue

60 Mammalian cells work too!

61  Rat alveolar macrophages

62 Mammalian cells work too!  Rat alveolar macrophages

63 Mammalian cells work too!  Rat alveolar macrophages  Presumably human cells work too!

64  APPLICATIONS!

65  Programmable chemistry

66  APPLICATIONS!  Programmable chemistry  Tissue assembly

67  APPLICATIONS!  Programmable chemistry  Tissue assembly  Art?

68  APPLICATIONS!  Programmable chemistry  Tissue assembly  Art?  … no one will be able to see it…

69 Microfluids

70 ARE

71 Microfluids ARE very useful when combined with an integrated circuit.


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