2. Putting a speed gun on macromolecules: what can we learn from how fast they go, and can we do something useful with that information? Monday, October 31 Cleveland State University National Science Foundation

3. Generic Talk Outline Thank hosts Tell joke, story or limerick Explain what we’re trying to do Explain what we actually did Today, that will lead naturally to applied things Thank accomplices This is what I mainly came to say!

4. There once was a theorist from France who wondered how molecules dance. “They’re like snakes,” he observed, “As they follow a curve, the large ones can hardly advance.” D ~ M -2 P.G. de Gennes Scaling Concepts in Polymer Physics Cornell University Press, 1979 P. G. de Gennes Nobel Prize Physics Tons per mole! Diffusion

5. When does the speed of polymers (and stuff dispersed in them) matter? How fast can it dissolve? How fast can we process it? How long until the additives ooze out? How long does it take to weld polymers together? How fast do chain termination steps occur during polymeriztion? How fast will phase separation destroy the polymer? Will an image on film (remember film?) stay sharp? Speed  Viscosity

6. DLS for Molecular Rheology of Complex Fluids: Prospects & Problems + + + Wide-ranging autocorrelators > 10 decades of time in one measurement! – – – Contrast stinks: everything scatters, esp. in aqueous systems or most supercritical fluids, where refractive index matching cannot hide the matrix. Studied a lot Barely studied

7. Translational Diffusion Leads to Intensity Fluctuations t Intensity

8. Rotational Diffusion Between Polarizers Leads to Intensity Fluctuations Crystalline inclusion Looking into the laser, vertically polarized dim bright Analyzer Polarizer

9. Dynamic Light Scattering  Hv = q 2 D trans + 6D rot LASERV H  PMT Hv Geometry (Depolarized) Uv Geometry (Polarized) V   Uv = q 2 D trans PMT LASER

10. DLS can be used for sizing if viscosity is known, for viscosity if size is known t IsIs DLS diffusion coefficient, inversely proportional to size. Large, slow molecules Small, fast molecules Stokes-Einstein Law D trans  = constant Also D rot  = constant

11. Correlation Functions etc. Where: G(  ) ~ cMP(qR g )  = q 2 D  q 2 kT/(6  R h ) R h = XR g g(t) log 10 t ILT  q 2 D G(  ) CALIBRATE MAP M c log 10 M log 10 D 

12. Strategy Find polymer that should not “entangle” Find a rodlike probe that is visible in DDLS Measure its diffusion in solutions of each polymer separately Random coil Polysaccharide Invisible in HvDLS Highly-branched Polysaccharide Invisible in HvDLS Rigid rod Virus Visible in HvDLS Dextran Ficoll TMV Find polymer that should (???) “entangle” BARELY

13. As expected, viscosity rises with c

14. Seedlings  Sick Plants  And close-up of mosaic pattern. DIY farming--keeping the “A” in LSU A&M

15. TMV Characterization Sedimentation, Electron Microscopy and DLS Most TMV is intact. Some TMV is fragmented –(weaker, faster mode in CONTIN) Intact TMV is easy to identify –(stronger, slower mode in CONTIN)

16. All measurements made at low TMV concentrations—no self-entanglement

17. Hv correlation functions for 14.5% dextran and 28% ficoll with and without added 0.5 mg/mL TMV The dilute TMV easily “outscatters” either matrix Matrix is invisible

18. Hey, it works!

19. I didn’t think—I experimented. ---Wilhelm Conrad Roentgen

20. Early results—very slight errors rotationtranslation Macromolecules 1997,30, 4920-6.

21. Stokes-Einstein Plots: if SE works, these would be flat. Instead, apparent deviations in different directions for D rot and D trans

22. Macromolecules 1997,30, 4920-6. At the sudden transition: L/  c.m. ~ 13 and L/  ~ 120 L   cm

23. rotation translation We believed that the transition represented topological constraints. It was suggested that more systems be studied. BEGIN FICOLL When we did Ficoll, many more points were added!

24. Huh? D rot still diving in Ficoll? rotation translation

25. Uh-oh, maybe we should think now.

26. The chiral dextran and ficoll alter polarization slightly before and after the scattering center. With a strongly depolarizing probe, this would not matter, but…  TMV = I Hv /I Uv ~ 0.003 While matrix scattering is minimal, polarized scattering from TMV itself leaks through a “twisted” Hv setup. Most damaging at low angles

27. Mixing in Polarized TMV Light Uv light from misalignTrue Hv light  q2q2 q2q2 q2q2 D rot too low 6Drot 

28. Even at the highest concentrations, only a few degrees out of alignment.

29. Slight, but important, improvement.

30. Improved D rot /D trans Ratio Plots

31. Improved Stokes-Einstein Plots Black = TMV Translation Blue = TMV Rotation

32. Hydrodynamic Ratio—Effect of Matrix M at High Matrix Concentration

33. Effect of Dextran Molecular Weight— High Dextran Concentration (~ 15%) TMV Translation TMV Rotation

34. Randy Cush David Neau Ding Shih Holly Ricks Jonathan Strange Amanda Brown Zimei Bu Grigor Bantchev Zuhal & Savas Kucukyavuz--METU Seth Fraden—Brandeis Nancy Thompson—Chapel Hill Summary: Depolarized DLS = new opportunities in nanometer-scale rheology. I cannot tell you the coolest part of this, but postdoc Grigor Bantchev found a trick that is definitely a treat!

35. “Too much dancing and not nearly enough prancing!” C. Montgomery Burns, “The Simpsons” Can probe diffusion actually do something?

36. Matrix Fluorescence Photobleaching Recovery for Macromolecular Characterization Garrett Doucet, Rongjuan Cong, David Neau, Others Louisiana State University Funding: NSF, NIH, Dow

37. Fluorescence & Photobleaching Blue input light Fluorescent Sample Green Detected Light

38. Recovery of Fluorescence Blue input light Fluorescent Sample With Fluorescence Hole in Middle Green Detected Light Slowly Recovers

39. Modulation FPR Device Lanni & Ware, Rev. Sci. Instrum. 1982 * * * * AOM M M D RR DM OBJ S PMT PA SCOPE TA/PVD ARGON ION LASER * = computer link IFIF XX c 5-10% bleach depth

40. Cue The Movie

41. Dextran Diffusion in Hydroxy- propylcellulose, a probe diffusion study: the more HPC, the more nonlinearity in semilog plots. Hmmm…. Bu & Russo, Macromolecules, 27, 1187 (1994)

42. Can FPR be used for MWD characterization? Questions bearing on this Need: are new analytical methods needed in a GPC/AFFF multidetector world? Ease of labeling the analyte? How hard to calibrate? Worth the price of setup? Miniaturization?

43. GPC Solvent flow carries molecules from left to right; big ones come out first while small ones get caught in the pores. Non-size mechanisms of separation complicate regular GPC, are much less of a problem for multidetector methods, but they correspondingly more complicated.

44. They were young when GPC was.

45. Small Subset of GPC Spare Parts To say nothing of unions, adapters, ferrules, tubing (low pressure and high pressure), filters and their internal parts, frits, degassers, injector spare parts, solvent inlet manifold parts, columns, pre-columns, pressure transducers, sapphire plunger, and on it goes…

46. Other SEC Deficiencies 0.05 M salt at 11 am, 0.1 M phosphate pH 6.5 at 1 pm? 45 o C at 8 am and 80 o C at noon? Non-size exclusion mechanisms: binding. Big, bulky and slow (typically 30 minutes/sample). Temperature/harsh solvents no fun. You learn nothing fundamental by calibrating. For straight GPC, what you measure is not what you calibrated. Good for qualitative work, otherwise problematic.

47. Must we separate ‘em to size ‘em? Your local constabulary probably doesn’t think so. Atlanta, GA I-85N at Shallowford Rd. A Saturday at 4 pm

48. Molecular Weight Distribution by DLS/Inverse Laplace Transform--B.Chu, C. Wu, &c. Where: G(  ) ~ cMP(qR g )  = q 2 D  q 2 kT/(6  R h ) R h = XR g g(t) log 10 t ILT  q 2 D G(  ) CALIBRATE MAP M c log 10 M log 10 D 

49. Hot Ben Chu / Chi Wu Example MWD of PTFE Special solvents at ~330 o C Macromolecules, 21, 397-402 (1988) Problems: Only “works” because MWD is broad Poor resolution. Low M part goofy. Some assumptions required.

50. Matrix Diffusion/Inverse Laplace Transformation Goal: Increase magnitude of  —this will improve resolution  Difficult in DLS because matrix scatters, except special cases. Difficult anyway: dust-free matrix not fun! Still nothing you can do about visibility of small scatterers DOSY not much better Replace DLS with FPR. Selectivity supplied by dye. Matrix = same polymer as analyzed, except no label. No compatibility problems. G(  ) ~ c (sidechain labeling) G(  ) ~ n (end-labeling) log 10 M log 10 D Stretching  Solution:   Matrix:  

51. The Plan to Measure M Using FPR Sample Analyze Using ILT Collect Data Using FPR Convert to Molar Mass by Mapping onto Calibration Plot

52. Labeling is Often Easy Dextran M = 2 Million Da as the matrix at different concentrations in 5 mM NaN 3 solution Pullulans of different M labeled with 5-DTAF as probes Pullulan 5-(4,6-dichlorotriazinyl)amino fluorescein

53. Matrix FPR for Pullulan (a polysaccharide) Probe Diffusion: Polymer physicsCalibration: polymer analysis

54. GPC vs. FPR for a Nontrivial Case 20,000 & 70,000 Dextran PL Aquagel 40A & 50A User-chosen CONTIN 25% Matrix  only ~1

55. How Good COULD it Be? Simulation of FPR Results for  = 2 (Most Desirable Situation)

56. What could we separate from 10K, according to  = 2 simulations? Shazamm!

57. Using an HPC Matrix  Indicates targeted M.

58. MFPR Conclusions We are entitled to expect something better than GPC. For some situations, MFPR could really work. What is good about GPC (straight GPC) is the simple concept; Matrix FPR keeps that—just replaces V e with D. We haven’t yet addressed two questions --Is it worth setting this up? --Miniaturization/Automation?

59. Macromolecules for The Demented and methods for their study Help from Keunok Yu, Jirun Sun, Bethany Lyles, George Newkome and LSU’s Alz-Hammer’s Research Team Krispy Kreme Donut Day, September 2003 Supported by National Institutes of Health-AG, NSF-DMR and NSF-IGERT How Alzheimer’s happens Attempts to prevent or reverse it Characterization challenges Alzheimer’s model systems with materials implications

60. PET images courtesy of the Alzheimer's Disease Education and Referral Center/National Institute on Aging; Postmortem images courtesy of Edward C. Klatt, Florida State University College of Medicine Positron emission tomography Age: 20 -- 80 Normal -- 80 AD Postmortem Coronal Sections NormalAlzheimer’s

61. http://www.bmb.leeds.ac.uk/staff/nmh/amy.html APP = Amyloid Precursor Protein APP = the larger, lighter pink one Transmembrane protein Normal function not known Educated guesses May help stem cells develop identity Or help relocate cells to final location May “mature” cells into structural type May protect brain cells from injury Synaptic action Copper homeostasis Anyway, you need it. Normal “clipping” of APP by a “secretase” enzyme (in red, and also assumed to be a transmembrane protein) is shown. There are several secretases, also associated proteins, and they seem to mutate easily: there is a genetic link. It is not exactly clear why things go awry with advanced age.

62. Amyloid hypothesis: fibrils or protofibrils cause cell death, possibly as the body’s own defenses tries to clear such “foreign” matter. Peter Lansbury Group http://focus.hms.harvard.edu/1998/June4_1998/neuro.html Competing hypothesis: channel formation disrupts Ca +2 metabolism

63. Two FPR Contrast Decay Modes are Often Observed: Fast = small; Slow = large.

64. Doing More Experiments Faster with Less Precious Amyloid: Dialysis FPR Cover slip PTFE spacer Dialysis membrane O-ring Sample Exchange Fluid Pump

65. Diffusion from in situ FPR of 5-carboxyfluorescein-A  1-40 (25% mixed with unlabeled 75% A  1-40 ) starting at pH 11, then alternately dialyzed between 50 mM phosphate (pH 2.7) and 50 mM phosphate (pH 7.4). Reversing Amyloid Aggregation…by pH

66. Probe diffusion works at fundamental and practical levels. Happy Halloween!

67. Examples of Separation Results from Simulation Data  Indicates targeted M.

68. Matrix FPR Chromatogram  Indicates targeted M. Sure this is easy. Also easy for GPC. But not for DLS or DOSY!

69. Cong, Turksen & Russo Macromolecules 37(12), 4731-4735 (2004) } 6 fractions from analytical scale GPC Enough for 100’s of FPR runs in ½ hour M w /M n ’s as now as good as anionically polymerized, patchy standards. Making the M vs. D calibration is fast & easy

70. “Cleanup on Aisle 1” Millipore Centricon -- http://www.millipore.com/userguides.nsf/docs/p99259 Millipore Centricon Device Pre-poured gel filtration columns are also very useful. Analytical scale GPC itself is a great way to clean up unreacted dye.

71. Why is the cup half empty?

72. Half empty, continued Pullulan (destran similar) dextran ( ● ), and pullulan probes ( ○ ).

73. No wonder the cup is half empty— no plateau modulus!

74. Correlations—suggests soft-sphere like behavior from branching of matrix.