1. Small Angle Neutron Scattering (SANS) A DANSE Subproject DANSE Kick-Off meeting Aug 15-16 Pasadena CA Paul Butler

2. SANS measures time averaged structure of 1 – 300 nm or more Mesoporous structures Biological structures (membranes, vesicles, proteins in solution) Polymers Colloids and surfactants Magnetic films and nanoparticles Voids and Precipitates

3. Velocity selector 2D detector sample L1L1 L2L2 Neutron Guide Beam attenutator Sample Aperture, A 2 Source Aperture, A 1 Anatomy of a SANS instrument Sizes of interest = “large scale structures” = 1 – 300 nm or more 0.02 < Q ~ 2  /d < 6 Q=4  sin  / 3-5< <20A and 0.1 <  <20 64 cm - 1m 20 – 40 k pixels

4. 1) Scattering from sample 2) Scattering from other than sample (neutrons still go through sample) 3) Stray neutrons and electronic noise (neutrons don’t go through sample) Stray neutrons and Electronic noise Incident beam aperture air sample cell Contribution to detector counts Sample Scattering I meas (i) = Φ t A ε(i) ΔΩ T c+s [(dΣ/dΩ) s (i) d s + (dΣ/dΩ) c (i) d c ] +I bgd t

6. Small Angle Neutron Scattering (SANS) |3-D Fourier Transform of scattering contrast| 2 normalized to sample scattering volume Slide Courtesy of William A. Hamilton Reciprocity in diffraction: Fourier features at Q S => size d ~ 2  /Q S Intensity at smaller Q S (angle) => larger structures Measure: Scattered Intensity => Macroscopic cross section = (Scattered intensity(Q) / Incident intensity) T d Macromolecular structures: polymers, micelles,complex fluids, precipitates,porous media, fractal structures

7. Uniqueness of models

8. SANS Model Independent Concepts At large q: S/V = specific surface are 10 % black 90 % white

9. SANS more detailed analysis 1 P(Q) = form factor (shape) Q S(Q) = Structure factor (interactions or correlations) or Fourier transform of g(r)

10. Fourier transform P(r) r Frequency Paid Distance Distribution Function PDDF Shape reconstruction (ab initio)

11. Analytic form Modeling Structural modeling Free form modeling At the same time we want: Add constraints In 2D.. For oriented objects Optimization with data based on some set of parameters Non particulate (i.e no P(Q) and S(Q) separation (e.g. Sponge) G(r) (interactions) – allowing easy input of new ones important Complicated additions based on specific model (e.g. waters of hydration, exchangeable protons Conformational or other search MC and MD ↔ I(Q) Time resolved (and other parametric studies AND (of course) Intuitive and easy to use and extend Graphical interface with full 3D visualization Preferably with automated guidance and idiot guards …. Fast (interactive as much as possible) So.. SANS DATA Analysis.. Let’s DANSE

12. I Get software from somewhere: IGOR macro package distributed from NIST (latest release last month) Grasp distributed by ILL (reduction mainly but used for vortex lattices) ATSAS 2.1 distributed by Dimitri Svergun EMBL (latest release this year) An eclectic array of routines available from various sources (ISIS maintains a site) II “Do-it yourself” (mostly command line fortran – barrier to doing new stuff) III Minimal Analysis (bigger, smaller, slope of xxx …. fractal?) Choices for Today’s user

13. Steps to the DANSE 1.Analytical model fits to 2D data sets and model independent fits 1.Include orientation with respect to beam 2.Include instrument resolution 3.Include orientation and resolution corrections 4.Include parametric analysis and simultaneous fitting 5.Include intelligent defaults and intelligent help 2.Ab initio (free form) modeling and P(R) 1.include most popular approaches (dummy atom, spherical harmonics, etc) 2.Include intelligent help, and defaults 3.Include “limit switches” 3.Modeling of arbitrary shapes (including inversion to P(R)) 1.3D model building from simple shapes 2.Coarse grain PDB file 3.Invert real space model to I(Q) 4.MC and MD simulations for complex interacting systems 5.Refinements based on constraints 4.Full instrument simulation with plug in sample for experimental planning

14. First step

15. I NIST and ORNL heavily involved -- Fall meeting planned to determine: Short term plan for collaboration and distribution of analysis software How to structure the short term plan to take advantage of DANSE components as soon as they become available Plan for smooth long term transition to new system Some questions: How do we co-ordinate with ATSAS, how to incorporate X-ray, is PDB sufficient or do we need a second “standard” II Other interested facilities US Los Alamos and IPNS International SANS instrument scientists interested: ILL ISIS ANSTO HANARO III First contacts with most well known SANS algorithm developers Svergun Glatter Pederson DANSE card

16. When the Music Stops: Beyond DANSE The goal is NOT software - it is to extract all possible information from the material being studied. Neutron scattering from the user’s point of view is a process in which the sample is placed in the machine and the relevant, meaningful information comes out the other end. Good software enables that process. The DANSE project is not the end but the beginning. It cannot deliver everything. Rather it must meet two objectives: 1.Provide baseline software that includes: 1.A library of well documented and tested re-usable components 2.Basic applications with sufficient new value to attract large numbers of users 3.A new vision of ease of use as a means of fully utilizing the heavy invetsments in hardware For success must do 3 things: Must provide everything that is commonly doable with today’s packages Must provide new functionality not commonly available with today’s packages Must provide an easy framework for extension and contribution by the community

17. THE END

18. Steps to the DANSE (I)

19. An application for protein conformational study by SANS Have been told the need of such program more than a year ago Two study cases: –domain hinge movement of yeast guanylate kinase from unligated to GMP binded –The inconsistence between the crystal structure and SANS data of a protein

20. Protein motions –http://molmovdb.mbb.yale.edu/molmovdb/ SANS is a unique technique for domain orientations, conformational changes and/or flexibility under near physiological conditions Software for shape determination (including sophiscated method to retrieve complexed shape using sphere harmonics and debye formula) from SANS data –Over-interpretation? Fact: extract 3D data from 1D data Major mechanisms of motions are “hinge” and “shear” By directly starting from high-resolution structures and moving the subunit (hinge or shear) with subunits’ structure restrained, we can reduce the ambiguity and study the conformational changes –Expanding PDB data bank with atomic-resolution structures –Available software to link high-resolution structures to SANS data There is no such tool that allows users easily manipulate protein’s conformation through interactive way and link the conformations to SANS data at run-time

21. Testing files for each components (tested both C and Python codes) and a simple GUI application

22. Working Progress Package SANSsimulation –Available components (for sphere and hollow sphere only): analmodelpy: new_analmodel(), calculateIQ() pointsmodelpy:new_loresmodel(), fillpoints(), distdistribution(), calculateIQ geoshapespy: new_sphere(), new_hollowsphere() iqpy: new_iq(), outputIQ()

23. Class Diagram

24. Required components

25. Budget profile SANS

26. UML Use Cases for SANS Analytic form Modeling User Analysis Simulate Reduce Structural modeling Free form modeling

27. Staffing plans SANS + QA SANS: Project Leader: Paul Butler Postdoc 1 (Current developer): Jing Zhou Postdoc 2 : start hiring process during first year to bring on board in year 2 Grad Stud 1: UMBC – eventually working with UT Biochemistry department and SNS/CSMB Tennessee FTE by Resource Type 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 year 1year 2year 3year 4year 5 PostdocTech WriterGrad StudentUndergrad OtherAdministrative SupportMinority StudentQuality Assurance

28. UML Activity Diagram (w/o start-stop) NeXus reduction B v K {C1XX’,...}  /M |QU  exp(iQr)| 2 Compare, Alter (C1XX,..} g(E) phononthermo.py Z, F, S LaptopLinux Cluster SNS Archive SNS g nw (E) d  /d  (Q)

29. What we plan to do II Build Executive level application Executive level: Data manager Parametric series manager Reduction Analytic forms Ab initio modeling “modeling” Instrument simulation NEW Packages Data Data manager Parametric series manager

30. Application Specification (from PEP)

31. Specular Neutron Reflection |1-D FT of depth derivative of scattering contrast| 2 / Q  R 4 Slide Courtesy of William A. Hamilton At lower Q  R, R reaches its maximum R=1 i.e. total reflection Similar to SANS but... This is only an approximation valid at large Q  R of an Optical transform - refraction happens Layered structures or correlations relative to a flat interface: Polymeric, semiconductor and metallic films and multilayers, adsorbed surface structures and complex fluid correlations at solid or free surfaces Measure: Reflection Coefficient = Specularly reflected intensity / Incident intensity

32. Specular Reflectivity vs. Scattering length density profiles Critical edge R=1 for Q R <Q C Q C =4(  ) 1/2  T Bragg peak a Q R =2  /a  Q R =2  /T sld step   Thin filmMultilayer Fourier features (as per SANS) Fresnel reflectivity Slide Courtesy of William A. Hamilton Thin film Interference fringes

33.  small θ … how Sizes of interest = “large scale structures” = 1 – 300 nm or more 0.02 < Q ~ 2  /d < 6 Q=4  sin  / Cold source spectrum  3-5< <20A Intensity  balance sample size with instrument length Approaches to small θ: Small detector resolution/Small slit (sample?) size Large collimation distance

34. Δθ Sizes of interest = “large scale structures” = 1 – 300 nm or more SANS Approach QSQS kiki kSkS SSD SDD ≈ S 1 ≈ 2 S 2 Optimized for ~ ½ - ¾ inch diameter sample 2 θ S1 3m – 16m 1m – 15m

35. Sizes of interest = “large scale structures” = 1 – 300 nm or more NR Approach θ ? ? = L s sinθ QRQR kRkR kiki Point by point scan ? ~ 1mm for low Q Ls

36. Sizes of interest = “large scale structures” = 1 – 300 nm or more QSQS kiki kSkS Ultra Small Angle Approach – when SANS isn’t small enough Point by point scan - again Fundamental Rule: intensity OR resolution … but not both  

37. I meas = Φ A ε t R +I bgd t Rocking Curve  i fixed, 2  f varying Specular Scan 2  f = 2  I  f =  i ii 2f2f Background Scan  f ≠  I

38. When measuring a gold layer on a Silicon substrate for example, many reflectometers can go to Q > 0.4 Å -1 and reflectivities of nearly 10 -8. However most films measured at the solid solution interface only get to 10 -5 and a Qmax of ~ 0.25Å -1 Why might this be and what might be done about it. (hint: think of sources of background) SANS is a transmission mode measurement, so with an infinitely thick sample the transmission will be zero and thus no scattering can be measured. If the sample is infinitely thin, there is nothing to scatter from…. So what thickness is best? (hint: look at the I meas equation) For a strong scatterer, a large fraction of the beam is coherently scattered. This is good for signal but how might it be a problem? (hint: think of the scattering from the back or downstream side of the sample)

39. Given the SANS pattern on the right, how can know what Q to associate with each pixel? (hint use geometry and the definition for Q) NR and SANS measure structures in the direction of Q. Given the NR Q is in the z direction, can NR be used to measure the average diameter of the spherically symmetric object floating randomly below the interface? USANS gets to very small angle. However SANS is a long instrument in order to reach small angles. Why not make the instrument longer? (Hint: particle or wave?) QRQR kRkR kiki D

40. Velocity selector 2D detector sample L1L1 L2L2 Neutron Guide Beam attenutator Sample Aperture, A 2 Source Aperture, A 1

41. Fundamentals of neutron scattering 100 Neutron diffraction 101 Nobel Prize in physics Neutron Scattering 102: SANS and NR Pre-requisites: Grade based on attendance and participation Paul Butler

42. SANS and NR measures interference patterns from structures in the direction of Q SANS and NR assume elastic scattering QRQR kRkR kiki 2R2R ii ff QSQS kiki kSkS incident beam wavevector |k i |=2  / scattered beam wavevector |k S |=2  / 2s2s Neutron Reflectometry (NR) Reflection mode Small Angle Neutron Scattering (SANS) Transmission mode  f =  i =  R k R = k i +Q  R Q  R =4  sin  R / Perpendicular to surface k S = k i +Q s Q s =|Q s |=4  sin  s /

43. 1) Scattering from sample 2) Scattering from other than sample (neutrons still go through sample) 3) Stray neutrons and electronic noise (neutrons don’t go through sample) We need MORE measurements Stray neutrons and Electronic noise Incident beam aperture air sample cell Contribution to detector counts Sample Scattering

44. SANS and NR measure structures in the direction of Q only SANS and NR assume elastic scattering SANS is a transmission technique that measures the average structures in the volume probed NR is a reflection technique that measures the z (depth) density profile of structures strongly correlated to the reflection interface Thinking aids: SANS I meas (i) = Φ t A ε(i) ΔΩ T c+s [(dΣ/dΩ) s (i) d s + (dΣ/dΩ) c (i) d c ] +I bgd t NR I meas = Φ A ε t R +I bgd t Summary

45. MA CA NC Rg = 31Å image A VISION constraints High resolution structure Protein Data Bank

47. When life is easy

48. smear_parameters_csssmear_coef_cssW_sigma scale0.010 core radius (A)43.80810.130794 shell thickness (A)18.29790.190327 Core SLD (A-2)6.15162e-061.80823e-05 Shell SLD (A-2)3.14889e-061.80825e-05 Solvent SLD (A-2)6.26021e-061.80778e-05 bkg (cm-1)0.006279940.00012066

49.  R =  C exp[-E F /k B T]  EF = 6.7kBT (170 meV) PRL 2004 “c” L  L3L3  R =0.40  0.08 s

50. Beyond the Sponge to Lamellar Transition- A Lamellar Collapse: (when life starts to get really hard) Simultaneous fits SLD,bgd,membrane thickness fixed x z Model: polydisperse aligned prolate ellipsoidal shells (vesicles) Qx semi-major axis ~ 520Å along flow direction Qz semi-minor axis ~ 225Å Structural analysis of a 4% Lamellar at 1500 s -1 Something is still missing

51. SANS: a plan Project Leader: Paul Butler Advisors: Sean Langridge, Dean Myles Postdoc 1: (Current developer): Jing Zhou Start hiring process in middle of first year to bring on board in year 2 Grad Students: UMBC and UT Work with ORNL’s CSMB and SANS team Work with NIST SANS team and Structural bio group Plans for international steering committee PostDoc and other developer FTE by year 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 year 1year 2year 3year 4year 5 Total Funding Profile $- $200 $400 $600 $800 $1,000 $1,200 $1,400 year 1year 2year 3year 4year 5 Incremental Funding ProfileCumulative

52. Clay polymer gels at rest When life starts to get hard Clay polymer gels under shear

53. I(Q) P(r) Fourier transform r Frequency How does one really calculate a theoretical Intensity

54. User-interactive GUI application Link the conformational changes to SANS data –Example –showing the I(Q) for the corresponding conformation in Run- time Mouse click to move selected subunit –VMD provide shear movement but no hinge movement Plan: start with the existing codes which uses VTK to load PDB files into 3D graphics and move models around –Other requirements: program CRYSON or XTAL2SAS and a 2D plotter Immediate usage at NIST Future distribution for broad users

55. Motivation: Structural studies of protein and nucleic acid complexes in solution CRP protein (yellow ribbon) and the DNA (blue spheres) Krueger et al., Biochemistry, 47(7), 1958-1968, 2003

56. UML Use Cases for SANS Analytic form Modeling User Analysis Plan Experiment Reduce Structural modeling Free form modeling Simulate