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Structure determination of triacylglycerols from powder diffraction data

Structure determination of triacylglycerols from powder diffraction data. René Peschar Laboratory for Crystallography Universiteit van Amsterdam The Netherlands. Overview. Introduction Why structure determination of TAG’s? Why Powder diffraction data X-ray diffraction and crystals

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Structure determination of triacylglycerols from powder diffraction data

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  1. Structure determination of triacylglycerols from powder diffraction data René Peschar Laboratory for Crystallography Universiteit van Amsterdam The Netherlands

  2. Overview • Introduction • Why structure determination of TAG’s? • Why Powder diffraction data • X-ray diffraction and crystals • Powder diffraction • Structure determination using powder diffraction data • Application to triacylglycerols • Conclusion

  3. Scheme of bloom formation on chocolate

  4. Introduction • Melt and crystallization behaviour of (natural) fats and triacylglycerols • (Natural) fats consist mainly of triacylglycerols • Phase transition behaviour • Explanation at atomic level => structure information • In solid state: crystalline! • X-ray diffraction (Single crystal/powder)

  5. X-ray diffraction and crystals • Crystal: regular 3D stacking of identical units • X-rays on crystal => diffraction (Bragg’s Law) • Single crystal (0.1 mm) : 3D diffraction pattern • Triacylglycerols single crystals difficult to grow • => Powder diffraction

  6. Bragg’s LawAll waves scatterd by the planes (hkl) must be in phase 2dhkl sin(qhkl) = n l

  7. X-ray diffraction • Intensity Ihkl  | Fhkl|2 • Structure factor Fhkl = | Fhkl| exp (ijhkl) • Atomic coordinates xj,yj,zj • Electron density r (x,y,z) • Maxima in r (x,y,z) are the xj,yj,zj • Phase problem: jhkl unknown

  8. Powder diffraction • Small crystals ( <10 mm) • Uniformly oriented sample (flat sample/capillary) • Diffraction gives: • ‘ID’ diffraction pattern Intensity (I) vs 2q • Application: • (Qualitative) identification • e.g. Polymorphs cocoa butter or TAGs • Crystal Structure determination • chain packing, atomic positions) • => 3D periodic electron density

  9. Polymorphs of cocoa butter

  10. Prerequisites for a successful structure determination from powder data • Sample preparation • Data collection • Pattern fitting and indexing • Choice of structure determination technique

  11. Sample preparation • Capillary diameter (0.3-1.5 mm) • Wavelength ! • Absorption • Particle statistics (Capillary 0.3 mm) • Preferred orientation • Laboratory data collection beforehand!

  12. Data collection • Synchrotron (if possible) FWHM = 0.04 • Wavelength (l > 0.8 Å) • Small slit size (reduce peak asymmetry at low 2q) • Data collection protocol • Reciprocal lattice point density vs exposure time • Total exposure time (~ 8 h) • Start at lowest possible 2q • 0-30 • 10-30 • 20-30 • Step size 0.005° 2q

  13. Pattern fitting and indexing • Extract intensity maxima • Background • Peak profile (e.g. Pseudo Voigt) • Auto-indexing programs (eg ITO, TREOR, DICVOL) • Check pattern if all maxima are covered (eg CHEKCELL, see CCP14 home page) • Extract reflection intensities and/or cluster intensities

  14. Pattern indexing E.g. orthorhombic lattice: (1/dhkl)2 = (h/a)2 + (k/b)2 + (l/c)2

  15. Results from powder data

  16. Choice of structure determination technique • ‘Traditional’ single-crystal methods • Patterson, Direct Methods, incl. maximum entropy/maximum likelyhood • Reciprocal space • No complete initial model required • Individual reflection intensities • Atomic resolution • Direct space grid search methods • Direct space • Complete model • Some but not all individual intensities required • Grid search, Monte Carlo, Simulated Annealing, Genetic algorithm

  17. Structure of C13C13C13

  18. Direct space grid search techniques • Basic assumption: • Almost complete structural model or fragment: standard inter atomic distances and angles (or from similar structure in data base, or via molecular modelling) • Structure can be expressed in terms of a set of 6+n variables (degrees of freedom): • Position (x,y,z) of a specific atom • Eulerian angles (q,j,y) • n Torsian angles t1,t2,….,tn

  19. Stereochemical model (trial model) • Build from stereochemical descriptors in Cartesian coordinate system • interatomic distances • interatomic angles • dihedral angles (torsian angles) • transform model to crystallographic unit cell • Take similar model • e.g. from Cambridge Structural Database. Modify wherever necessary (standard bond lengths, angles), optionally using Molecular Modelling (eg Cerius2TM)

  20. Grid search direct space • General algorithm • Generate trial structures(s) • Calculate powder diffraction pattern/intensities/structure factors • Compare with experimental data • Accept or reject on basis of a criterion function • Advantage: Extraction of all individual intensities not required. Degrees of freedom determine complexity of global optimization problem • Disadvantage: Model should be realistic; time consuming

  21. Consistency criterion Single (resolved) reflection Xj(obs) = Ihkl Cluster of overlapping reflections Xj(obs) = S Ihkl Correct solution: low R(X) ( < 0.5)

  22. Grid search implementation • Systematic change of variable values (pre-defined grid increments) • Extract 50-300 low-angle individual intensities X=I or clusters of overlapping intensities X= S I in full pattern decomposition • Perform rotation (steps 10-30°) and translation searches (0.5-0.6Å) • For minima found: decrease steps to 5° - 1° and 0.1 Å • Torsion angle searches (initially 20° => 5°) • Advantage:minimum in criterion function R(X) not likely to be missed • Disadvantage:Time-consumpton can become prohibitive if degrees of freedom is large MRIA system (local version) Zlokazov V.B. and Cherneyschev V.V. (1992) J Appl. Cryst. 25 - 447-451 (MRIA) Chernyshev V.V. and Schenk H. (1998) Z. Kristallogr. 213, 1-3 (Grid Search)

  23. Refinement • Bond-restrained Rietveld refinement • e.g. Baerlocher, 1993 • Very small parameter shifts • Coupling Uiso

  24. Nomenclature of some fatty acids Chain: double bond 10:0 decanoic C(apric) 12:0 dodecanoic L(auric) 13:0 tridecanoic 14:0 tetradecanoic M(yristic) 15:0 pentadecanoic 16:0 hexadecanoic P(almitic) 17:0 heptadecanoic 18:0 octadecanoic S(t)(earic) 18:1 octadec-cis-9-enoic O(leic) 18:1 octadec-trans-9-enoic E(laidic) 19:0 nonadecanoic 20:0 icosanoic A(rachidic)

  25. Structures of triacylglycerols on the basis of powder-diffraction data • b-CnCnCn (n=even; 14 =MMM, 18=SSS) • b-CnCnCn (n=13,15,17,19) • b’-CnCn+2Cn (n=14; MPM) Poster: The structure of b’-PSP and b-PSP

  26. References (ESRF beam-line used) 15.15.15; 17.17.17; 19.19.19 Helmholdt R.B., Peschar R. and Schenk H. (2002) Acta Cryst B58, 134-139 (BM16) MMM; SSS Van Langevelde A., Peschar, R. and Schenk, H. (2001) Acta Cryst B57, 372-377 (BM01B, BM16) 13.13.13 Van Langevelde A., Peschar, R. and Schenk, H. (2001) Chem. Mater. 13, 1089-1094. (BM16) MPM; CLC (Single Crystal) Van Langevelde, A., Van Malssen, K.F., Driessen, R., Goubitz, K., Hollander, F., Peschar, R., Zwart, P. and Schenk, H.. (2000) Acta Cryst. B56, 1103-1111 (ID11, BM16)

  27. CnCnCn (n=even) series • Structures are homologous, Unit cell transformed • CCC(10.10.10), LLL(12.12.12),MMM(14.14.14),PPP(16.16.16)

  28. CnCnCn (n=even) series • Structures are homologous, Unit cell transformed • CCC(10.10.10), LLL(12.12.12),MMM(14.14.14),PPP(16.16.16)

  29. Structures of triacylglycerols on the basis of powder-diffraction data • b-CnCnCn (n=even; 14 =MMM, 18=SSS) • b-CnCnCn (n=13,15,17,19) • b’-CnCn+2Cn (n=14; MPM) Poster: The structure of b’-PSP and b-PSP

  30. Melting point alternation Larson (1966): melting point alternation for long-chain compounds is caused by differences in packing densities at the layer interface Lutton and Fehl (1970)

  31. Triacylglycerol cell parameters

  32. Melting point alternation CnCnCn (Left, A: n=odd, right, B: n=even) For n=odd packing is less dense, so a lower melting point

  33. Structures of triacylglycerols on the basis of powder-diffraction data • b-CnCnCn (n=even; 14 =MMM, 18=SSS) • b-CnCnCn (n=13,15,17,19) • b’-CnCn+2Cn (n=14; MPM) Poster: The structure of b’-PSP and b-PSP

  34. The b’ structure of CLC and MPM • Homologous

  35. The b’ structure of CLC and MPM • Homologous

  36. The b’ structures of CLC and MPM • Bend molecules • Orthogonal zigzag planes

  37. Packing diagrams of b’-CLC Top: Along the b-axis, showing the bending of the molecules Bottom: Along the c-axis, showing the chain packing Notice: flat methyl-end planes

  38. b’-CnCn+2Cn vs b-CnCnCn structures CLC (Chair I, II, III) PPP (Tuning fork, I, III, II)

  39. Triacylglycerol conformations Chair Tuning fork

  40. Conclusion Crystal structure determination of triacylglycerols on the basis of powder diffraction data is possible, provided • Well-prepared sample • High-resolution (synchrotron) data • Pattern can be indexed • Homologous model available

  41. Laboratorium voor Kristallografie, Universiteit van Amsterdam, The Netherlands V. Chernyshev (Moscow State University) D.J.A. De Ridder E. Dova R.A.J. Driessen K. Goubitz R.B. Helmholdt A. van Langevelde K.F. van Malssen J.B. van Mechelen M.M. Pop H. Schenk E. Sonneveld P. Zwart ESRF (Grenoble, France) Staff at BM16 and BM01b NWO/CW Netherlands Foundation for Chemical Research STW Netherlands Technology Foundation Unilever Acknowledgements

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