Ab Initio Computation for Materials Characterization Elements of ICME Workshop, UIUC, July 2014

1. Ab InitioComputation for Materials CharacterizationElements of ICME Workshop, UIUC, July 2014 Maria Chan Center for Nanoscale Materials & CEES Energy Frontier Research Ctr Argonne National Laboratory

2. Collaborators • Lynn Trahey, Zhenzhen Yang, MaliBalasubramanian, Mike Thackeray, Tim Fister, Argonne National Lab • Jeff Greeley, Purdue University • Eric Shirley, NIST • Chris Wolverton, Northwestern University • Chris Buurma, TadasPaulauskas, Robert Klie, University of Illinois at Chicago • HadiTavassol, Maria Caterello, Andy Gewirth, David Cahill, UIUC

3. Materials Characterization stimulus material signal ??? machinery

4. Materials Characterization stimulus material = unknown arrangement of atoms + electronic/magnetic state signal ??? machinery

5. Materials Characterization stimulus photons (visible, x-ray, infrared) electrons, voltage, magnetic field, etc material signal ??? machinery synchrotrons, microscopes, spectrometers, etc

6. Materials Characterization stimulus signal: absorption, scattering, diffraction, image, current, etc material ??? machinery

7. Ab initio materials modeling DFT, QMC, etc {Properties} (e.g. energy, voltage, band structure etc)

8. Life goal of a computational materials scientist Skeptical experimental collaborator Confident experimental collaborator

9. Case studies: Li-ion & Li-O2 batteries Li-ion battery cathode anode electrolyte electrolyte Lithium anode porous air electrode Oxygen Li+ Li+ Li-O2 (“Li-Air”) battery

10. = X-rays Some x-ray characterization techniques • x-ray diffraction • crystal structures, lattice parameters • pair-distribution function • local coordination up to ~10Å • x-ray absorption/inelastic scattering • local electronic environment

11. Other modes of characterization Electrochemical characterization = current or voltage Electron microscopy = electron beam

12. X-ray Diffraction (XRD) 2d sin = n Image credit: Wikipedia

13. Li-air (Li-O2) battery Lithium anode porous air electrode electrolyte Oxygen How do electrocatalysts affect Li-O2 reaction? Li+ 2Li+O2Li2O2 or 2Li+½O2Li2O or?

14. MnO2: put Li/Li+O into tunnels? MnO2 ramsdellite-MnO2 O 2x2 2x1 Mn 1x1 DFT Calculations PBE+U ~200 structures Li

15. Energetics (& experience) suggest Li insertion into tunnels likely Mn Li O Li2O & Li2O2~ 3V LiMnO2 2.5-2.7 V Li0.5MnO2 3.2-3.5 V  increasing voltage 

16. LixOy insertion into tunnels also plausible Mn Li O Li2O & Li2O2~ 3V Li0.5. 0.25Li2O. MnO2 3.3V 0.125Li2O.MnO2 2.9 V  Predictions: LixOy go into tunnel, O removal kinetically limited Li2O2 unit 3.1 V LiMnO2 2.5-2.7 V Li0.5MnO2 3.2-3.5 V  increasing voltage  Trahey et al, Adv Energy Mat 2013, Ch. 5 in “The Li-air Battery” Ed. Imanishi 2014

17. Does this actually happen? Synchrotron XRD shows lattice parameter changes, but crystal structure mostly remains In-situ XRD changes during cycling Ref: Yang, Trahey, Chan, et al, in preparation

18. Lattice parameter changes MnO2 In-situ lattice parameters (a=b, c) change during cycling b a c

19. DFT also captures volume changes Li0. 25(Li2O)0.125MnO2 Li0. 5MnO2 but not individual lattice parameter changes, i.e. a/c ratio (compared to pure MnO2 ) (Li2O)0.125MnO2 hydrated MnO2 (H2O)0.125MnO2 XRD: Johnson et al, J Power Sources 1997

20. In-situ XRD data+DFTmodel consistent with Li+Oco-insertion e f b c d Amount of Li in tunnel Amount of Li2O in tunnel

21. But precise ratio not obtained e f ? b c d Amount of Li in tunnel Amount of Li2O in tunnel Need another technique e.g. x-ray absorption

22. Moral of the story • XRD is good for observing structural changes during a process for a mostly crystalline material • DFT calculations give approximate volume changes, but not perfectly accurate • Other techniques that measure electronic structures may be needed

23. X-ray Diffraction (XRD) & Non-resonant Inelastic X-ray Scattering (NIXS) Image credit: Tim Fister

24. A tale of two structures: Li2O2 Both proposed from XRD in 1950’s O-O distance 1.28Å 1.55Å • Formation energies from • density functional theory calculations Which one is the actual structure of Li2O2? DFT predicts Föppl– verification? Chan et al, J. Phys. Chem. Lett., 2, 2483 (2011)

25. X-ray diffraction patterns Errors (“Residuals”) × 3

26. Synchrotron vs “lab” XRD Cu K

27. NIXS better distinguishes between two measured calculated (ab initio Bethe-Salpeter Equation)

28. Moral of the story • XRD refinement is not always perfect! • DFT formation energies are strong indicators of relative phase stability, but independent verification is a bonus • Synchrotron XRD give additional information over lab XRD • NIXS is sensitive to local structures

29. Pair Distribution Function (PDF) & Electrochemistry Structure function X-ray Powder Diffraction Pair distribution function Image credit: Billinge, Z. Kristallogr. 219 (2004) 117

30. Lithiatingcr-Si – atomistic picture? carbon Si Carbon, transition metal oxides: Li goes into empty sites ? Li

31. LixSi: complex crystalline phases 0 0.1 0.2 0.3 0.4 V vs Li/Li+ …. which don’t form at room temperature (data is at 415C) x in LixSi 0 1 2 3 4 5 Wen and Huggins, J. Solid State Chem 37, 271 (1981)

32. ? Li Si

33. DFT simulation of Li insertion Surface Li Li sites relax 1 by 1 lowest energy Si Li Si repeat

34. Evolution of atomic configurations as amount of Li increases increasing Li content

35. Corroboration with PDF from APS Computed Si-Si radial distribution function Ex-situ measurements (at APS) Baris Key et al JACS 2011

36. Goldman, Long, Gewirth, Nuzzo Adv. Func. Mater. 2011 (111) (110)

37. Compare surface orientations: DFT simulation results (110) (111) (100) Different orientations: similar expansion at full lithiation

38. Anisotropy in lithiation voltages • V(110) > V(111) • insertion through (110) is more thermodynamically favorable • voltage  anisotropic expansion?

39. How does voltage difference lead to anisotropic expansion? Solution to diffusion equation crystalline Si amorphous LixSi time 10 m Note: Li enters side surfaces >> top surface isotropic diffusion coefficient Chan, Wolverton & Greeley, JACS 2012

40. Orientation-dependent voltage subsequently validated by experiment Pharr et al Nano Lett. 2012, 12, 5039

41. Moral of the story • PDF is suitable for amorphous/disordered materials and can be used for qualitative verification of DFT simulations • Prediction of a yet-unmeasured quantity is paramount for verification of any new modeling approach!

42. Electrochemistry and Surface Stress measurements

43. Au: model electrode What Li/Au surface processes occur before lithiation? Li Au model system: gold surface

44. Initiation of Li deposition @ ~ 1 V LiClO4 PC 1. onset ~ 1V ionic liquid

45. Large voltage range for Li deposition LiClO4 PC 2. broad reductive feature ionic liquid

46. Overlayer (upd) models Au 1.1V Li obtained from genetic algorithm using DFT

47. Voltage curve from overlayer model

48. Multilayers Li Au Considered 1-5 Li layers

49. Stress during deposition LiClO4 PC 3. stress: compressive & magnitude increases with more Li

50. Stress from Li overlayers • stress is compressive • magnitude increases with amount of Li • magnitude comparable to experiment