X-ray Absorption Spectroscopy studies at the GILDA

Transcription

X-ray Absorption Spectroscopy studies at the GILDA
beamline (ESRF): the role of ab-initio structural modeling
in data analysis
F. d'Acapito, CNR-IOM-OGG, [email protected]
Layout
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The GILDA beamline
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Ab-initio structural modeling for XAS analysis
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Layout
XAS station
Novel experimental techniques: XEOL and TR-XAS
BVM
DFT
MD (-DFT)
Conclusion
News from the GILDA beamline at ESRF
Beamline layout
Optic Hutch
•beam sizing
•mono-chromatization
• focalization
Control room
• Remote
instrumentation control
• Data analysis
3 Experimental cabins
• XAS Hutch (Instrumentation for XAS experiments)
• Diffraction Hutch (Instrumentation for XRD experiments)
• “Open Hutch” (Open to user’s experimental apparata)
F. d’Acapito et al. ESRF Newsletter 30 (1998), 42
A new MONO configuration
Si311
Si311
1st crystal split in two
●Si(311): 6-30keV
●Si(755) 18-90 keV
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Si755
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Access a wide energy range without intervention.
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XAS
3 experimental chambers
• Standard sample environment
• User’s sample environment
• ReflEXAFS
Fluorescence detectors
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2* multi elements HP-Ge
Resolution 200 eV @ 6.4 keV
Max CR 80kcps/element
Digital data collection
X-ray Emission Yield from sample (Arb. Units)
Excit. energy 28170 eV
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2 10
G. Ciatto et al. JSR 11 (2004), 278-283
Compton
Emission
fit
gaussian
background
Elastic
In-K
4
2.2 10
4
4

2.4 10
2.6 10
Energy (eV)
4
2.8 10
4
3 10
4
Time structures at ESRF
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16 bunches (spacing = 176 ns)
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4 bunches (spacing = 704 ns)
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X-ray pulse ~100ps.
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Stroboscopic pump-probe data collection possible even on a BM
beamline provided that
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Full bunch rate
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Reversible processes
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Process timescale << bunch spacing
Typical experimental layout
Data acq.
XAS
detect.
Sample
ESRF
RF
signal
Driver
Pulse generator
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sample excited in phase with the bunches
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Fixed time delay pump-probe
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Use of slow detectors.
XEOL
st
1 Lens
2nd Lens
Fibre
Sample
Detector
Detectors: Si-PIN diode and PMT
Range 300 – 1100 nm
2014: filters for band selection
The role of Structural modeling in the XAS data analysis
(and comprehension)
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XAS provides easily
– Distance with neighbors
– Number and nature of neighbors
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So, what ?
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Need of tools for interpreting the data in a more general vision.
Comparison with theories for structural prediction.
Easier job due to the increase of computing power in recent
years.
Bond Valence Model
I. D. Brown, The Chemical Bond in Inorganic Chemistry: The Bond Valence Model, Oxford University Press, 2002.
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Empirical method, useful for bonds with high ionic character
Defines a relation between the ith cation valence Vi, bond
length rij and number of neighbors
V i =∑bonds j sij
r ' o−r ij
B
si=e
Cation-anion parameters r'0 and B tabulated basing on crystal
structures
(http://www.iucr.org/resources/data/datasets/bond-valence-parameters)
Calculator:
http://www.esrf.eu/UsersAndScience/Experiments/CRG/BM08/Users/UserUtilities
Smalt: Co based potash glass (very basic).
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CoII ions, blue hue
● Tetrahedral environment
● Degradation to grey color with time (and humidity).
● K moves out from the glass grains. Loosing K the
glass becomes acidic.
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More acid environment: Co switches to octahedral
sites
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Deterioration of smalt pigment
1
BVM Co
0.8
2+
0.6
s
ij
N=4
0.4
N=6
0.2
1.94 A
2.09 A
0
1.6
1.8
2
2.2
2.4
2.6
2.8
3
3.2
R (Ang. )
ij
Modelign a octahedron distortion
CoII-O case
● BVM permits to
modelize the
distortion keeping
constant the valence
● Easily implemented
in XAS fitting codes.
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Using Bond Valence Model for XAS analysis
F. d'Acapito et al. JNCS accepted 2014
Mg+Er -doped Silica Optic Fiber preforms
● Looking for possible structural origin of the
modified optical response with growing Mg
content
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Density Functional Theory
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Necessary in a general case
Useful when bond parameters are not available.
Several powerful codes
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VASP
AbInit
Quantum Espresso...
Predictions
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Structure
Site energetics
M. Rovezzi et al.
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Main issue in Magnetic SMC: precipitates.
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QE code
● LSD-GGA-U
● U fixed from previous studies.
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Beamline SAMBA @ SOLEIL
● Structure simulated with DFT
● XANES calculated with Real Space
methods (FeFF)
● Evidence of Co
-VO complexes by
Zn
looking at the 1-2 valley and 3 peak.
● Complexes linked to the
magnetization saturation.
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What makes amethyst different
from other Fe-bearing quatz.
● Hypotesei
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Fe4+
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Fe3+ with Li or H
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Fe mainly as Fe3+
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Fe2+ < 20%
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DFT
● LSD-GGA-U
Site of Fe in amethyst
Fe3+ + H+
Fe4+
Color centers easily created in LiF upon X-ray exposure
● Useful for X-ray imaging.
● Pb added to increase sensitivity
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EXAFS data
DFT
●VASP
●64 atoms supercell
●GGA
Site energetics
Equilibrium
F2
PbF2
LiF
2µF=EF
µPb+2µF=EPbF2
µLi+µF=ELiF
̂ μ= ⃗
A∗⃗
E
⃗ =μ
Â−1∗E
⃗
E f =∑i N i∗μ i
Doping process
PbLi+VLi-f
 PbLi+VLi-n
Pbi+2VLi-f  Pbi+2VLi-n
MD-(DFT)
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Useful to simulate whole XAS/XANES spectra
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Careful ! Classic MD fails at low temp.
Computationally heavy
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Cases involving complex environments
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Many bond distances / ligands
High configurational disorder
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Additional Support to static DFT calculations
BM29 beamline, ESRF
● Hg-H O pair potentials
2
determined by QM methods
● Classical MD
● Equilibration time 5ns
● Snapshots every 12.5 ps
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MXAN code for XANES
generation
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Corresponding
structure with 2
shells of H2O
molecules
Experimental XANES data (dots) with the MDderived XANES spectrum
Evidence of 7 coordination for Hg
Method:
● Loeffen & Pettifer PRL 76 636
● Vila, Rehr, Rossner, Krappe, PRB 76 014301.
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Simulate the structure via DFT
● Calculate the dynamical matrix
● Calculate the DWF for the most important paths
● Simulate the spectrum
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DM codes non available for any DFT code.
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TEM from M. Jamet et al. Nature materials 5 (2006), 653
Energetics of the various structures
XAS data simulation via MD-DFT
DFT:
●LSDA-GGA
●96 atoms spc
MD
●1000 time steps, 2fs
●NVT
●T target 300K
●XAS: Last 200 frames
averaged
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The interface disorder of the
NC permits to reproduce the
XAS data
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Found Zn and Fe in yellow Pb animonates
● Presumably added on purpose
● Do they enter the structure of the crystal ?
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Zn site: static DFT
Zn in Pb
● Zn-O: 2*1.762, 6*2.679
● Zn-Pb: 6* 3.553
● Zn-Sb: 6* 3.669
Zn site: spectrum simulation
MD-DFT
NVT, 300K
● 1000 steps
● 2fs/step
● Last 200 spectra averaged
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Conclusion
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GILDA: well adapted to XAS on diluted systems
New opportunities: TR-XAS and XEOL
Ab-initio methods necessary for a more complete
interpretation of XAS data
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Site geometry
Site energetics
Dynamics

X-ray Absorption Spectroscopy studies at the GILDA

Transcription

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