17
Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sof Petko Petkov, Hristiyan Aleksandrov, Georgi N. Vayssilov University of Sofia, Bulgaria

Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

Embed Size (px)

Citation preview

Page 1: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

Density functional modeling of catalytic materials and adsorbents for potential industrial applications

University of Sofia

Petko Petkov, Hristiyan Aleksandrov, Georgi N. VayssilovUniversity of Sofia, Bulgaria

Page 2: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

2

Purification of hydrogen for fuel cell applications by transition metal exchanged zeolites

Other modeled systems Cerium dioxide nanoparticles:

Platinum clusters on CeO2

Surface carbonates Hydrogenated transition metal clusters Metal-organic frameworks (MOF)

Outline

Page 3: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

Purification of hydrogen for fuel cell applications by transition metal exchanged zeolites – DFT study

3

Complexes of small molecules with transition metal ions

Purification from CO

Purification from H2S and NH3

Page 4: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

4

Hydrogen for fuel cell applications

Proton-exchange membrane (PEM) FCs require highly

purified H2 feed due to poisoning of the noble metal

catalyst on the electrode by CO

Desired CO concentration in the feed: below 10 ppm

Strategies for purification:

Selective catalytic oxidation of the CO in H2 rich feed (PROX)

on different supported transition metal catalysts

Highly selective CO adsorption from the hydrogen feed at

ambient conditions Determination of adsorbents that allow to produce

ultrapure of hydrogen using thermodynamic data derived from computational modeling

Aleksandrov, Petkov, Vayssilov, Energy Environ. Sci., 2011, 4, 1879.

Page 5: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

Model and computational details

5

monoclinic unit cella = b = 13.675 Å, c = 7.540 Å

double cell: a = b = 13.675 Å, c = 15.08 Å

Unit cell

Periodic calculations (VASP) DFT: PW91 Ultrasoft pseudopotentials Γ point Energy cutoff 400 eV spin-polarized calculations for Ir+, Co+, and Ni+

force on each atom less than 2104 eV/pm

MOR structure

Page 6: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

Ag+ - thermodynamically unstable (ΔG>0 at 298 K)

Cu+ forms tetrahedral dicarbonyl complexes

All other cations form planar M(CO)2+ complexes

Rh(CO)2+ and Ir(CO)2

+ → more stable than the monocarbonyls7

M(CO)2+ complexes

-372

-86

-304

-232

-240

-280

2xΔG

-458

-180

-398

-334

-324

-372

2xΔH

-139-224Cu+

-127-223Ni+-187-289Co+

-445-544Ir+

14-74Ag+

-323-422Rh+

ΔGΔH

Cu(CO)2+ Ir(CO)2

+

M(CO)+ M(CO)2+

site-specificdicarbonyls

complex-specificdicarbonyls All values are in kJ/mol, ΔG at 298 K

Page 7: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

8

Purification of H2 from CO

Minimal CO concentration that can be achieved if most of the cations participate in

M(CO)2 and/or M(CO)

With dicarbonyl:Rh+: 2.610-10 Co+: 5.910-9 Ir+: 4.810-8

With monocarbonyls:Ni+: 7.710-17 Co+: 1.910-15 Cu+: 3.910-12

Additional advantage of Cu, Co and Ni – lower cost

M(CO)2 (dotted lines)

M(CO)2 + M(CO) (solid lines)

1 – {[M(CO)2] + [M(CO)]} < 10-5

< 10-5 of the metal centers to be involved in complexes other than that with the impurity

Page 8: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

9

Summary

Recommended adsorbent - Cu exchanged zeolite:

H2 purification down to CO concentrations of 10-12

Purifies H2 also from H2S and NH3

Lower price of copper compared to the other metals

For even deeper purification - Co or Ni exchanged zeolite to reach CO concentrations below 10-15

For zeolite with Si:Al ratio of 47 and feed with initial concentration of CO in hydrogen of 100 ppm,

1.00 kg of adsorbent (Co+, Ni+, Cu+) will purify 76 m3 H2

Aleksandrov, Petkov, Vayssilov, Energy Environ. Sci., 2011, 4, 1879.

Page 9: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

Modeling of cerium dioxide nanoparticles

10

Platinum cluster supported on ceria

Carbonate species on ceria nanoparticle

CeO2 - key component and support in heterogeneous catalysts:

automotive catalysts, WGS, preferential CO oxidation (PROX) ..

Main activity - oxygen storage and release

The release of O2 is accompanied by reduction of part of Ce4+ ions

CenO2n → CenO2n-1 + ½ O2 (nCe4+ → 2 Ce3+ + (n-2)Ce4+)

Page 10: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

Platinum of cerium oxide nanoparticles

Pt8 cluster on the CeO2 - formation of Ce3+ due to electron transfer

Oxygen spillover from CeO2 to Pt8 cluster

favored on nanoparticles but disfavored on regular CeO2(111)

generates large fraction of Ce3+ ions

Vayssilov, Lykhach, Migani, Staudt, Petrova, Tsud, Skála, Bruix, Illas, Prince, Matolín, Neyman, Libuda, Nature Mater. 10, 310 (2011).

Page 11: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

Carbonates on CeO2 nanoparticles

Computational modeling resulted in:

new assignment of the vibrational bands in the complex IR spectra of surface carbonates on ceria

reliable detection of the surface species on ceria surface, which is critical for clarification of the mechanisms of the rich variety surface processes on ceria

Page 12: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

Hydrogen spillover on transition metal clusters in zeolites

14

Confirmed for Rh6/zeolite

MD simulation of the process

Н+

Н-

Bare adsorbed cluster Hydrogenated cluster

218262Rh6H3/zeo

237251Rh6/zeo(3H)

214268±4Experiment

Rh-Oz<Rh-Rh>

Vayssilov, Gates, Rösch Angew. Chem. Int. Ed. 42 (2003) 1391

ERS = -120 kJ/mol per transferred HOxidation of the metal moiety: q(Rh6)=~2.0 e

Page 13: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

15

10ps MD run

Page 14: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

16

Modeling of metal-organic frameworks

Search of materials for hydrogen storage

Clarification of the catalytic active centerse.g. in Au-functionalized MOFs

Understanding the structure and chemical/sorption behavior of defects in MOFs

Page 15: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

17

Other computationally demanding problems

Dynamics of noble (Au, Pt) metal nanowires in cavities or on surfaces

Simulation of hydrogen production from water on ceria

Dynamical behavior and stability of defects in MOFs

……..

Page 16: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

18

Acknowledgments

Bulgarian Supercomputing Center

Center of Excellence “Supercomputing Applications”

HPC Europa2 at Barcelona Supercomputing Center

National Center of Excellence on Advanced materials UNION

Page 17: Density functional modeling of catalytic materials and adsorbents for potential industrial applications University of Sofia Petko Petkov, Hristiyan Aleksandrov,

19