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Computational and literature investigation to understand the
mechanism behind the catalyzed hydrogenation of CO2
- Darrell Nelson
Outline I. Background
II. Attacking the Problem
III. Metal Oxides
IV. Mechanism
V. Additional Factors
VI. Future Work
Background
Converting CO2 into useful fuels (i.e. methanol, methane)
(MTO) Methanol to Olefins (i.e. ethylene, propylene)
Create CO to be used as syngas
1$27 billion annual market for ethylene glycol
1. © 2013 Liquid Light Corporation. All rights reserved. | www.llchemical.com
2
35,000 Mt produced per year 27,000 MtCO2
3
Energy Crisis
Over 7 billion people in the world
Depleting energy sources rapidly
Economies of both China and India are growing
Creating scarcity of natural resources
2 problems 1 solution Hydrogenation of CO2 instead of sequestration
Stops emissions and provides very cheap fuel can be used again and again
Attacking the problem
CO2 is a very stable and oxidized form of C Linear molecule No strain Add a high energy electron makes it unstable
Catalyst lifetime
4
How to unravel this complex system?
𝐴+𝐵 𝐴𝐵CAT
How to make the best catalyst?
What is the composition/structure of the catalyst Bulk structure (lattice) Surface composition Subsurface composition “Active Sites”
How to make the best catalyst?
What is the reaction mechanism?
Surface chemistry is dynamic
Active Sites are changing
5
How to make the best catalyst?
4
4
Metal Oxides (Chosen catalyst)
e.g. (Al2O3, SiO2) High surface area Very stable under usual chemical reaction conditions Reduced metal oxides (i.e. CuO, Ce2O) that can change their oxidation
states and have vacancies in their structure upon release/storage of oxygen Diffusion from the bulk
4
Optimization Problem
Keeping the reactivity high involves not changing the catalyst. But, reactivity means that the catalyst is unstable and willing to change.
Using an industrial high-throughput approach to find the maximum between lifetime and reactivity
What is the chemistry? As you can see from previous slides Surface properties of the catalyst are the most
important (e.g. solid acid/base)
CO2 is a Lewis acid
Look at materials that are willing to donate electrons Low valent ion oxides are preferred
Correlation
0 0.5 1 1.5 2 2.5 3 3.50
10
20
30
40
50
60
70
80
Activation vs Conversion
Activation Energy
% C
O2 co
nver
sion
Statistical Analysis
Highest conversion came from Ni and Fe
46 out of 287 Ni, 34 out of 287 Fe
Mechanism (microscopic)
Understanding mechanism sheds light on the “why and how” Create a high performance catalyst based off of its properties and not
through trial and error Adsorption creates carbonate group on M.O. (not MgO)
Why not MgO? What’s special/different? Makes sense to use compounds that have coordinated oxygens because of
their high electronegativity The electronegativity of oxygen activates the binding sites
5
Note on transition states
3H2 + CO2 CH3OH + H2O
6Some elements help facilitate other parts of the reaction (Pt – good at disassocitating H2 , Zn – good at binding, Cu – catalyzes transition states)
6. Ref #2 of J. Graciani, K. Mudiyanselage, F. Xu, a. E. Baber, J. Evans, S. D. Senanayake, D. J. Stacchiola, P. Liu, J. Hrbek, J. F. Sanz, and J. a. Rodriguez, “Highly active copper-ceria and copper-ceria-titania catalysts for methanol synthesis from CO2,” Science (80-. )., vol. 345, no. 6196, pp. 546–550, 2014.
Analyzing hydrogenation of CO2 on ceria
% use ode45 first and then compare to ode15s, this is a 'stiff' problem% (concentrations are changing at different time scales) so I want to% measure the accuracy between the twox0=0; xf=40; %start at time zero and go for 40 seconds%assume 1:1 molar ratio of CO2 and H2 with the number active sites being 7y0=[5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 5]; %last point is active sitesoptions = odeset('RelTol',1e-3,'NonNegative',ones(25,1));
[x,y] = ode15s(@f,[x0 xf],y0,options);
%plot methanol as a function of timefigureplot(x,y(:,19))xlabel('time (s)')ylabel('[CH_3OH]')%plot adsorbed hrdroxylfigureplot(x,y(:,20))xlabel('time (s)')ylabel('[OH*]')%adsorbed waterfigureplot(x,y(:,21))xlabel('time (s)')ylabel('[H_2O*]')%carbon dioxidefigureplot(x,y(:,1))xlabel('time (s)')ylabel('[CO_2]')
% Assume number of available active sites to be 7, therefore they are not% rate limiting. Need 5 sites total for the mechanism.
function dC = f(~,y)% all rate constants are in INVERSE SECONDS%assume them to be for second order processesglobal rateskload myparam% ratesk = [1.95e4 3.23e1% 2.67e4 5.19e4% 6.31e3 3.13e5% 3.11e1 1.78e2% 2.17e3 4.21e3% 1.02e1 3.57e3% 4.24e6 3.82e6% 3.82e-3 1.31e-2% 7.33e-4 5.41e-5% 6.55e-2 8.21e-4% 3.91e4 3.55e2% 5.11e3 8.26e5% 7.63e3 5.19e2% 4.55e-4 1.98e-2% 1.02e1 2.82e3% 3.76e1 5.43e-1% 9.21 2.13e-1% 8.33e1 4.08e2% 5.91e-3 3.41e-5% 7.32e2 2.45e2% 5.89e1 2.87e1];% ratesk=ratesk*1e-5;%rates of depletion -r_1dC(1) = ratesk(1,1)*y(1)*y(25) - ratesk(1,2)*y(2); %multiplying by one species instead of two?dC(2) = ratesk(2,1)*y(2)*y(24) - ratesk(2,2)*y(3)*y(25) - ratesk(1,1)*y(1)*y(25) + ratesk(1,2)*y(2) + ratesk(11,1)*y(2)*y(24) - ratesk(11,2)*y(12)*y(25);dC(3) = ratesk(3,1)*y(3)*y(25) - ratesk(3,2)*y(4)*y(20) + ratesk(4,1)*y(3)*y(24) - ratesk(4,2)*y(5)*y(25)- ratesk(2,1)*y(2)*y(24) + ratesk(2,2)*y(3)*y(25);dC(4) = ratesk(6,1)*y(4) - ratesk(6,2)*y(7)*y(25) - ratesk(3,1)*y(3)*y(25) + ratesk(3,2)*y(4)*y(20) + ratesk(7,1)*y(4)*y(24) - ratesk(7,2)*y(8)*y(25);dC(5) = ratesk(5,1)*y(5) - ratesk(5,2)*y(6)*y(25) - ratesk(4,1)*y(3)*y(24) + ratesk(4,2)*y(5)*y(25);dC(6) = -ratesk(5,1)*y(5) + ratesk(5,2)*y(6)*y(25);dC(7) = -ratesk(6,1)*y(4) + ratesk(6,2)*y(7)*y(25);dC(8) = ratesk(8,1)*y(8)*y(24) - ratesk(8,2)*y(9)*y(25) - ratesk(7,1)*y(4)*y(24) + ratesk(7,2)*y(8)*y(25);dC(9) = -ratesk(8,1)*y(8)*y(24) + ratesk(8,2)*y(9)*y(25) + ratesk(9,1)*y(9)*y(24) - ratesk(9,2)*y(10)*y(25);dC(10) = -ratesk(9,1)*y(9)*y(24) + ratesk(9,2)*y(10)*y(25) + ratesk(10,1)*y(10)*y(24) - ratesk(10,2)*y(11)*y(25);dC(11) = -ratesk(10,1)*y(10)*y(24) + ratesk(10,2)*y(11)*y(25) - ratesk(17,1)*y(17)*y(24) + ratesk(17,2)*y(18)*y(25) + ratesk(18,1)*y(18) - ratesk(18,2)*y(19)*y(25);dC(12) = -ratesk(11,1)*y(2)*y(24) + ratesk(11,2)*y(12)*y(25) + ratesk(12,1)*y(12)*y(24) - ratesk(12,2)*y(13)*y(25);dC(13) = -ratesk(12,1)*y(12)*y(24) + ratesk(12,2)*y(13)*y(25) + ratesk(13,1)*y(13)*y(24) - ratesk(13,2)*y(14)*y(25);dC(14) = -ratesk(13,1)*y(13)*y(24) + ratesk(13,2)*y(14)*y(25) + ratesk(14,1)*y(14)*y(25) - ratesk(14,2)*y(15)*y(20);dC(15) = -ratesk(14,1)*y(14)*y(25) + ratesk(14,2)*y(15)*y(20) + ratesk(15,1)*y(15) - ratesk(15,2)*y(16)*y(25) + ratesk(16,1)*y(15)*y(24) - ratesk(16,2)*y(17)*y(25);dC(16) = -ratesk(15,1)*y(15) + ratesk(15,2)*y(16)*y(25);dC(17) = -ratesk(16,1)*y(15)*y(24) + ratesk(16,2)*y(17)*y(25) + ratesk(17,1)*y(17)*y(24) - ratesk(17,2)*y(18)*y(25);dC(18) = -ratesk(10,1)*y(10)*y(24) + ratesk(10,2)*y(11)*y(25) - ratesk(17,1)*y(17)*y(24) + ratesk(17,2)*y(18)*y(25) + ratesk(18,1)*y(18) - ratesk(18,2)*y(19)*y(25);dC(19) = -ratesk(18,1)*y(18) + ratesk(18,2)*y(19)*y(25);dC(20) = -ratesk(3,1)*y(3)*y(25) + ratesk(3,2)*y(4)*y(20) - ratesk(14,1)*y(14)*y(25) + ratesk(14,2)*y(15)*y(20) + ratesk(19,1)*y(24)*y(20) - ratesk(19,2)*y(21)*y(25);dC(21) = -ratesk(19,1)*y(24)*y(20) + ratesk(19,2)*y(21)*y(25) + ratesk(20,1)*y(21) - ratesk(20,2)*y(22)*y(25);dC(22) = -ratesk(20,1)*y(21) + ratesk(20,2)*y(22)*y(25);dC(23) = ratesk(21,1)*y(23)*y(24)*y(24) - ratesk(21,2)*y(25)*y(25);dC(24) = ratesk(2,1)*y(2)*y(24) - ratesk(2,2)*y(3)*y(25) + ratesk(4,1)*y(3)*y(24) - ratesk(4,2)*y(5)*y(25) + ratesk(7,1)*y(4)*y(24) - ratesk(7,2)*y(8)*y(25) + ratesk(8,1)*y(8)*y(24) - ratesk(8,2)*y(9)*y(25)... + ratesk(9,1)*y(9)*y(24) - ratesk(9,2)*y(10)*y(25) + ratesk(10,1)*y(10)*y(24) - ratesk(10,2)*y(11)*y(25) + ratesk(11,1)*y(2)*y(24) - ratesk(11,2)*y(12)*y(25) + ratesk(12,1)*y(12)*y(24) - ratesk(12,2)*y(13)*y(25)... + ratesk(13,1)*y(13)*y(24) - ratesk(13,2)*y(14)*y(25) + ratesk(16,1)*y(15)*y(24) - ratesk(16,2)*y(17)*y(25) + ratesk(17,1)*y(17)*y(24) - ratesk(17,2)*y(18)*y(25) + ratesk(19,1)*y(24)*y(20) - ratesk(19,2)*y(21)*y(25)... -2*ratesk(21,1)*y(23)*y(24)*y(24) + 2*ratesk(21,2)*y(25)*y(25);dC(25) = dC(1) - ratesk(2,1)*y(2)*y(24) + ratesk(2,2)*y(3)*y(25) + ratesk(3,1)*y(3)*y(25) - ratesk(3,2)*y(4)*y(20) - ratesk(4,1)*y(3)*y(24) + ratesk(4,2)*y(5)*y(25) - ratesk(5,1)*y(5) + ratesk(5,2)*y(6)*y(25)... - ratesk(7,1)*y(4)*y(24) + ratesk(7,2)*y(8)*y(25) - ratesk(8,1)*y(8)*y(24) + ratesk(8,2)*y(9)*y(25) - ratesk(9,1)*y(9)*y(24) + ratesk(9,2)*y(10)*y(25) - ratesk(10,1)*y(10)*y(24) + ratesk(10,2)*y(11)*y(25)... - ratesk(11,1)*y(2)*y(24) + ratesk(11,2)*y(12)*y(25) - ratesk(12,1)*y(12)*y(24) + ratesk(12,2)*y(13)*y(25) - ratesk(13,1)*y(13)*y(24) + ratesk(13,2)*y(14)*y(25) + ratesk(14,1)*y(14)*y(25) - ratesk(14,2)*y(15)*y(20)... - ratesk(15,1)*y(15) + ratesk(15,2)*y(16)*y(25)- ratesk(16,1)*y(15)*y(24) + ratesk(16,2)*y(17)*y(25) - ratesk(17,1)*y(17)*y(24) + ratesk(17,2)*y(18)*y(25) - ratesk(18,1)*y(18) + ratesk(18,2)*y(19)*y(25)... - ratesk(19,1)*y(24)*y(20) + ratesk(19,2)*y(21)*y(25) - ratesk(20,1)*y(21) + ratesk(20,2)*y(22)*y(25) + 2*ratesk(21,1)*y(23)*y(24)*y(24) - 2*ratesk(21,2)*y(25)*y(25);
dC = dC'; %to return a column vector
% dC(7) = ratesk(7,1)*y(4)*y(24) - ratesk(7,2)*y(8)*y(25);% dC(8) = ratesk(8,1)*y(8)*y(24) - ratesk(8,2)*y(9)*y(25);% dC(9) = ratesk(9,1)*y(9)*y(24) - ratesk(9,2)*y(10)*y(25);% dC(10) = ratesk(10,1)*y(10)*y(24) - ratesk(10,2)*y(11)*y(25);% dC(11) = ratesk(11,1)*y(2)*y(24) - ratesk(11,2)*y(12)*y(25);% dC(12) = ratesk(12,1)*y(12)*y(24) - ratesk(12,2)*y(13)*y(25);% dC(13) = ratesk(13,1)*y(13)*y(24) - ratesk(13,2)*y(14)*y(25);% dC(14) = ratesk(14,1)*y(14)*y(25) - ratesk(14,2)*y(15)*y(20);% dC(15) = ratesk(15,1)*y(15) - ratesk(15,2)*y(16)*y(25);% dC(16) = ratesk(16,1)*y(15)*y(24) - ratesk(16,2)*y(17)*y(25);% dC(17) = ratesk(17,1)*y(17)*y(24) - ratesk(17,2)*y(18)*y(25);% dC(18) = ratesk(18,1)*y(18) - ratesk(18,2)*y(19)*y(25);% dC(19) = ratesk(19,1)*y(24)*y(20) - ratesk(19,2)*y(21)*y(25);% dC(20) = ratesk(20,1)*y(21) - ratesk(20,2)*y(22)*y(25);% dC(21) = ratesk(21,1)*y(23)*y(24)*y(24) - ratesk(21,2)*y(25)*y(25); %make sure this rate form is correct
EndEnd
function dC = f(~,y)% all rate constants are in INVERSE SECONDSglobal rateskload myparam% ratesk = [1.95e4 3.23e1% 2.67e4 5.19e4% 6.31e3 3.13e5% 3.11e1 1.78e2% 2.17e3 4.21e3% 1.02e1 3.57e3% 4.24e6 3.82e6% 3.82e-3 1.31e-2% 7.33e-4 5.41e-5% 6.55e-2 8.21e-4% 3.91e4 3.55e2% 5.11e3 8.26e5% 7.63e3 5.19e2% 4.55e-4 1.98e-2% 1.02e1 2.82e3% 3.76e1 5.43e-1% 9.21 2.13e-1% 8.33e1 4.08e2% 5.91e-3 3.41e-5% 7.32e2 2.45e2% 5.89e1 2.87e1];
Additional Factors
Treatments (a priori) Incipient wetness method, reverse microemulsion (RM), coprecipitation
and impregnation
Dopants and deposits
Varying temperature and pressure a priori and/or in situ Thermodynamic and kinetic effects
Future Work Comparing catalysts from database Mapping and understanding the change in electron density as CO2 is adsorbed onto
surface and converted
Plot activity, activation energy and adsorption energy vs d-band center
Machine Learning
Understand Transition State Theory and recalculate k’s
Future Work
Machine Learning Supervised Learning
Using gradient descent to maximize specified characteristics (θ0, θ1 are independent variables)
Machine Learning Classification
Where 0 is negative and 1 is positive
Decision Boundary
Machine Learning
Questions?
Works Cited1. © 2013 Liquid Light Corporation. All rights reserved. | www.llchemical.com
2. UNEP, Introduction to Climate Change http://www.grida.no/climate/vital/05.htm
3. Global greenhouse gas emissions (2012), International Energy Agency.4. Dr. John T. Gleaves – received on December 2, 2015
5. Lo, C.; Cheng, Zhuo. EECE Washington University6. Ref #2 of J. Graciani, K. Mudiyanselage, F. Xu, a. E. Baber, J. Evans, S. D. Senanayake, D. J. Stacchiola, P. Liu, J. Hrbek, J. F. Sanz, and J. a. Rodriguez, “Highly active copper-ceria and copper-ceria-titania catalysts for methanol synthesis from CO2,” Science (80-. )., vol. 345, no. 6196, pp. 546–550, 2014.
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