TY - JOUR
T1 - Surface-Plasmon-Induced Ammonia Decomposition on Copper
T2 - Excited-State Reaction Pathways Revealed by Embedded Correlated Wavefunction Theory
AU - Bao, Junwei Lucas
AU - Carter, Emily Ann
N1 - Funding Information:
J.L.B. acknowledges helpful suggestions from and fruitful discussions with Dr. John Mark P. Martirez and Dr. Linan Zhou. E.A.C. acknowledges financial support from the Air Force Office of Scientific Research via the Department of Defense Multidisciplinary University Research Initiative, under Award No. FA9550-15-1-0022. Princeton University’s Terascale Infrastructure for Groundbreaking Research in Engineering and Science (TIGRESS) provided the computational resources.
Publisher Copyright:
© 2019 American Chemical Society.
PY - 2019/9/24
Y1 - 2019/9/24
N2 - Ammonia is a promising hydrogen storage medium; however, its decomposition via conventional thermal catalysis requires a significant amount of thermal energy input in order to overcome the reaction barriers. Here, we use embedded correlated wavefunction (ECW) theory to quantify reaction pathways and energetics for ammonia decomposition (N-H bond dissociation and N2 and H2 associative desorption) on copper (Cu) nanoparticles using a Cu (111) surface model. We predict that surface plasmon excitations will be able to facilitate ammonia decomposition by substantially reducing the effective barriers along excited-state pathways. We estimate the reductions in reaction barriers for breaking the first N-H bond and for recombinative desorption of surface-bound nitrogen and hydrogen atoms to be approximately 1.7, 0.8, and 0.5 eV, respectively. Further, by using the experimental N2 desorption barrier as a reference, we compare the accuracy of various theoretical methods, including plane-wave Kohn-Sham density functional theory calculations with commonly used exchange-correlation functionals, embedded complete active space second-order perturbation theory, and embedded multiconfiguration pair-density functional theory. This work offers further confirmation that the ECW theoretical framework is the most robust for treating highly correlated local electronic structures of solids.
AB - Ammonia is a promising hydrogen storage medium; however, its decomposition via conventional thermal catalysis requires a significant amount of thermal energy input in order to overcome the reaction barriers. Here, we use embedded correlated wavefunction (ECW) theory to quantify reaction pathways and energetics for ammonia decomposition (N-H bond dissociation and N2 and H2 associative desorption) on copper (Cu) nanoparticles using a Cu (111) surface model. We predict that surface plasmon excitations will be able to facilitate ammonia decomposition by substantially reducing the effective barriers along excited-state pathways. We estimate the reductions in reaction barriers for breaking the first N-H bond and for recombinative desorption of surface-bound nitrogen and hydrogen atoms to be approximately 1.7, 0.8, and 0.5 eV, respectively. Further, by using the experimental N2 desorption barrier as a reference, we compare the accuracy of various theoretical methods, including plane-wave Kohn-Sham density functional theory calculations with commonly used exchange-correlation functionals, embedded complete active space second-order perturbation theory, and embedded multiconfiguration pair-density functional theory. This work offers further confirmation that the ECW theoretical framework is the most robust for treating highly correlated local electronic structures of solids.
KW - ammonia decomposition
KW - embedded correlated wavefunction theory
KW - hydrogen associative desorption
KW - localized surface plasmon resonance
KW - nitrogen associative desorption
KW - photocatalysis
UR - http://www.scopus.com/inward/record.url?scp=85071661645&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071661645&partnerID=8YFLogxK
U2 - 10.1021/acsnano.9b05030
DO - 10.1021/acsnano.9b05030
M3 - Article
C2 - 31393708
AN - SCOPUS:85071661645
SN - 1936-0851
VL - 13
SP - 9944
EP - 9957
JO - ACS Nano
JF - ACS Nano
IS - 9
ER -