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WIREs Comput Mol Sci
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Material descriptors for photocatalyst/catalyst design

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Rational design of high‐performance photocatalysts/catalysts is crucial for sustainable development. To achieve this goal, a comprehensive understanding and precise description of structure–performance relationships of photocatalysts/catalysts are highly desirable. While photocatalysis/catalysis involves complex systems and processes, approximate descriptors have been proposed for sorting out simple pictures of complicated structure–performance relationships concerned. In this review, some important descriptors involved in photocatalyst/catalyst design including work function, dipole moment, d‐band center, and Fermi softness are reviewed first with special attention being paid to their working mechanisms and applications. Then strategies of tuning photocatalytic/catalytic performance on the basis of these descriptors are outlined. Finally, challenges and opportunities for photocatalyst/catalyst design based on descriptor control are discussed.

This article is categorized under:

  • Structure and Mechanism > Computational Materials Science
  • Structure and Mechanism > Reaction Mechanisms and Catalysis
  • Electronic Structure Theory > Density Functional Theory
  • Software > Quantum Chemistry
(a) The activation energy for CH3H bond scission as a function of the surface d‐band center. (b) The volcano‐relation of the d‐band center and the rate of the methanation reaction (CO + 3H2 → CH4 + H2O). (c) Schematic illustration of a two‐step model taking into consideration the dissociative adsorption of reactants and associative desorption of products on a heterogeneous catalytic surface. (d) Schematic illustration of volcano curves associated with reactions in which the adsorption (red) and desorption (blue) are rate determining, together with the real volcano curve (black) (left). The right side of the panel shows the energy profiles on three typical catalytic surfaces. Figure panel a is reprinted with permission from Abild‐Pedersen et al. (). Copyright 2005 Springer Nature. Figure panel b is reprinted with permission from Nørskov et al. (). Copyright 2009 Springer Nature. Figure panels c and d are reprinted with permission from Yang, Burch, et al. (). Copyright 2013 American Chemical Society
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(a) Schematic illustration of the formation of a metal–adsorbate bond. The d‐band center dependence of (b) CO, (c) oxygen and (d) hydrogen chemisorption energies. Figure panels a and c are reprinted with permission from Hammer and Nørskov (). Copyright 2000 Elsevier Inc. Figure panel b is reprinted with permission from Sakong et al. (). Copyright 2007 Royal Society of Chemistry. Figure panel d is reprinted with permission from Jiao et al. (). Copyright 2015 Royal Society of Chemistry
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(a) Structure of the TC5b trp‐cage peptide NLYIQWLKDGG PSSGRPPPS. (b) The indole fragment of Trp6 and the phenol fragment of Tyr3. The electric dipoles of the Wa and Wb transitions are depicted by red arrows, and the polarizations Pzzzz of the Ultra Violet laser pulses are shown as purple arrows. Distance (c) and coupling intensity (d) of the Yb and Wb transitions in the TC5b trp‐cage as the function of their dipole angle (φYbWb). (e) Dependence on dipole angle of the intensity changes from 0 to 10 ps t2 time delay for the three 2DNUV peaks YbYb, WbWb, and YbWb. Colors from green to red represent occurrence frequencies in 60,000 MD snapshots. Figure panels a–e are reprinted with permission from Li et al. (). Copyright 2015 American Chemical Society
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Schematic illustration of comparison between wavefunction distribution, point charge and dipole moment
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(a) Schematic illustration of the parameters used in modeling the interface dipole and potential step formation at the graphene–metal interface. (b) Calculated Fermi energy shift with respect to the conical point, ΔEF (dots) and change in the work function WWG (triangles) as a function of WM − WG, the difference between the clean metal and graphene work functions. These results are for equilibrium (~3.3 Å) separation of graphene and the metal surfaces. Figure panels a and b are reprinted with permission from Giovannetti et al. (). Copyright 2008 American Physical Society
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Potential diagrams of Cu2O (a) (100) and (b) (111) surfaces obtained from first‐principles simulations. (c) Schematic illustration of the charge spatial distribution between the Cu2O (100) and (111) surfaces. (d) Three‐dimensional models of three porous NiO nanowires (NWs), with the step facets clearly indexed. (e) The calculated energy difference between NiO high‐index nanofacets and the electrochemical potential for reducing H+ to H2 in water for these three NiO NW systems. The x‐axis represents the distance starting from the left‐most side of each model. Lower energy differences facilitate electron transfer from NiO to water for hydrogen reduction, as most dramatically demonstrated by the NiO NWs‐II sample. Figure panels a–c are reprinted with permission from Wang, Ge, et al. (). Copyright 2014 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim; panels d and e are reprinted with permission from Shen et al. (). Copyright 2015 Springer Nature
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Schematic illustration of band bending and charge transfer driven by photo‐excitation of a Z‐scheme system
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Schematic illustration of charge transfer driven by (a) semiconductor photo‐excitation or (b) the plasmonic effect at an n‐type (left) or p‐type (right) semiconductor–metal interface (e, electron; h +, hole)
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(a) Schematic diagram of X‐doped graphene nanoribbons showing the possible positions of dopants and (b) the corresponding volcano relation between the OER/ORR overpotentials and descriptor Φ. (c) Schematic diagram of NX‐co‐doped graphene nanoribbons, showing the possible positions of dopants and (d) the corresponding inverse volcano relation between the OER/ORR overpotentials and descriptor Φ. Figure panels a and b are reprinted with permission from Zhao et al. (). Copyright 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim; figure panels c and d are reprinted with permission from Zhao and Xia (). Copyright 2016 American Chemical Society
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(a) The spatially resolved quantification of the local Fermi softness fields ( SF(r)) of the Pt3Y (111), Pt (111) and Y (001) surfaces. (b) Examination of the reactivity of the Pt and Y sites on Pt3Y (111) by comparing the binding strengths of various adsorbates. (c) The projected density of states (PDOS) of the Pt and Y atoms at the first layer of the Pt3Y (111) surface, showing that the d‐band center does not serve as an accurate reactivity index for this alloy system. (d) The spatially resolved quantification of the local Fermi softness field ( SF(r)) of a one‐dimensional MoS2 edge. (e) The computational model, involving three types of S atoms (S#1, S#2, and S#3) and two types of Mo atoms (Mo#1 and Mo#2). (f) Potential energy curves for the 2Had → H2 reaction, highlighting the barrier energy differential between two kinds of bridge sites (br–x or br–y, as indicated by the inset) on the S#1 dimer edge, obtained from nudged elastic band calculations. Figure panels a–f are reprinted with permission from Huang et al. (). Copyright 2016 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim
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Spatially resolved quantification of the local Fermi softness ( SF(r)) of close‐packed surfaces of transition metals. Figure is reprinted with permission from Huang et al. (). Copyright 2016 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim
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Summary of the relationships among the d‐band center, chemisorption energy, activation energy, and catalytic activity
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Schematic illustration of (a) n‐type and (b) p‐type semiconductor energy bands bending after contact with the metal
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Upper panel: Adsorption energy for acetylene (red) and ethylene (blue) plotted against the adsorption energy of methyl radical on different catalysts. Lower panel: Cost (in 2006 metal prices) of 70 binary intermetallic compounds plotted against calculated methyl adsorption energies. The smooth transition between regions of low selectivity and high reactivity (blue) and high selectivity and low reactivity (red) is indicated. Figure is reprinted with permission from Studt et al. (). Copyright 2008 American Association for the Advancement of Science
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Software > Quantum Chemistry
Structure and Mechanism > Reaction Mechanisms and Catalysis
Structure and Mechanism > Computational Materials Science
Electronic Structure Theory > Density Functional Theory

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