Lone but Not Alone: Precise Positioning of Lone Pairs for the Design of Photocatalytic Architectures

Lone but Not Alone: Precise Positioning of Lone Pairs for the Design of Photocatalytic Architectures
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DOI:
10.1021/acs.chemmater.1c03762
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发表时间:
2022-01-31
影响因子:
8.6
通讯作者:
Banerjee, Sarbajit
Banerjee, Sarbajit
中科院分区:
材料科学2区
文献类型:
--
作者:
Handy, Joseph, V;Zaheer, Wasif;Banerjee, Sarbajit

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With current economic growth and consumption trends projected to bring about a precipitous and rapid rise of the global temperature, the world stands at a crossroads with regards to climate change. The rate at which greenhouse gas emissions from fossil fuels, industry, and land-use is curtailed over the next decade will determine the trajectory of global warming for the rest of the century. It is increasingly apparent that far-reaching decarbonization of the transportation infrastructure will need to be supplemented by extensive carbon capture, storage, and utilization. Taking a leaf from Nature's playbook, photocatalytic architectures that can utilize water or CO2 in conjunction with energy harvested from sunlight and store it in the form of energy-dense chemical bonds represent an attractive proposition. Harnessing solar irradiance, through solar energy conversion involving photovoltaics, as well as the photocatalytic generation of solar fuels, and the photocatalytic reduction of CO2 have emerged as urgent imperatives for the energy transition. Functional photocatalysts must be capable of efficiently absorbing sunlight, effectively separating electron-hole pairs, and ensuring they are delivered at appropriate potentials to catalytic sites to mediate redox reactions. Such photocatalytic architectures must further direct redox events down specific pathways to yield desired products, and ensure the transport of reactants between catalytic sites; all with high efficiency and minimal degradation. In this Perspective, we describe a palette of heterostructures designed to promote robust and efficient direct solar-driven water splitting and CO2 reduction. The heterostructures comprise M(x)V(2)O(5 )or MxMy'V2O5, where M is a p-block cation, M' is an s-, p-, or d-block cation, and V2O5 represents one of multiple polymorphs of this composition interfaced with semiconductor quantum dots (QDs, binary or ternary II-VI or III-V QDs). The stereochemically active 5/6s(2) electron lone pairs of p-block cations in M(x)V(2)O(5 )give rise to filled midgap electronic states that reside above the O 2p-derived valence band. Within heterostructures, the photoexcitation of QDs results in the transfer of holes to the midgap states of M(x)V(2)O(5 )or MxMy'V2O5 on subpicosecond time scales. Ultrafast charge separation minimizes the photoanodic corrosion of QDs, which has historically been a major impediment to their use in photocatalysis, and enables charge transport and the subsequent redox reactions underpinning photocatalysis to compete with electron-hole recombination. The energy positioning and dispersion of lone pair states is tunable through multiple chemical and compositional levers accessible across the palette of M(x)V(2)O(5 )or MxMy'V2O5 compounds: choice of lone-pair cation M and its stoichiometry x, atomic connectivity of V2O5 polymorphs, cointercalation of M' cations in "quaternary" vanadium oxide bronzes, anionic substitution, and alternative lone pair vanadate frameworks with altogether different compositions and lattice structures.Design principles for understanding the nature of lone pair states are discussed with reference to hard X-ray photoemission, crystal orbital Hamiltonian population analyses, and spectroelectrochemical signatures.The dimensions, composition, and doping of QDs along with interfacial structure afford additional levers for heterostructure integration, enabling tuning of thermodynamic energy offsets and charge-transfer dynamics, which have been systematically optimized across several generations of heterostructures to improve photocatalytic performance. Synthetic strategies to prepare new lone-pair M(x)V(2)O(5 )or MxMy'V2O5 compounds and their integration within heterostructures are described. Given the large number of variables, we also discuss prospects for the applicability of machine learning and high-throughput synthesis to tackle high-dimensional materials design problems.