First principles high throughput screening of oxynitrides for water-splitting photocatalysts

Wu, Yabi; Lazić, Predrag; Hautier, Geoffroy; Persson, Kristin A.; Ceder, Gerbrand

doi:10.1039/c2ee23482c

Cited by 335 publications

(288 citation statements)

References 63 publications

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“…Vertical potentials, based on approach I or II, are routinely reported in the literature [33,[89][90][91][92][93][94][95][96][97][98][99]. See the work of Stevanovic et al [89] for a nice illustration for the case of GW vertical potentials for the surfaces of typical crystalline photocatalysts, which also clearly illustrates that potentials are surface rather than bulk properties (see figure 3).…”

Section: Thermodynamic Driving Forcementioning

confidence: 99%

See 1 more Smart Citation

Modelling materials for solar fuel synthesis by artificial photosynthesis; predicting the optical, electronic and redox properties of photocatalysts

Guiglion

Berardo

Butchosa

et al. 2016

J. Phys.: Condens. Matter

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In this mini-review, we discuss what insight computational modelling can provide into the working of photocatalysts for solar fuel synthesis and how calculations can be used to screen for new promising materials for photocatalytic water splitting and carbon dioxide reduction. We will extensively discuss the different relevant (material) properties and the computational approaches (DFT, TD-DFT, GW/BSE) available to model them. We illustrate this with examples from the literature, focussing on polymeric and nanoparticle photocatalysts. We finish with a perspective on the outstanding conceptual and computational challenges.

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Section: Thermodynamic Driving Forcementioning

confidence: 99%

“…Another clear application of computational modelling in this context is to rapidly screen for potential photocatalysts [92][93][94][95]. Both in the case of inorganic and polymeric photocatalysts, the possible chemical space is enormous.…”

Section: Perspectivementioning

confidence: 99%

Modelling materials for solar fuel synthesis by artificial photosynthesis; predicting the optical, electronic and redox properties of photocatalysts

Guiglion

Berardo

Butchosa

et al. 2016

J. Phys.: Condens. Matter

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“…7 Nitrides are a particularly compelling class of materials to explore computationally, 8−11 as they are rare in nature and difficult to synthesize in the laboratory. They also have significant technological relevance, as the unique bonding characteristics in nitrides yield electronic structures that range from metallic to semiconducting, producing materials with properties relevant to applications spanning refractory ceramics, 12,13 superconductors, 14,15 solid-state lighting, 16,17 photovoltaics, 18,19 photocatalysts, 20,21 thermoelectrics, 22,23 piezoelectrics, 24,25 permanent magnets, 26 and more.…”

Section: ■ Introductionmentioning

confidence: 99%

Thermodynamic Routes to Novel Metastable Nitrogen-Rich Nitrides

et al. 2017

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Compared to oxides, the nitrides are relatively unexplored, making them a promising chemical space for novel materials discovery. Of particular interest are nitrogen-rich nitrides, which often possess useful semiconducting properties for electronic and optoelectronic applications. However, such nitrogen-rich compounds are generally metastable, and the lack of a guiding theory for their synthesis has limited their exploration. Here, we review the remarkable metastability of observed nitrides, and examine the thermodynamics of how reactive nitrogen precursors can stabilize metastable nitrogen-rich compositions during materials synthesis. We map these thermodynamic strategies onto a predictive computational search, training a data-mined ionic substitution algorithm specifically for nitride discovery, which we combine with grand-canonical DFT-SCAN phase stability calculations to compute stabilizing nitrogen chemical potentials. We identify several new nitrogen-rich binary nitrides for experimental investigation, notably the transition metal nitrides Mn 3 N 4 , Cr 3 N 4 , V 3 N 4 , and Nb 3 N 5 , the main group nitride SbN, and the pernitrides FeN 2 , CrN 2 , and Cu 2 N 2 . By formulating rational thermodynamic routes to metastable compounds, we expand the search space for functional technological materials beyond equilibrium phases and compositions.

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“…Titania is widely studied in various photoelectrochemical applications, and accurate theoretical assessment is required to be able to enhance its catalytic properties. In addition, to further improve the properties of TiO 2 as a photocatalyst, an optimization of the band structure is required, including narrowing the bandgap (Eg) to improve visible light absorption, and proper positioning of the valence band (VB) and the conduction band (CB) [41]. Efforts on narrowing the bandgap of the TiO 2 have been done through doping with metallic and nonmetallic elements that typically replace Ti or O atoms, and thus change the position of the VB and or the CB leading to a change in the bandgap [42].…”

Section: The Effect Of U On Pure and Defected Systemsmentioning

confidence: 99%

The DFT+U: Approaches, Accuracy, and Applications

Tolba¹,

Gameel²,

Ali³

et al. 2018

Density Functional Calculations - Recent Progresses of Theory and Application

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This chapter introduces the Hubbard model and its applicability as a corrective tool for accurate modeling of the electronic properties of various classes of systems. The attainment of a correct description of electronic structure is critical for predicting further electronic-related properties, including intermolecular interactions and formation energies. The chapter begins with an introduction to the formulation of density functional theory (DFT) functionals, while addressing the origin of bandgap problem with correlated materials. Then, the corrective approaches proposed to solve the DFT bandgap problem are reviewed, while comparing them in terms of accuracy and computational cost. The Hubbard model will then offer a simple approach to correctly describe the behavior of highly correlated materials, known as the Mott insulators. Based on Hubbard model, DFT+U scheme is built, which is computationally convenient for accurate calculations of electronic structures. Later in this chapter, the computational and semiempirical methods of optimizing the value of the Coulomb interaction potential (U) are discussed, while evaluating the conditions under which it can be most predictive. The chapter focuses on highlighting the use of U to correct the description of the physical properties, by reviewing the results of case studies presented in literature for various classes of materials.

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First principles high throughput screening of oxynitrides for water-splitting photocatalysts

Cited by 335 publications

References 63 publications

Modelling materials for solar fuel synthesis by artificial photosynthesis; predicting the optical, electronic and redox properties of photocatalysts

Modelling materials for solar fuel synthesis by artificial photosynthesis; predicting the optical, electronic and redox properties of photocatalysts

Thermodynamic Routes to Novel Metastable Nitrogen-Rich Nitrides

The DFT+U: Approaches, Accuracy, and Applications

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