J. Semicond. > Volume 39 > Issue 7 > Article Number: 071001

Data-driven material discovery for photocatalysis: a short review

Jinbo Pan and Qimin Yan ,

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Abstract: In this short review, we introduce recent progress in the research field of data-driven material discovery and design for solar fuel generation. Construction of material databases under the materials genome initiative provides a great platform for material discovery and design by creating computational screening pipelines based on the materials’ descriptors. In the field of solar water splitting, data-driven computational discovery approach has been effective in making material predictions. When combined with synergistic and complimentary experimental efforts, high-throughput computations based on density functional theory showed great predictive power for accelerated discovery of inorganic compounds as functional materials for solar fuel generation. As an example, we introduce the theory–experiment joint discovery of a large set of metal oxide photoanode materials that have been theoretically predicted to be efficient candidates and soon verified by synergistic experimental fabrication and characterization processes. In the field of two-dimensional materials, the application of data-driven approach has realized the prediction of many promising candidates with suitable direct band gaps and optimal band edges for the generation of chemical fuels from sunlight, greatly expanding the number of theoretically predicted 2D photoelectrocatalysts that are awaiting experimental verification. We discuss the challenges for the continued discovery and design of novel bulk and 2D compounds for photocatalysis via a data-driven approach. At the end of this review, we provide a brief outlook for future material discoveries in the field of solar fuel generation.

Key words: photocatalysisdensity functional theorytwo-dimensional materials

Abstract: In this short review, we introduce recent progress in the research field of data-driven material discovery and design for solar fuel generation. Construction of material databases under the materials genome initiative provides a great platform for material discovery and design by creating computational screening pipelines based on the materials’ descriptors. In the field of solar water splitting, data-driven computational discovery approach has been effective in making material predictions. When combined with synergistic and complimentary experimental efforts, high-throughput computations based on density functional theory showed great predictive power for accelerated discovery of inorganic compounds as functional materials for solar fuel generation. As an example, we introduce the theory–experiment joint discovery of a large set of metal oxide photoanode materials that have been theoretically predicted to be efficient candidates and soon verified by synergistic experimental fabrication and characterization processes. In the field of two-dimensional materials, the application of data-driven approach has realized the prediction of many promising candidates with suitable direct band gaps and optimal band edges for the generation of chemical fuels from sunlight, greatly expanding the number of theoretically predicted 2D photoelectrocatalysts that are awaiting experimental verification. We discuss the challenges for the continued discovery and design of novel bulk and 2D compounds for photocatalysis via a data-driven approach. At the end of this review, we provide a brief outlook for future material discoveries in the field of solar fuel generation.

Key words: photocatalysisdensity functional theorytwo-dimensional materials



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[1]

Holdren J P. Materials genome initiative for global competitiveness. National Science and Technology Council OSTP. Washington, USA, 2011

[2]

Scheffler M, Draxl C. The NoMaD repository. Computer Center of the Max-Planck Society, 2014

[3]

Jain A, Ong S P, Hautier G, et al. Commentary: the materials project: a materials genome approach to accelerating materials innovation. APL Mater, 2013, 1: 011002

[4]

Saal J E, Kirklin S, Aykol M, et al. Materials design and discovery with high-throughput density functional theory: the open quantum materials database (OQMD). Jom-Us, 2013, 65: 1501

[5]

Curtarolo S, Setyawan W, Wang S, et al. AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations. Comput Mater Sci, 2012, 58: 227

[6]

Curtarolo S, Hart G L W, Nardelli M B, et al. The high-throughput highway to computational materials design. Nat Mater, 2013, 12: 191

[7]

Hautier G, Miglio A, Ceder G, et al. Identification and design principles of low hole effective mass p-type transparent conducting oxides. Nat Commun, 2013, 4: 2292

[8]

Wu Y B, Lazic P, Hautier G, et al. First principles high throughput screening of oxynitrides for water-splitting photocatalysts. Energy Environ Sci, 2013, 6: 157

[9]

Castelli I E, Olsen T, Datta S, et al. Computational screening of perovskite metal oxides for optimal solar light capture. Energy Environ Sci, 2012, 5: 5814

[10]

Jain A, Shin Y, Persson K A. Computational predictions of energy materials using density functional theory. Nat Rev Mater, 2016, 1: 15004

[11]

Sendek A D, Yang Q, Cubuk E D, et al. Holistic computational structure screening of more than 12 000 candidates for solid lithium-ion conductor materials. Energ Environ Sci, 2017, 10: 306

[12]

Woodhouse M, Parkinson B A. Combinatorial discovery and optimization of a complex oxide with water photoelectrolysis activity. Chem Mater, 2008, 20: 2495

[13]

Fujishima A, Honda K. Electrochemical photolysis of water at a semiconductor electrode. Nature, 1972, 238: 37

[14]

Osterloh F E. Inorganic materials as catalysts for photochemical splitting of water. Chem Mater, 2008, 20: 35

[15]

Yan Q, Yu J, Suram S K, et al. Solar fuels photoanode materials discovery by integrating high-throughput theory and experiment. Proceedings of the National Academy of Sciences, 2017, 114: 3040

[16]

Shinde A, Suram S K, Yan Q, et al. Discovery of manganese-based solar fuel photoanodes via integration of electronic structure calculations, pourbaix stability modeling, and high-throughput experiments. ACS Energy Lett, 2017, 2: 2307

[17]

Persson K A, Waldwick B, Lazic P, et al. Prediction of solid-aqueous equilibria: Scheme to combine first-principles calculations of solids with experimental aqueous states. Phys Rev B, 2012, 85: 235438

[18]

Chen S Y, Wang L W. Thermodynamic oxidation and reduction potentials of photocatalytic semiconductors in aqueous solution. Chem Mater, 2012, 24: 3659

[19]

Maeda K, Domen K. New non-oxide photocatalysts designed for overall water splitting under visible light. J Phys Chem C, 2007, 111: 7851

[20]

Maeda K. Photocatalytic water splitting using semiconductor particles: history and recent developments. J Photoch Photobio C, 2011, 12: 237

[21]

Sayama K, Nomura A, Zou Z, et al. Photoelectrochemical decomposition of water on nanocrystalline BiVO4 film electrodes under visible light. Chem Commun, 2003, 23: 2908

[22]

Walsh A, Yan Y, Huda M N, et al. Band edge electronic structure of BiVO4: elucidating the role of the Bi s and V d orbitals. Chem Mater, 2009, 21: 547

[23]

Castelli I E, Olsen T, Datta S, et al. Computational screening of perovskite metal oxides for optimal solar light capture. Energ Environ Sci, 2012, 5: 5814

[24]

Castelli I E, Landis D D, Thygesen K S, et al. New cubic perovskites for one- and two-photon water splitting using the computational materials repository. Energ Environ Sci, 2012, 5: 9034

[25]

Castelli I E, Landis D D, Thygesen K S, et al. New cubic perovskites for one- and two-photon water splitting using the computational materials repository. Energy Environ Sci, 2012, 5: 9034

[26]

Butler M A, Ginley D S. Prediction of flatband potentials at semiconductor-electrolyte interfaces from atomic electronegativities. J Electrochem Soc, 1978, 125: 228

[27]

Chan M K Y, Ceder G. Efficient band gap prediction for solids. Phys Rev Lett, 2010, 105: 196403

[28]

Yan Q, Li G, Newhouse P F, et al. Mn2V2O7: an earth abundant light absorber for solar water splitting. Adv Energy Mater, 2015, 5: 1401840

[29]

Yan Q, Li G, Newhouse P F, et al. Mn2V2O7: an earth abundant light absorber for solar water splitting. Adv Energy Mater, 2015, 5: 1401840

[30]

Chemelewski W D, Mabayoje O, Mullins C B. SILAR growth of Ag3VO4 and characterization for photoelectrochemical water oxidation. J Phys Chem C, 2015, 119: 26803

[31]

Mandal H, Shyamal S, Hajra P, et al. Development of ternary iron vanadium oxide semiconductors for applications in photoelectrochemical water oxidation. RSC Adv, 2016, 6: 4992

[32]

Morton C D, Slipper I J, Thomas M J K, et al. Synthesis and characterisation of Fe–V–O thin film photoanodes. J Photochem Photobiol A, 2010, 216: 209

[33]

Seabold J A, Neale N R. All 1st row transition metal oxide photoanode for water splitting based on Cu3V2O8. Chem Mater, 2015, 27: 1005

[34]

Zhou L, Yan Q, Shinde A, et al. High throughput discovery of solar fuels photoanodes in the CuO–V2O5 system. Adv Energy Mater, 2015, 5: 1500968

[35]

Vi A, Aryasetiawan F, Lichtenstein A I. First-principles calculations of the electronic structure and spectra of strongly correlated systems: the LDA+U method. J Phys Condens Matter, 1997, 9: 767

[36]

Kresse G, Furthmuller J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput Mater Sci, 1996, 6: 15

[37]

Heyd J, Scuseria G E, Ernzerhof M. Hybrid functionals based on a screened Coulomb potential. J Chem Phys, 2006, 124: 219906

[38]

Moses P G, Miao M S, Yan Q M, et al. Hybrid functional investigations of band gaps and band alignments for AlN, GaN, InN, and InGaN. J Chem Phys, 2011, 134: 084703

[39]

Stevanovic V, Lany S, Ginley D S, et al. Assessing capability of semiconductors to split water using ionization potentials and electron affinities only. Phys Chem Chem Phys, 2014, 16: 3706

[40]

Hu S, Shaner M R, Beardslee J A, et al. Amorphous TiO2 coatings stabilize Si, GaAs, and GaP photoanodes for efficient water oxidation. Science, 2014, 344: 1005

[41]

Lichterman M F, Sun K, Hu S, et al. Protection of inorganic semiconductors for sustained, efficient photoelectrochemical water oxidation. Catalysis Today, 2016, 262: 11

[42]

Guevarra D, Shinde A, Suram S K, et al. Development of solar fuels photoanodes through combinatorial integration of Ni–La–Co–Ce oxide catalysts on BiVO4. Energy Environ Sci, 2016, 9: 565

[43]

Zachaus C, Abdi F F, Peter L M, et al. Photocurrent of BiVO4 is limited by surface recombination, not surface catalysis. Chem Sci, 2017, 8: 3712

[44]

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J B Pan, Q M Yan, Data-driven material discovery for photocatalysis: a short review[J]. J. Semicond., 2018, 39(7): 071001. doi: 10.1088/1674-4926/39/7/071001.

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Manuscript received: 07 November 2017 Manuscript revised: 17 December 2017 Online: Accepted Manuscript: 11 February 2018 Uncorrected proof: 12 April 2018 Published: 01 July 2018

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