Computationally driven high-throughput identification of CaTe and 
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 as promising candidates for high-mobility 
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-type transparent conducting materials

Ha, Viet-Anh; Yu, Guodong; Ricci, Francesco; Dahliah, Diana; Setten, Michiel J. van; Giantomassi, Matteo; Rignanese, Gian‐Marco; Hautier, Geoffroy

doi:10.1103/physrevmaterials.3.034601

Cited by 21 publications

(19 citation statements)

References 67 publications

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“…108 Very recently, Ha et al screened all nonoxide compounds from the ICSD and identified CaTe and Li 3 Sb as potential p-type TCM candidates. 109 They also performed a defect study and computed the phonon-limited mobility for these candidates to further assess their potential. Nonoxides were also screened by Raghupathy et al with a focus on nontoxic binary nonoxide chalcogenide-based semiconductors from the ICSD and Materials Project (more than 500 materials).…”

Section: Ht Approachmentioning

confidence: 99%

Transparent conducting materials discovery using high-throughput computing

et al. 2019

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Transparent conducting materials (TCMs) are required in many applications from solar cells to transparent electronics. Developing high performance materials combining the antagonistic properties of transparency and conductivity has been challenging especially for p-type materials. Recently, high-throughput ab initio computational screening has emerged as a formidable tool for accelerating materials discovery. In this review, we discuss how this approach has been applied for identifying TCMs. We provide a brief overview of the different materials properties of importance for TCMs (e.g., dopability, effective mass, and transparency) and present the ab initio techniques available to assess them. We focus on the accuracy of the methodologies as well as their suitability for high-throughput computing. Finally, we review the different high-throughput computational studies searching for new TCMs and discuss their differences in terms of methodologies and main findings.

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Section: Ht Approachmentioning

confidence: 99%

Transparent conducting materials discovery using high-throughput computing

et al. 2019

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“…In recent years, a wealth of literature is focused on HT computational screening and discovery of p-type TCMs. 25,[157][158][159][160][161][162][163][164][165][166] Especially, a set of 18 valence electron ternary ABX compounds (with 1:1:1 stoichiometry) were identified as promising p-type TCMs. 37,167 Based on the HT DFT calculations, Ran et al 168 potential p-type TCOs, among which the p-type dopability was found to be promisingly feasible for the compounds with larger n value.…”

Section: Transparent Conducting Materialsmentioning

confidence: 99%

“…The TCMs can be classified into two types, namely p‐type and n‐type. In recent years, a wealth of literature is focused on HT computational screening and discovery of p‐type TCMs 25,157–166 . Especially, a set of 18 valence electron ternary ABX compounds (with 1:1:1 stoichiometry) were identified as promising p‐type TCMs 37,167 .…”

Section: Ht Computational Materials Screening and Discovery Of Optoelmentioning

confidence: 99%

High‐throughput computational materials screening and discovery of optoelectronic semiconductors

Luo

Wang

et al. 2020

WIREs Comput Mol Sci

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In the recent past, optoelectronic semiconductors have attracted significant research attention both experimentally and theoretically toward large-scale applications in energy conversion, lighting, imaging, detection, and so on. With advancement in computing power and rapid development of computational algorithms, scientific community resorts to materials simulation to explore the hidden potential behind thousands of potentially unknown materials within short timeframes that the real experiments might take a long time. Within this context, the high-throughput (HT) computational materials screening has emerged as a useful tool to accelerate materials discovery, especially in the field of optoelectronic semiconductors. One of the important consequences is the construction of a number of material databases containing wide range of functional materials with their diverse physical properties and applications. Herein, we reviewed the recent progress on HT computational screening of optoelectronic semiconductors, with focus on photovoltaic solar absorbers, photoelectrochemical cells, semiconductor light-emitting diodes, and transparent conducting materials. We have also summarized the general workflow of HT computational screening, released workhorse models, and existing material databases. Finally, we offer perspectives for future research with a hope that this study could inspire new ideas for computational-driven optoelectronic semiconductor discovery in the HT routine. This article is categorized under: Structure and Mechanism > Computational Materials Science K E Y W O R D S first principles calculations, high-throughput, materials by design, optoelectronic semiconductors 1 | INTRODUCTION The excessive use of fossil fuels has caused global energy crisis and environmental concerns at the current stage. 1 Finding and designing novel energy materials is the key to sustainable development of human society. 2-4 Additionally, the information and electronic devices are widely used in industrials, astronautic, environmental, medical, and biological fields. 5 Materials with low cost and superior electroluminescence performance are the metrics for the development of

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“…This method of computationally driven design has been successfully implemented in advancing the search for highmobility transparent p-type semiconductors in previous studies. [52][53][54] Combining this with technological breakthroughs in thin-film and solid-state synthesis procedures allow for the fabrication of ''designer'' layered compounds; thus, greater control is achievable, allowing previously unobtainable metastable or difficult-tosynthesize layered compounds to be realized. [55][56][57][58] In this work, using cation substitution in the oxide layer, we computationally predict eight layered oxysulfides with optical band gaps spanning the range 0.…”

Section: Progress and Potentialmentioning

confidence: 99%

Computationally Driven Discovery of Layered Quinary Oxychalcogenides: Potential p-Type Transparent Conductors?

Williamson

Limburn

Watson

et al. 2020

Matter

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The realization of transparent electronics is hindered by the lack of a suitable highmobility p-type transparent conductor (TC). This work used ab initio simulations to search for a p-type TC based on the layered oxychalcogenide [Cu 2 S 2 ][A 3 M 2 O 5 ] structure. The main result of this study was the discovery of the optimum p-type oxychalcogenide TC, [Cu 2 S 2 ][Ba 3 Sc 2 O 5 ], predicted to have a higher optical band gap, better hole mobility, and greater stability than its parent compound [Cu 2 S 2 ] [Ba 3 Sc 2 O 5 ]; this was verified experimentally.

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Computationally driven high-throughput identification of CaTe and Li3Sb as promising candidates for high-mobility p -type transparent conducting materials

Cited by 21 publications

References 67 publications

Transparent conducting materials discovery using high-throughput computing

Transparent conducting materials discovery using high-throughput computing

High‐throughput computational materials screening and discovery of optoelectronic semiconductors

Computationally Driven Discovery of Layered Quinary Oxychalcogenides: Potential p-Type Transparent Conductors?

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