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RESEARCH PAPER · InfoMat · 2020

Computational functionality‐driven design of semiconductors for optoelectronic applications

Zhun Liu, Guangren Na, Fuyu Tian, Liping Yu, Jingbo Li, Lijun Zhang

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Computational functionality‐driven design of semiconductors for optoelectronic applicationsOriginalPitfalls of simulation-based machine learning in optoelectronic device design1Pitfalls of simulation-based machine learning in optoelectronic device design1High‐throughput computational materials screening and discovery of optoelectronic semiconductors100Rashba band splitting in two-dimensional Ruddlesden–Popper halide perovskites17Explanation for the conductivity difference of half-Heusler transparent conductors via ionization energy9Harvesting High-Quality White-Light Emitting and Remarkable Emission Enhancement in One-Dimensional Halide Perovskites Upon Compression23Optical emission enhancement of bent InSe thin films11High‐Throughput Screening for Phase‐Change Memory Materials90Simulation-based machine learning for optoelectronic device design: perspectives, problems, and prospects25Discovery of New Phases of Bismuth Oxyselenide Semiconductor Bi2OSe2 by Global Structure Search Approach2Phase transition pathway of hybrid halide perovskites under compression: Insights from first-principles calculations16JAMIP: an artificial-intelligence aided data-driven infrastructure for computational materials informatics85Grain Boundaries in Methylammonium Lead Halide Perovskites Facilitate Water Diffusion18Efficient Modeling Workflow for Accurate Electronic Structures of Hybrid Perovskites13Metal Halide Semiconductors beyond Lead-Based Perovskites for Promising Optoelectronic Applications54A New Star-shaped Amino Functionalized poly(phenylene oxide) for Optoelectronic Applications1On topological materials as photocatalysts for water splitting by visible light3Electronic and Photoelectronic Memristors Based on 2D Materials74Universal machine learning framework for defect predictions in zinc blende semiconductors56Global instability index as a crystallographic stability descriptor of halide and chalcogenide perovskites43A first principles investigation of ternary and quaternary II–VI zincblende semiconductor alloys13Evaluation of performance of machine learning methods in mining structure–property data of halide perovskite materials21The Electronic Structure of Cs2AgBiBr6 at Room Temperature24Inorganic Crystal Structure Prototype Database Based on Unsupervised Learning of Local Atomic Environments11Data-driven design of high-performance MASnxPb1-xI3 perovskite materials by machine learning and experimental realization66First-principles calculations to investigate structural, electronic and optical properties of two-dimensional ZnIn2S416Design of New Ternary Nitrides for Photovoltaic Applications via High-Throughput Calculations8Clathrate‐Like Alkali and Alkaline‐Earth Metal Borides: A New Family of Superconductors with Superior Hardness30Synthesizability of transition-metal dichalcogenides: a systematic first-principles evaluation22DFT with corrections for an efficient and accurate description of strong electron correlations in NiO23From the perspective of experimental practice: High-throughput computational screening in photocatalysis15Analysis of good and bad fingerprint for identification of NIR based optical frameworks using Monte Carlo method4Deep Learning-Based Chemical Similarity for Accelerated Organic Light-Emitting Diode Materials Discovery9Miniaturized droplets flow reactor for one-step highly controlled synthesis of SnO2 quantum dots at room temperature4Accelerating defect predictions in semiconductors using graph neural networks39The Applicable Guideline for the Three Criteria in Identifying p/n-Type Characteristics16Metallic superhard CaB12 with novel waffle-like boron backbone14Designing semiconductor materials and devices in the post-Moore era by tackling computational challenges with data-driven strategies33A guide to discovering next-generation semiconductor materials using atomistic simulations and machine learning14Theoretical methods for physical characterization of nanostructures0Structural, electronic, mechanical, optical and magnetic properties of RhNbZ (Z = Li, Si, As) Half-Heusler compounds: a first-principles study7Comprehensive evaluation of transparent electrode materials: A hybrid methodology of AHP, FOM, and cost-efficiency metrics1Computational investigations of structural, electronic, and optical properties of (Mg, Li, Fe)-doped CsSnCl3 for optoelectronic applications: By first principles3Defect modeling in semiconductors: the role of first principles simulations and machine learning17Unveiling the potential of Ca₃PBr₃ perovskite for solar applications: A study of structural, mechanical, electronic and optical properties3Optoelectronics, mechanical and thermoelectric properties of wide-band-gap semiconductors MgXS: X= Cd, Zn in the non-magnetic rock salt phase0Third-order nonlinear optical properties of TiO2 nano colloidal synthesized via sol–gel and hydrothermal methods: A comparison6Machine learning-enabled optoelectronic material discovery: a comprehensive review31Artificial Intelligence‐Driven Approaches in Semiconductor Research44First-principles study on the electronic, optical, and transport properties of P-type transparent conductive oxides Sn2NbxTa2-xO7 (x = 2, 1.5, 1, 0.5, 0)18Density functional theory study of Mg3TeO6 with excellent optical properties and p-type performance1Synergistic Effects of TiO 2 @CdS Heterojunctions Enable High-Performance Blue-Light-Sensitive Photodetectors and Iontronic Synapse Fibers for Underwater Interactions7Enhancing Business Management Decisions with COPRAS A Roundtable Evaluation of Farouche0Room Temperature Wafer‐Scale Synthesis of Highly Transparent and Conductive p‐Type Sulfur‐Doped Copper Iodide3Influence of Iodination Methods at Room Temperature on Crystallinity and Electrical Property of CuI Thin Films0Identifying A/B-Site Effects and Screening of β-ABO 2 Ferroelectrics toward Optoelectronic Functionality0Tunable Electronic and Optical Properties of LiN 1 − x P x Mg Half‐Heusler Phases for Advanced Optoelectronic Applications0

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  1. Pitfalls of simulation-based machine learning in optoelectronic device design

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  2. Pitfalls of simulation-based machine learning in optoelectronic device design

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  3. High‐throughput computational materials screening and discovery of optoelectronic semiconductors

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  4. Rashba band splitting in two-dimensional Ruddlesden–Popper halide perovskites

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    Shidong Yu, Guangren Na, Shulin Luo, Oleg Rubel, Lijun Zhang

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  5. Explanation for the conductivity difference of half-Heusler transparent conductors via ionization energy

    Physical Chemistry Chemical Physics · 2021-01-01

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  6. Harvesting High-Quality White-Light Emitting and Remarkable Emission Enhancement in One-Dimensional Halide Perovskites Upon Compression

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  7. Optical emission enhancement of bent InSe thin films

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  8. High‐Throughput Screening for Phase‐Change Memory Materials

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  9. Simulation-based machine learning for optoelectronic device design: perspectives, problems, and prospects

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  10. Discovery of New Phases of Bismuth Oxyselenide Semiconductor Bi2OSe2 by Global Structure Search Approach

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  11. Phase transition pathway of hybrid halide perovskites under compression: Insights from first-principles calculations

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  12. JAMIP: an artificial-intelligence aided data-driven infrastructure for computational materials informatics

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  13. Grain Boundaries in Methylammonium Lead Halide Perovskites Facilitate Water Diffusion

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  14. Efficient Modeling Workflow for Accurate Electronic Structures of Hybrid Perovskites

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  15. Metal Halide Semiconductors beyond Lead-Based Perovskites for Promising Optoelectronic Applications

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  16. A New Star-shaped Amino Functionalized poly(phenylene oxide) for Optoelectronic Applications

    Polymer Science Series B · 2021-11-01

    T. A. Zidan, Ahmed Mahmoud Youssef, E.M. El-Menyawy, Heba Kandil

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  17. On topological materials as photocatalysts for water splitting by visible light

    Journal of Physics Materials · 2021-11-03

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  18. Electronic and Photoelectronic Memristors Based on 2D Materials

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  19. Universal machine learning framework for defect predictions in zinc blende semiconductors

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  20. Global instability index as a crystallographic stability descriptor of halide and chalcogenide perovskites

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  21. A first principles investigation of ternary and quaternary II–VI zincblende semiconductor alloys

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  22. Evaluation of performance of machine learning methods in mining structure–property data of halide perovskite materials

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  23. The Electronic Structure of Cs2AgBiBr6 at Room Temperature

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  24. Inorganic Crystal Structure Prototype Database Based on Unsupervised Learning of Local Atomic Environments

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  25. Data-driven design of high-performance MASnxPb1-xI3 perovskite materials by machine learning and experimental realization

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  26. First-principles calculations to investigate structural, electronic and optical properties of two-dimensional ZnIn2S4

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  27. Design of New Ternary Nitrides for Photovoltaic Applications via High-Throughput Calculations

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  50. First-principles study on the electronic, optical, and transport properties of P-type transparent conductive oxides Sn2NbxTa2-xO7 (x = 2, 1.5, 1, 0.5, 0)

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