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RESEARCH PAPER · Computational Materials Science · 2018

Accelerated search for perovskite materials with higher Curie temperature based on the machine learning methods

Xiuyun Zhai, Mingtong Chen, Wencong Lu

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Accelerated search for perovskite materials with higher Curie temperature based on the machine learning methodsOriginalUsing Data Mining To Search for Perovskite Materials with Higher Specific Surface Area44High critical transition temperature of lead-based perovskite ferroelectric crystals: A machine learning study12The pLoc_bal-mPlant is a powerful artificial intelligence tool for predicting the subcellular localization of plant proteins purely based on their sequence information9Prediction of liquidus temperature for complex electrolyte systems Na3AlF6-AlF3-CaF2-MgF2-Al2O3-KF-LiF based on the machine learning methods14Recent advances and applications of machine learning in solid-state materials science2607Artificial Intelligence (AI) Tools Constructed via the 5-Steps Rule for Predicting Post-Translational Modifications32Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design384Calcium Pattern Assessment in Patients with Severe Aortic Stenosis Via the Chou’s 5-Steps Rule27Impacts of Pseudo Amino Acid Components and 5-steps Rule to Proteomics and Proteome Analysis38Data mining assisted prediction of liquidus temperature for primary crystallization of different electrolyte systems4The Cradle of Gordon Life Science Institute and its Development and Driving Force11The Cradle of Gordon Life Science Institute and Its Development and Driving Force4An Insightful Recollection for Predicting Protein Subcellular Locations in Multi-Label Systems8Gordon Life Science Institute and Its Impacts on Computational Biology and Drug Development5Some illuminating remarks on molecular genetics and genomics as well as drug development13The Development of Gordon Life Science Institute: Its Driving Force and Accomplishments19The pLoc_bal-mGneg Predictor is a Powerful Web-Server for Identifying the Subcellular Localization of Gram-Negative Bacterial Proteins based on their Sequences Information Alone11The Significant and Profound Impacts of Chou’s 5-Steps Rule4Showcase to Illustrate How the Webserver ploc_Bal-Meuk Is Working12https://researchopenworld.com/showcase-to-illustrate-how-the-web-server-ploc_balmeuk-is-working/#0Metaheuristic-based inverse design of materials – A survey46Magnetic and superconducting phase diagrams and transition temperatures predicted using text mining and machine learning98Machine Learning Assisted Discovery of New Metal-free Perovskites for Blue Light Emission0The Ploc_Bal-Mhum Is a Powerful Web-Serve for Predicting the Subcellular Localization of Human Proteins Purely Based on Their Sequence Information5Two-dimensional hybrid organic–inorganic perovskites as emergent ferroelectric materials48A novel graphene-like titanium carbide MXene/Au–Ag nanoshuttles bifunctional nanosensor for electrochemical and SERS intelligent analysis of ultra-trace carbendazim coupled with machine learning134Fuel Ratio Optimization of Blast Furnace Based on Data Mining25Machine learning in materials design: Algorithm and application*62AntiFlamPred: An Anti-Inflammatory Peptide Predictor for Drug Selection Strategies13Machine learning for perovskite materials design and discovery536Machine learning aided design of perovskite oxide materials for photocatalytic water splitting156Accelerated search for ABO3-type the electronic contribution of polycrystalline dielectric constants by machine learning26Machine Learning Model for High-Throughput Screening of Perovskite Manganites with the Highest Néel Temperature8How can artificial intelligence be used for peptidomics?22Search for ABO3 Type Ferroelectric Perovskites with Targeted Multi-Properties by Machine Learning Strategies65A Property‐Driven Stepwise Design Strategy for Multiple Low‐Melting Alloys via Machine Learning26Innovative Materials Science via Machine Learning194Methodological Approach to the High-Pressure Synthesis of Nonmagnetic Li2B4+B′6+O6 Oxides19Accelerating perovskite materials discovery and correlated energy applications through artificial intelligence62Predictions on the Phase Constitution of SmCo7−XMx Alloys by Data Mining6Discovery of direct band gap perovskites for light harvesting by using machine learning60PSO-SVR predicting for the Ehull of ABO3-type compounds to screen the thermodynamic stable perovskite candidates based on multi-scale descriptors23Reconstructing Chromatic-Dispersion Relations and Predicting Refractive Indices Using Text Mining and Machine Learning25Review on Perovskite-Type Compound Using Machine Learning5Applications of machine learning in perovskite materials80Machine Learning‐Assisted Microfluidic Synthesis of Perovskite Quantum Dots34A machine learning-based nano-photocatalyst module for accelerating the design of Bi 2 WO 6 /MIL-53(Al) nanocomposites with enhanced photocatalytic activity18Prediction of ferromagnetic materials with high Curie temperature based on material composition information2Analysis and evaluation of machine learning applications in materials design and discovery33Machine learning for fast development of advanced energy materials23Machine learning predictions of high-Curie-temperature materials19Machine learning aided accelerated prediction and experimental validation of functional properties of K1-xNaxNbO3-based piezoelectric ceramics18Rapid screening B-site doping ferroelectric perovskite with high curie temperature for electronic applications by a novel IDBO-RF approach4Machine learning for deconstructing contributions of atomic characterizations to achieve hybridization-determined electron transfer in a perovskite catalyst6Interpretable machine learning model of effective mass in perovskite oxides with cross-scale features3Understanding Defects in Perovskite Solar Cells through Computation: Current Knowledge and Future Challenge83Data extension-based analysis and application selection of process-composition-properties of die casting aluminum alloy13Predicting the Curie temperature of Sm-Co-based alloys via data-driven strategy16Accelerated Design for Perovskite-Oxide-Based Photocatalysts Using Machine Learning Techniques18AI for dielectric capacitors16Nonlinear Optical Effects in Europium Melilite Eu2MgSi2O70Machine learning assisted innovative strategy for experimental validation of functional properties of lead-free ceramics8Predicting the Curie temperature of magnetic materials with automated calculations across chemistries and structures10Multi-Properties prediction of perovskite materials using Machine learning and Meta-Heuristic feature selection9Machine Learning Methodologies Applied to Magnetocaloric Perovskites Discovery13Computational modeling of the magnetic couplings in Quadruple Perovskite CaCu3Mn2Os2O12: Monte Carlo investigation2Quadruple perovskite CaCu3Fe2Re2O12: Monte Carlo modeling of the exchange constants3Predicting the Curie temperature in substitutionally disordered alloys using a first-principles based model0A hybrid machine learning approach for predicting the performance of perovskite solar cells under varying temperatures2Modeling of ferroelectric properties of KNN-based ceramics1Review: machine learning-driven design and discovery of halide perovskite materials1Structure-driven prediction and mechanism insights into piezoelectric performance of potassium sodium niobate via interpretable machine learning4Artificial Intelligence-Based Applications in Perovskite Photovoltaic Cells7Machine learning-driven prognostication of multifunctional properties of (K,Na)NbO3-based lead-free ceramics for optimized materials design3Accelerated design and thermal stability optimization of γ-U-Mo metallic nuclear fuels1Data-driven approaches for functional ceramics3Integrating NSGA-II and TOPSIS for Stacking Model Optimization in Pursuit of Halide Double Perovskite Screening0Accelerating accurate multi-property prediction of perovskites via meta-heuristic algorithm tuned machine learning0Prediction of ferroelectric properties of (K,Na)NbO3-based solid solutions with the aid of interpretable descriptors0

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  1. Using Data Mining To Search for Perovskite Materials with Higher Specific Surface Area

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  2. High critical transition temperature of lead-based perovskite ferroelectric crystals: A machine learning study

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  3. The pLoc_bal-mPlant is a powerful artificial intelligence tool for predicting the subcellular localization of plant proteins purely based on their sequence information

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  4. Prediction of liquidus temperature for complex electrolyte systems Na3AlF6-AlF3-CaF2-MgF2-Al2O3-KF-LiF based on the machine learning methods

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  5. Recent advances and applications of machine learning in solid-state materials science

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  6. Artificial Intelligence (AI) Tools Constructed via the 5-Steps Rule for Predicting Post-Translational Modifications

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  7. Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design

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  8. Calcium Pattern Assessment in Patients with Severe Aortic Stenosis Via the Chou’s 5-Steps Rule

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  9. Impacts of Pseudo Amino Acid Components and 5-steps Rule to Proteomics and Proteome Analysis

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  10. Data mining assisted prediction of liquidus temperature for primary crystallization of different electrolyte systems

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  11. The Cradle of Gordon Life Science Institute and its Development and Driving Force

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  12. The Cradle of Gordon Life Science Institute and Its Development and Driving Force

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  13. An Insightful Recollection for Predicting Protein Subcellular Locations in Multi-Label Systems

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  14. Gordon Life Science Institute and Its Impacts on Computational Biology and Drug Development

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  15. Some illuminating remarks on molecular genetics and genomics as well as drug development

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  16. The Development of Gordon Life Science Institute: Its Driving Force and Accomplishments

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  17. The pLoc_bal-mGneg Predictor is a Powerful Web-Server for Identifying the Subcellular Localization of Gram-Negative Bacterial Proteins based on their Sequences Information Alone

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  18. The Significant and Profound Impacts of Chou’s 5-Steps Rule

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  19. Showcase to Illustrate How the Webserver ploc_Bal-Meuk Is Working

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  21. Metaheuristic-based inverse design of materials – A survey

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  22. Magnetic and superconducting phase diagrams and transition temperatures predicted using text mining and machine learning

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  23. Machine Learning Assisted Discovery of New Metal-free Perovskites for Blue Light Emission

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  24. The Ploc_Bal-Mhum Is a Powerful Web-Serve for Predicting the Subcellular Localization of Human Proteins Purely Based on Their Sequence Information

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  25. Two-dimensional hybrid organic–inorganic perovskites as emergent ferroelectric materials

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  26. A novel graphene-like titanium carbide MXene/Au–Ag nanoshuttles bifunctional nanosensor for electrochemical and SERS intelligent analysis of ultra-trace carbendazim coupled with machine learning

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  27. Fuel Ratio Optimization of Blast Furnace Based on Data Mining

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  28. Machine learning in materials design: Algorithm and application*

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  30. Machine learning for perovskite materials design and discovery

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  31. Machine learning aided design of perovskite oxide materials for photocatalytic water splitting

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  32. Accelerated search for ABO3-type the electronic contribution of polycrystalline dielectric constants by machine learning

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  33. Machine Learning Model for High-Throughput Screening of Perovskite Manganites with the Highest Néel Temperature

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  39. Accelerating perovskite materials discovery and correlated energy applications through artificial intelligence

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  40. Predictions on the Phase Constitution of SmCo7−XMx Alloys by Data Mining

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  41. Discovery of direct band gap perovskites for light harvesting by using machine learning

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  42. PSO-SVR predicting for the Ehull of ABO3-type compounds to screen the thermodynamic stable perovskite candidates based on multi-scale descriptors

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  47. A machine learning-based nano-photocatalyst module for accelerating the design of Bi 2 WO 6 /MIL-53(Al) nanocomposites with enhanced photocatalytic activity

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  48. Prediction of ferromagnetic materials with high Curie temperature based on material composition information

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