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RESEARCH PAPER · Chemistry of Materials · 2019

Virtual Issue on Machine-Learning Discoveries in Materials Science

Anton O. Oliynyk, Jillian M. Buriak

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29 direct citing papers in this saved network. Explore the next layer with second-order citations.

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Virtual Issue on Machine-Learning Discoveries in Materials ScienceOriginalSearch for high-capacity oxygen storage materials by materials informatics12Artificial intelligence: the silver bullet for sustainable materials development86High-Throughput Screening of Antisolvents for the Deposition of High-Quality Perovskite Thin Films16Twenty years of exceptional success: The molecular education and research consortium in undergraduate computational chemistry ( MERCURY )29Effect of Increasing the Descriptor Set on Machine Learning Prediction of Small Molecule-Based Organic Solar Cells102Enhancing the stability of organic photovoltaics through machine learning68Machine learning for high performance organic solar cells: current scenario and future prospects375Proof of Concept: Calibration of an Overhead Line Conductors’ Movements Simulation Model Using Ensemble-Based Machine Learning Model3Machine learning approach for the prediction and optimization of thermal transport properties71Machine Learning in Magnetic Materials48A Conceptual Typology of Scientific Surprise in AI-Guided Discovery0Limitations of machine learning models when predicting compounds with completely new chemistries: possible improvements applied to the discovery of new non-fullerene acceptors39Perspective: Predicting and optimizing thermal transport properties with machine learning methods54Accelerating the discovery of high-performance donor/acceptor pairs in photovoltaic materials via machine learning and density functional theory23Green Chemistry Applied to Transition Metal Chalcogenides through Synthesis, Design of Experiments, Life Cycle Assessment, and Machine Learning5How statistical modeling and machine learning could help in the calibration of numerical simulation and fluid mechanics models? Application to the calibration of models reproducing the vibratory behavior of an overhead line conductor3Material machine learning for alloys: Applications, challenges and perspectives150Data-driven materials discovery and synthesis using machine learning methods14What is a minimal working example for a self-driving laboratory?49Machine Learning-Directed Predictive Models: Deciphering Complex Energy Transfer in Mn-Doped CsPb(Cl 1– y Br y ) 3 Perovskite Nanocrystals21Revolutionizing Low‐Cost Solar Cells with Machine Learning: A Systematic Review of Optimization Techniques35Efficient modeling of double absorber layered structure in perovskite solar cells using machine learning techniques18Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations32OCPMDM 2.0: An intelligent solution for materials data mining6Aprendizaje automático aplicado a la caracterización de nanoestructuras base carbono0Stabilization of the elusive or non-existent “YbMnPt” phase by chemical heterogeneity: The pseudo-ternary phases Eu0.28Yb0.72MnPt and YbCd0.13Mn0.87Pt with TiNiSi type structure1A Review on Fabrication and Quantum Chemical Designing of Organic Solar Cells: Role of DFT and Machine Learning Technologies3Artificial intelligence in the development of structural and functional materials: A transformative frontier and complementary enabler of the rational alloy design framework10Comparative assessment of dilute alloys and complex concentrated alloys: Design principles, processing, mechanisms, properties, and sustainability0

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  1. Search for high-capacity oxygen storage materials by materials informatics

    RSC Advances · 2019-01-01

    Nobuko Ohba, Takuro Yokoya, Seiji Kajita, Kensuke Takechi

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  2. Artificial intelligence: the silver bullet for sustainable materials development

    Green Chemistry · 2020-01-01

    Rifan Hardian, Zhenwen Liang, Xiangliang Zhang, György Székely

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  3. High-Throughput Screening of Antisolvents for the Deposition of High-Quality Perovskite Thin Films

    ACS Applied Materials & Interfaces · 2020-05-13

    Joseph G. Manion, Andrew H. Proppe, Garion E. J. Hicks, Edward Hartley Sargent, Dwight S. Seferos

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  4. Twenty years of exceptional success: The molecular education and research consortium in undergraduate computational chemistry ( MERCURY )

    International Journal of Quantum Chemistry · 2020-06-01

    George C. Shields

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  5. Effect of Increasing the Descriptor Set on Machine Learning Prediction of Small Molecule-Based Organic Solar Cells

    Chemistry of Materials · 2020-08-25

    Zhi‐Wen Zhao, Marcos del Cueto, Yun Geng, Alessandro Troisi

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  6. Enhancing the stability of organic photovoltaics through machine learning

    Nano Energy · 2020-09-01

    Tudur Wyn David, Helder Scapin Anizelli, T. Jesper Jacobsson, Cameron Gray, William J. Teahan, Jeff Kettle

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  7. Machine learning for high performance organic solar cells: current scenario and future prospects

    Energy & Environmental Science · 2020-11-25

    Asif Mahmood, Jin‐Liang Wang

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  8. Proof of Concept: Calibration of an Overhead Line Conductors’ Movements Simulation Model Using Ensemble-Based Machine Learning Model

    IEEE Access · 2021-01-01

    Hamdi Amroun, Mehdi Ammi, Fikri Hafid

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  9. Machine learning approach for the prediction and optimization of thermal transport properties

    Frontiers of Physics · 2021-02-11

    Yulou Ouyang, Cuiqian Yu, Gang Feng Yan, Jie Chen

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  10. Machine Learning in Magnetic Materials

    physica status solidi (b) · 2021-05-05

    Georgios Katsikas, C. Sarafidis, Joseph Kioseoglou

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  11. A Conceptual Typology of Scientific Surprise in AI-Guided Discovery

    Journal of Artificial Intelligence for Materials Science · 2022-01-01

    Claire Martin, Julien Robert, Sophie Bernard, Antoine Girard

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  12. Limitations of machine learning models when predicting compounds with completely new chemistries: possible improvements applied to the discovery of new non-fullerene acceptors

    Digital Discovery · 2022-01-01

    Zhi‐Wen Zhao, Marcos del Cueto, Alessandro Troisi

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  13. Perspective: Predicting and optimizing thermal transport properties with machine learning methods

    Energy and AI · 2022-03-12

    Wei Han, Hua Bao, Xiulin Ruan

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  14. Accelerating the discovery of high-performance donor/acceptor pairs in photovoltaic materials via machine learning and density functional theory

    Materials & Design · 2022-03-18

    Xiujuan Liu, Yueyue Shao, Tian Lu, Dongping Chang, Minjie Li, Wencong Lu

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  15. Green Chemistry Applied to Transition Metal Chalcogenides through Synthesis, Design of Experiments, Life Cycle Assessment, and Machine Learning

    IntechOpen eBooks · 2022-05-20

    Alexandre H. Pinto, Dylan R. Cho, Anton O. Oliynyk, Julian R. Silverman

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  16. How statistical modeling and machine learning could help in the calibration of numerical simulation and fluid mechanics models? Application to the calibration of models reproducing the vibratory behavior of an overhead line conductor

    Array · 2022-05-30

    Hamdi Amroun, Fikri Hafid, Mehdi Ammi

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  17. Material machine learning for alloys: Applications, challenges and perspectives

    Journal of Alloys and Compounds · 2022-06-21

    Xiujuan Liu, Pengcheng Xu, Juanjuan Zhao, Wencong Lu, Minjie Li, Gang Wang

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  18. Data-driven materials discovery and synthesis using machine learning methods

    Elsevier eBooks · 2022-11-04

    Sterling G. Baird, Marianne Liu, Hasan Muhammad Sayeed, Taylor D. Sparks

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  19. What is a minimal working example for a self-driving laboratory?

    Matter · 2022-12-01

    Sterling G. Baird, Taylor D. Sparks

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  20. Machine Learning-Directed Predictive Models: Deciphering Complex Energy Transfer in Mn-Doped CsPb(Cl 1– y Br y ) 3 Perovskite Nanocrystals

    Chemistry of Materials · 2023-06-13

    Hyejin Choe, Ho Jin, Seon Joo Lee, Junsang Cho

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  21. Revolutionizing Low‐Cost Solar Cells with Machine Learning: A Systematic Review of Optimization Techniques

    Advanced Energy and Sustainability Research · 2023-08-23

    Satyam Bhatti, Habib Ullah Manzoor, Bruno Michel, Ruy S. Bonilla, Richard Abrams, Ahmed Zoha, Sajjad Hussain, Rami Ghannam

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  22. Efficient modeling of double absorber layered structure in perovskite solar cells using machine learning techniques

    Physica Scripta · 2023-08-30

    J. Prasanna, Ekta Goel, Amarjit Kumar

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  23. Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations

    Results in Materials · 2023-09-01

    Desmond Edem Primus Klenam, Tabiri Kwayie Asumadu, Mobin Vandadi, Nima Rahbar, Fred McBagonluri, Winston Oluwole Soboyejo

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  24. OCPMDM 2.0: An intelligent solution for materials data mining

    Chemometrics and Intelligent Laboratory Systems · 2023-10-29

    Dongping Chang, Pengcheng Xu, Minjie Li, Wencong Lu

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  25. Aprendizaje automático aplicado a la caracterización de nanoestructuras base carbono

    Unknown journal · 2023-12-01

    Luis Enrique Vivanco-Benavides, División de Ciencias Básicas e Ingeniería, Universidad Autónoma Metropolina, Unidad Azcapotzlco., Cecilia Mercado Zúñiga

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  26. Stabilization of the elusive or non-existent “YbMnPt” phase by chemical heterogeneity: The pseudo-ternary phases Eu0.28Yb0.72MnPt and YbCd0.13Mn0.87Pt with TiNiSi type structure

    ChemRxiv · 2024-05-13

    Siméon Ponou, Anja‐Verena Mudring, Benedikt Friedrich

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  27. A Review on Fabrication and Quantum Chemical Designing of Organic Solar Cells: Role of DFT and Machine Learning Technologies

    High Energy Chemistry · 2024-11-01

    Sehar Shahzadi, Tayyaba Shahzadi, Zunaira Shafiq, Muhammad Ramzan Saeed Ashraf Janjua

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  28. Artificial intelligence in the development of structural and functional materials: A transformative frontier and complementary enabler of the rational alloy design framework

    Next research. · 2025-12-01

    Desmond Edem Primus Klenam

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  29. Comparative assessment of dilute alloys and complex concentrated alloys: Design principles, processing, mechanisms, properties, and sustainability

    Journal of Alloys and Compounds Communications · 2026-07-18

    Desmond Edem Primus Klenam, Tabiri Kwayie Asumadu, Michael Oluwatosin Bodunrin, Winston Oluwole Soboyejo

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