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RESEARCH PAPER · Nanomaterials · 2021

Scalable Graphene Defect Prediction Using Transferable Learning

Bowen Zheng, Zeyu Zheng, Grace X. Gu

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

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Scalable Graphene Defect Prediction Using Transferable LearningOriginalUncertainty quantification and prediction for mechanical properties of graphene aerogels via Gaussian process metamodels7Designing mechanically tough graphene oxide materials using deep reinforcement learning33A generalized machine learning framework for brittle crack problems using transfer learning and graph neural networks29Applications of Graphene Derivatives in All‐Solid‐State Supercapacitors7Energy storage in supercapacitor researches: Interdisciplinary applications from molecular simulations to machine learning15Multiscale modeling of graphene and carbon nanostructures: advances in atomistic, coarse-grained, and machine learning approaches4Machine Learning Strategies to Circumvent Variabilities in Chemical Vapour‐Deposited Graphene Coatings for Remarkable Corrosion Resistance of Metals3

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  1. Uncertainty quantification and prediction for mechanical properties of graphene aerogels via Gaussian process metamodels

    Nano Futures · 2021-11-23

    Bowen Zheng, Zeyu Zheng, Grace X. Gu

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  2. Designing mechanically tough graphene oxide materials using deep reinforcement learning

    npj Computational Materials · 2022-11-05

    Bowen Zheng, Zeyu Zheng, Grace X. Gu

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  3. A generalized machine learning framework for brittle crack problems using transfer learning and graph neural networks

    Mechanics of Materials · 2023-04-01

    Roberto Perera, Vinamra Agrawal

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  4. Applications of Graphene Derivatives in All‐Solid‐State Supercapacitors

    ChemistrySelect · 2024-11-01

    Edwin T. Mombeshora, Edigar Muchuweni, Hamed Hashemi

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  5. Energy storage in supercapacitor researches: Interdisciplinary applications from molecular simulations to machine learning

    Applied Energy · 2025-05-10

    Yawen Dong, Yutong Liu, Fei‐Fei Mao, Hua Wu

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  6. Multiscale modeling of graphene and carbon nanostructures: advances in atomistic, coarse-grained, and machine learning approaches

    RSC Advances · 2026-01-01

    Iman Najafipour, Santanu Chaudhuri

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  7. Machine Learning Strategies to Circumvent Variabilities in Chemical Vapour‐Deposited Graphene Coatings for Remarkable Corrosion Resistance of Metals

    Small Structures · 2026-02-01

    Pragyan Goswami, R.K. Singh Raman, Alankar Alankar

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