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RESEARCH PAPER · ACS Physical Chemistry Au · 2021

Feature Blending: An Approach toward Generalized Machine Learning Models for Property Prediction

Swanti Satsangi, Avanish Mishra, Abhishek Kumar Singh

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

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42 direct citing works

Feature Blending: An Approach toward Generalized Machine Learning Models for Property PredictionOriginalA universal similarity based approach for predictive uncertainty quantification in materials science25Machine-Learning-Based Predictions of Polymer and Postconsumer Recycled Polymer Properties: A Comprehensive Review62Predicting the work function of 2D MXenes using machine-learning methods45Crowd Counting and Density Estimation using Deep Network-A Comprehensive Survey2Crowd Counting and Density Estimation using Deep Network-A Comprehensive Survey2Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations32Recovery of Brine Resources Through Crown-Passivated Graphene, Silicene, and Boron Nitride Nanosheets Based on Machine-Learning Structural Predictions23Enhancing Li + recovery in brine mining: integrating next-gen emotional AI and explainable ML to predict adsorption energy in crown ether-based hierarchical nanomaterials14When Machine Learning Meets 2D Materials: A Review156Study of the novel boron nitride polymorphs: First- principles calculations and machine learning62D MXenes as electrode materials for metal-sulfur batteries: A review27Recent computational insights into hydrogen storage by MXene-based materials and shedding light on the storage mechanism37Material informatics-driven insights into brain cancer nanocarriers: A bibliometric comparison of PLGA vs. liposomes4Enhancing ML Model Generalizability for Locomotion Mode Recognition in Prosthetic Gait0Development and validation of predictive models for diabetic retinopathy using machine learning20Exploring New Nitrogen-Rich Compounds: Hybrid First-Principle Calculations and Machine-Learning Algorithms0Recent progress in the design and application of machine learning for the hydrogen evolution reaction in electrocatalysis and photocatalysis3Machine Learning Integrating Surface Features and Crystal Similarity for Exploring 2D Materials1Nb 2 CBr 2 MXene Monolayer as a Novel Material: A First Principle Study6

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  1. A universal similarity based approach for predictive uncertainty quantification in materials science

    Scientific Reports · 2022-09-02

    Vadim Korolev, Iurii M. Nevolin, Pavel V. Protsenko

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  2. Machine-Learning-Based Predictions of Polymer and Postconsumer Recycled Polymer Properties: A Comprehensive Review

    ACS Applied Materials & Interfaces · 2022-09-14

    Nagababu Andraju, Greg W. Curtzwiler, Yun Ji, Evguenii I. Kozliak, Prakash Ranganathan

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  3. Predicting the work function of 2D MXenes using machine-learning methods

    Journal of Physics Energy · 2023-01-13

    Pranav Roy, Lavie Rekhi, See Wee Koh, Hong Li, Tej Salil Choksi

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  4. Crowd Counting and Density Estimation using Deep Network-A Comprehensive Survey

    Unknown journal · 2023-06-02

    Muhammad Jawad Babar, Mujtaba Husnain, Malik Muhammad Saad Missen, Ali Samad, Muhammad Nasir, Abdul Karim Nawaz Khan

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  5. Crowd Counting and Density Estimation using Deep Network-A Comprehensive Survey

    Unknown journal · 2023-06-02

    Muhammad Jawad Babar, Mujtaba Husnain, Malik Muhammad Saad Missen, Ali Samad, Muhammad Nasir, Abdul Karim Nawaz Khan

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  6. 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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  7. Recovery of Brine Resources Through Crown-Passivated Graphene, Silicene, and Boron Nitride Nanosheets Based on Machine-Learning Structural Predictions

    ACS Applied Nano Materials · 2023-12-08

    Ismail Abdulazeez, Sani Isah Abba, Jamilu Usman, Abdullahi Garba Usman, Isam H. Aljundi

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  8. Enhancing Li + recovery in brine mining: integrating next-gen emotional AI and explainable ML to predict adsorption energy in crown ether-based hierarchical nanomaterials

    RSC Advances · 2024-01-01

    Sani Isah Abba, Jamilu Usman, Ismail Abdulazeez, Lukka Thuyavan Yogarathinam, Abdullahi Garba Usman, Dahiru Umar Lawal, Billel Salhi, Nadeem Baig, Isam H. Aljundi

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  9. When Machine Learning Meets 2D Materials: A Review

    Advanced Science · 2024-01-26

    Bin Lu, Yuze Xia, Yuqian Ren, Xie Miaomiao, Liguo Zhou, Giovanni Vinai, Simon A. Morton, Andrew T. S. Wee, Wilfred G. van der Wiel, Wen Zhang, Ping Kwan Johnny Wong

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  10. Study of the novel boron nitride polymorphs: First- principles calculations and machine learning

    Chinese Journal of Physics · 2024-04-24

    Qingyang Fan, Wenjiao Li, Nan Chun Wu, Yingbo Zhao, Yanxing Song, Xinhai Yu, Sining Yun

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  11. 2D MXenes as electrode materials for metal-sulfur batteries: A review

    Materials Today Physics · 2024-05-07

    Irfan Ali Soomro, Muhammad Nazim Lakhan, Abdul Hanan, Hamad R. Almujibah, Altaf Hussain, Abdul Hameed Pato, Mukhtiar Ahmed, Imran Ali Chandio, Saeed Ahmed Memon, Muhammad Umer, Faiza Bibi, Ming Lei

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  12. Recent computational insights into hydrogen storage by MXene-based materials and shedding light on the storage mechanism

    Journal of Energy Storage · 2024-07-11

    Türkan Kopaç

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  13. Material informatics-driven insights into brain cancer nanocarriers: A bibliometric comparison of PLGA vs. liposomes

    OpenNano · 2024-12-11

    Brilly Andro Makalew, Syauqi Abdurrahman Abrori

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  14. Enhancing ML Model Generalizability for Locomotion Mode Recognition in Prosthetic Gait

    IEEE Sensors Journal · 2025-01-07

    Muhammad Zeeshan Arshad, Aliaa Gouda, Jan Andrysek

    Read original paper ↗ ·

  15. Development and validation of predictive models for diabetic retinopathy using machine learning

    PLoS ONE · 2025-02-24

    Penglu Yang, Bin Yang

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  16. Exploring New Nitrogen-Rich Compounds: Hybrid First-Principle Calculations and Machine-Learning Algorithms

    Crystals · 2025-02-27

    Hang Zhou, Jie Wu, Jiangtao Yang, Qingyang Fan

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  17. Recent progress in the design and application of machine learning for the hydrogen evolution reaction in electrocatalysis and photocatalysis

    Materials Today Communications · 2025-04-08

    Kaifeng Zhang, Xudong Wang, Yanjing Su

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  18. Machine Learning Integrating Surface Features and Crystal Similarity for Exploring 2D Materials

    The Journal of Physical Chemistry Letters · 2025-08-19

    Junhao Liang, Caiyuan Ye, Xinyi Lin, Chunlin Yu, Yilimiranmu Rouzhahong, Chao Lun Liang, Huashan Li

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  19. Nb 2 CBr 2 MXene Monolayer as a Novel Material: A First Principle Study

    Advanced Theory and Simulations · 2025-11-11

    Leonardo S. Barbosa, Willian Oliveira Santos, Félix Silva Costa, Edvan Moreira, David L. Azevedo

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