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RESEARCH PAPER · Chem · 2018

Reaction: The Near Future of Artificial Intelligence in Materials Discovery

Rafael Gómez‐Bombarelli

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

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42 direct citing works

Reaction: The Near Future of Artificial Intelligence in Materials DiscoveryOriginalNext-Generation Experimentation with Self-Driving Laboratories421Predicting charge density distribution of materials using a local-environment-based graph convolutional network65CO2 hydrogenation to high-value products via heterogeneous catalysis1176What Lies Behind Teaching and Learning Green Chemistry to Promote Sustainability Education? A Literature Review65High‐Throughput/High‐Output Experimentation in Polymer Research0Analysis and evaluation of machine learning applications in materials design and discovery33Autonomous and online detection of dry areas on a boiling surface using deep learning and infrared thermometry20Full Metal Species Quantification of Supported Catalysts: Beyond Metal Dispersion3Machine learning-driven catalyst design, synthesis and performance prediction for CO2 hydrogenation31Artificial Intelligence in Computational and Materials Chemistry: Prospects and Limitations13

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  1. Next-Generation Experimentation with Self-Driving Laboratories

    Trends in Chemistry · 2019-03-06

    Florian Häse, Loı̈c M. Roch, Alán Aspuru‐Guzik

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  2. Predicting charge density distribution of materials using a local-environment-based graph convolutional network

    Physical review. B./Physical review. B · 2019-11-07

    Sheng Rong Gong, Tian Xie, Taishan Zhu, Shuo Wang, Eric Fadel, Yawei Li, Jeffrey C. Grossman

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  3. CO2 hydrogenation to high-value products via heterogeneous catalysis

    Nature Communications · 2019-12-13

    Runping Ye, Jie Ding, Weibo Gong, Morris D. Argyle, Qin Zhong, Yujun Wang, Christopher K. Russell, Zhenghe Xu, Armistead Goode Russell, Qiaohong Li, Maohong Fan, Yuan‐Gen Yao

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  4. What Lies Behind Teaching and Learning Green Chemistry to Promote Sustainability Education? A Literature Review

    International Journal of Environmental Research and Public Health · 2020-10-27

    Meiai Chen, Eila Kyllikki Jeronen, Anming Wang

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  5. High‐Throughput/High‐Output Experimentation in Polymer Research

    Unknown journal · 2022-03-04

    Víctor Lechuga‐Islas, Carlos Guerrero‐Sánchez, Ramiro Guerrero‐Santos, Jürgen Vitz, Ulrich S. Schubert

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  6. Analysis and evaluation of machine learning applications in materials design and discovery

    Materials Today Communications · 2023-01-25

    Mahsa Golmohammadi, Masoud Aryanpour

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  7. Autonomous and online detection of dry areas on a boiling surface using deep learning and infrared thermometry

    Experimental Thermal and Fluid Science · 2023-02-22

    Madhumitha Ravichandran, Artyom Kossolapov, Gustavo Aguiar, Bren Phillips, Matteo Bucci

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  8. Full Metal Species Quantification of Supported Catalysts: Beyond Metal Dispersion

    ChemPlusChem · 2023-05-04

    Shuhui Liu, Ronghe Lin, Wei Liu, Yunjie Ding

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  9. Machine learning-driven catalyst design, synthesis and performance prediction for CO2 hydrogenation

    Journal of Industrial and Engineering Chemistry · 2024-09-21

    Muhammad Asif, Chengxi Yao, Zitu Zuo, Muhammad Bilal, Hassan Zeb, Seungjae Lee, Ziyang Wang, Taesung Kim

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  10. Artificial Intelligence in Computational and Materials Chemistry: Prospects and Limitations

    Chemistry Africa · 2025-06-11

    David B. Olawade, Oluwaseun Fapohunda, Sunday Oluwadamilola Usman, Abiola D. Akintayo, Ayokunle Olalekan Ige, Yemi Adekola Adekunle, Adedapo Oluwasanu Adeola

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