BetaCitation Atlas

RESEARCH PAPER · ChemCatChem · 2022

Theory‐Guided Machine Learning to Predict the Performance of Noble Metal Catalysts in the Water‐Gas Shift Reaction

Read original paper ↗

See where this research leads.

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

Open in your workspace →Saved 2026-10-14 · complete coverage
Filter Citing Papers
Press Enter or comma to add · × to remove · searches titles and available abstracts
Journals
All journals
Most represented first · select one or more
Explore Terms In These PapersHide SuggestionsShow Suggestions

Original and current center papers stay visible as anchors.
Numbers show citations received
42 direct citing works

Theory‐Guided Machine Learning to Predict the Performance of Noble Metal Catalysts in the Water‐Gas Shift ReactionOriginalKnowledge-Driven Transfer Learning for Tree Species Recognition2Data-Driven Design and Understanding of Noble Metal-Based Water–Gas Shift Catalysts from Literature Data6Prediction of Avena sativa MicroRNAs and Their Impact on the Growth and Development0Predictive Modeling of Co2 Methanation Reaction for Carbon Capture2Preparation of a Water–Gas Shift Database to Evaluate the Performance of Noble Metal Catalysts Using Theory-Guided Machine Learning8Digital twins based on machine learning for optimal control of chemical looping hydrogen generation processes21Machine learning-enhanced optimal catalyst selection for water-gas shift reaction7Accelerating catalytic experimentation of water gas shift reaction using machine learning models6Introducing an improved rime algorithm combined with gate current unit as an innovative stability monitoring and controlling model for flexible biogas-to-hydrogen/methanol system0Thermodynamics-Guided Machine Learning Framework with a Multiobjective Optimizer for Catalyst Discovery4Physicochemical Feature-Driven Machine Learning and Multi-Objective Optimization for CO2 Capture in MEA/PZ Blends0

Arrows point to the paper being cited. Selecting a paper shows its incoming citations and its known path back to the original paper.

Browse Matching Papers

Papers that cite this work

11 direct citing papers saved.

  1. Knowledge-Driven Transfer Learning for Tree Species Recognition

    International Conference on Control, Automation, Robotics and Vision (ICARCV) · 2022-12-11

    Joyjit Chattoraj, Feng Yang, Chi Wan Lim, Like Gobeawan, Xuan Liu, Venugopalan Raghavan

    Read original paper ↗ ·
  2. Data-Driven Design and Understanding of Noble Metal-Based Water–Gas Shift Catalysts from Literature Data

    The Journal of Physical Chemistry C · 2023-03-23

    Fernando Garcia‐Escobar, Shun Nishimura, KEISUKE G. TAKAHASHI

    Read original paper ↗ ·
  3. Prediction of Avena sativa MicroRNAs and Their Impact on the Growth and Development

    Research Square · 2023-06-30

    Animesh Ray, Neelam Nathani, Yengkhom Sophiarani, N. Seema Devi, Prosenjit Paul

    Read original paper ↗ ·
  4. Predictive Modeling of Co2 Methanation Reaction for Carbon Capture

    Preprints.org · 2023-09-08

    Osman Okur

    Read original paper ↗ ·
  5. Preparation of a Water–Gas Shift Database to Evaluate the Performance of Noble Metal Catalysts Using Theory-Guided Machine Learning

    ACS Catalysis · 2023-10-24

    Joyjit Chattoraj, Brahim Hamadicharef, Yusuf Nizar Aris Syadzali, Gerren Owen Limantara, Yingzhi Zeng, Chee Kok Poh, Luwei Chen, Teck Leong Tan

    Read original paper ↗ ·
  6. Digital twins based on machine learning for optimal control of chemical looping hydrogen generation processes

    International Journal of Hydrogen Energy · 2024-03-03

    Yiwen Song, Zehua Chen, Yongxian Zhou, Diyan Fang, Yingjie Lu, Rui Xiao, Dewang Zeng

    Read original paper ↗ ·
  7. Machine learning-enhanced optimal catalyst selection for water-gas shift reaction

    Digital Chemical Engineering · 2024-06-25

    Rahul Golder, Shraman Pal, Sathish Kumar C., Koustuv Ray

    Read original paper ↗ ·
  8. Accelerating catalytic experimentation of water gas shift reaction using machine learning models

    Process Safety and Environmental Protection · 2024-11-22

    Sathish Kumar C, Koustuv Ray

    Read original paper ↗ ·
  9. Introducing an improved rime algorithm combined with gate current unit as an innovative stability monitoring and controlling model for flexible biogas-to-hydrogen/methanol system

    Renewable Energy · 2025-04-05

    Tao Tan, Zetao Huang, Zuhao Li, Taoli Huhe, Zhige Zhang, Yushu Chen, Yong Chen

    Read original paper ↗ ·
  10. Thermodynamics-Guided Machine Learning Framework with a Multiobjective Optimizer for Catalyst Discovery

    ACS Catalysis · 2026-01-02

    Zhenfeng Tan, Yuanming Zhu, Bin Shao, Feng Qian, Jun Hu

    Read original paper ↗ ·
  11. Physicochemical Feature-Driven Machine Learning and Multi-Objective Optimization for CO2 Capture in MEA/PZ Blends

    Processes · 2026-05-27

    Ying Liu, Xuezhi Zhang, Chuanchao Zhao, Yudong Mao, Kaimin Yang, Shengze Lu, Jiying Liu

    Read original paper ↗ ·