BetaCitation Atlas

RESEARCH PAPER · Batteries & Supercaps · 2022

Battery Materials Discovery and Smart Grid Management using Machine Learning

Andrew Jun Yao Wong, Xin Zhou, Yanwei Lum, Zhenpeng Yao, Yang Choo Chua, Yonggang Wen, Zhi Wei Seh

Read original paper ↗

See where this research leads.

8 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

Battery Materials Discovery and Smart Grid Management using Machine LearningOriginalNavigating materials chemical space to discover new battery electrodes using machine learning26Data‐Driven Online Prognosis of Rechargeable Batteries: Prospect and Perspective7Machine Learning-Driven Smart Discovery in IoT-Enabled Environments0Machine learning-assisted design and prediction of materials for batteries based on alkali metals8Screening of potential candidates for solid electrolyte interphase materials for lithium-ion batteries through a data-driven approach5Generative Deep Learning for Advanced Battery Materials3Towards artificial intelligence-enabled autonomous battery prognostics and management12Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO 2 Conversion3

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

Drag to pan · Use + / − to zoom · Escape to close43 nodes / 53 citation links
Browse Matching Papers

Papers that cite this work

8 direct citing papers saved.

  1. Navigating materials chemical space to discover new battery electrodes using machine learning

    Energy storage materials · 2023-12-06

    Mukhtar Lawan Adam, Oyawale Adetunji Moses, Jonathan P. Mailoa, Chang‐Yu Hsieh, Xue‐Feng Yu, Hao Li, Haitao Zhao

    Read original paper ↗ ·

  2. Data‐Driven Online Prognosis of Rechargeable Batteries: Prospect and Perspective

    Batteries & Supercaps · 2024-01-17

    Kun‐Yu Liu, T. Wang, Xinyan Liu, Hong‐Jie Peng

    Read original paper ↗ ·

  3. Machine Learning-Driven Smart Discovery in IoT-Enabled Environments

    Advances in civil and industrial engineering book series · 2024-08-26

    N. Naveen, Suresh Bysani Venkata Naga, G. Satish, B M Chandrakala, H. K. Bhargav, A. P. Latha

    Read original paper ↗ ·

  4. Machine learning-assisted design and prediction of materials for batteries based on alkali metals

    Physical Chemistry Chemical Physics · 2025-01-01

    Kexin Si, Zhipeng Sun, Huaxin Song, Xiangfen Jiang, Xuebin Wang

    Read original paper ↗ ·

  5. Screening of potential candidates for solid electrolyte interphase materials for lithium-ion batteries through a data-driven approach

    Physical Chemistry Chemical Physics · 2025-01-01

    Sadhana Barman, Utpal Sarkar

    Read original paper ↗ ·

  6. Generative Deep Learning for Advanced Battery Materials

    Batteries & Supercaps · 2025-09-08

    D. Rajagopal, Adrian Cierpka, Britta Nestler, Arnd Koeppe

    Read original paper ↗ ·

  7. Towards artificial intelligence-enabled autonomous battery prognostics and management

    Journal of Energy Chemistry · 2025-10-15

    Dapai Shi, Misheng Cai, Yunhong Che, Lili Xie, Jingyuan Zhao

    Read original paper ↗ ·

  8. Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO 2 Conversion

    Advanced Intelligent Discovery · 2026-02-22

    Paul Rossener Regonia, Christian Mark Pelicano

    Read original paper ↗ ·
Citation Atlas · A map of research, not a ranking.