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RESEARCH PAPER · APL Machine Learning · 2023

Materials cartography: A forward-looking perspective on materials representation and devising better maps

Steven B. Torrisi, Martin Z. Bazant, Alexander E. Cohen, Min Gee Cho, Jens S. Hummelshøj, Linda Hung, Gaurav Ashish Kamat, Arash Khajeh, Adeesh Kolluru, Xiangyun Lei, Handong Ling, Joseph H. Montoya, Tim Mueller, Aini Palizhati, Benjamin Paren, Brandon K. Phan, Jacob Pietryga, Elodie Sandraz, Daniel Schweigert, Yang Shao‐Horn, Amalie Trewartha, Ruijie Zhu, Debbie Zhuang, Shijing Sun

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13 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
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42 direct citing works

Materials cartography: A forward-looking perspective on materials representation and devising better mapsOriginalPhysics-Informed Design of Hybrid Pulse Power Characterization (HPPC) Tests for Rechargeable Batteries3Calibration in machine learning uncertainty quantification: Beyond consistency to target adaptivity21Autonomous laboratories for accelerated materials discovery: a community survey and practical insights33Surface Segregation Studies in Ternary Noble Metal Alloys: Comparing DFT and Machine Learning with Experimental Data6Atoms as words: A novel approach to deciphering material properties using NLP-inspired machine learning on crystallographic information files (CIFs)4Physics-Informed Design of Hybrid Pulse Power Characterization Tests for Rechargeable Batteries28Size-Resolved Shape Evolution in Inorganic Nanocrystals Captured via High-Throughput Deep Learning-Driven Statistical Characterization12Epitaxy of Emerging Materials and Advanced Heterostructures for Microelectronics and Quantum Sciences12Computation and machine learning for materials: Past, present, and future perspectives9Machine learning and its impact on advanced membrane materials0Mapping connections and pathways0Node transfer for multi-fidelity and multimodal machine learning for predicting experimental bandgaps0Data-Driven Inverse Design of Magnetoelectric Composites Using Hybrid Machine Learning and Optimization0

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  1. Physics-Informed Design of Hybrid Pulse Power Characterization (HPPC) Tests for Rechargeable Batteries

    ChemRxiv · 2023-11-20

    Debbie Zhuang, Michael L. Li, Vivek Lam, Richard D. Braatz, William C. Chueh, Martin Z. Bazant

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  2. Calibration in machine learning uncertainty quantification: Beyond consistency to target adaptivity

    APL Machine Learning · 2023-12-01

    Pascal Pernot

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  3. Autonomous laboratories for accelerated materials discovery: a community survey and practical insights

    Digital Discovery · 2024-01-01

    Linda Hung, Joyce A. Yager, Danielle R. Monteverde, Dave Baiocchi, Ha-Kyung Kwon, Shijing Sun, Santosh K. Suram

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  4. Surface Segregation Studies in Ternary Noble Metal Alloys: Comparing DFT and Machine Learning with Experimental Data

    ChemPhysChem · 2024-03-22

    Kirby Broderick, Robert A. Burnley, Andrew J. Gellman, John R. Kitchin

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  5. Atoms as words: A novel approach to deciphering material properties using NLP-inspired machine learning on crystallographic information files (CIFs)

    AIP Advances · 2024-04-01

    Lalit Yadav

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  6. Physics-Informed Design of Hybrid Pulse Power Characterization Tests for Rechargeable Batteries

    Journal of The Electrochemical Society · 2024-04-25

    Debbie Zhuang, Michael L. Li, Vivek Lam, Richard D. Braatz, William C. Chueh, Martin Z. Bazant

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  7. Size-Resolved Shape Evolution in Inorganic Nanocrystals Captured via High-Throughput Deep Learning-Driven Statistical Characterization

    ACS Nano · 2024-10-19

    Min Gee Cho, Katherine Sytwu, Luis Rangel DaCosta, Catherine Groschner, Myoung Hwan Oh, Mary Cooper Scott

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  8. Epitaxy of Emerging Materials and Advanced Heterostructures for Microelectronics and Quantum Sciences

    Small Methods · 2025-01-07

    Yeonjoo Lee, Soo Ho Choi, Hyunseok Kim, Jinkyoung Yoo

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  9. Computation and machine learning for materials: Past, present, and future perspectives

    MRS Bulletin · 2025-09-09

    Sobin Alosious, Meng Jiang, Tengfei Luo

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  10. Machine learning and its impact on advanced membrane materials

    Elsevier eBooks · 2025-09-27

    Kiran Mustafa, Mashallah Rezakazemi, Rao Muhammad Mahtab Mahboob

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  11. Mapping connections and pathways

    Elsevier eBooks · 2026-01-01

    Krishna Rajan

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  12. Node transfer for multi-fidelity and multimodal machine learning for predicting experimental bandgaps

    The Journal of Chemical Physics · 2026-04-08

    Shuai Li, Wen-Cheng Yao, Bin-Bin Xie, Lin Fang Shen, Ling Chen, Wei‐Hai Fang

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  13. Data-Driven Inverse Design of Magnetoelectric Composites Using Hybrid Machine Learning and Optimization

    International Conference on Emerging Techniques in Computational Intelligence (ICETCI) · 2026-08-01

    S. Sai Harsha, Sai Naveen Jonnala, Kondaiah P.

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