BetaCitation Atlas

RESEARCH PAPER · Science Advances · 2022

Rapid discovery of stable materials by coordinate-free coarse graining

Rhys E. A. Goodall, Abhijith S. Parackal, Felix A. Faber, Rickard Armiento, Alpha A. Lee

Read original paper ↗

See where this research leads.

61 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

Rapid discovery of stable materials by coordinate-free coarse grainingOriginalPrediction without Transferability: Domain Shift in Cross-Material AI Inference0The Problem of Scientific Regret in AI-Driven Materials Selection0Heterogeneous Catalysis in Grammar School8Recent advances and applications of deep learning methods in materials science1161Ab initio machine learning of phase space averages18Data-augmentation for graph neural network learning of the relaxed energies of unrelaxed structures45Exploiting Machine Learning in Multiscale Modelling of Materials12Direction-Based Graph Representation to Accelerate Stable Catalyst Discovery8A chemically inspired convolutional neural network using electronic structure representation4A Theory of Justifiable Abstraction in Multi-Scale Materials AI0WyCryst: Wyckoff Inorganic Crystal Generator Framework4Machine‐Learning‐Assisted Determination of the Global Zero‐Temperature Phase Diagram of Materials109On the combinatorics of crystal structures. II. Number of Wyckoff sequences of a given subdivision complexity3Symmetry-based computational search for novel binary and ternary 2D materials33Accelerating the Search for New Solid Electrolytes: Exploring Vast Chemical Space with Machine Learning-Enabled Computational Calculations21Accelerating the prediction of stable materials with machine learning104Atomic Scale Design of MXenes and Their Parent Materials─From Theoretical and Experimental Perspectives184Generative adversarial networks and diffusion models in material discovery88AI-driven inorganic materials by design0Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange52Fast and accurate characterization of magnetorheological elastomers based on machine learning1Pretraining Strategies for Structure Agnostic Material Property Prediction17Coarse-Grained Crystal Graph Neural Networks for Reticular Materials Design8Multimodal learning of heat capacity based on transformers and crystallography pretraining9WyCryst: Wyckoff inorganic crystal generator framework42Inorganic Metal Thiocyanates24Optical materials discovery and design with federated databases and machine learning9Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange18High-Throughput Screening of Li Solid-State Electrolytes with Bond Valence Methods and Machine Learning32Kitaev physics in the two-dimensional magnet NiPSe 32Multi-scale computational study of high-temperature corrosion and the design of corrosion-resistant alloys33Neural network ensembles for band gap prediction10Discovery of high-performance dielectric materials with machine-learning-guided search9Identifying crystal structures beyond known prototypes from x-ray powder diffraction spectra7Prediction methods for phonon transport properties of inorganic crystals: from traditional approaches to artificial intelligence4Machine Learning Enabled High‐Throughput Screening of 2D Ultrawide Bandgap Semiconductors for Flexible Resistive Materials2ASUGNN: an asymmetric-unit-based graph neural network for crystal property prediction1Application of Li3InCl6-PEO composite electrolyte in all-solid-state battery0Probing out-of-distribution generalization in machine learning for materials81Machine learning for discrimination of phase‐change chalcogenide glasses25Symmetry-oriented enumeration method for molecular crystal structure prediction and its application0Benchmarking machine learning models for predicting lithium ion migration27Computational Material Science Has a Data Problem4A framework to evaluate machine learning crystal stability predictions154Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys17Artificial intelligence for science in quantum, atomistic, and continuum systems71Exploring lightweight language models for materials informatics with AlchemBERT4Prediction and characterization of chemically complex σ − phase intermetallics with graph neural network3Space group informed transformer for crystalline materials generation28Informatics for thermodynamics: Stability to synthesizability0The Problem of Scientific Path Abandonment in AI-Guided Materials Research0Bridging theory and experiment in materials discovery: Machine-learning-assisted prediction of synthesizable structures3Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review3CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning1Valence equivalence guided high-throughput search for stable monolayer MA2Z4 and M2A2Z40Design Principles and Mechanistic Understanding of Cobalt‐Oxide‐Based Electrocatalysts for Nitrate Reduction to Ammonia0The Open Materials 2024 (OMat24) inorganic materials dataset and models20Score-based diffusion models for accurate crystal-structure inpainting and reconstruction of hydrogen positions1SCOPE+: Physically enriched crystal representations for the CLOUD model0Machine learning-accelerated inverse design of energy materials: A critical review of graph neural networks, physics-informed models, and generative AI for batteries, perovskite solar cells, and electrocatalysts0The AFLOW library of crystallographic prototypes: Part 50

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

61 direct citing papers saved. Showing the first 50 here; use Browse Matching Papers in the map for all loaded papers.

  1. Prediction without Transferability: Domain Shift in Cross-Material AI Inference

    Journal of Computational and Data-Driven Materials Engineering · 2022-01-01

    Maria Gonzalez, Javier Ruiz, Lucia Torres

    Read original paper ↗ ·

  2. The Problem of Scientific Regret in AI-Driven Materials Selection

    Journal of Artificial Intelligence for Materials Science · 2022-01-01

    Hiroshi Tanaka, Yuki Sato, Kenji Mori, Rina Okabe, Takashi Ito

    Read original paper ↗ ·

  3. Heterogeneous Catalysis in Grammar School

    The Journal of Physical Chemistry C · 2022-02-03

    Johannes T. Margraf, Zachary W. Ulissi, Yousung Jung, Karsten Reuter

    Read original paper ↗ ·

  4. Recent advances and applications of deep learning methods in materials science

    npj Computational Materials · 2022-04-05

    Kamal Kumar Choudhary, Brian DeCost, Chi Chen, Anubhav Jain, Francesca Tavazza, Ryan Cohn, Cheol Woo Park, Alok Choudhary, Ankit Agrawal, Simon J. L. Billinge, Elizabeth A. Holm, Shyue Ping Ong, Chris M. Wolverton

    Read original paper ↗ ·

  5. Ab initio machine learning of phase space averages

    The Journal of Chemical Physics · 2022-07-13

    Jan Weinreich, Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld

    Read original paper ↗ ·

  6. Data-augmentation for graph neural network learning of the relaxed energies of unrelaxed structures

    npj Computational Materials · 2022-09-30

    Jason Gibson, Ajinkya C. Hire, Richard G. Hennig

    Read original paper ↗ ·

  7. Exploiting Machine Learning in Multiscale Modelling of Materials

    Journal of The Institution of Engineers (India) Series D · 2022-11-28

    G. Anand, Swarnava Ghosh, Liwei Zhang, Angesh Anupam, Colin L. Freeman, Christoph Ortner, Markus Eisenbach, James R. Kermode

    Read original paper ↗ ·

  8. Direction-Based Graph Representation to Accelerate Stable Catalyst Discovery

    Chemistry of Materials · 2022-12-27

    Dong Hyeon Mok, Jong Seung Kim, Seoin Back

    Read original paper ↗ ·

  9. A chemically inspired convolutional neural network using electronic structure representation

    Journal of Materials Chemistry A · 2023-01-01

    Dong Hyeon Mok, Daeun Shin, Jonggeol Na, Seoin Back

    Read original paper ↗ ·

  10. A Theory of Justifiable Abstraction in Multi-Scale Materials AI

    Journal of Artificial Intelligence for Materials Science · 2023-01-01

    Oliver Grant, David Clark, Sophia Nguyen

    Read original paper ↗ ·

  11. WyCryst: Wyckoff Inorganic Crystal Generator Framework

    SSRN Electronic Journal · 2023-01-01

    Ruiming Zhu, Wei Nong, Shuya Yamazaki, Kedar Hippalgaonkar

    Read original paper ↗ ·

  12. Machine‐Learning‐Assisted Determination of the Global Zero‐Temperature Phase Diagram of Materials

    Advanced Materials · 2023-03-22

    Jonathan Schmidt, Noah Hoffmann, Hai‐Chen Wang, Pedro Borlido, Pedro J. M. A. Carriço, Tiago F. T. Cerqueira, Silvana Botti, Miguel A. L. Marques

    Read original paper ↗ ·

  13. On the combinatorics of crystal structures. II. Number of Wyckoff sequences of a given subdivision complexity

    Acta Crystallographica Section A Foundations and Advances · 2023-03-24

    Wolfgang Hornfeck, Kamil Červený

    Read original paper ↗ ·

  14. Symmetry-based computational search for novel binary and ternary 2D materials

    2D Materials · 2023-04-12

    Hai‐Chen Wang, Jonathan Schmidt, Miguel A. L. Marques, Ludger Wirtz, Aldo Humberto Romero

    Read original paper ↗ ·

  15. Accelerating the Search for New Solid Electrolytes: Exploring Vast Chemical Space with Machine Learning-Enabled Computational Calculations

    ACS Applied Materials & Interfaces · 2023-11-04

    Jong Seung Kim, Dong Hyeon Mok, Heejin Kim, Seoin Back

    Read original paper ↗ ·

  16. Accelerating the prediction of stable materials with machine learning

    Nature Computational Science · 2023-11-09

    Sean D. Griesemer, Yi Xia, Chris M. Wolverton

    Read original paper ↗ ·

  17. Atomic Scale Design of MXenes and Their Parent Materials─From Theoretical and Experimental Perspectives

    Chemical Reviews · 2023-11-17

    Jie Zhou, Martin Dahlqvist, Jonas Björk, Johanna Rosén

    Read original paper ↗ ·

  18. Generative adversarial networks and diffusion models in material discovery

    Digital Discovery · 2023-12-06

    Michael Alverson, Sterling G. Baird, Ryan Murdock, Sin-Hang Enoch Ho, Jeremy A. Johnson, Taylor D. Sparks

    Read original paper ↗ ·

  19. AI-driven inorganic materials by design

    Unknown journal · 2024-01-01

    Ruiming Zhu

    Read original paper ↗ ·

  20. Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

    Digital Discovery · 2024-01-01

    Matthew L. Evans, J. Bergsma, Andrius Merkys, Casper Welzel Andersen, Oskar B. Andersson, Daniel Beltrán Mora, Evgeny Blokhin, Tara M. Boland, Rubén Castañeda Balderas, Kamal Kumar Choudhary, Alberto Díaz Díaz, R. García, Hagen Eckert, Kristjan Eimre, María E. Fuentes, Adam M. Krajewski, Jens Jørgen Mortensen, José Manuel Nápoles Duarte, Jacob Pietryga, Ji Qi, Felipe de Jesús Trejo Carrillo, Antanas Vaitkus, Ju‐Song Yu, Adam C. Zettel, Pedro Baptista de Castro, Johan Martin Carlsson, Tiago F. T. Cerqueira, Simon Divilov, Hamidreza Hajiyani, Felix Hanke, Kevin Jose, Corey Oses, Janosh Riebesell, Jonathan Schmidt, Donny Winston, Christen Xie, Xiaoyu Yang, Sara Bonella, Silvana Botti, Stefano Curtarolo A, Claudia Draxl, L. Fuentes, Adam Hospital, Zi‐Kui Liu, Miguel A. L. Marques, Nicola Marzari, Andrew J. Morris, Shyue Ping Ong, Modesto Orozco, Kristin Aslaug Persson, Kristian Sommer Thygesen, Chris M. Wolverton, Markus Scheidgen, Cormac Toher, G. J. Conduit, Giovanni Pizzi, S. Gražulis, Gian‐Marco Rignanese, Rickard Armiento

    Read original paper ↗ ·

  21. Fast and accurate characterization of magnetorheological elastomers based on machine learning

    Acta Physica Sinica · 2024-01-01

    Hang Ren, Dan Zhao, Liqiang Dong, Shaogang Liu, Jin‐Shui Yang

    Read original paper ↗ ·

  22. Pretraining Strategies for Structure Agnostic Material Property Prediction

    Journal of Chemical Information and Modeling · 2024-02-01

    Hongshuo Huang, Rishikesh Magar, Amir Barati Farimani

    Read original paper ↗ ·

  23. Coarse-Grained Crystal Graph Neural Networks for Reticular Materials Design

    Journal of Chemical Information and Modeling · 2024-03-08

    Vadim Korolev, Artem A. Mitrofanov

    Read original paper ↗ ·

  24. Multimodal learning of heat capacity based on transformers and crystallography pretraining

    Journal of Applied Physics · 2024-04-24

    Hongshuo Huang, Amir Barati Farimani

    Read original paper ↗ ·

  25. WyCryst: Wyckoff inorganic crystal generator framework

    Matter · 2024-06-25

    Ruiming Zhu, Wei Nong, Shuya Yamazaki, Kedar Hippalgaonkar

    Read original paper ↗ ·

  26. Inorganic Metal Thiocyanates

    Inorganic Chemistry · 2024-07-09

    Matthew J. Cliffe

    Read original paper ↗ ·

  27. Optical materials discovery and design with federated databases and machine learning

    Faraday Discussions · 2024-07-10

    Victor Trinquet, Matthew L. Evans, Cameron J. Hargreaves, Pierre-Paul De Breuck, Gian‐Marco Rignanese

    Read original paper ↗ ·

  28. Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

    Repository for Publications and Research Data (ETH Zurich) · 2024-08-01

    Matthew L. Evans, J. Bergsma, Andrius Merkys, Casper Welzel Andersen, Oskar B. Andersson, Daniel Beltrán Mora, Evgeny Blokhin, Tara M. Boland, Rubén Castañeda Balderas, Kamal Kumar Choudhary, Alberto Díaz Díaz, R. García, Hagen Eckert, Kristjan Eimre, María E. Fuentes, Adam M. Krajewski, Jens Jørgen Mortensen, José Manuel Nápoles-Duarte, Jacob Pietryga, Ji Qi, Jonathan Schmidt, Antanas Vaitkus

    Read original paper ↗ ·

  29. High-Throughput Screening of Li Solid-State Electrolytes with Bond Valence Methods and Machine Learning

    Chemistry of Materials · 2024-08-05

    Stephen Xie, Shreyas J. Honrao, John W. Lawson

    Read original paper ↗ ·

  30. Kitaev physics in the two-dimensional magnet NiPSe 3

    Physical Review Research · 2024-08-22

    Cheng Peng, Sougata Mardanya, Alexander N. Petsch, Vineet Kumar Sharma, Shuyi Li, Chunjing Jia, Arun Bansil, Sugata Chowdhury, Joshua J. Turner

    Read original paper ↗ ·

  31. Multi-scale computational study of high-temperature corrosion and the design of corrosion-resistant alloys

    Progress in Materials Science · 2024-08-30

    Terrence Wenga, Digby D. Macdonald, Wenchao Ma

    Read original paper ↗ ·

  32. Neural network ensembles for band gap prediction

    Computational Materials Science · 2024-09-09

    Taichi Masuda, Katsuaki Tanabe

    Read original paper ↗ ·

  33. Discovery of high-performance dielectric materials with machine-learning-guided search

    Cell Reports Physical Science · 2024-10-01

    Janosh Riebesell, Todd Wesley Surta, Rhys E. A. Goodall, Michael W. Gaultois, Alpha A. Lee

    Read original paper ↗ ·

  34. Identifying crystal structures beyond known prototypes from x-ray powder diffraction spectra

    Physical Review Materials · 2024-10-02

    Abhijith S. Parackal, Rhys E. A. Goodall, Felix A. Faber, Rickard Armiento

    Read original paper ↗ ·

  35. Prediction methods for phonon transport properties of inorganic crystals: from traditional approaches to artificial intelligence

    Nanoscale Horizons · 2024-10-29

    Yi Wei, Zhixiang Liu, Guangzhao Qin

    Read original paper ↗ ·

  36. Machine Learning Enabled High‐Throughput Screening of 2D Ultrawide Bandgap Semiconductors for Flexible Resistive Materials

    Advanced Electronic Materials · 2024-11-04

    Chi Chen, Hao Wang, Houzhao Wan, Dan Sun

    Read original paper ↗ ·

  37. ASUGNN: an asymmetric-unit-based graph neural network for crystal property prediction

    Journal of Applied Crystallography · 2024-12-05

    Bin Cao, Daniel Anderson, Luke Davis

    Read original paper ↗ ·

  38. Application of Li3InCl6-PEO composite electrolyte in all-solid-state battery

    SSRN Electronic Journal · 2025-01-01

    Paolo Piccardo, Roberto Spotorno, Han-xin Mei

    Read original paper ↗ ·

  39. Probing out-of-distribution generalization in machine learning for materials

    Communications Materials · 2025-01-11

    Kangming Li, Andre Niyongabo Rubungo, Xiangyun Lei, Daniel Persaud, Kamal Kumar Choudhary, Brian DeCost, Adji Bousso Dieng, Jason R. Hattrick-Simpers

    Read original paper ↗ ·

  40. Machine learning for discrimination of phase‐change chalcogenide glasses

    InfoMat · 2025-02-24

    Qundao Xu, Meng Kai Xu, Meng Kai Xu, Siqi Tang, Shaojie Yuan, Ming Xu, Ming Xu, Wei Zhang, Xianbin Li, Zhongrui Wang, Xiangshui Miao, Chengliang Wang, Matthias Wuttig

    Read original paper ↗ ·

  41. Symmetry-oriented enumeration method for molecular crystal structure prediction and its application

    Physical review. B./Physical review. B · 2025-04-23

    Xin Yu, Zhuohang Xie, Yun-Ting Chen, Pengyue Gao, Hong Jian Zhao, Jian Lv, Yanchao Wang, Yanming Ma

    Read original paper ↗ ·

  42. Benchmarking machine learning models for predicting lithium ion migration

    npj Computational Materials · 2025-05-13

    Artem D. Dembitskiy, Innokentiy S. Humonen, Roman A. Eremin, Dmitry A. Aksyonov, Stanislav S. Fedotov, Semen Budennyy

    Read original paper ↗ ·

  43. Computational Material Science Has a Data Problem

    Journal of Chemical Information and Modeling · 2025-06-04

    Sherif Abdulkader Tawfik

    Read original paper ↗ ·

  44. A framework to evaluate machine learning crystal stability predictions

    Nature Machine Intelligence · 2025-06-23

    Janosh Riebesell, Rhys E. A. Goodall, Philipp Benner, Yuan Chiang, Bowen Deng, Gerbrand Ceder, Mark Asta, Alpha A. Lee, Anubhav Jain, Kristin Aslaug Persson

    Read original paper ↗ ·

  45. Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys

    Machine Learning Science and Technology · 2025-06-30

    Fei Shuang, Zixiong Wei, Kai Liu, Wei Gao, Poulumi Dey

    Read original paper ↗ ·

  46. Artificial intelligence for science in quantum, atomistic, and continuum systems

    Foundations and Trends® in Machine Learning · 2025-07-21

    Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Xu Zhao, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, YuQing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, E. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru‐Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Žitnik, Animashree Anandkumar, Stefano Ermon, Píetro Lió, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, Shuiwang Ji

    Read original paper ↗ ·

  47. Exploring lightweight language models for materials informatics with AlchemBERT

    Cell Reports Physical Science · 2025-07-23

    Yuhang Wang, Xiaotong Liu, Xiaotong Liu, Haotian Chen, Tao Yang, Xingchen Liu, Xingchen Liu, Xiaodong Wen

    Read original paper ↗ ·

  48. Prediction and characterization of chemically complex σ − phase intermetallics with graph neural network

    Acta Materialia · 2025-08-26

    Wenhao Zhang, Mariano Forti, Runan Xie, Céline Barreteau, Taichi Abe, Jean‐Marc Joubert, Thomas Hammerschmidt, Jean‐Claude Crivello

    Read original paper ↗ ·

  49. Space group informed transformer for crystalline materials generation

    中国科学通报：英文版 · 2025-09-25

    Zhendong Cao, Xiaoshan Luo, Jian Lv, Lei Wang

    Read original paper ↗ ·

  50. Informatics for thermodynamics: Stability to synthesizability

    Elsevier eBooks · 2026-01-01

    Krishna Rajan

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