BetaCitation Atlas

RESEARCH PAPER · Annual Review of Chemical and Biomolecular Engineering · 2022

Machine Learning for the Discovery, Design, and Engineering of Materials

Chenru Duan, Aditya Nandy, Heather J. Kulik

Read original paper ↗

See where this research leads.

66 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

Machine Learning for the Discovery, Design, and Engineering of MaterialsOriginalActive Learning Exploration of Transition-Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores37Reaching the Full Potential of Machine Learning in Mitigating Environmental Impacts of Functional Materials6Generative organic electronic molecular design informed by quantum chemistry21Learning Conductance: Gaussian Process Regression for Molecular Electronics14Post-Activation Function for Managing the Behavior of a Neural Network Potential with a Low-Dimensional Potential1AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS)122Parametrically Managed Activation Function for Fitting a Neural Network Potential with Physical Behavior Enforced by a Low-Dimensional Potential18Generative Organic Electronic Molecular Design via Reinforcement Learning Integration with Quantum Chemistry: Tuning Singlet and Triplet Energy Energy Levels0Permafrost viremia and immune tweening3Generative Organic Electronic Molecular Design via Reinforcement Learning Integration with Quantum Chemistry: Tuning Singlet and Triplet Energy Levels1Machine learning guided hydrothermal synthesis of thermochromic VO2 nanoparticles39Advances in data‐assisted high‐throughput computations for material design112Deep machine learning, molecular dynamics and experimental studies of liquid Al-Cu-Co alloys13Machine learning for analyzing atomic force microscopy (AFM) images generated from polymer blends24OM-Diff: inverse-design of organometallic catalysts with guided equivariant denoising diffusion19Prediction, interpretation and extrapolation for shear modulus and bulk modulus of solid-state electrolytes based on machine learning12A mini review on the applications of artificial intelligence (AI) in surface chemistry and catalysis27Partnerships and collaboration drive innovative graduate training in materials informatics3Machine learning for analyses and automation of structural characterization of polymer materials43Efficient Removal of Greenhouse Gases: Machine Learning-Assisted Exploration of Metal–Organic Framework Space32Porous materials0The future of bone regeneration: Artificial intelligence in biomaterials discovery24A semi-automated quantum-mechanical workflow for the generation of molecular monolayers and aggregates4Virtual Ligand-Assisted Optimization: A Rational Strategy for Ligand Engineering12Machine Learnable Language for the Chemical Space of Nanopores Enables Structure–Property Relationships in Nanoporous 2D Materials16Intelligent Generic High‐Throughput Oscillatory Shear Technology Fabricates Programmable Microrobots for Real‐Time Visual Guidance During Embolization8Inverse design of microstructures using conditional continuous normalizing flows20Prediction of the sound absorption performance for micro-perforated panel based on machine learning2Dual-Level Parametrically Managed Neural Network Method for Learning a Potential Energy Surface for Efficient Dynamics1Highly Efficient Screening of Halide Double Perovskite Optoelectronic Materials Based on Machine learning16Advances in the Design and Discovery of Organic Semiconductors Aided by Machine Learning18Accelerated discovery of near-zero ablation ultra-high temperature ceramics via GAN-enhanced directionally constrained active learning9Revolutionizing Bone Repair and Regeneration: The Role of Machine Learning in Designing Advanced Nanocomposite Hydrogels12Discovery of Spin-Crossover Materials with Equivariant Graph Neural Networks and Relevance-Based Classification1Deep learning enhanced prediction of microwave dielectric constant of spinel ceramics eliminating manual feature engineering4Screening of Biomaterials for Stem Cell Culture Applications0New Methods of Preparing Calcium Nanomaterials as a Keystone in Biotechnology4Theoretical High-Throughput Screening of Single-Atom CO2 Electroreduction Catalysts to Methanol Using Active Learning18Machine Learning Tackles the Challenge of Powder X-ray Diffraction Indexing for All Crystal Systems3Untangling linker dynamics in a metal–organic framework using ab initio molecular dynamics and physics-informed machine learning2Machine learning prediction and efficient screening method for thermally induced fluorescence enhancement of Er 3+ doped materials6Machine Learning‐Accelerated Specific Surface Prediction Strategy in Janus‐Based Z‐Scheme Heterostructures for Efficient Photocatalytic Water Splitting30Tailor-made adsorbent materials on machine learning instructions for efficient purification of heavy metal contaminants in wastewater1Computacional modeling of chirality in porous frameworks: Advanced methods and applications in enantioselective catalysis and separation4AI for Transmission Electron Microscopy4Artificial Intelligence, Machine Learning, and High-Throughput Material Discovery Tools0Decoding physical mechanisms governing elastic moduli in inorganic materials through interpretable machine learning1Large language models for porous materials: from text mining to autonomous laboratory6Machine Learning (ML) and Artificial Intelligence (AI) in Textile Surface Modification1Machine Learning-Enhanced Molecular Dynamics: Current State, Challenges and Perspectives5Recent advances in HER electrocatalysis derived from Fe, Co, Ni, and Mo-based phosphides24Towards a sustainable high-quality materials data ecosystem: frameworks and strategies6Physics-constrained machine learning for constitutive modelling of high-strength concrete across strain rates5Machine learning-driven composition optimization for high strength and ductility in Al-Mg-Si-Zr-Er alloys4GLOBE: Global Topological Exploration for Large-Displacement Compliant Constant-Force Mechanism Synthesis0Recent progress in density functional theory and machine learning for predicting MXene properties2AI-Driven Acceleration of Nanomaterials Development: Advanced Computational Tools and Techniques0Machine learning-driven acceleration of Mg-MOF-74 synthesis optimization for enhanced CO₂ adsorption16Interpretable machine learning for predicting the fluorescence properties of carbazole derivatives for bioimaging1Δ‐Machine Learning for the Prediction of Metal Complex Properties0Progress on Halide Solid State Electrolytes: Structural Regulation, Interfacial Engineering, and Machine Learning Driven Paradigms2Retardation of Cr diffusion by Re in FCC Ni–Re–Cr alloys: High-throughput experiments and CALPHAD-based mobility assessment0Active Learning for Optimizing Adsorption Energy Predictions in Large Chemical Spaces0Machine Learning–Assisted Exploration of the Structural, Dielectric, and Ferroelectric Properties of CaTiO3 Nanoceramics0Physics-informed hybrid learning for dynamic constitutive and equation-of-state parameter identification with case-level ballistic assessment of titanium alloys0AI-assisted molecular and materials discovery in chemistry and chemical engineering: A methodological and bibliometric review0

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

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

  1. Active Learning Exploration of Transition-Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores

    JACS Au · 2022-12-01

    Chenru Duan, Aditya Nandy, Gianmarco Terrones, David W. Kastner, Heather J. Kulik

    Read original paper ↗ ·

  2. Reaching the Full Potential of Machine Learning in Mitigating Environmental Impacts of Functional Materials

    Reviews of Environmental Contamination and Toxicology · 2022-12-01

    Ying He, Guohong Liu, Chengjun Li, Xiliang Yan

    Read original paper ↗ ·

  3. Generative organic electronic molecular design informed by quantum chemistry

    Chemical Science · 2023-01-01

    Cheng-Han Li, Daniel P. Tabor

    Read original paper ↗ ·

  4. Learning Conductance: Gaussian Process Regression for Molecular Electronics

    Journal of Chemical Theory and Computation · 2023-01-24

    Michael Deffner, Marc Philipp Weise, Haitao Zhang, Maike Mücke, Jonny Proppe, Ignacio Franco, Carmen Herrmann

    Read original paper ↗ ·

  5. Post-Activation Function for Managing the Behavior of a Neural Network Potential with a Low-Dimensional Potential

    ChemRxiv · 2023-04-21

    Farideh Badichi Akher, Yinan Shu, Zoltan Varga, Suman Bhaumik, Donald G. Truhlar

    Read original paper ↗ ·

  6. AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS)

    ACS Nano · 2023-06-02

    Honghao Chen, Yingzhe Zheng, Jiali Li, Lanyu Li, Xiaonan Wang

    Read original paper ↗ ·

  7. Parametrically Managed Activation Function for Fitting a Neural Network Potential with Physical Behavior Enforced by a Low-Dimensional Potential

    The Journal of Physical Chemistry A · 2023-06-12

    Farideh Badichi Akher, Yinan Shu, Zoltán Varga, Suman Bhaumik, Donald G. Truhlar

    Read original paper ↗ ·

  8. Generative Organic Electronic Molecular Design via Reinforcement Learning Integration with Quantum Chemistry: Tuning Singlet and Triplet Energy Energy Levels

    ChemRxiv · 2023-06-30

    Cheng-Han Li, Daniel P. Tabor

    Read original paper ↗ ·

  9. Permafrost viremia and immune tweening

    Bioinformation · 2023-06-30

    Francesco Chiappelli

    Read original paper ↗ ·

  10. Generative Organic Electronic Molecular Design via Reinforcement Learning Integration with Quantum Chemistry: Tuning Singlet and Triplet Energy Levels

    ChemRxiv · 2023-07-02

    Cheng-Han Li, Daniel P. Tabor

    Read original paper ↗ ·

  11. Machine learning guided hydrothermal synthesis of thermochromic VO2 nanoparticles

    Ceramics International · 2023-07-06

    Yongxing Chen, Haining Ji, Mingying Lu, Bin Liu, Yong Zhao, Yangyong Ou, Yi Wang, Jundong Tao, Ting Zou, Yan Hua Huang, Junlong Wang

    Read original paper ↗ ·

  12. Advances in data‐assisted high‐throughput computations for material design

    Materials Genome Engineering Advances · 2023-09-01

    Dingguo Xu, Qiao Zhang, Xiangyu Huo, Yitong Wang, Mingli Yang

    Read original paper ↗ ·

  13. Deep machine learning, molecular dynamics and experimental studies of liquid Al-Cu-Co alloys

    Journal of Molecular Liquids · 2023-11-24

    Larisa V. Kamaeva, Elena Nikolaevna Tsiok, N. M. Chtchelkatchev

    Read original paper ↗ ·

  14. Machine learning for analyzing atomic force microscopy (AFM) images generated from polymer blends

    Digital Discovery · 2024-01-01

    Aanish Paruchuri, Yunfei Wang, Xiaodan Gu, Arthi Jayaraman

    Read original paper ↗ ·

  15. OM-Diff: inverse-design of organometallic catalysts with guided equivariant denoising diffusion

    Digital Discovery · 2024-01-01

    François Cornet, Bardi Benediktsson, Bjarke Hastrup, Mikkel Nørgaard Schmidt, Arghya Bhowmik

    Read original paper ↗ ·

  16. Prediction, interpretation and extrapolation for shear modulus and bulk modulus of solid-state electrolytes based on machine learning

    Materials Today Communications · 2024-02-03

    Yinghe Wang, Shu Li, Shuai Li, Minghua Chen

    Read original paper ↗ ·

  17. A mini review on the applications of artificial intelligence (AI) in surface chemistry and catalysis

    Tenside Surfactants Detergents · 2024-04-29

    Faisal Al‐Akayleh, Ahmed S.A. Ali Agha, Rami A. Abdel‐Rahem, Mayyas M. Al-Remawi

    Read original paper ↗ ·

  18. Partnerships and collaboration drive innovative graduate training in materials informatics

    Science Advances · 2024-05-01

    Angela M. Slates, Shana L. McAlexander, Jennifer Nolan, Juan Pablo, Junhong Chen, Harley T. Johnson, L. Catherine Brinson

    Read original paper ↗ ·

  19. Machine learning for analyses and automation of structural characterization of polymer materials

    Progress in Polymer Science · 2024-05-03

    Shizhao Lu, Arthi Jayaraman

    Read original paper ↗ ·

  20. Efficient Removal of Greenhouse Gases: Machine Learning-Assisted Exploration of Metal–Organic Framework Space

    ACS Nano · 2024-07-01

    Ruiqi Xin, Chaohai Wang, Yingchao Zhang, Rongfu Peng, Rui Li, Junning Wang, Yanli Mao, Xinfeng Zhu, Wenkai Zhu, Minjun Kim, Ho Ngoc Nam, Yusuke Yamauchi

    Read original paper ↗ ·

  21. Porous materials

    Elsevier eBooks · 2024-07-16

    İlknur Eruçar, Seda Keskın

    Read original paper ↗ ·

  22. The future of bone regeneration: Artificial intelligence in biomaterials discovery

    Materials Today Communications · 2024-07-28

    Jinfei Fan, Jiazhen Xu, Xiaobo Wen, Li Guo Sun, Yutao Xiu, Zongying Zhang, Ting Liu, Daijun Zhang, Pan Wang, Dongming Xing

    Read original paper ↗ ·

  23. A semi-automated quantum-mechanical workflow for the generation of molecular monolayers and aggregates

    The Journal of Chemical Physics · 2024-09-25

    Julia T. Kohn, Stefan Grimme, Andreas Hansen

    Read original paper ↗ ·

  24. Virtual Ligand-Assisted Optimization: A Rational Strategy for Ligand Engineering

    ACS Catalysis · 2024-10-21

    Wataru Matsuoka, Taihei Oki, Ren Yamada, Tomohiko Yokoyama, Shinichi Suda, Carla M. Saunders, Bastian Bjerkem Skjelstad, Yu Harabuchi, Natalie Fey, Satoru Iwata, Satoshi Maeda

    Read original paper ↗ ·

  25. Machine Learnable Language for the Chemical Space of Nanopores Enables Structure–Property Relationships in Nanoporous 2D Materials

    Journal of the American Chemical Society · 2024-10-25

    Piyush Sindhu Sharma, Sneha Thomas, Mahika Nair, Ananth Govind Rajan

    Read original paper ↗ ·

  26. Intelligent Generic High‐Throughput Oscillatory Shear Technology Fabricates Programmable Microrobots for Real‐Time Visual Guidance During Embolization

    Small · 2024-12-15

    Xuqi Peng, Haitian Tang, Zhenwen Zhao, Yating Zheng, Xiran Gui, Aijun Jiang, Pan He, Xiaofei Wen, Qian Zhang, Ziyang Mei, Yesi Shi, Chengchao Chu, Yang Zhang, Gang Liu

    Read original paper ↗ ·

  27. Inverse design of microstructures using conditional continuous normalizing flows

    Acta Materialia · 2025-01-01

    Hossein Mirzaee, Serveh Kamrava

    Read original paper ↗ ·

  28. Prediction of the sound absorption performance for micro-perforated panel based on machine learning

    Journal of Engineering and Applied Science · 2025-02-20

    Binxia Yuan, Tianqi You, Huanhuan Jiang, Hong Qian, Lan Cao, Rui Zhu

    Read original paper ↗ ·

  29. Dual-Level Parametrically Managed Neural Network Method for Learning a Potential Energy Surface for Efficient Dynamics

    Journal of Chemical Theory and Computation · 2025-02-27

    Suman Bhaumik, Dayou Zhang, Yinan Shu, Donald G. Truhlar

    Read original paper ↗ ·

  30. Highly Efficient Screening of Halide Double Perovskite Optoelectronic Materials Based on Machine learning

    ACS Applied Materials & Interfaces · 2025-03-15

    Wen Luo, Xinying Xian, Jiang Zhu, Yangyi Shen, Lefei Cao, Feifan Chen, Yayun Pu, Fei Qi, Nan Zhang, Xiaosheng Tang, Qiang Huang

    Read original paper ↗ ·

  31. Advances in the Design and Discovery of Organic Semiconductors Aided by Machine Learning

    Annual Review of Materials Research · 2025-03-26

    Moses Ogbaje, Vinayak Bhat, Chad M. Risko

    Read original paper ↗ ·

  32. Accelerated discovery of near-zero ablation ultra-high temperature ceramics via GAN-enhanced directionally constrained active learning

    Advanced Powder Materials · 2025-03-28

    Wenjian Guo, Fayuan Li, Lingyu Wang, Li’an Zhu, Yicong Ye, Zhen Wang, Bin Yang, Shifeng Zhang, Shuxin Bai

    Read original paper ↗ ·

  33. Revolutionizing Bone Repair and Regeneration: The Role of Machine Learning in Designing Advanced Nanocomposite Hydrogels

    Polymers for Advanced Technologies · 2025-03-28

    Ashkan Farazin, Amirhossein Gheisizadeh

    Read original paper ↗ ·

  34. Discovery of Spin-Crossover Materials with Equivariant Graph Neural Networks and Relevance-Based Classification

    Journal of Chemical Theory and Computation · 2025-04-01

    Angel Albavera-Mata, Pawan Prakash, Jason Gibson, Eric Fonseca, Sijin Ren, Xiaoguang Zhang, Hai‐Ping Cheng, Michael Shatruk, Samuel B. Trickey, Richard G. Hennig

    Read original paper ↗ ·

  35. Deep learning enhanced prediction of microwave dielectric constant of spinel ceramics eliminating manual feature engineering

    Materials Today Physics · 2025-04-08

    Xiaobin Liu, Qiuxia Huang, Chang Su, Ning Shao, Lei Zhang, Yapeng Tian, Huanfu Zhou

    Read original paper ↗ ·

  36. Screening of Biomaterials for Stem Cell Culture Applications

    ACS Biomaterials Science & Engineering · 2025-06-09

    Margot J. Amitrano, Mina Cho, William L. Murphy

    Read original paper ↗ ·

  37. New Methods of Preparing Calcium Nanomaterials as a Keystone in Biotechnology

    Advances in Applied NanoBio-Technologies · 2025-06-30

    Alireza Asadi, Ehsan Khaksar, Setareh Valanik, Yasamin Ghahramani

    Read original paper ↗ ·

  38. Theoretical High-Throughput Screening of Single-Atom CO2 Electroreduction Catalysts to Methanol Using Active Learning

    Engineering · 2025-08-06

    Honghao Chen, Jun Yin, Jiali Li, Xiaonan Wang

    Read original paper ↗ ·

  39. Machine Learning Tackles the Challenge of Powder X-ray Diffraction Indexing for All Crystal Systems

    Journal of Chemical Information and Modeling · 2025-09-22

    Ke Shu, Dong‐Yun Gui, Wei-Xin Yan, Chun‐Hai Wang

    Read original paper ↗ ·

  40. Untangling linker dynamics in a metal–organic framework using ab initio molecular dynamics and physics-informed machine learning

    Computational Materials Science · 2025-10-04

    Deep Choudhuri, Rashedul Alam Chowdhury

    Read original paper ↗ ·

  41. Machine learning prediction and efficient screening method for thermally induced fluorescence enhancement of Er 3+ doped materials

    Optics Express · 2025-10-24

    Qiang Bao, Jianning He, Zhixuan Li, Yanyan Bu, Xiangfu Wang

    Read original paper ↗ ·

  42. Machine Learning‐Accelerated Specific Surface Prediction Strategy in Janus‐Based Z‐Scheme Heterostructures for Efficient Photocatalytic Water Splitting

    Small · 2025-11-26

    Xi Shen, Peng Zhao, Wenxue Zhang, Cheng He

    Read original paper ↗ ·

  43. Tailor-made adsorbent materials on machine learning instructions for efficient purification of heavy metal contaminants in wastewater

    Environmental Functional Materials · 2025-12-09

    Jinwen Zeng, Minjie Qin, Mingzhe Jiang, Shaochi Wang, Xinyue Xie, Lijia Li, Wei Ren, Penghui Shao, Xiao Xiao, Xubiao Luo

    Read original paper ↗ ·

  44. Computacional modeling of chirality in porous frameworks: Advanced methods and applications in enantioselective catalysis and separation

    Coordination Chemistry Reviews · 2025-12-22

    Rodrigo Ramírez‐Tagle

    Read original paper ↗ ·

  45. AI for Transmission Electron Microscopy

    Photon Science · 2025-12-23

    Yangfan Li, Mengshu Ge, Xiaozhi Liu, Dong Su

    Read original paper ↗ ·

  46. Artificial Intelligence, Machine Learning, and High-Throughput Material Discovery Tools

    World sustainability series · 2026-01-01

    Praveen Kumar Verma, Hitesh Vasudev

    Read original paper ↗ ·

  47. Decoding physical mechanisms governing elastic moduli in inorganic materials through interpretable machine learning

    Journal of Materials Chemistry A · 2026-01-01

    Xin Zhang, Hongwei Yang, Wu Li, Juan Du

    Read original paper ↗ ·

  48. Large language models for porous materials: from text mining to autonomous laboratory

    Digital Discovery · 2026-01-01

    Seunghee Han, Taeun Bae, Junho Kim, Youjin Kim, Young-Hun Kim, Jihan Kim, Jihan Kim

    Read original paper ↗ ·

  49. Machine Learning (ML) and Artificial Intelligence (AI) in Textile Surface Modification

    Textile science and clothing technology · 2026-01-01

    Badhon Chandra Mazumder, Nowrin Ahmed Urmi, Md. Himel Mahmud, Md. Shohave Sarkar, Sakil Mahmud, Md. Reazuddin Repon

    Read original paper ↗ ·

  50. Machine Learning-Enhanced Molecular Dynamics: Current State, Challenges and Perspectives

    Archives of Computational Methods in Engineering · 2026-01-24

    Christos Stavrogiannis, Filippos D. Sofos, Theodoros E. Karakasidis

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