Papers citing Machine learning material properties from the periodic table using convolutional neural networks
Deep dive into machine learning density functional theory for materials science and chemistry
Physical Review Materials · 2022-04-05
Lenz Fiedler, Karan Shah, Michael Bußmann, Attila Cangi
Read original paper ↗ ·MaterialsAtlas.org: a materials informatics web app platform for materials discovery and survey of state-of-the-art
npj Computational Materials · 2022-04-11
Jianjun Hu, Stanislav Stefanov, Yuqi Song, Sadman Sadeed Omee, Steph-Yves Louis, Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Lai Wei
Read original paper ↗ ·Data‐Driven Materials Innovation and Applications
Advanced Materials · 2022-04-22
Zhuo Wang, Zhehao Sun, Hang Yin, Xinghui Liu, Jinlan Wang, Haitao Zhao, Cheng Heng Pang, Tao Wu, Shuzhou Li, Zongyou Yin, Xue‐Feng Yu
Read original paper ↗ ·Origins of magnetic memory and strong exchange bias bordering magnetic compensation in mixed-lanthanide systems
Physical Review Materials · 2022-04-28
Tyler J. Del Rose, Yaroslav Mudryk, D. Haskel, Arjun Kumar Pathak, V. K. Pecharsky
Read original paper ↗ ·Enhanced Cellular Materials through Multiscale, Variable-Section Inner Designs: Mechanical Attributes and Neural Network Modeling
Materials · 2022-05-17
Nikolaos Karathanasopoulos, Dimitrios C. Rodopoulos
Read original paper ↗ ·Reflections on one million compounds in the open quantum materials database (OQMD)
Journal of Physics Materials · 2022-06-23
Jiahong Shen, Sean D. Griesemer, Abhijith Gopakumar, Bianca Baldassarri, James E. Saal, Muratahan Aykol, Vinay I. Hegde, Chris M. Wolverton
Read original paper ↗ ·Rapidly predicting Kohn–Sham total energy using data-centric AI
Scientific Reports · 2022-08-24
Hasan Kurban, Mustafa Kurban, Mehmet M Dalkilic
Read original paper ↗ ·Discovering constitutive equations of crystal structures by sparse identification
International Journal of Mechanical Sciences · 2022-09-21
Sun-Young Im, Hyungjun Kim, Wonbae Kim, Hayoung Chung, Maenghyo Cho
Read original paper ↗ ·Neural network potentials for chemistry: concepts, applications and prospects
Digital Discovery · 2022-12-21
Silvan Käser, Luis Itza Vazquez-Salazar, Markus Meuwly, Kai Töpfer
Read original paper ↗ ·Intercalation Hosts for Multivalent‐Ion Batteries
Small Structures · 2022-12-29
Aniruddha S. Lakhnot, Reena A. Panchal, Joy Datta, Varad Mahajani, Kevin Bhimani, Rishabh Jain, Dibakar Datta, Nikhil A. Koratkar
Read original paper ↗ ·A first-principles exploration of the conformational space of sodiated pyranose assisted by neural network potentials
Physical Chemistry Chemical Physics · 2023-01-01
Huu Trong Phan, Pei‐Kang Tsou, Po‐Jen Hsu, Jer‐Lai Kuo
Read original paper ↗ ·Machine Learning Approaches for Predicting Crystal Systems: A Brief Review and a Case Study
Lecture notes in computer science · 2023-01-01
Gaetano Settembre, Nicola Corriero, Nicoletta Del Buono, Flavia Esposito, Rosanna Rizzi
Read original paper ↗ ·What key contextual factors contribute to students’ reading literacy among top-performing countries and economies? Statistical and machine learning analyses
International Journal of Educational Research · 2023-01-01
Yujia Bu, Fu Chen
Read original paper ↗ ·Transfer Learning in Inorganic Compounds’ Crystal Structure Classification
Crystals · 2023-01-02
Hanan A. Hosni Mahmoud
Read original paper ↗ ·Perspectives on development of biomedical polymer materials in artificial intelligence age
Journal of Biomaterials Applications · 2023-01-11
Shijin Xie
Read original paper ↗ ·Exploring a general convolutional neural network-based prediction model for critical casting diameter of metallic glasses
Journal of Alloys and Compounds · 2023-02-28
Jing Hu, Songran Yang, Jun Wei Mao, Chaojie Shi, Guangchuan Wang, Yijing Liu, Xuemei Pu
Read original paper ↗ ·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 ↗ ·Accelerated prediction of perovskite material properties with classical machine learning and graph neural network
Materials Express · 2023-04-01
Zhihao Dong, Youyong Li, Youyong Li
Read original paper ↗ ·Representations of Materials for Machine Learning
Annual Review of Materials Research · 2023-04-18
James R. Jr. Damewood, Jessica Karaguesian, Jaclyn R. Lunger, Aik Rui Tan, Mingrou Xie, Jiayu Peng, Rafael Gómez‐Bombarelli
Read original paper ↗ ·The six stages of the convergence of the periodic system to its final structure
Communications Chemistry · 2023-05-02
Andres M Bran, Peter Florian Stadler, Jürgen Jost, Guillermo Restrepo
Read original paper ↗ ·Geometries and electronic structures of Zr n Cu (n = 2–12) clusters: A joint machine-learning potential density functional theory investigation
Chinese Physics B · 2023-05-16
Yizhi 一志 Wang 王, Xiuhua 秀花 Cui 崔, Jing 静 Liu 刘, Qun Jing, Haiming 海明 Duan 段, Haibin 海宾 Cao 曹
Read original paper ↗ ·Machine learning the spectral function of a hole in a quantum antiferromagnet
Physical review. B./Physical review. B · 2023-05-16
Jackson Lee, Matthew R. Carbone, Wei‐Guo Yin
Read original paper ↗ ·A materials informatics approach for composition and property prediction of polymer-derived silicon oxycarbides
Materials Today Advances · 2023-05-31
Yi Je Cho, Kathy Lu
Read original paper ↗ ·Physically explainable statistical learning of flat bands in stoichiometric materials from the periodic table
Physical Review Materials · 2023-06-22
Xiuying Zhang, Yi-Ming Zhao, Zhigang Song, Lei Shen
Read original paper ↗ ·Accelerating the Search for Stable Full Heusler Compounds through Machine Learning
IEEE International Conference on Information Reuse and Integration for Data Science (IRI) · 2023-08-01
Bhavya Mehta, Vijay Kharche, Sandeep Sambhaji Udmale
Read original paper ↗ ·Hardness prediction of high entropy alloys with periodic table representation of composition, processing, structure and physical parameters
Journal of Alloys and Compounds · 2023-08-14
Shuai Li, Shuai Li, Shu Li, Jia Yang, Mingyu Zhang
Read original paper ↗ ·Machine-learned constitutive relations for mechanoluminescent ZnS:Cu–PDMS composites
Smart Materials and Structures · 2023-08-21
George Hoover, Andy Huang, Donghyeon Ryu
Read original paper ↗ ·Probabilistic physics-guided transfer learning for material property prediction in extrusion deposition additive manufacturing
Computer Methods in Applied Mechanics and Engineering · 2023-11-27
Akshay Jacob Thomas, Mateusz Jaszczuk, Eduardo Barocio, Gourab Ghosh, Ilias Bilionis, R. Byron Pipes
Read original paper ↗ ·On Predefined-time Synchronization of Complex-valued Neural Networks With Inertial Terms
International Conference on Neuromorphic Computing (ICNC) · 2023-12-15
Linchao Dong, Ting Liu, Peng Liu, Hangjun Che, Junwei Sun, Peizhao Yu
Read original paper ↗ ·AI-driven inorganic materials by design
Unknown journal · 2024-01-01
Ruiming Zhu
Read original paper ↗ ·The Framework of Cyber Resilience Engineering Empowered by Endogenous Security and Safety
Springer eBooks · 2024-01-01
Jiangxing Wu
Read original paper ↗ ·Machine learning assisted discovery of high-efficiency self-healing epoxy coating for corrosion protection
npj Materials Degradation · 2024-01-19
Tong Liu, Zhuoyao Chen, Jingzhi Yang, Lingwei Ma, J.M.C. Mol, Dawei Zhang
Read original paper ↗ ·A data-driven method for optimization of classical interatomic potentials
MRS Advances · 2024-03-08
Benjamin A. Jasperson, Harley T. Johnson
Read original paper ↗ ·A comparative study of predicting high entropy alloy phase fractions with traditional machine learning and deep neural networks
npj Computational Materials · 2024-08-09
Shusen Liu, Brandon J. Bocklund, James Diffenderfer, Shreya Chaganti, Bhavya Kailkhura, S. McCall, Brian J. Gallagher, Aurélien P. Perron, Joseph T. McKeown
Read original paper ↗ ·Materials Properties Prediction (MAPP): Empowering the Prediction of Material Properties Solely Based on Chemical Formulas
Materials · 2024-08-23
Si-Da Xue, Qi‐Jun Hong
Read original paper ↗ ·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 ↗ ·Time mesh independent framework for learning materials constitutive relationships
Engineering Applications of Artificial Intelligence · 2024-09-06
Marcello Laurenti, Qing‐Jie Li, Ju Li, Ju Li
Read original paper ↗ ·Exploring uncertainty in glass phase transitions through machine learning
Physica Scripta · 2024-09-13
Rui Qi, Saihua Liu, Chengqiao Yang, Minhua Sun
Read original paper ↗ ·Asparagus: A toolkit for autonomous, user-guided construction of machine-learned potential energy surfaces
Computer Physics Communications · 2024-11-22
Kai Töpfer, Luis Itza Vazquez-Salazar, Markus Meuwly
Read original paper ↗ ·Machine learning prediction of materials properties from chemical composition: Status and prospects
Chemical Physics Reviews · 2024-12-01
Mohammed Alghadeer, Nufida D. Aisyah, Mahmoud Hezam, Saad M. Alqahtani, Ahmer A.B. Baloch, Fahhad H. Alharbi
Read original paper ↗ ·Clustering Cu-S based compounds using periodic table representation and compositional Wasserstein distance
Scientific Reports · 2024-12-30
Shuyan Hao, Ting Xia, Ruizhi Zhang, Meng Chao Guo
Read original paper ↗ ·The Periodic Table: Chemical Properties and Mendeleev Meets Physical Properties and Machine Learning
Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · 2025-01-01
Sarthak Pattnaik, Eugene Pinsky, Kathleen Park
Read original paper ↗ ·On the Sufficiency of a Single Hidden Layer in Feed-Forward Neural Networks Used for Machine Learning of Materials Properties
Physchem · 2025-01-16
Ye min Thant, Sergei Manzhos, Sergei Manzhos, Methawee Nukunudompanich
Read original paper ↗ ·Artificial Intelligence and Li Ion Batteries: Basics and Breakthroughs in Electrolyte Materials Discovery
Crystals · 2025-01-23
Haneen Alzamer, Russlan Jaafreh, Jung-Gu Kim, Kotiba Hamad
Read original paper ↗ ·Atomic Scale Modeling via Molecular Dynamics and Machine Learning of Na2O-V2O5-TeO2 Glass-Based Cathodes
Unknown journal · 2025-01-24
Firas Shuaib
Read original paper ↗ ·Enhancing material property prediction via a dual stream model fusing spatial and topological information
Computational Materials Science · 2025-01-30
Jiangnan Xie, Xiaolong Zheng, Zhihua Ying, Hui Zheng, Liang Zheng
Read original paper ↗ ·Self-reasoning assisted learning for non-Abelian gauge fields design
Physical review. B./Physical review. B · 2025-03-19
Jinyang Sun, Xi Chen, Xiumei Wang, Dandan Zhu, Xingping Zhou
Read original paper ↗ ·Application of Machine Learning in Nano Research — A Review
Nano LIFE · 2025-04-26
Fatema Tuz Zohura, Mariam Akter Mimona, Md Mir Shakib Ahmed, Md Israfil Hossain Rimon, Md. Aminul Islam, Nayem Hossain, Md Hosne Mobarak
Read original paper ↗ ·Leveraging generative models with periodicity-aware, invertible and invariant representations for crystalline materials design
Nature Computational Science · 2025-05-09
Zhilong Wang, Fengqi You
Read original paper ↗ ·Phase classification of high entropy alloys with composition, common physical, elemental-property descriptors and periodic table representation
Transactions of Nonferrous Metals Society of China · 2025-06-01
Shuai LI, Shuai LI, Jia Yang, Shu LI, Shu LI, Dong-Rong Liu, Mingyu Zhang
Read original paper ↗ ·