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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Pragmatic generative optimization of novel structural lattice metamaterials with machine learning
Anthony Garland, Benjamin White, Scott Jensen, et al.
Materials & Design (2021) Vol. 203, pp. 109632-109632
Open Access | Times Cited: 79

Showing 1-25 of 79 citing articles:

Rapid inverse design of metamaterials based on prescribed mechanical behavior through machine learning
Chan Soo Ha, Desheng Yao, Zhenpeng Xu, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 127
Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design
Xiaoyang Zheng, Xubo Zhang, Ta‐Te Chen, et al.
Advanced Materials (2023) Vol. 35, Iss. 45
Open Access | Times Cited: 122
On the use of artificial neural networks in topology optimisation
Rebekka V. Woldseth, Niels Aage, Jakob Andreas Bærentzen, et al.
Structural and Multidisciplinary Optimization (2022) Vol. 65, Iss. 10
Closed Access | Times Cited: 111
Data‐Driven Design for Metamaterials and Multiscale Systems: A Review
Doksoo Lee, Wei Chen, Liwei Wang, et al.
Advanced Materials (2023) Vol. 36, Iss. 8
Open Access | Times Cited: 72
Big data, machine learning, and digital twin assisted additive manufacturing: A review
Liuchao Jin, Xiaoya Zhai, Kang Wang, et al.
Materials & Design (2024) Vol. 244, pp. 113086-113086
Open Access | Times Cited: 47
Biomimetic Mechanical Robust Cement‐Resin Composites with Machine Learning‐Assisted Gradient Hierarchical Structures
Zhangyu Wu, Hao Pan, Peng Huang, et al.
Advanced Materials (2024) Vol. 36, Iss. 35
Closed Access | Times Cited: 44
The arrangement patterns optimization of 3D honeycomb and 3D re-entrant honeycomb structures for energy absorption
BingChen Xia, Xingyuan Huang, Lijun Chang, et al.
Materials Today Communications (2023) Vol. 35, pp. 105996-105996
Closed Access | Times Cited: 43
Machine learning predictions on the compressive stress–strain response of lattice-based metamaterials
Lijun Xiao, Gaoquan Shi, Weidong Song
International Journal of Solids and Structures (2024) Vol. 300, pp. 112893-112893
Closed Access | Times Cited: 31
Machine intelligence in metamaterials design: a review
Gabrielis Cerniauskas, Haleema Sadia, Parvez Alam
Oxford Open Materials Science (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 22
A review of machine learning (ML) and explainable artificial intelligence (XAI) methods in additive manufacturing (3D Printing)
Jeewanthi Ukwaththa, Sumudu Herath, D.P.P. Meddage
Materials Today Communications (2024) Vol. 41, pp. 110294-110294
Open Access | Times Cited: 19
Deep Learning-Accelerated Designs of Tunable Magneto-Mechanical Metamaterials
Chunping Ma, Yilong Chang, Shuai Wu, et al.
ACS Applied Materials & Interfaces (2022) Vol. 14, Iss. 29, pp. 33892-33902
Closed Access | Times Cited: 64
Design, mechanical properties and optimization of lattice structures with hollow prismatic struts
Miao Zhao, Xinwei Li, David Z. Zhang, et al.
International Journal of Mechanical Sciences (2022) Vol. 238, pp. 107842-107842
Closed Access | Times Cited: 54
Topology optimization of additive-manufactured metamaterial structures: A review focused on multi-material types
Sattar Mohammadi Esfarjani, Ali Dadashi, Mohammad Azadi
Forces in Mechanics (2022) Vol. 7, pp. 100100-100100
Open Access | Times Cited: 47
Systematic design of Cauchy symmetric structures through Bayesian optimization
Haris Moazam Sheikh, Timon Meier, Brian W. Blankenship, et al.
International Journal of Mechanical Sciences (2022) Vol. 236, pp. 107741-107741
Open Access | Times Cited: 46
A systematic review on data of additive manufacturing for machine learning applications: the data quality, type, preprocessing, and management
Ying Zhang, Mutahar Safdar, Jiarui Xie, et al.
Journal of Intelligent Manufacturing (2022) Vol. 34, Iss. 8, pp. 3305-3340
Closed Access | Times Cited: 41
Optimization with artificial intelligence in additive manufacturing: a systematic review
Francesco Ciccone, Antonio Bacciaglia, Alessandro Ceruti
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2023) Vol. 45, Iss. 6
Open Access | Times Cited: 41
Machine learning-based prediction and inverse design of 2D metamaterial structures with tunable deformation-dependent Poisson's ratio
Jie Tian, Keke Tang, Xianyan Chen, et al.
Nanoscale (2022) Vol. 14, Iss. 35, pp. 12677-12691
Closed Access | Times Cited: 39
Deep Learning for Size‐Agnostic Inverse Design of Random‐Network 3D Printed Mechanical Metamaterials
H. Pahlavani, Kostas Tsifoutis‐Kazolis, Mauricio Cruz Saldívar, et al.
Advanced Materials (2023) Vol. 36, Iss. 6
Open Access | Times Cited: 39
Computational Design and Manufacturing of Sustainable Materials through First-Principles and Materiomics
Sabrina C. Shen, Eesha Khare, Nicolas A. Lee, et al.
Chemical Reviews (2023) Vol. 123, Iss. 5, pp. 2242-2275
Closed Access | Times Cited: 38
Perspectives for multiphase mechanical metamaterials
Yuan Chen, Yiu‐Wing Mai, Lin Ye
Materials Science and Engineering R Reports (2023) Vol. 153, pp. 100725-100725
Closed Access | Times Cited: 35
Recent Advancements in Design Optimization of Lattice‐Structured Materials
Abdulla Almesmari, Ali N. Alagha, Mohammed M. Naji, et al.
Advanced Engineering Materials (2023) Vol. 25, Iss. 17
Open Access | Times Cited: 28
Inverse design of 3D cellular materials with physics-guided machine learning
Mohammad Abu-Mualla, Jida Huang
Materials & Design (2023) Vol. 232, pp. 112103-112103
Open Access | Times Cited: 27
On vibration isolation performance and crashworthiness of a three-dimensional lattice metamaterial
Linwei Zhang, Zhonghao Bai, Qiang Zhang, et al.
Engineering Structures (2023) Vol. 292, pp. 116510-116510
Closed Access | Times Cited: 23
Review of Machine Learning applications in Additive Manufacturing
Sirajudeen Inayathullah, Raviteja Buddala
Results in Engineering (2024) Vol. 25, pp. 103676-103676
Open Access | Times Cited: 13
Deep learning-based inverse design of lattice metamaterials for tuning bandgap
Kai Zhang, Yaoyao Guo, Xiangbing Liu, et al.
Extreme Mechanics Letters (2024) Vol. 69, pp. 102165-102165
Closed Access | Times Cited: 12
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