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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:

Deep learning for topology optimization of 2D metamaterials
Hunter T. Kollmann, Diab W. Abueidda, Seid Korić, et al.
Materials & Design (2020) Vol. 196, pp. 109098-109098
Open Access | Times Cited: 274

Showing 1-25 of 274 citing articles:

A review of artificial neural networks in the constitutive modeling of composite materials
Xin Liu, Su Tian, Fei Tao, et al.
Composites Part B Engineering (2021) Vol. 224, pp. 109152-109152
Closed Access | Times Cited: 288
Additively manufactured materials and structures: A state-of-the-art review on their mechanical characteristics and energy absorption
Yaozhong Wu, Jianguang Fang, Chi Wu, et al.
International Journal of Mechanical Sciences (2023) Vol. 246, pp. 108102-108102
Closed Access | Times Cited: 226
Mechanical metamaterials and beyond
Pengcheng Jiao, J. Howard Mueller, Jordan R. Raney, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 219
Additive manufacturing of polymeric composites from material processing to structural design
Shangqin Yuan, Shaoying Li, Jihong Zhu, et al.
Composites Part B Engineering (2021) Vol. 219, pp. 108903-108903
Closed Access | Times Cited: 188
Deep learning for plasticity and thermo-viscoplasticity
Diab W. Abueidda, Seid Korić, Nahil Sobh, et al.
International Journal of Plasticity (2020) Vol. 136, pp. 102852-102852
Closed Access | Times Cited: 157
From Photonic Crystals to Seismic Metamaterials: A Review via Phononic Crystals and Acoustic Metamaterials
Muhammad Gulzari, C.W. Lim
Archives of Computational Methods in Engineering (2021) Vol. 29, Iss. 2, pp. 1137-1198
Closed Access | Times Cited: 129
Deep learning framework for material design space exploration using active transfer learning and data augmentation
Yongtae Kim, Youngsoo Kim, Charles Yang, et al.
npj Computational Materials (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 119
Meshless physics‐informed deep learning method for three‐dimensional solid mechanics
Diab W. Abueidda, Qiyue Lu, Seid Korić
International Journal for Numerical Methods in Engineering (2021) Vol. 122, Iss. 23, pp. 7182-7201
Open Access | Times Cited: 113
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
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: 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: 71
Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling
Li Zheng, Konstantinos Karapiperis, Siddhant Kumar, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 69
Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads
Junyan He, Seid Korić, Shashank Kushwaha, et al.
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 415, pp. 116277-116277
Open Access | Times Cited: 50
Unleashing the Power of Artificial Intelligence in Materials Design
Silvia Badini, Stefano Regondi, Raffaele Pugliese
Materials (2023) Vol. 16, Iss. 17, pp. 5927-5927
Open Access | Times Cited: 49
Rational designs of mechanical metamaterials: Formulations, architectures, tessellations and prospects
Jie Gao, Xiaofei Cao, Mi Xiao, et al.
Materials Science and Engineering R Reports (2023) Vol. 156, pp. 100755-100755
Closed Access | Times Cited: 49
Topology optimization via machine learning and deep learning: a review
Seungyeon Shin, Dongju Shin, Namwoo Kang
Journal of Computational Design and Engineering (2023) Vol. 10, Iss. 4, pp. 1736-1766
Open Access | Times Cited: 48
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
Sequential Deep Operator Networks (S-DeepONet) for predicting full-field solutions under time-dependent loads
Junyan He, Shashank Kushwaha, Jaewan Park, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107258-107258
Open Access | Times Cited: 41
Human-Centered and Sustainable Artificial Intelligence in Industry 5.0: Challenges and Perspectives
Barbara Martini, Denise Bellisario, Paola Coletti
Sustainability (2024) Vol. 16, Iss. 13, pp. 5448-5448
Open Access | Times Cited: 35
Machine Learning Aided Design and Optimization of Thermal Metamaterials
Changliang Zhu, Emmanuel Anuoluwa Bamidele, Xiangying Shen, et al.
Chemical Reviews (2024) Vol. 124, Iss. 7, pp. 4258-4331
Open Access | Times Cited: 33
Topology optimization methods for thermal metamaterials: A review
Wei Sha, Mi Xiao, Yihui Wang, et al.
International Journal of Heat and Mass Transfer (2024) Vol. 227, pp. 125588-125588
Closed Access | Times Cited: 22
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: 21
The mixed Deep Energy Method for resolving concentration features in finite strain hyperelasticity
Jan N. Fuhg, Nikolaos Bouklas
Journal of Computational Physics (2021) Vol. 451, pp. 110839-110839
Open Access | Times Cited: 92
Controllable inverse design of auxetic metamaterials using deep learning
Xiaoyang Zheng, Ta‐Te Chen, Xiaofeng Guo, et al.
Materials & Design (2021) Vol. 211, pp. 110178-110178
Open Access | Times Cited: 91
TONR: An exploration for a novel way combining neural network with topology optimization
Zeyu Zhang, Yu Li, Weien Zhou, et al.
Computer Methods in Applied Mechanics and Engineering (2021) Vol. 386, pp. 114083-114083
Closed Access | Times Cited: 67
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