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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:

Predicting aggregate morphology of sequence-defined macromolecules with recurrent neural networks
Debjyoti Bhattacharya, Devon C. Kleeblatt, Antonia Statt, et al.
Soft Matter (2022) Vol. 18, Iss. 27, pp. 5037-5051
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

TransPolymer: a Transformer-based language model for polymer property predictions
Changwen Xu, Yuyang Wang, Amir Barati Farimani
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 85
Emerging Trends in Machine Learning: A Polymer Perspective
Tyler B. Martin, Debra J. Audus
ACS Polymers Au (2023) Vol. 3, Iss. 3, pp. 239-258
Open Access | Times Cited: 84
Data-Driven Design of Polymer-Based Biomaterials: High-throughput Simulation, Experimentation, and Machine Learning
Roshan Patel, Michael Webb
ACS Applied Bio Materials (2023) Vol. 7, Iss. 2, pp. 510-527
Closed Access | Times Cited: 51
The Rise of Machine Learning in Polymer Discovery
Cheng Yan, Guoqiang Li
Advanced Intelligent Systems (2023) Vol. 5, Iss. 4
Open Access | Times Cited: 38
Sequence Patterning, Morphology, and Dispersity in Single-Chain Nanoparticles: Insights from Simulation and Machine Learning
Roshan Patel, Sophia Colmenares, Michael Webb
ACS Polymers Au (2023) Vol. 3, Iss. 3, pp. 284-294
Open Access | Times Cited: 17
Sequence- and stereo-defined macromolecules: Properties and emerging functionalities
Róża Szweda
Progress in Polymer Science (2023) Vol. 145, pp. 101737-101737
Closed Access | Times Cited: 17
PolyNC: a natural and chemical language model for the prediction of unified polymer properties
Haoke Qiu, Lunyang Liu, Xuepeng Qiu, et al.
Chemical Science (2023) Vol. 15, Iss. 2, pp. 534-544
Open Access | Times Cited: 16
Sizing up feature descriptors for macromolecular machine learning with polymeric biomaterials
Samantha Stuart, Jeffrey Watchorn, Frank Gu
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 15
Generative BigSMILES: an extension for polymer informatics, computer simulations & ML/AI
Ludwig Schneider, Dylan J. Walsh, Bradley D. Olsen, et al.
Digital Discovery (2023) Vol. 3, Iss. 1, pp. 51-61
Open Access | Times Cited: 15
nanoNET: machine learning platform for predicting nanoparticles distribution in a polymer matrix
Kumar Ayush, Abhishek Seth, Tarak K. Patra
Soft Matter (2023) Vol. 19, Iss. 29, pp. 5502-5512
Open Access | Times Cited: 12
Simulations of morphology control of self‐assembled amphiphilic surfactants
Qinyu Zhu, Douglas R. Tree
Journal of Polymer Science (2023) Vol. 61, Iss. 12, pp. 1214-1240
Open Access | Times Cited: 11
Machine Learning Approaches in Polymer Science: Progress and Fundamental for a New Paradigm
Chunhui Xie, Haoke Qiu, Lu Liu, et al.
SmartMat (2025) Vol. 6, Iss. 1
Open Access
Machine learning-enabled exploration of mesoscale architectures in amphiphilic-molecule self-assembly
Takeo Sudo, Satoki Ishiai, Yuuki Ishiwatari, et al.
Next research. (2025), pp. 100150-100150
Open Access
Application of Digital Methods in Polymer Science and Engineering
Timo Schuett, Patrick Endres, Tobias Standau, et al.
Advanced Functional Materials (2023) Vol. 34, Iss. 8
Open Access | Times Cited: 8
Quantifying Pairwise Similarity for Complex Polymers
Jiale Shi, Nathan Rebello, Dylan J. Walsh, et al.
Macromolecules (2023) Vol. 56, Iss. 18, pp. 7344-7357
Closed Access | Times Cited: 7
Data-driven models for predicting intrinsically disordered protein polymer physics directly from composition or sequence
Tzu‐Hsuan Chao, Shiv Rekhi, Jeetain Mittal, et al.
Molecular Systems Design & Engineering (2023) Vol. 8, Iss. 9, pp. 1146-1155
Closed Access | Times Cited: 6
Machine learning prediction of self-assembly and analysis of molecular structure dependence on the critical packing parameter
Yuuki Ishiwatari, T. Yokoyama, Tomoya Kojima, et al.
Molecular Systems Design & Engineering (2023) Vol. 9, Iss. 1, pp. 20-28
Open Access | Times Cited: 6
Polymer sequence design via molecular simulation-based active learning
Praneeth S Ramesh, Tarak K. Patra
Soft Matter (2022) Vol. 19, Iss. 2, pp. 282-294
Closed Access | Times Cited: 10
A High-Throughput Workflow to Analyze Sequence-Conformation Relationships and Explore Hydrophobic Patterning in Disordered Peptoids
Erin C. Day, Supraja S. Chittari, Keila C. Cunha, et al.
(2024)
Open Access | Times Cited: 1
Generative BigSMILES: An Extension for Polymer Informatics, Computer Simulations & ML/AI
Ludwig Schneider, Dylan J. Walsh, Bradley D. Olsen, et al.
(2023)
Open Access | Times Cited: 3
Template Design for Complex Block Copolymer Patterns Using a Machine Learning Method
Zhihan Liu, Yixin Liu, Yuliang Yang, et al.
ACS Applied Materials & Interfaces (2023) Vol. 15, Iss. 25, pp. 31049-31056
Closed Access | Times Cited: 2
A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids
Erin C. Day, Supraja S. Chittari, Keila C. Cunha, et al.
Chem (2024) Vol. 10, Iss. 11, pp. 3444-3458
Closed Access
Large language models design sequence-defined macromolecules via evolutionary optimization
Wesley F. Reinhart, Antonia Statt
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access
Prediction and Evaluation of Protein Aggregation with Computational Methods
Mubashir Hassan, Saba Shahzadi, Mai Suan Li, et al.
Methods in molecular biology (2024), pp. 299-314
Closed Access
Developing efficient deep learning model for predicting copolymer properties
Himanshu, Kaushik Chakraborty, Tarak K. Patra
Physical Chemistry Chemical Physics (2023) Vol. 25, Iss. 37, pp. 25166-25176
Closed Access | Times Cited: 1
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