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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:

Physics-informed neural networks for hybrid modeling of lab-scale batch fermentation for β-carotene production using Saccharomyces cerevisiae
Mohammed Saad Faizan Bangi, Katy C. Kao, Joseph Sang‐Il Kwon
Process Safety and Environmental Protection (2022) Vol. 179, pp. 415-423
Closed Access | Times Cited: 74

Showing 1-25 of 74 citing articles:

Perspectives on the integration between first-principles and data-driven modeling
William A. Bradley, Jinhyeun Kim, Zachary Kilwein, et al.
Computers & Chemical Engineering (2022) Vol. 166, pp. 107898-107898
Open Access | Times Cited: 104
Deep neural network-based hybrid modeling and experimental validation for an industry-scale fermentation process: Identification of time-varying dependencies among parameters
Parth Shah, M. Ziyan Sheriff, Mohammed Saad Faizan Bangi, et al.
Chemical Engineering Journal (2022) Vol. 441, pp. 135643-135643
Closed Access | Times Cited: 91
Exploring the potential of time-series transformers for process modeling and control in chemical systems: An inevitable paradigm shift?
Niranjan Sitapure, Joseph Sang‐Il Kwon
Process Safety and Environmental Protection (2023) Vol. 194, pp. 461-477
Closed Access | Times Cited: 78
CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers
Niranjan Sitapure, Joseph Sang‐Il Kwon
Computers & Chemical Engineering (2023) Vol. 177, pp. 108339-108339
Open Access | Times Cited: 52
Introducing Hybrid Modeling with Time-Series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization
Niranjan Sitapure, Joseph Sang‐Il Kwon
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 49, pp. 21278-21291
Open Access | Times Cited: 40
Unveiling Latent Chemical Mechanisms: Hybrid Modeling for Estimating Spatiotemporally Varying Parameters in Moving Boundary Problems
Silabrata Pahari, Parth Shah, Joseph Sang‐Il Kwon
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 3, pp. 1501-1514
Closed Access | Times Cited: 16
Deep hybrid model‐based predictive control with guarantees on domain of applicability
Mohammed Saad Faizan Bangi, Joseph Sang‐Il Kwon
AIChE Journal (2022) Vol. 69, Iss. 5
Closed Access | Times Cited: 38
Physics-informed machine learning for MPC: Application to a batch crystallization process
Guoquan Wu, Wallace Tan Gian Yion, Khoa Le Nguyen Quang Dang, et al.
Process Safety and Environmental Protection (2023) Vol. 192, pp. 556-569
Open Access | Times Cited: 35
Machine learning applications in biomass pyrolysis: From biorefinery to end-of-life product management
David Akorede Akinpelu, Adekoya Oluwaseun Abiodun, Peter Olusakin Oladoye, et al.
Digital Chemical Engineering (2023) Vol. 8, pp. 100103-100103
Open Access | Times Cited: 35
Physics-Informed Online Machine Learning and Predictive Control of Nonlinear Processes with Parameter Uncertainty
Yingzhe Zheng, Zhe Wu
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 6, pp. 2804-2818
Closed Access | Times Cited: 31
Hybrid modeling in bioprocess dynamics: Structural variabilities, implementation strategies, and practical challenges
Biswanath Mahanty
Biotechnology and Bioengineering (2023) Vol. 120, Iss. 8, pp. 2072-2091
Open Access | Times Cited: 23
Achieving robustness in hybrid models: A physics-informed regularization approach for spatiotemporal parameter estimation in PDEs
Silabrata Pahari, Parth Shah, Joseph Sang‐Il Kwon
Process Safety and Environmental Protection (2024) Vol. 204, pp. 292-302
Closed Access | Times Cited: 11
Machine learning for sustainable organic waste treatment: a critical review
Rohit Gupta, Zahra Hajabdollahi Ouderji, Uzma Uzma, et al.
npj Materials Sustainability (2024) Vol. 2, Iss. 1
Open Access | Times Cited: 9
Hybrid Modeling for On-Line Fermentation Optimization and Scale-Up: A Review
Mariana Albino, Carina L. Gargalo, Gisela Nadal‐Rey, et al.
Processes (2024) Vol. 12, Iss. 8, pp. 1635-1635
Open Access | Times Cited: 7
A general deep hybrid model for bioreactor systems: Combining first principles with deep neural networks
José M. Pinto, Mykaella Mestre, João R. C. Ramos, et al.
Computers & Chemical Engineering (2022) Vol. 165, pp. 107952-107952
Open Access | Times Cited: 36
An adaptive data-driven approach for two-timescale dynamics prediction and remaining useful life estimation of Li-ion batteries
Bhavana Bhadriraju, Joseph Sang‐Il Kwon, Faisal Khan
Computers & Chemical Engineering (2023) Vol. 175, pp. 108275-108275
Closed Access | Times Cited: 18
Multi-objective optimization for sustainable and economical polycarbonate production with reaction kinetics inference for real-world industrial process
Eunbyul Lee, Minsu Kim, Il Moon, et al.
Chemical Engineering Journal (2024) Vol. 490, pp. 151484-151484
Closed Access | Times Cited: 6
Hybrid modeling of first-principles and machine learning: A step-by-step tutorial review for practical implementation
Parth Shah, Silabrata Pahari, Raj Bhavsar, et al.
Computers & Chemical Engineering (2024), pp. 108926-108926
Closed Access | Times Cited: 5
A review on full-, zero-, and partial-knowledge based predictive models for industrial applications
Stefano Zampini, Guido Parodi, Luca Oneto, et al.
Information Fusion (2025), pp. 102996-102996
Open Access
Multi‐rate observer design and optimal control to maximize productivity of an industry‐scale fermentation process
Parth Shah, M. Ziyan Sheriff, Mohammed Saad Faizan Bangi, et al.
AIChE Journal (2022) Vol. 69, Iss. 2
Closed Access | Times Cited: 25
Design and Analysis of a New COVID-19 Model with Comparative Study of Control Strategies
Azhar Iqbal Kashif Butt, Saira Batool, Muhammad Imran, et al.
Mathematics (2023) Vol. 11, Iss. 9, pp. 1978-1978
Open Access | Times Cited: 13
Physics-Informed Neural Networks for Process Systems: Handling Plant-Model Mismatch
Farshad Moayedi, Aswin Chandrasekar, S.K. Rasmussen, et al.
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 31, pp. 13650-13659
Closed Access | Times Cited: 4
A Critical Evaluation of Using Physics-Informed Neural Networks for Simulating Voltammetry: Strengths, Weaknesses and Best Practices
Haotian Chen, Christopher Batchelor‐McAuley, Enno Kätelhön, et al.
Journal of Electroanalytical Chemistry (2022) Vol. 925, pp. 116918-116918
Open Access | Times Cited: 20
Physics-informed machine learning methods for biomass gasification modeling by considering monotonic relationships
Shaojun Ren, Shiliang Wu, Qihang Weng
Bioresource Technology (2022) Vol. 369, pp. 128472-128472
Closed Access | Times Cited: 19
Data-driven identification and comparison of full multivariable models for propofol–remifentanil induced general anesthesia
Erhan Yumuk, Dana Copoţ, Clara M. Ionescu, et al.
Journal of Process Control (2024) Vol. 139, pp. 103243-103243
Open Access | Times Cited: 3
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