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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:

A novel physics-informed neural networks approach (PINN-MT) to solve mass transfer in plant cells during drying
Chanaka Batuwatta-Gamage, Charith Rathnayaka, H.C.P. Karunasena, et al.
Biosystems Engineering (2023) Vol. 230, pp. 219-241
Open Access | Times Cited: 19

Showing 19 citing articles:

From PINNs to PIKANs: recent advances in physics-informed machine learning
Juan Diego Toscano, Vivek Oommen, Alan John Varghese, et al.
Machine learning for computational science and engineering (2025) Vol. 1, Iss. 1
Closed Access | Times Cited: 3
A complete Physics-Informed Neural Network-based framework for structural topology optimization
Hyogu Jeong, Chanaka Batuwatta-Gamage, Jinshuai Bai, et al.
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 417, pp. 116401-116401
Open Access | Times Cited: 37
The Application of Physics-Informed Machine Learning in Multiphysics Modeling in Chemical Engineering
Zhi‐Yong Wu, Huan Wang, Chang He, et al.
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 44, pp. 18178-18204
Closed Access | Times Cited: 24
Toward intelligent food drying: Integrating artificial intelligence into drying systems
Seyed-Hassan Miraei Ashtiani, Alex Martynenko
Drying Technology (2024) Vol. 42, Iss. 8, pp. 1240-1269
Closed Access | Times Cited: 13
CFD Simulation of Micro-Level Water Transport in Potato Cells Under Periodic Boundary Conditions: Apoplastic Versus Symplastic Hydrodynamic
Fatemeh Mozafari Ghoraba, A. Ghazanfari, M. Shamsi, et al.
Food Biophysics (2025) Vol. 20, Iss. 2
Closed Access
A Physics-Informed Neural Network framework to investigate nonlinear and heterogenous shrinkage of drying plant cells
Chanaka Batuwatta-Gamage, Charith Rathnayaka, H.C.P. Karunasena, et al.
International Journal of Mechanical Sciences (2024) Vol. 275, pp. 109267-109267
Open Access | Times Cited: 4
An advanced physics-informed neural network-based framework for nonlinear and complex topology optimization
Hyogu Jeong, Chanaka Batuwatta-Gamage, Jinshuai Bai, et al.
Engineering Structures (2024) Vol. 322, pp. 119194-119194
Open Access | Times Cited: 4
Microwave-based and convective drying of cabbage (Brassica oleracea L. var capitata L.): Computational intelligence modeling, thermophysical properties, quality and mid-infrared spectrometry
Bobby Shekarau Luka, Miriam Jummai Mactony, Queen Msurshima Vihikwagh, et al.
Measurement Food (2024) Vol. 15, pp. 100187-100187
Open Access | Times Cited: 3
A comprehensive review of heat pump wood drying technologies
Lei Gao, Andrew J. Fix, Tamoy Seabourne, et al.
Energy (2024) Vol. 311, pp. 133241-133241
Closed Access | Times Cited: 3
Recent advances in determining the cellular-level property evolutions of plant-based food materials during drying
Vindya Thathsaranee Weligama Thuppahige, Zachary G. Welsh, Mohammad U. H. Joardder, et al.
Trends in Food Science & Technology (2023) Vol. 143, pp. 104291-104291
Open Access | Times Cited: 6
A Complete Physics-Informed Neural Network-Based Framework for Structural Topology Optimization
Hyogu Jeong, Chanaka Batuwatta-Gamage, Jinshuai Bai, et al.
(2023)
Closed Access | Times Cited: 5
A data-physic driven method for gear fault diagnosis using PINN and pseudo-dynamic features
Yikun Yang, Xifeng Wang, Jinfeng Li, et al.
Measurement (2024) Vol. 236, pp. 115124-115124
Closed Access | Times Cited: 1
A Data-Physic Driven Method for Gear Fault Diagnosis Using Pinn and Pseudo-Dynamic Features
Yikun Yang, Xifeng Wang, Jinfeng Li, et al.
(2024)
Closed Access
A novel machine learning-based computational framework for predicting microscale morphological changes of plant cells during drying
Chanaka Prabuddha Batuwatta Gamage
(2024)
Open Access
CFD Simulation of Micro-Level Water Transport of Potato Cells in Periodic Condition: Apoplastic and Symplastic Hydrodynamic
Fatemeh Mozafari Ghorba, A. Ghazanfari, M. Shamsi, et al.
Research Square (Research Square) (2024)
Closed Access
A meshless Runge-Kutta-based Physics-Informed Neural Network framework for structural vibration analysis
Shusheng Xiao, Jinshuai Bai, Hyogu Jeong, et al.
Engineering Analysis with Boundary Elements (2024) Vol. 170, pp. 106054-106054
Closed Access
Microwave-Based and Convective Drying of Cabbage (Brassica Oleracea L. VAR Capitata L.): Computational Intelligence Modelling, Thermophysical Properties, Quality and Mid-Infrared Spectrometry
Bobby Shekarau Luka, Miriam Jummai Mactony, Queen Msurshima Vihikwagh, et al.
(2023)
Closed Access | Times Cited: 1
A Physics-Informed Neural-Network-Based Multi-Domain Computational Model to Investigate Nonlinear and Heterogenous Shrinkage of Plant Cells During Drying
Chanaka Batuwatta-Gamage, Charith Rathnayaka, H.C.P. Karunasena, et al.
(2023)
Closed Access | Times Cited: 1
Physics-Informed Machine Learning: the Next Big Trend in Food Process Modelling?
Emmanuel Purlis
Current Food Science and Technology Reports (2023) Vol. 2, Iss. 1, pp. 1-6
Closed Access | Times Cited: 1
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