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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:

Learning new physical descriptors from reduced-order analysis of bubble dynamics in boiling heat transfer
Arif Rokoni, Lige Zhang, Tejaswi Soori, et al.
International Journal of Heat and Mass Transfer (2022) Vol. 186, pp. 122501-122501
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Advances in micro and nanoengineered surfaces for enhancing boiling and condensation heat transfer: a review
Nithin Vinod Upot, Kazi Fazle Rabbi, Siavash Khodakarami, et al.
Nanoscale Advances (2022) Vol. 5, Iss. 5, pp. 1232-1270
Open Access | Times Cited: 51
Computer Vision and Machine Learning Methods for Heat Transfer and Fluid Flow in Complex Structural Microchannels: A Review
Bin Yang, Xin Zhu, Boan Wei, et al.
Energies (2023) Vol. 16, Iss. 3, pp. 1500-1500
Open Access | Times Cited: 26
Mechanisms and modeling of bubble dynamic behaviors and mass transfer under gravity: A review
Shenglin Yan, Xu-Qing Wang, Li‐Tao Zhu, et al.
Chemical Engineering Science (2023) Vol. 277, pp. 118854-118854
Closed Access | Times Cited: 25
Nonintrusive heat flux quantification using acoustic emissions during pool boiling
Christy Dunlap, Hari Pandey, Ethan Weems, et al.
Applied Thermal Engineering (2023) Vol. 228, pp. 120558-120558
Open Access | Times Cited: 21
Recent progress of artificial intelligence for liquid-vapor phase change heat transfer
Youngjoon Suh, Aparna Chandramowlishwaran, Yoonjin Won
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 7
Advances in the modeling of multiphase flows and their application in nuclear engineering—A review
Mengqi Wu, Jinsong Zhang, Nan Gui, et al.
Experimental and Computational Multiphase Flow (2024) Vol. 6, Iss. 4, pp. 287-352
Closed Access | Times Cited: 6
Machine learning enabled condensation heat transfer measurement
Siavash Khodakarami, Kazi Fazle Rabbi, Youngjoon Suh, et al.
International Journal of Heat and Mass Transfer (2022) Vol. 194, pp. 123016-123016
Open Access | Times Cited: 23
A framework for generalizing critical heat flux detection models using unsupervised image-to-image translation
Firas Al-Hindawi, Tejaswi Soori, Han Hu, et al.
Expert Systems with Applications (2023) Vol. 227, pp. 120265-120265
Open Access | Times Cited: 14
Deep learning segmentation to analyze bubble dynamics and heat transfer during boiling at various pressures
Ivan Malakhov, Aleksandr Seredkin, Andrey Chernyavskiy, et al.
International Journal of Multiphase Flow (2023) Vol. 162, pp. 104402-104402
Closed Access | Times Cited: 13
Autonomous and online detection of dry areas on a boiling surface using deep learning and infrared thermometry
Madhumitha Ravichandran, Artyom Kossolapov, Gustavo Aguiar, et al.
Experimental Thermal and Fluid Science (2023) Vol. 145, pp. 110879-110879
Closed Access | Times Cited: 11
Multi-task image-based deep learning for boiling analysis: Material recognition and heat flux prediction
Mengqi Wu, Nan Gui, Xingtuan Yang, et al.
International Communications in Heat and Mass Transfer (2025) Vol. 163, pp. 108763-108763
Closed Access
VISION-iT: A Framework for Digitizing Bubbles and Droplets
Youngjoon Suh, S. Chang, Peter Simadiris, et al.
Energy and AI (2023) Vol. 15, pp. 100309-100309
Open Access | Times Cited: 10
BubbleID: A deep learning framework for bubble interface dynamics analysis
Christy Dunlap, Changgen Li, Hari Pandey, et al.
Journal of Applied Physics (2024) Vol. 136, Iss. 1
Open Access | Times Cited: 3
Investigation of acoustic spectral variations in the pool boiling regimes of water on wire heater
Sreeram Barathula, Jaswanth K.K. Alapati, K. Srinivasan
Applied Thermal Engineering (2023) Vol. 226, pp. 120281-120281
Closed Access | Times Cited: 8
Review of the current status and the potential of machine learning tools in boiling heat transfer
Avinash Upadhyay, Soumya Kanti Hazra, Ashwani Assam, et al.
Numerical Heat Transfer Part B Fundamentals (2023), pp. 1-44
Closed Access | Times Cited: 7
Rapid identification of boiling crisis with event-based visual streaming analysis
Dale Lu, Youngjoon Suh, Yoonjin Won
Applied Thermal Engineering (2023) Vol. 239, pp. 122004-122004
Open Access | Times Cited: 7
Data-driven dryout prediction in helical-coiled once-through steam generator: A physics-informed approach leveraging the Buckingham Pi theorem
Yang Kuang, Haifan Liao, Bo Xu, et al.
Energy (2024) Vol. 294, pp. 130822-130822
Closed Access | Times Cited: 2
Data-driven diagnostics of boiling heat transfer on flat heaters from non-intrusive visualization
Vinicius K. Scariot, Gustavo M. Hobold, Alexandre K. da Silva
Applied Thermal Engineering (2024) Vol. 248, pp. 123068-123068
Closed Access | Times Cited: 2
Bubble mass transfer in fluids under gravity: a review of theoretical models and intensification technologies in industry
Yiyi Ma, Linjiang Guo, Yuanhao Xiao, et al.
Frontiers in Physics (2024) Vol. 12
Open Access | Times Cited: 2
Numerical modeling based machine learning approach for the optimization of falling - film evaporator in thermal desalination application
Shantanu Shahane, Hong-Qing Jin, Sophie Wang, et al.
International Journal of Heat and Mass Transfer (2022) Vol. 196, pp. 123223-123223
Open Access | Times Cited: 12
Domain-knowledge Inspired Pseudo Supervision (DIPS) for unsupervised image-to-image translation models to support cross-domain classification
Firas Al-Hindawi, Md Mahfuzur Rahman Siddiquee, Teresa Wu, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107255-107255
Open Access | Times Cited: 4
Machine learning in critical heat flux studies in nuclear systems: A detailed review
S.L. Qi, Bin Han, Xiaoliang Zhu, et al.
Progress in Nuclear Energy (2024) Vol. 179, pp. 105535-105535
Closed Access | Times Cited: 1
Experimental study on condensate heat transfer coefficient of multi-channel cylinder dryer integrated with Bayesian-optimized machine learning prediction
Lijie Qiao, Dong Ji-xian, K. L. Zhang, et al.
Drying Technology (2023) Vol. 41, Iss. 14, pp. 2309-2322
Open Access | Times Cited: 3
An intelligent strategy for phase change heat and mass transfer: Application of machine learning
Siavash Khodakarami, Youngjoon Suh, Yoonjin Won, et al.
Advances in heat transfer (2023), pp. 113-168
Closed Access | Times Cited: 3
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