Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Prediction of CO2 solubility in ionic liquids via convolutional autoencoder based on molecular structure encoding
Tianxiong Liu, Dingchao Fan, Yusen Chen, et al.
AIChE Journal (2023) Vol. 69, Iss. 10
Closed Access | Times Cited: 14

Showing 14 citing articles:

Insight to the prediction of CO2 solubility in ionic liquids based on the interpretable machine learning model
Ao Yang, Shirui Sun, Yang Su, et al.
Chemical Engineering Science (2024) Vol. 297, pp. 120266-120266
Closed Access | Times Cited: 10
An Overview of Flue Gas SO2 Capture Technology Based on Absorbent Evaluation and Process Intensification
Jiangpeng Xie, Dongliang Wang, Li Liu, et al.
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 14, pp. 6066-6086
Closed Access | Times Cited: 8
Prediction of Electrical Conductivity of Ionic Liquids: From COSMO-RS Derived QSPR Evaluation to Boosting Machine Learning
Zixin Chen, Jiahui Chen, Yuxin Qiu, et al.
ACS Sustainable Chemistry & Engineering (2024) Vol. 12, Iss. 17, pp. 6648-6658
Closed Access | Times Cited: 8
An Improved WOA (Whale Optimization Algorithm)-Based CNN-BIGRU-CBAM Model and Its Application to Short-Term Power Load Forecasting
Lei Dai, Haiying Wang
Energies (2024) Vol. 17, Iss. 11, pp. 2559-2559
Open Access | Times Cited: 7
Review of ionic liquid and ionogel-based biomaterials for advanced drug delivery
Muzammil Kuddushi, Ben Bin Xu, Naved I. Malek, et al.
Advances in Colloid and Interface Science (2024) Vol. 331, pp. 103244-103244
Open Access | Times Cited: 6
Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids
Shadfar Davoodi, Hung Vo Thanh, David A. Wood, et al.
Journal of Industrial Information Integration (2024) Vol. 41, pp. 100662-100662
Closed Access | Times Cited: 6
Machine learning modeling of the CO2 solubility in ionic liquids by using σ-profile descriptors
J. Laakso, Ali Ebrahimpoor Gorji, Petri Uusi‐Kyyny, et al.
Chemical Engineering Science (2025), pp. 121226-121226
Open Access
Interpretable Feedforward Neural Network and XGBoost-Based Algorithms to Predict CO2 Solubility in Ionic Liquids
Ao Yang, Shirui Sun, Hongfu Mi, et al.
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 18, pp. 8293-8305
Closed Access | Times Cited: 2
Exploring the chemical space of ionic liquids for CO2 dissolution through generative machine learning models
Xiuxian Chen, Guzhong Chen, Kunchi Xie, et al.
Green Chemical Engineering (2024)
Open Access | Times Cited: 2
A Deep Learning Hybrid Framework Combining an Efficient Evolutionary Algorithm for Complex Many-Objective Optimization of Sustainable Triple CO2 Feed Methanol Production
Hong‐Tao Cao, Yue Li, Chenglin Chang, et al.
ACS Sustainable Chemistry & Engineering (2024) Vol. 12, Iss. 17, pp. 6682-6696
Closed Access | Times Cited: 1
Development of an interpretable QSPR model to predict the octanol-water partition coefficient based on three artificial intelligence algorithms
Ao Yang, Shirui Sun, Qi Lu, et al.
Green Chemical Engineering (2024)
Open Access | Times Cited: 1
An interpretable surrogate model for H2S solubility forecasting in ionic liquids based on machine learning
Yanjiang He, Ao Yang, Changjun Zou, et al.
Separation and Purification Technology (2024) Vol. 357, pp. 130061-130061
Closed Access
Evaluating ionic liquid toxicity with machine learning and structural similarity methods
Rongli Shan, Runqi Zhang, Ying Gao, et al.
Green Chemical Engineering (2024)
Open Access
Predicting the solubility of CO2 and N2 in ionic liquids based on COSMO-RS and machine learning
Hongling Qin, Ke Wang, Xifei Ma, et al.
Frontiers in Chemistry (2024) Vol. 12
Open Access
Page 1

Scroll to top