Accurate prediction of carbon dioxide capture by deep eutectic solvents using quantum chemistry and a neural network

Mood Mohan, Omar Demerdash, Blake A. Simmons, Jeremy C. Smith, Michelle K. Kidder and Seema Singh

Green Chem., 2023, 25, 3475
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Novel hybrid QSPR-GPR approach for modeling of carbon dioxide capture using deep eutectic solvents

Iman Salahshoori, Alireza Baghban and Amirhosein Yazdanbakhsh

RSC Adv., 2023, 13, 30071
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Study of fluconazole drug behavior in deep eutectic solvents: thermodynamic properties, solubility measurement, and fluorescence spectroscopy

Hadi Azad, Hemayat Shekaari, Fariba Ghaffari, Masumeh Mokhtarpour and Mohammad Bagheri Hokm Abad

RSC Adv., 2025, 15, 11194
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Enhancing precision in PANI/Gr nanocomposite design: robust machine learning models, outlier resilience, and molecular input insights for superior electrical conductivity and gas sensing performance

Abir Boublia, Zahir Guezzout, Nacerddine Haddaoui, Michael Badawi, Ahmad S. Darwish, Tarek Lemaoui, Fawzi Banat, Krishna Kumar Yadav, Byong-Hun Jeon, Noureddine Elboughdiri, Yacine Benguerba and Inas M. AlNashef

J. Mater. Chem. A, 2024, 12, 2209
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Graph neural networks for CO2 solubility predictions in Deep Eutectic Solvents

Gabriel Hernández Morales, Edgar Ivan Sanchez Medina, Arturo Jiménez-Gutiérrez and Victor M. Zavala

Computers & Chemical Engineering, 2024, 187, 108750
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Predicting the Surface Tension of Deep Eutectic Solvents Using Artificial Neural Networks

Tarek Lemaoui, Abir Boublia, Ahmad S. Darwish, Manawwer Alam, Sungmin Park, Byong-Hun Jeon, Fawzi Banat, Yacine Benguerba and Inas M. AlNashef

ACS Omega, 2022, 7, 32194
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SaPt-CNN-LSTM-AR-EA: a hybrid ensemble learning framework for time series-based multivariate DNA sequence prediction

Wu Yan, Li Tan, Li Meng-Shan, Sheng Sheng, Wang Jun and Wu Fu-an

PeerJ, 2023, 11, e16192
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Boosting Graph Neural Networks with Molecular Mechanics: A Case Study of Sigma Profile Prediction

Dinis O. Abranches, Edward J. Maginn and Yamil J. Colón

J. Chem. Theory Comput., 2023, 19, 9318
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Molecular-based artificial neural networks for selecting deep eutectic solvents for the removal of contaminants from aqueous media

Narjis E. Awaja, Ghaiath Almustafa, Ahmad S. Darwish, Tarek Lemaoui, Yacine Benguerba, Fawzi Banat, Hassan A. Arafat and Inas AlNashef

Chemical Engineering Journal, 2023, 476, 146429
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Development of a Generalizable Gradient Boosting Regression-Based Framework for Predicting the Properties of Single and Binary IL Systems

Kimia Fereydooni and Oscar Nordness

ACS Appl. Eng. Mater., 2025, 3, 1024
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Stochastic machine learning via sigma profiles to build a digital chemical space

Dinis O. Abranches, Edward J. Maginn and Yamil J. Colón

Proc. Natl. Acad. Sci. U.S.A., 2024, 121
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Application of statistical physical, DFT computation and molecular dynamics simulation for enhanced removal of crystal violet and basic fuchsin dyes utilizing biosorbent derived from residual watermelon seeds (Citrullus lanatus)

Noureddine Elboughdiri, Imane Lakikza, Abir Boublia, Saoussen Imene Aouni, Nour El Houda Hammoudi, Jordana Georgin, Dison Stracke Pfingsten Franco, Hana Ferkous, Djamel Ghernaout and Yacine Benguerba

Process Safety and Environmental Protection, 2024, 186, 995
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Gabapentin drug interactions in water and aqueous solutions of green betaine based compounds through volumetric, viscometric and interfacial properties

Elaheh Janbezar, Hemayat Shekaari and Mohammad Bagheri

Sci Rep, 2025, 15
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The shape of water - how cluster formation explains the hydrophobic effect

Martin P. Andersson

Journal of Molecular Liquids, 2024, 400, 124491
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Multiple linear regression in adsorption capacity prediction: Application in plastic waste pyrolysis oil purification

Thien Nguyen Luu Minh, Michiel Van Melkebeke, Elisabetta Carrieri, Joël Hogie, Hilde Poelman, Youri Michiels, Kevin M. Van Geem and Steven De Meester

Separation and Purification Technology, 2025, 134651
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Application of interpretable machine learning models to improve the prediction performance of ionic liquids toxicity

Dingchao Fan, Ke Xue, Runqi Zhang, Wenguang Zhu, Hongru Zhang, Jianguang Qi, Zhaoyou Zhu, Yinglong Wang and Peizhe Cui

Science of The Total Environment, 2024, 908, 168168
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Harnessing the potential of deep eutectic solvents in biocatalysis: design strategies using CO2 to formate reduction as a case study

Marijan Logarušić, Karla Šubar, Maja Nikolić, Ana Jurinjak Tušek, Anja Damjanović, Mia Radović, Ivana Radojčić Redovniković, Polona Žnidaršič-Plazl, Wolfgang Kroutil and Marina Cvjetko Bubalo

Front. Chem., 2024, 12
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Physics-Based Machine Learning Models Predict Carbon Dioxide Solubility in Chemically Reactive Deep Eutectic Solvents

Mood Mohan, Omar N. Demerdash, Blake A. Simmons, Seema Singh, Michelle K. Kidder and Jeremy C. Smith

ACS Omega, 2024, 9, 19548
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ConvPred: A deep learning‐based framework for predictions of potential organic reactions

Wenlong Wang, Qilei Liu, Yachao Dong, Jian Du, Qingwei Meng and Lei Zhang

AIChE Journal, 2023, 69
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Prediction on Air–Nasal Mucus Partition Coefficients of Odor Compounds

Junwei Shen, Yuki Harada and Shinichiro Nakamura

ACS Omega, 2024, 9, 31328
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Molecular-based artificial neural network for predicting the electrical conductivity of deep eutectic solvents

Abir Boublia, Tarek Lemaoui, Farah Abu Hatab, Ahmad S. Darwish, Fawzi Banat, Yacine Benguerba and Inas M. AlNashef

Journal of Molecular Liquids, 2022, 366, 120225
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Developing deep learning-based large-scale organic reaction classification model via sigma-profiles

Wenlong Wang, Chenyang Xu, Jian Du and Lei Zhang

Green Chemical Engineering, 2025, 6, 181
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Current Practices and Continuing Needs in Thermophysical Properties for the Chemical Industry

Sumnesh Gupta, J. Richard Elliott, Andrzej Anderko, Jacob Crosthwaite, Walter G. Chapman and Carl T. Lira

Ind. Eng. Chem. Res., 2023, 62, 3394
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Deep learning model based on Bayesian optimization for predicting the infinite dilution activity coefficients of ionic liquid-solute systems

Dingchao Fan, Wenguang Zhu, Yusen Chen, Ke Xue, Tianxiong Liu, Peizhe Cui, Jianguang Qi, Zhaoyou Zhu and Yinglong Wang

Engineering Applications of Artificial Intelligence, 2023, 126, 107127
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Unveiling CO2 capture in tailorable green neoteric solvents: An ensemble learning approach informed by quantum chemistry

Reza Soleimani and Amir Hossein Saeedi Dehaghani

Journal of Environmental Management, 2024, 354, 120298
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Leveraging spatial charge descriptor in deep learning models: Toward highly accurate prediction of vapor-liquid equilibrium

Hsiu-Min Hung and Ying-Chieh Hung

Journal of the Taiwan Institute of Chemical Engineers, 2025, 171, 106054
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Rational design of deep eutectic solvents for the stabilization of dehydrogenases: an artificial neural network prediction approach

Mia Radović, Ana Jurinjak Tušek, Tamara Reiter, Wolfgang Kroutil, Marina Cvjetko Bubalo and Ivana Radojčić Redovniković

Front. Chem., 2024, 12
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Modeling the toxicity of ionic liquids based on deep learning method

Dingchao Fan, Ke Xue, Yangyang Liu, Wenguang Zhu, Yusen Chen, Peizhe Cui, Shiqin Sun, Jianguang Qi, Zhaoyou Zhu and Yinglong Wang

Computers & Chemical Engineering, 2023, 176, 108293
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Roadmap for integrating deep eutectic solvents into adsorption processes: A critical review & design blueprint

Ghaiath Almustafa, Rawan Abu Alwan, Ho Kyong Shon, Jorge Rodríguez and Inas AlNashef

Progress in Materials Science, 2025, 154, 101501
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Mapping the Flammability Space of Sustainable Refrigerant Mixtures through an Artificial Neural Network Based on Molecular Descriptors

Carlos G. Albà, Ismail I. I. Alkhatib, Lourdes F. Vega and Fèlix Llovell

ACS Sustainable Chem. Eng., 2024, 12, 11561
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Deep Eutectic Solvents for Biodiesel Purification in a Microextractor: Solvent Preparation, Selection and Process Optimization

Sara Anđelović, Marko Božinović, Željka Ćurić, Anita Šalić, Ana Jurinjak Tušek, Kristina Zagajski Kučan, Marko Rogošić, Mia Radović, Marina Cvjetko Bubalo and Bruno Zelić

Bioengineering, 2022, 9, 665
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Remediation of cationic dye from aqueous solution through adsorption utilizing natural Haloxylon salicornicum: An integrated experimental, physical statistics and molecular modeling investigation

Samiya Telli, Houria Ghodbane, Maroua Nessaibia, Ramzi Jalgham, Abir Boublia, Yacine Benguerba, Louiza Ouksel, Naima Maouche and Mohamed Khalfaoui

Journal of Molecular Liquids, 2024, 411, 125777
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Exploration of extracting ethyl lactate from aqueous solution using alkyl alcohols: Combination of experiment and mechanism analysis

Houchun Yan, He Ma, Xuqiang Li, Tao Li, Wenxue Lu and Qingsong Li

Journal of Molecular Liquids, 2025, 433, 127928
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Quantum Chemistry-Driven Machine Learning Approach for the Prediction of the Surface Tension and Speed of Sound in Ionic Liquids

Mood Mohan, Micholas Dean Smith, Omar N. Demerdash, Blake A. Simmons, Seema Singh, Michelle K. Kidder and Jeremy C. Smith

ACS Sustainable Chem. Eng., 2023, 11, 7809
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An Overview of Computer‐aided Molecular and Process Design

Ashfaq Iftakher, Mohammed Sadaf Monjur and M. M. Faruque Hasan

Chemie Ingenieur Technik, 2023, 95, 315
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High-throughput screening of 2,500 ionic liquids for sustainable furfural recovery: Bridging quantum simulations, machine learning, and experimental validation

Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef and Fawzi Banat

Chemical Engineering Journal, 2024, 496, 153965
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Quantum Chemical and Experimental Insight into Structure, Physicochemical Properties and Dissolving Behavior of Deep Eutectic Solvents

Yuling Zhang, Hongwei Ren, Yize Liu, Meiyu Li, Adnan Hameed Rasheed, Hajar Alias and Erhong Duan

J. Comput. Biophys. Chem., 2022, 21, 883
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Reaction Thermochemistry for Carbon Dioxide Absorption by Aprotic N-Heterocyclic Anion Ionic Liquids

Austin N. Keller, Pranav J. Thacker, Michael Baldea, Mark A. Stadtherr and Joan F. Brennecke

ACS Sustainable Chem. Eng., 2024, 12, 13634
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Multitask Neural Network for Mapping the Glass Transition and Melting Temperature Space of Homo- and Co-Polyhydroxyalkanoates Using σProfiles Molecular Inputs

Abir Boublia, Tarek Lemaoui, Jawaher AlYammahi, Ahmad S. Darwish, Akil Ahmad, Manawwer Alam, Fawzi Banat, Yacine Benguerba and Inas M. AlNashef

ACS Sustainable Chem. Eng., 2023, 11, 208
DOI: 10.1021/acssuschemeng.2c05225