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References from Applying diverse data-driven paradigms to estimate the density of aqueous solutions of natural amino acid salts. Local targets link to admitted publications; unresolved targets remain external evidence.
Machine learning in carbon capture, utilization, storage, and transportation: a review of applications in greenhouse gas emissions reduction
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Quantitative impacts and patterns of greenhouse gas emission trends: implications for global change and policy
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Techno-economic analysis of acid gas removal from associated and non-associated sour gas using amine blend
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Optimization of hybrid CO2 capture processes
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Greenhouse gas emissions vs CO2 emissions: Comparative analysis of a global carbon tax
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Current status of carbon capture, utilization, and storage technologies in the global economy: A survey of technical assessment
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Recent advances in carbon capture storage and utilisation technologies: a review
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A review on the state-of-the-art and commercial status of carbon capture technologies
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Strategies for mitigating carbon dioxide emissions: advanced carbon capture and storage technologies
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2025 · External reference
A review on the role of carbon capture, utilization and storage (CCUS) in energy transition: An industrial perspective
2025 · External reference
The application of amine-based materials for carbon capture and utilisation: an overarching view
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Research progress of aqueous amine solution for CO2 capture: A review
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A framework for the environmental, health and safety hazard assessment for amine-based post combustion CO2 capture
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Air pollution impacts of amine scrubbing for CO2 capture
2024 · External reference
An energy-efficient cyclic amine system developed for carbon capture from both flue gas and air
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Techno-economic analysis of advanced stripper configurations for post-combustion CO2 capture amine processes
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Ionic liquids promoted transformation of carbon dioxide
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Application of ionic liquids in CO2 capture and conversion: A review
10.1016/j.seppur.2024.130981 · 2025 · External reference
Deep eutectic solvents vs biomass as carbon precursors: To respond to the need of CO2 capture and energy storage system
2024 · External reference
Carbon dioxide capture and its electrochemical reduction study in deep eutectic solvent (DES) via experimental and molecular simulation approaches
10.1016/j.jcou.2022.102349 · 2023 · External reference
An overview on the carbon capture technologies with an approach of green coal production study
2020 · External reference
Post-combustion carbon capture
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Facile and accurate calculation of the density of amino acid salt solutions: a simple and general correlation vs artificial neural networks
10.1021/acs.energyfuels.2c01705 · 2022 · External reference
Generalized viscosity model based on free-volume theory for amino acid salt solutions as green CO2 capture solvents
10.1016/j.molliq.2023.122176 · 2023 · External reference
Facile estimation of viscosity of natural amino acid salt solutions: Empirical models vs artificial intelligence
2023 · External reference
CO2 capture, utilization, and storage using amino acids
10.1002/adsu.202501422 · 2025 · External reference
State-of-the-art of CO2 capture with amino acid salt solutions
10.1515/revce-2020-0012 · 2022 · External reference
Physiochemical properties of several aqueous potassium amino acid salts
10.1021/je700699u · 2008 · External reference
Reactive absorption of carbon dioxide in L-prolinate salt solutions
10.1021/ie501083v · 2014 · External reference
CO2 absorption into aqueous potassium salts of lysine and proline: Density, viscosity and solubility of CO2
10.1016/j.fluid.2015.04.021 · 2015 · External reference
Physicochemical properties of aqueous potassium salts of basic amino acids as absorbents for CO2 capture
10.1021/acs.jced.6b00013 · 2016 · External reference
Solubilities of carbon dioxide and densities of aqueous sodium glycinate solutions before and after CO2 absorption
10.1021/je800672r · 2009 · External reference
Physicochemical properties of aqueous solutions of sodium l-prolinate as an absorbent for CO2 removal
10.1021/je400830w · 2014 · External reference
Selected physical properties of aqueous potassium salt of l-phenylalanine as a solvent for CO2 capture
10.1016/j.cherd.2016.07.015 · 2016 · External reference
Measurement and prediction of density, viscosity and refractive index of aqueous potassium β-alaninate
2015 · External reference
Physical properties of aqueous sodium glycinate solution as an absorbent for carbon dioxide removal
10.1021/je050210x · 2005 · External reference
Application of machine learning techniques to the modeling of solubility of sugar alcohols in ionic liquids
10.1038/s41598-023-39441-7 · 2023 · External reference
Scikit-learn: Machine learning in Python
2011 · External reference
Predicting ship fuel consumption based on LASSO regression
10.1016/j.trd.2017.09.014 · 2018 · External reference
Ridge regression and artificial neural network to predict the thermodynamic properties of alkali metal Rankine cycles for space nuclear power
10.1016/j.enconman.2022.116385 · 2022 · External reference
Insights into the prediction of the liquid density of refrigerant systems by artificial intelligent approaches
10.1038/s41598-024-53007-1 · 2024 · External reference
Artificial neural network approach for investigating the impact of convector design parameters on the heat transfer and total weight of panel radiators
10.1016/j.ijthermalsci.2022.107845 · 2023 · External reference
Modeling heat capacity of ionic liquids using group method of data handling: A hybrid and structure-based approach
10.1016/j.ijheatmasstransfer.2018.09.057 · 2019 · External reference
Application of adaptive neuro-fuzzy inference system in prediction of fluid density for a gamma ray densitometer in petroleum products monitoring
10.1016/j.measurement.2013.07.005 · 2013 · External reference
Least squares support vector machines
2002 · External reference
Smart tracking of the influence of alumina nanoparticles on the thermal coefficient of nanosuspensions: application of LS-SVM methodology
10.1007/s13204-021-01949-7 · 2021 · External reference
Developing a global approach for determining the molar heat capacity of deep eutectic solvents
10.1016/j.measurement.2021.110630 · 2022 · External reference
Random forest models to predict aqueous solubility
10.1021/ci060164k · 2007 · External reference
Formation resistivity prediction using decision tree and random forest
10.1007/s13369-022-06900-8 · 2022 · External reference
Determination of bubble point pressure and oil formation volume factor: Extra trees compared with LSSVM-CSA hybrid and ANFIS models
10.1016/j.fuel.2019.116834 · 2020 · External reference
Modeling hydrogen solubility in hydrocarbons using extreme gradient boosting and equations of state
10.1038/s41598-021-97131-8 · 2021 · External reference
Group contribution methods for estimating CO2 absorption capacities of imidazolium and ammonium-based polyionic liquids
10.1016/j.jclepro.2018.08.127 · 2018 · External reference
Hydrogen solubility in n-alkanes: data mining and modelling with machine learning approach
10.1016/j.ijhydene.2022.08.195 · 2022 · External reference
On the evaluation of the carbon dioxide solubility in polymers using gene expression programming
10.1038/s41598-023-39343-8 · 2023 · External reference