Thermodynamic modeling and rational design of ionic liquids for pre-combustion carbon capture

Zhou, Teng; Shi, Huaiwei; Ding, Xuechong; Zhou, Yageng

doi:10.1016/j.ces.2020.116076

Cited by 61 publications

(35 citation statements)

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“…For instance, the solvent regeneration temperature needs to be conducted at a lower temperature than currently used to avoid any reduction in the solvent. Thus, ionic liquids are being utilised to overcome this issue, as they are characterised with their negligible volatility (Zhou et al 2021;Krishnan et al 2020;McDonald et al 2014). On the other hand, selecting the appropriate ionic liquid is not an easy task due to the existence of possible structures from various anion and cation combinations which requires trial and error to find the best separation performance (Lu et al 2019).…”

Section: Pre-combustionmentioning

confidence: 99%

“…For that purpose, computer-aided molecular design (CAMD) is recently being used to find out the best combinations to design ionic liquids structurally. (Zhou et al 2021) have investigated 10116 solubility data along with 463 hydrogen solubility data from the literature of ionic liquids with modelling to find out the best ionic liquids for pre-combustion technology. They found out that the most promising ionic liquid solvents are hydroxyl (OH)-ammonium ( NH 3 ) and hydroxyl-imidazolium ([Tf 2 N ]) bis (trifluoromethyl sulphonyl) amide at 40 • C and 30 bars according to industrial pre-combustion conditions.…”

Section: Pre-combustionmentioning

confidence: 99%

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Recent advances in carbon capture storage and utilisation technologies: a review

et al. 2020

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Human activities have led to a massive increase in $$\hbox {CO}_{2}$$ CO 2 emissions as a primary greenhouse gas that is contributing to climate change with higher than $$1\,^{\circ }\hbox {C}$$ 1 ∘ C global warming than that of the pre-industrial level. We evaluate the three major technologies that are utilised for carbon capture: pre-combustion, post-combustion and oxyfuel combustion. We review the advances in carbon capture, storage and utilisation. We compare carbon uptake technologies with techniques of carbon dioxide separation. Monoethanolamine is the most common carbon sorbent; yet it requires a high regeneration energy of 3.5 GJ per tonne of $$\hbox {CO}_{2}$$ CO 2 . Alternatively, recent advances in sorbent technology reveal novel solvents such as a modulated amine blend with lower regeneration energy of 2.17 GJ per tonne of $$\hbox {CO}_{2}$$ CO 2 . Graphene-type materials show $$\hbox {CO}_{2}$$ CO 2 adsorption capacity of 0.07 mol/g, which is 10 times higher than that of specific types of activated carbon, zeolites and metal–organic frameworks. $$\hbox {CO}_{2}$$ CO 2 geosequestration provides an efficient and long-term strategy for storing the captured $$\hbox {CO}_{2}$$ CO 2 in geological formations with a global storage capacity factor at a Gt-scale within operational timescales. Regarding the utilisation route, currently, the gross global utilisation of $$\hbox {CO}_{2}$$ CO 2 is lower than 200 million tonnes per year, which is roughly negligible compared with the extent of global anthropogenic $$\hbox {CO}_{2}$$ CO 2 emissions, which is higher than 32,000 million tonnes per year. Herein, we review different $$\hbox {CO}_{2}$$ CO 2 utilisation methods such as direct routes, i.e. beverage carbonation, food packaging and oil recovery, chemical industries and fuels. Moreover, we investigated additional $$\hbox {CO}_{2}$$ CO 2 utilisation for base-load power generation, seasonal energy storage, and district cooling and cryogenic direct air $$\hbox {CO}_{2}$$ CO 2 capture using geothermal energy. Through bibliometric mapping, we identified the research gap in the literature within this field which requires future investigations, for instance, designing new and stable ionic liquids, pore size and selectivity of metal–organic frameworks and enhancing the adsorption capacity of novel solvents. Moreover, areas such as techno-economic evaluation of novel solvents, process design and dynamic simulation require further effort as well as research and development before pilot- and commercial-scale trials.

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Section: Pre-combustionmentioning

confidence: 99%

Section: Pre-combustionmentioning

confidence: 99%

Recent advances in carbon capture storage and utilisation technologies: a review

et al. 2020

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“…21,22 In order to make accurate predictions, the involved UNIFAC model parameters for IL systems have been extensively fitted from experimental data. 23,24 This article is protected by copyright. All rights reserved.…”

Section: Introductionmentioning

confidence: 99%

“…Besides, for predicting thermodynamic properties (e.g., activity coefficient and solubility) of IL systems, the nonlinear GC‐based UNIFAC models are often used 21,22 . In order to make accurate predictions, the involved UNIFAC model parameters for IL systems have been extensively fitted from experimental data 23,24 …”

Section: Introductionmentioning

confidence: 99%

Integrated ionic liquid and rate‐based absorption process design for gas separation: Global optimization using hybrid models

et al. 2021

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A new method for integrated ionic liquid (IL) and absorption process design is proposed where a rigorous rate-based process model is used to incorporate absorption thermodynamics and kinetics. Different types of models including group contribution models and thermodynamic models are employed to predict the process-relevant physical, kinetic, and thermodynamic (gas solubility) properties of ILs. Combining the property models with process models, the integrated IL and process design problem is formulated as an MINLP optimization problem. Unfortunately, due to the model complexity, the problem is prone to convergence failure. To lower the computational difficulty, tractable surrogate models are used to replace the complex thermodynamic models while maintaining the prediction accuracy. This provides an opportunity to find the global optimum for the integrated design problem. A pre-combustion carbon capture case study is provided to demonstrate the applicability of the method. The obtained global optimum saves 14.8% cost compared to the Selexol process.

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“…These models are regressed from experimental property data and can provide satisfying predictions on the properties of new ILs that are not used in model training. Such well-established property models have been widely used in the computer-aided molecular design (CAMD) of IL solvents [9][10][11][12][13][14], where optimal ILs possessing desirable properties are identified based on the property Processes 2021, 9, 65 2 of 10 models. Unfortunately, up to now, mathematical models for the toxicity properties of ILs have been explored more scarcely in comparison to other IL properties.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning for Ionic Liquid Toxicity Prediction

2020

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In addition to proper physicochemical properties, low toxicity is also desirable when seeking suitable ionic liquids (ILs) for specific applications. In this context, machine learning (ML) models were developed to predict the IL toxicity in leukemia rat cell line (IPC-81) based on an extended experimental dataset. Following a systematic procedure including framework construction, hyper-parameter optimization, model training, and evaluation, the feedforward neural network (FNN) and support vector machine (SVM) algorithms were adopted to predict the toxicity of ILs directly from their molecular structures. Based on the ML structures optimized by the five-fold cross validation, two ML models were established and evaluated using IL structural descriptors as inputs. It was observed that both models exhibited high predictive accuracy, with the SVM model observed to be slightly better than the FNN model. For the SVM model, the determination coefficients were 0.9289 and 0.9202 for the training and test sets, respectively. The satisfactory predictive performance and generalization ability make our models useful for the computer-aided molecular design (CAMD) of environmentally friendly ILs.

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Thermodynamic modeling and rational design of ionic liquids for pre-combustion carbon capture

Cited by 61 publications

References 50 publications

Recent advances in carbon capture storage and utilisation technologies: a review

Recent advances in carbon capture storage and utilisation technologies: a review

Integrated ionic liquid and rate‐based absorption process design for gas separation: Global optimization using hybrid models

Machine Learning for Ionic Liquid Toxicity Prediction

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