Ionic Liquid Design via Computer-Aided Molecular Design

Computer-aided molecular design (CAMD) approach is proven to be able to design or choose a list of potential substitutes to the commercial organic compounds and their mixtures. More recently, this approach is extended to design potential ionic liquids (ILs) for specific tasks. Matsuda et al. (2007) first presented the design of ILs, using property prediction models for ionic conductivities and viscosities, which are based on quantitative structure property coupled with descriptor of group contribution (GC). Firstly, the value of the target property needed for application is set, and followed by exhaustively searches by calculating ILs properties. These searches are performed by changing cation, anion, and length of side chains attached to cation. The structures of ILs that satisfy target properties value will be determined. Matsuda et al. (2007) also built a Java program specifically to reverse design ILs using the approach presented, but only ionic conductivity and viscosity were considered in this program.

McLeese et al. (2010) applied CAMD approach to design ILs for use within environmentally friendly refrigeration systems. The ILs design problem is formulated as a mixed integer linear programming (MILP) problem. Therefore, the presented approach was claimed to be able to provide optimal results using standard techniques. In the same work, McLeese et al. (2010) also compared the computational efficiency of different algorithms in solving the problem. The group concluded that Tabu Search algorithm is more

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efficient compared to deterministic algorithm for the purpose of generating near-optimal solutions to this design formulation.

Billard et al. (2011) established a quantitative structure property relationship (QSPR) between chemical structure of ILs and their viscosity. The same QSPR model was used to reverse design ILs with targeted viscosity. Billard et al. (2011) also demonstrated in silico design of three new ILs by using the developed QSPR model, prior to synthesis and experimental test. These ILs were synthesised and tested afterwards, the predicted viscosities are in good qualitative agreement with the experimentally measured ones.

Chávez-Islas et al. (2011) then presented mixed integer non-linear programming (MINLP) formulation for optimal design of IL to recover high purity ethanol from ethanol-water system, where IL should feature water affinity to break ethanol-water azeotrope. The presented model considers the mole balances and equilibrium relationships using UNIFAC method. Process restrictions are considered in this work, which are not included by previous works. The results showed that higher purity of ethanol product, higher energy consumption of the distillation process, and hence trade-off between these two contradicting objectives should be included. Therefore, Valencia-marquez et al. (2012) then extended the work by Chávez-Islas et al. (2011) by considering IL design and extractive distillation column design simultaneously.

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Roughton et al. (2012) also proposed to design ILs entrainers and azeotropic separation processes at once. Several of the existing GC models were used, along with a newly developed solubility parameter GC model and UNIFAC-IL model. The UNIFAC-IL model is used to screen design candidates based on minimum IL concentration required to break azeotrope. The extractive distillation column is designed once the IL is chosen, using the driving force method with a new proposed feed stage scaling to minimise energy inputs. This is followed by design of an IL regeneration stage.

Karunanithi and Mehrkesh (2013) presented a general framework that can be applied for computer-aided ILs design. This framework is similar to CAMD approach for organic chemical design; consist of a general mathematical framework of the proposed approach, a set of structural constraints that define feasibility and bonding rules for ILs design, physical properties constraints, and solution properties constraints. Both physical and solution properties of ILs are estimated using GC based approach. The presented framework is suitable for different applications, and few simple case studies were shown, including electrolytes, heat transfer fluids, and separation process. The problems are formulated as MINLP models and solved using decomposition methods and genetic algorithm (GA) based optimisation.

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A computational scheme based on CAMD has been proposed by Harini et al. (2015) to design a task-specific IL for extraction of pharmaceutical immediate. Structural constraints and properties constraints have been defined for this design problem. In this proposed approach, UNIFAC-IL model and GC method were used to estimate properties of ILs. Exhaustive direct search (EDS) approach was employed in this approach to determine the suitable IL for the specific purpose. However, this approach is appropriate when there are only few groups for study, the computational time increases as the number of groups is increased. Any optimisation technique can be employed to replace EDS approach in this proposed methodology. Table 2-1 is included to summarise the work done on IL design using CAMD technique thus far.

Table 2-1: Work done for IL design using CAMD

Year Authors Research work

2007 Matsuda et al. · Designed ILs based on ionic conductivities

and viscosities

· Built a Java program based on the same concept

2010 McLeese et al. · Designed ILs to be used within

environmental-friendly refrigeration system

· Formulated the problem as MILP problem

and solved using standard techniques

· Compared computational efficiency of

different solving algorithms

2011 Billard et al. · Established QSPR between IL structure and

viscosity

· Applied the same QSPR model to present

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Table 2-1 Continued

Chávez-Islas et al. · Designed IL to recover high purity ethanol

from ethanol-water system

· Formulated the problem as MINLP problem

· Considered mole balance, equilibrium

relationship using UNIFAC method, and process restriction

2012 Valencia-marquez

et al.

· Extended the work by Chávez-Islas et al. (2011)

· Considered IL design and extractive distillation column design simultaneously

Roughton et al. · Designed IL entrainers and azeotropic

separation processes simultaneously

· Adapted newly developed solubility

parameter for IL and UNIFAC-IL model

2013 Karunanithi and

Mehrkesh

· Presented a general framework for computer-aided IL design

· Formulated the problem as MINLP problem

and solved using decomposition methods and GA based optimisation

2015 Harini et al. · Proposed computational scheme to design

task-specific IL for extraction of pharmaceutical immediate

· UNIFAC-IL model and GC methods were

used to estimate properties of ILs

· Employed EDS approach to determine

suitable IL

· Appropriate when there are only few groups

for study