3.1.1. Physical/Mechanical Processes

Physical/mechanical processes refer to processes that change the physical properties of the biomass, such as reduction of the size of the biomass material or separating biomass feedstock components without changing the state/composition. These processes are usually applied as pre-treatments in the early stages of a biorefinery to process the biomass feedstock into appropriate size ranges for subsequent conversion processes. Note that size reduction technologies refer to the physical treatment of biomass feedstock that includes cutting or commuting processes that result in changing of particle size, shape, and bulk density of the biomass. On the other hand, separation processes are used to separate the bulk biomass feedstock into its constituent components. Extraction methods can also be utilized as physical/mechanical processes to isolate valuable compounds from a bulk and inhomogeneous substrate [78].

#### 3.1.2. Thermochemical Processes

Thermochemical processes are generally referred to as the decomposition of biomass into smaller molecules via thermal energy (i.e., gasification and pyrolysis, etc.). Gasification is a process that partially oxidizes biomass into syngas by keeping the biomass at a high temperature (above 700 ◦C) [79]. Syngas is a gaseous mixture primarily consisting of carbon dioxide, carbon monoxide, hydrogen, methane, and water. It can be used directly as a stationary fuel or further converted into important intermediates such as methanol, ammonia, and oxyalcohols. Pyrolysis is a process that converts biomass into bio-oil, solid charcoal, and light gases similar to syngas in the absence of oxygen [80] and can generally be categorized as fast or slow pyrolysis. Fast pyrolysis normally operates at high heating rates with short vapor residence time (ranging from a few seconds to a few minutes) in the absence of oxygen. The typical operating temperature for fast pyrolysis is around 500 ◦C. Meanwhile, slow pyrolysis operates at a lower heating rate, longer vapor residence time, and a lower operating temperature at around 400 ◦C. According to Brownsort [81], bio-oil and charcoal are the main products of fast pyrolysis and slow pyrolysis, respectively. Additionally, direct combustion is another type of thermochemical conversion process. Direct combustion of biomass involves the burning of biomass in an oxygen-rich environment to produce heat [82]. According to Demirbas [83], liquefaction of biomass into heavy oil is also considered a thermochemical process. In this process, biomass is reacted with carbon monoxide/hydrogen in the presence of sodium carbonate to form heavy oil.

#### 3.1.3. Chemical Processes

Chemical processes refer to processes that change the chemical structure of biomass molecules at high temperature and pressure. Most of the time these chemical processes occur in the presence of a catalyst. Although chemical processes include a wide class of chemical reactions, the most common chemical processes to convert biomass into value-added products are hydrolysis and transesterification [76]. The hydrolysis process utilizes acids, alkalis, or enzymes to decompose molecules with complex molecular structures such as polysaccharides and proteins into their component sugars or derivative chemicals [84]. For example, hydrolysis depolymerizes cellulose into glucose while the derivative compound, levulinic acid can then be obtained from the resulting glucose. Transesterification is a chemical process that converts vegetable oils into biodiesel such as methyl esters and ethyl esters of fatty acids [85]. Fischer-Tropsch (FT) synthesis, steam reforming, and methanization are other common chemical processes for converting biomass into bio-chemicals.

#### 3.1.4. Biochemical/Biological Processes

Biochemical/biological processes utilize biological enzymes or living organisms as biological catalysts to transform biomass into a commodity and specialty bio-chemicals. Compared to thermochemical and chemical processes which involve high temperatures and pressures, biochemical processes normally occur at lower temperatures and thus results in lower reaction rates [76]. Some established biochemical processes are anaerobic digestion and fermentation. Anaerobic digestion utilizes bacteria for the breakdown of biodegradable organic material in the absence of oxygen at a mild temperature (30–65 ◦C). The main product of anaerobic digestion is biogas, which is a mixture of methane, carbon dioxide, hydrogen sulfide, water, and other impurities. According to Romano and Zhang [86], the product biogas can be purified into more than 97% methane via different technologies (e.g., pressure swing adsorption, membrane, etc.), which can serve as a natural gas substitute. On the other hand, in the fermentation processes, the fermentable substrate is converted into different products such as alcohols or organic acids via enzymes or microorganisms [87].

#### *3.2. Synthesis and Design of Integrated Biorefineries*

To synthesize a sustainable integrated biorefinery with maximum performance and minimum environmental impact, it is essential to integrate different conversion technologies in a systematic and efficient manner. Process synthesis methods developed for conventional chemical processes can be extended to enable the synthesis of integrated biorefineries. Process synthesis is defined as the activity to identify the optimal interconnection of unit operations involved in the overall process and the optimal design and configuration of the units within the process [88]. According to Douglas [89], process synthesis can generally be classified into seven categories, i.e., synthesis of reaction pathway, synthesis of reactor network, synthesis of separation network, synthesis of mass exchange network, synthesis of material, synthesis of heat exchanger network, and synthesis of the complete flowsheet.

According to Kokossis and Yang [90], PSE approaches have the potential to support process synthesis and design, which can be applied and utilized in the design of integrated biorefineries. PSE is the field that covers the actions and activities involved in the engineering of systems consist of physical, chemical, and/or biological processing operations [91]. Throughout the years, various PSE approaches have been developed for the synthesis and design of integrated biorefineries [7,8,92], each with its own advantages and disadvantages. Some of the commonly used approaches are presented below.

#### 3.2.1. Hierarchical Approaches

According to Douglas [93], hierarchical approaches use a series of decision-making processes and short-cut models at different hierarchical levels/stages for solving process synthesis problems. These approaches emphasize the decomposition of the problem and the screening of alternatives to identify the solution. According to Li and Kraslawski [94], hierarchical approaches generally offer a quick solution for process synthesis problems, however, they are not able to guarantee an optimal solution as they employ a sequential decomposition strategy. Ng et al. [95] proposed a hierarchical approach to synthesis and analysis of integrated biorefineries based on the Forward-Reverse Synthesis Tree concept. The proposed approach is a sequence of interlinked activities that utilize an appropriate level of information for the initial design. Later, Conde-Mejía et al. [96] applied a hierarchical design approach for the selection of processing routes in biorefinery facilities. Most recently, Tey et al. [97] further extended the developed hierarchical approach (commonly known as "Douglas' hierarchical approach") to the synthesis of an integrated biorefinery with consideration of the pretreatment system.

#### 3.2.2. Heuristic Searches

According to Stephanopoulos and Westerberg [98], heuristic searches utilize engineering expertise to generate solutions for process synthesis problems. The first step is to identify a suitable base case design. This is followed by subsequent modification and fine-tuning to enhance the overall process performance. While heuristic searches are effective in providing feasible solutions for process synthesis problems, it is difficult for such methods to guarantee an optimal solution [99]. A heuristic framework for debottlenecking of a palm oil-based integrated biorefinery was presented by Kasivisvanathan et al. [100].

#### 3.2.3. Insight-Based Approaches

Insight-based approaches such as pinch analysis, ternary diagrams, distillation residue curve maps, etc. have been developed for various applications in process flow sheeting. For example, Tay et al. [8] presented a graphical synthesis approach based on a carbon-hydrogen-oxygen ternary diagram, which enables tracking the change of atomic components within the process. Patel [101] presented a thermodynamic targeting approach based on Van Krevelen diagrams and energy balances for screening, evaluating, and comparing various biomass conversion processes. According to Voll [10], insight-based approaches enable visualization of process synthesis problems, however, employing such approaches in solving complicated process synthesis problems is prone to be restricted by the limited number of parameters and variables that can be considered.

#### 3.2.4. Algorithmic Approaches

Examples of algorithmic approaches include the process graph (P-graph) method. According to Oppenheim [102], algorithmic approaches execute a sequential set of actions based on automated reasoning, calculation, and data processing to determine solutions to process synthesis problems. Benjamin et al. [103] utilized the P-graph approach to generate alternative processes for an integrated biorefinery. As these approaches involve search space reduction, they are powerful and reliable to solve process synthesis problems related to process network synthesis, and often provide quick alternative solutions. However, algorithmic approaches are less flexible when applied to complicated process synthesis problems compared to mathematical optimization approaches [104]. Most recently, Yeo et al. [105] applied a graph-theoretic method to synthesize a sustainable biorefinery for the palm oil industry with optimum resources, which include fertilizer, steam, and electricity generation.

#### 3.2.5. Mathematical Optimization Approaches

According to Grossmann [106], various mathematical optimization models (i.e., linear programming, mixed-integer linear programming, nonlinear programming, and mixed-integer nonlinear programming models) can be formulated to solve process synthesis problems. The models are then solved using different optimization techniques and/or commercial optimization software. Depending on the required information and the complexity/nature of the process synthesis problem, a range of mathematical programming models can be developed and solved to identify optimal solutions for various objectives. Bao et al. [107] presented a superstructure-based shortcut approach to track the feedstock to final products via chemical species for the synthesis of integrated biorefineries. Pham and El-Halwagi [108] presented a mathematical optimization model for integrated biorefineries based on the backward and forward synthesis concept. Later, various mathematical optimization models based on superstructure approaches have been developed for different configurations of integrated biorefineries; e.g., palm-based biorefinery [109], fast pyrolysis-gasification for production of liquid fuels and propylene [110], microalgal biorefinery [111], cyanobacteria biorefinery [112], seaweed-based biorefinery [113], etc. To further enhance the process performance in an integrated biorefinery, efforts have been devoted to the consideration of simultaneous reactor modeling, heating/cooling and work [114], simultaneous process synthesis, heat and power integration [115], production of biodiesel, hydrogen, and synthesis gas integrated with CHP [116], total site analysis [117]. Some studies have focused on retrofitting existing processes and integrating biorefinery technologies with such production facilities (e.g., palm oil industry [118], sago industry [119,120], pulp, and paper industry [121], etc.).

Additionally, many other alternative mathematical optimization methods such as value analysis [122], decomposition approach [9], disjunctive programming [123], modular optimization approach [124], fuzzy optimization [8,125], robust optimization [126], Monte Carlo type sampling [127], flexibility optimization [128], multi-objective optimization based on a genetic algorithm [129], multi-objective target-oriented robust optimization [130], etc. have been applied in synthesis and analysis of integrated biorefineries. Martín and Grossmann [131] reviewed alternative mathematical programming techniques for the design of sustainable biorefineries for the production of biofuels from different raw materials. While mathematical optimization approaches are useful and effective in solving process synthesis/design problems, such approaches may require intensive computational effort when rigorous process modeling is required [132].

#### 3.2.6. Hybrid Methods

Hybrid methods that combine insights-based and mathematical optimization approaches have been developed to take advantage of the specific strengths of both approaches. An automated targeting method was developed to integrate the cascade approach into a mathematical optimization environment [133–135] for the synthesis of resource conservation networks. Ng [136] further developed the automated targeting method for the synthesis of integrated biorefineries by tracking carbon content from raw material (biomass) to final products. Tay and Ng [137] further extended the approach into a multiple-cascade automated targeting method for the synthesis of gasification based integrated biorefineries, where syngas composition is used as the quality measure of the gasification process. Finally, Shabbir et al. [138] combined a superstructure optimization approach with the automated targeting approach for the synthesis of integrated biorefineries with maximum economic performance and minimal environmental impact.

#### *3.3. Challenges in Designing Integrated Biorefineries*

While integrated biorefineries provide advantages as discussed in earlier sections, it should be noted that the unique features of integrated biorefineries make them less straightforward compared to conventional chemical processes. Due to the complex structure and varying compositions of biomass, the important thermodynamic properties (e.g., enthalpy, entropy, heat capacity, etc.) of biomass are often not well established. Besides, the rate of reaction for biomass conversion technologies such as fermentation, hydrolysis, etc. are difficult to determine accurately most of the time. Therefore, most of the available contributions in process synthesis for chemical processes cannot be directly applied for the synthesis of integrated biorefineries. Therefore, it is essential to develop systematic procedures to address the abovementioned issues. In order to synthesize and design a sustainable integrated biorefinery, the following criteria shall be fulfilled [139,140]:


Identifying new potential product molecules from a given biomass feedstock can be achieved through reaction pathway approaches. Andiappan et al. [141] presented a reaction pathway synthesis approach for integrated biorefineries with consideration of economic, energy assessment, and environmental impact in terms of incremental burden. Most recently, Tey et al. [142] further extended the chemical reaction pathway map to synthesize a sustainable integrated biorefinery for the production of fine chemicals from palm-based biomass. Additionally, Madenoor Ramapriya et al. (2018) extended the usage of the superstructure approach for integrated biorefineries synthesis with consideration of complex reaction networks. Similarly, Filho et al. [143] presented an integrated biorefinery for bioethanol production with an analysis of the molecular transformations.

Design of integrated biorefineries requires the ability to handle process/market uncertainties while maintaining the process performance. Tang et al. [144] presented a superstructure optimization approach for the synthesis of integrated biorefineries with consideration of biomass feedstock, value-added products, trenda of market price, constraints of technology, and system uncertainties at multi-periods. Later, Tay et al. [145] presented a mathematical optimization model for the synthesis of integrated biorefineries with supply and demand uncertainties based on a robust optimization approach. Moreover, a framework that uses a superstructure-based process synthesis approach integrated with uncertainty analysis was developed to consider price effects on the design of an integrated biorefinery [146]. To address the effect of changing biomass type and composition in a multi-product biorefinery, Giuliano et al. [147] presented a MINLP to synthesize an integrated biorefinery that converts lignocellulosic biomass into levulinic acid, succinic acid, and ethanol. Meanwhile, Cuˇ ˇ cek et al. [148] developed a multi-period optimization approach for a heat-integrated biorefinery's supply network with maximum economic performance. Additionally, the biomass supply chain also impacts the overall performance of the integrated biorefinery. In order to address such uncertainties, a two-stage optimization approach (macro- and micro-stage) has been presented. The micro-stage involves waste (biomass, industrial waste, etc.) optimization and allocation, as well as the design of the integrated biorefinery, while the macro-stage focuses on supply chain network synthesis and optimization. Various review papers on biomass supply chains covering different aspects (e.g., uncertainties and sustainability [149]; value chain optimization [150]; economic, social and environmental perspectives [151]; design and management [152]; modeling and optimization [153]; techno-economic modeling and optimization [154] have been presented in the literature. Stewart and El-Halwagi [155] provided a detailed review and analysis of the integration of biorefinery innovations into existing processes. This book also covers the application of PSE tools in various stages of the design of such processes, biorefinery products, supply chains, policies, and environmental impacts. Most recently, Lo et al. [156] provided a state-of-the-art review of techno-economic analysis for biomass supply chains.

In addition to the synthesis of independent integrated biorefineries and supply chain networks, the synthesis of industrial symbiosis for bioenergy networks has also received much interest from the research community. Ng et al. [157] developed a superstructure model for the synthesis of palm-based biorefineries, which considers multiple owners in an industrial symbiosis network. Later, Ng et al. [158] presented a superstructure-based disjunctive fuzzy optimization approach for planning and synthesis of industrial symbiosis in bioenergy systems. More recently, Barla et al. [159] applied circular economy concepts in the design of a textile waste biorefinery.

#### **4. Application of Molecular Design within the Context of Integrated Biorefineries**

As presented in the previous section, the products produced from integrated biorefineries are generally classified into two major categories of chemical/material products and energy products [76]. Examples of energy products include biogas, bio-oil, biodiesel, etc. which are products that are utilized based on their energy content. These products are commonly used for the generation of heat, electricity, and energy for different electrification and transportation purposes. On the other hand, chemical/material products are often utilized based on different functionalities given by their physical and chemical properties. Carbohydrates are identified as one of the commonly utilized biomass feedstocks for the production of commodity chemicals and specialty chemicals [72]. According to Lichtenthaler and Mondel [160], the primary form of carbohydrates is in the form of polysaccharides (which are also known as starch). Traditionally, starch (polysaccharide) and its derivative D-glucose (monosaccharide) have been greatly utilized as raw material to produce commodity chemicals and polymers by chemical industries [161]. As starch is an important food resource, utilization of starch to produce chemical products has raised a lot of concerns from the community on the competition of starch utilization between food and industrial applications. For this reason, the utilization of lignocellulosic biomass to produce biochemical products has been receiving focus and attraction as lignocellulosic biomass is mostly plant-based waste in different forms [72]. According to Wyman [162], lignocellulosic biomass is made up of primarily cellulose, hemicellulose, and lignin. Lignocellulosic biomass can be converted into different value-added products via different conversion technologies. Moreover, lignocellulosic biomass can be converted into different intermediate products with a high content of hydroxyl groups through the liquefaction process [163].

In view of the possibility of lignocellulosic biomass conversion into different value-added chemical products, extensive effort has been invested by industrial and research sectors to identify these value-added chemical products. Elliott [164] conducted a study on potential chemical products that can be produced from biomass, based on different biomass conversion. According to Elliot [164], the potential chemical products can be commonly classified into fermentation products, gasification products, catalytic/bioprocessing products, derivatives of carbohydrates, and derivatives of plants. Later, findings on the identification of twelve chemical building blocks that are possible to be converted from starch through different processing technologies are presented by Werpy and Peterson [165]. There exists a potential for these twelve building blocks to be further converted into new families of useful chemical molecules. Hence, these twelve building blocks provide the

potential to be utilized to produce different bio-based chemical products that fulfill market needs. In addition, Holladay et al. [166] presented their study on the potential of lignin recovery to produce macromolecules, aromatics, and miscellaneous monomers. These potential products include different fuel additives, adhesives, carbon fiber, etc. Skibar et al. [167] emphasized the future of biomass through their discussion on the efforts of the chemical industry in utilizing biomass to produce value-added products. In addition to the traditional usage of biomass to produce polymers, the future of biomass lies in the production of specialty products as biomass has the potential to be utilized in producing specialty chemicals such as pharmaceutical, beauty, and personal care products [167]. From the works discussed above, it is obvious that the future of biomass utilization covers the production of energy products, bulk chemical products, and new and novel products such as fine and specialty chemical products. In most cases, such products are designed to satisfy product needs [168]. Thus, the product design aspects have to be taken into account while synthesizing an optimally integrated biorefinery to make sure that the products produced by integrated biorefinery meet the required product needs. This goal can be fulfilled by integrating the synthesis of integrated biorefineries with chemical product design.

Chemical product design problems are suitable to be explained as a process to search for chemical products that fulfill preferred product needs. Traditionally, the product designers first hypothesize a target molecule that has the preferred product needs while designing a chemical product. The subsequent step would be the product synthesis step, which is followed soon by the product testing step to test for the preferred product needs. Target molecule revision and redesign are required repeated if the target molecule does not satisfy the preferred product needs. Hence, it can be seen that the traditional approaches of chemical product design require an iterative process, which leads them to being inefficient, laborious, and low in cost-effectiveness [169]. In light of these limitations, CAMD techniques provide efficient and effective options for the design of chemical products.

In the past decades, CAMD techniques have been gaining attraction and appeared as reliable techniques for their capability in identifying feasible molecules that possess the desired set of product needs [170]. This includes the integration of CAMD techniques with process synthesis for the consideration of product design aspects while synthesizing integrated biorefineries. Hechinger et al. (2010) [171] prosed an integrated approach to the design of biofuels by combining product and process design aspects. The presented study designs biofuels in terms of their molecular structure by using CAMD techniques and identify alternative conversion pathways for the production of biofuels by applying reaction network flux analysis. Ng et al. b [172] proposed an integrated optimization approach for the design of optimal chemical products and synthesis of optimal biomass processing pathways in integrated biorefineries. The optimal biochemical products are designed using CAMD techniques while optimum biomass processing pathways are identified through the developed mathematical superstructure optimization approach. Later, Ng et al. b [173] extended the integrated optimization approach for the design of optimal mixture and synthesis of optimal processing pathways in an integrated biorefinery. Later, Bertran et al. [174] presented two special tools which include a database that employs specially developed knowledge to represent the processing system, and Super-O, which is a software with a practical user interface to guide users for the synthesis of molecular product and integrated biorefinery.

#### *4.1. Integrated Tools for Ionic Liquid Design within Integrated Biorefineries*

The availability of huge data libraries and property prediction models along with the general improvements in computational tools has enabled the application of ionic liquids in the chemical process industry. One of the early applications of the CAMD approach for an integrated process is the design of ionic liquid via the CAMD approach for the purification of bioethanol [175]. CAMD is used to design ionic liquids that can be used to produce 99% pure ethanol from bioethanol with an ethanol concentration of 85%. Various GC models have been used to predict the properties and activity coefficients required to estimate/predict vapor-liquid equilibria.

An extended CAMD approach for carbon capture was developed by Chong et al. [176] to model task-specific ionic liquids. In this work, optimal ionic liquid candidates and conditions for the carbon capture process were determined simultaneously by considering the effect of process conditions as part of the developed approach. To reduce the search space, continuous variables of operating conditions are discretized by introducing disjunctive programming. The thermophysical properties of ionic liquids are predicted using an extended UNIFAC model. To ensure the feasibility of the synthesized ionic liquids, appropriate structural constraints, including cation-anion pairing constraints are included in the design.

In another effort, optimal ionic liquid candidates were screened using the COSMO-RS model, absorption mechanisms, and experimental data for the decarbonization of shale gas [177]. In addition to the Henry's constant, viscosity and toxicity of the ionic liquids are considered in the screening of candidates. Thermodynamic property models, physicochemical properties, and phase equilibria related to the decarbonization process were established. The new ionic liquid-based decarbonization technology was then evaluated by process simulation. Simulations confirmed that the use of ionic liquid requires less energy than the conventional methyl diethanolamine (MDEA) process for CO2 capture.

Chong et al. [178] presented a comprehensive study, where the ionic liquid design was integrated with the entire bioenergy production system that produces multiple energy products from biomass. In this work, ionic liquid is used to remove CO2 from a bioenergy production plant. This process is a bioenergy with carbon capture and storage (BECCS) system. Since the production of bioenergy is considered to be carbon neutral, the CO2 removal and storage make this a negative emission process. One of the challenges in this design was identifying the optimal conditions for bioenergy production and for CO2 removal. Therefore, the bioenergy production system was retrofitted to provide utilities for the carbon capture system.

Liu et al. [179] applied a CAMD approach to screen and predict ionic liquid candidates for shale gas separation. In this work, an extensive ionic liquid-database was established for various gas-ionic liquid systems which consisted of the solubility data of gases in several ionic liquids. Henry's law constants have also been established for several combinations of gases and ionic liquids. A corrected COSMO-RS model was developed to generate pseudo-experimental data after validation to model the systems for which no experimental data were available. A UNIFAC-IL method was established to predict the solubility of shale gas components in ionic liquids. The model showed good agreement between the predictions and experimental solubility data.

Ionic liquids have also been introduced as suitable solvents for the recovery of bioisoprene, which is a promising alternative to petroleum-derived isoprene [180]. In this work, CAILD and UNIFAC-IL models are applied for the thermodynamic calculations and GC based methods are used for the prediction of physical properties. The thermodynamic behavior of the bioisoprene systems involving ionic liquids was described using the extended UNIFAC-IL model that combines gas-organic chemicals using extensive experimental data from literature and pseudo-experimental data from COSMO-RS calculations. The final verification of the process improvements with the designed ionic liquid has been performed via a detailed simulation of the process.

To design ionic liquid for absorbents, the Absorption-Selectivity-Desorption index (ASDI) has been integrated with CAMD tools for ionic liquid design [181]. Thermodynamic properties of ionic liquids are predicted by the COSMO-GC-IL integrated with the COSMO-SAC model. The ionic liquid design was formulated as an optimization problem where the rest of the physical properties were modeled using GC models. A case study has been performed on sour gas absorption in a syngas production process. The integrated ASDI was shown to be capable of determining promising ionic liquid absorbents that can meet the thermodynamic property targets while maintaining low energy consumption for the process.

#### *4.2. Opportunities for Further Research*

#### 4.2.1. Expanding the Optimization Scope/Parameters for Integrated Biorefinery Design

The above-detailed review of existing synthesis/optimization approaches for integrated biorefineries has discussed various approaches ranging from insights-based approaches to complex mathematical optimization models. The developed approaches can address steady-state processes, batch processes, as well as process and market uncertainties. In order to incorporate a sustainable integrated biorefinery, global life cycle optimization ought to be applied during the synthesis stage. The Life Cycle Optimization approach [182] can be extended for concurrent synthesis and optimization of sustainable integrated biorefineries with consideration of economic, environmental, and societal factors/impacts. It is noted that most of the above-mentioned methods focus on technical feasibility, environmental sustainability, market uncertainties, etc. However, there is limited consideration of societal impacts during the design/development of the integrated biorefinery. Therefore, society impacts should be taken into consideration in future efforts.

It should also be noted that a lot of research and development activities are moving towards human-centered design approaches; which is an approach to problem-solving that incorporates the human perspective in all steps. Human-centered design [183] is generally applied in design and management frameworks to solve problems with developed solutions. In order to consider human perspectives in the synthesis and analysis of integrated biorefineries, integration of the human-centered design methodology into PSE approaches would need to be developed.

#### 4.2.2. Design of Novel Ionic Liquids

As discussed in earlier sections, most property prediction models are only applicable for commonly studied ionic liquids such as pyrrolidinium-, ammonium-, imidazolium-, phosphonium- and pyridinium-based ionic liquids, which hinder the discovery of potential new ionic liquids using CAMD tools. Future directions should focus on developing property prediction models that are able to estimate properties for a wider range of pure ionic liquids and/or ionic liquid mixtures. This shortcoming may be addressed by predicting properties of ionic liquids based on functional groups rather than ionic liquid constituents. Accurate correlation equations are key to ensuring that the results generated by process/product design methods/tools are reliable. In addition, there are several works conducted on the effect of solvents on reaction rates. However, no such studies have been conducted on the influence of ionic liquid solvents on reactions. Therefore, it is worth exploring the application of quantum mechanical calculations to predict the rate constants of reactions in various ionic liquid media. Another new class of solvents called deep eutectic solvents (DESs) have received much attention in recent years as they are relatively cheap, simple to synthesize, and have good biodegradability [184]. DESs are solvents that comprise both hydrogen bond acceptors and donors. Some researchers have validated their feasibility as entrainers in the separation of azeotropic mixtures through experiments. With the use of DESs as entrainers in the ethanol-water azeotropic system, the relative volatility of the ethanol-water system increased 4.7 times compared to the DES-free system [185]. Despite the potential of these materials, studies on modeling extractive distillation processes using DESs as entrainers remain limited. This may be due to the fact that there is very limited thermophysical property data available, as this particular research field is still relatively new. A general model that requires only critical pressure, temperature, and one reference viscosity point has been developed to predict the viscosities of DESs [186]. However, there is still a need to improve the model accuracy and develop more property prediction models for DESs to facilitate the computational design and/or screening of solvents.

#### **5. Conclusions**

Recent advances in the development of computational PSE tools have enabled the design of ionic liquids and the design of integrated biorefineries. It is imperative that ionic liquids may serve as potential replacements for current organic solvents when considering stringent environmental regulations and the implementation of a clean manufacturing practice. Nevertheless, the process of identifying an optimal ionic liquid through experimentation is a very tedious task as a very large number of possible ionic liquid combinations exist. Various PSE approaches have been developed in order to make an optimal selection of ionic liquids prior to experimental testing. Similarly, numerous research works have been performed to optimize the synthesis and design of sustainable integrated biorefineries with maximum performance and minimal environmental impact. The application of existing PSE tools to these problems had been extremely challenging because of the difficulty in incorporating accurate property prediction tools in the design of ionic liquids and the computational challenges in the design of such a large and complex processing facility. Decomposition-based approaches developed by different researchers have been instrumental in reducing the complexity of these design problems.

**Author Contributions:** Conceptualization, N.G.C. and D.K.S.N.; Methodology, L.Y.N. and J.O.; Software, validation, formal analysis, J.W.C.; Investigation, resources, data curation; N.G.C. and D.K.S.N.; writing- original draft preparation, L.Y.N. and J.O.; Writing—review and editing, M.R.E.; visualization, J.W.C.; supervision, N.G.C. and D.K.S.N.; project administration—N.G.C. and M.R.E.; funding acquisition, N.G.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Ministry of Higher Education, Malaysia, Grant number FRGS/1/2019/TK02/UNIM/02/1.

**Conflicts of Interest:** The authors declare no conflict of interest.
