Screening of ionic liquids for the extraction of biologically active compounds using emulsion liquid membrane: COSMO-RS prediction and experiments

New solubility model for solid drugs in pure solvents based on solute-solvent interfacial tension

The solubility of drugs in biological fluids is associated with pharmacokinetic properties (absorption, biotransformation and excretion), efficacy and toxicity. It is a fascinating and challenging task to uncover the intrinsic reason underlying the dissolution behavior of pharmaceuticals. The classical thermodynamic method estimates the drug solubility in liquid solvent via Solid-Liquid Equilibrium (SLE) equation plus activity coefficient models (UNIFAC, COSMO-RS, COSMO-SAC, etc), where the molar dissolution energy (partial molar excess Gibbs energy) of solute molecules in solution is calculated through activity coefficient models. The new method predicts the solute solubility via the transfer free energy (from solid phase to liquid phase) of solute molecules in terms of fusion properties and solute-solvent (liquid-liquid) interfacial tension, where the molar dissolution energy of solute molecules is determined by solute-solvent interfacial tension, and the solute-solvent (liquid-liquid) interfacial tension is obtained from the cohesive energy calculation results of COSMO-UCE (Conductor-Like Screening Model for Universal Cohesive Energy estimation) based merely on the molecular structure. The application of this model in solubility prediction of solid drugs in pure liquid solvents has been verified extensively with successful results. This model yields similar solute solubility representation performance as that of SLE + UNIFAC, and obtains much better solubility prediction results than SLE + COSMO-SAC.

Computational Advances in Ionic Liquid Applications for Green Chemistry: A Critical Review of Lignin Processing and Machine Learning Approaches

The valorization and dissolution of lignin using ionic liquids (ILs) is critical for developing sustainable biorefineries and a circular bioeconomy. This review aims to critically assess the current state of computational and machine learning methods for understanding and optimizing IL-based lignin dissolution and valorization processes reported since 2022. The paper examines various computational approaches, from quantum chemistry to machine learning, highlighting their strengths, limitations, and recent advances in predicting and optimizing lignin-IL interactions. Key themes include the challenges in accurately modeling lignin's complex structure, the development of efficient screening methodologies for ionic liquids to enhance lignin dissolution and valorization processes, and the integration of machine learning with quantum calculations. These computational advances will drive progress in IL-based lignin valorization by providing deeper molecular-level insights and facilitating the rapid screening of novel IL-lignin systems.

Ionic liquid-based dispersive liquid-liquid microextraction of succinic acid from aqueous streams: COSMO-RS screening and experimental verification

In the present investigation, a total of 108 combinations of ionic liquids (ILs) were screened using the conductor-like screening model for real solvents (COSMO-RS) with the aid of six cations and eighteen anions for the extraction of succinic acid (SA) from aqueous streams through dispersive liquid-liquid microextraction (DLLME). Using the screened ILs, an ionic liquid-based DLLME (IL-DLLME) was developed to extract SA and the role of different reaction parameters in the effectiveness of IL-DLLME approach was investigated. COSMO-RS results suggested that, quaternary ammonium and choline cations form effective IL combinations with [OH¯], [F¯], and [SO42¯] anions due to hydrogen bonding. In view of these results, one of the screened ILs, tetramethylammonium hydroxide [TMAm][OH] was chosen as the extractant in IL-DLLME process and acetonitrile was adopted as the dispersive solvent. The highest SA removal efficiency of 97.8% was achieved using 25 μL of IL [TMAm][OH] as a carrier and 500 μL of acetonitrile as dispersive solvent. The highest amount of SA was extracted with a stir time of 20 min at 300 rpm, followed by centrifugation for 5 min at 4500 rpm. Overall, the findings showed that IL-DLLME is efficient in extracting succinic acid from aqueous environments while adhering to the first-order kinetics.

Evaluating ionic liquids for its potential as eco-friendly solvents for naproxen removal from water sources using COSMO-RS: Computational and experimental validation

An emerging contaminant of concern in aqueous streams is naproxen. Due to its poor solubility, non-biodegradability, and pharmaceutically active nature, the separation is challenging. Conventional solvents employed for naproxen are toxic and harmful. Ionic liquids (ILs) have attracted great attention as greener solubilizing and separating agent for various pharmaceuticals. ILs have found extensive usage as solvents in nanotechnological processes involving enzymatic reactions and whole cells. The employment of ILs can enhance the effectiveness and productivity of such bioprocesses. To avoid cumbersome experimental screening, in this study, conductor like screening model for real solvents (COSMO-RS) was used to screen ILs. Thirty anions and eight cations from various families were chosen. Activity coefficient at infinite dilution, capacity, selectivity, performance index, molecular interactions using σ-profiles and interaction energies were used to make predictions about solubility. According to the findings, quaternary ammonium cations, highly electronegative, and food-grade anions will form excellent ionic liquid combinations for solubilizing naproxen and hence will be better separating agents. This research will contribute easy designing of ionic liquid-based separation technologies for naproxen. In different separation technologies, ionic liquids can be employed as extractants, carriers, adsorbents, and absorbents.

New Model to Predict Infinite Dilution Activity Coefficients Based on (∂p/∂x) T,x → 0

Accurate prediction of infinite dilution activity coefficient (γ^∞) is essential for the calculation of phase equilibria, solubility, and related properties in molecular thermodynamics. Here, we propose a new model to accurately predict the value of γ^∞. It is applicable to calculate γ^∞ for compounds in aqueous solution at different temperatures. The model is based on the relationship of (∂p/∂x) _T,x→0 with γ^∞ and temperature at low pressure. First, we introduce the new idea of using the group contribution method to estimate (∂p/∂x) _T,x→0 and then obtain the activity coefficient of a solute at infinite dilution in water based on the relationship between (∂p/∂x) _T,x→0 and γ^∞. The accuracy of this model is verified using experimental data from 46 systems and more than 450 data points. The result shows that the total average relative deviation of the predicted values from the experimental values for training data is 4.73%. Besides, we test the applicability of the model using solutes that are not part of the training data set. The result shows that the model is satisfactory for the prediction of testing data. Compared with other models, the results prove that the developed model outperforms the UNIFAC model, the modified UNIFAC model, and previous predictive models for aqueous systems. The final equation with only simple arithmetic is more easily applied in engineering practices.

Hope-hype of green innovation, corporate governance index, and impact on firm financial performance: a comparative study of Southeast Asian countries

The current production and conception have impacted the environmental hazards. Green innovation (GI) is the ideal solution for sustainable production, consumption, and ecological conservation. The objective of the study is to compare comprehensive green innovation (green product, process, service, and organization) impact on firm financial performance in Malaysia and Indonesia, along with the first study to measure the moderation role of the corporate governance index. This study has addressed the gap by developing the green innovation and corporate governance index. Collected panel data from the top 188 publicly listed firms for 3 years and analyzed it using the general least square method. The empirical evidence demonstrates that the green innovation practice is better in Malaysia, and the outcome also shows that the significance level is higher in Indonesia. This study also provides empirical evidence that board composition has a positive moderation relationship betwixt GI and business performance in Malaysia but is insignificant in Indonesia. This comparative study provides new insights to the policymakers and practitioners of both countries to monitor and manage green innovation practices.

Ionic Liquid-Based Green Emulsion Liquid Membrane for the Extraction of the Poorly Soluble Drug Ibuprofen

Ibuprofen (Ibf) is a biologically active drug (BADs) and an emerging contaminant of concern (CECs) in aqueous streams. Due to its adverse effects upon aquatic organisms and humans, the removal and recovery of Ibf are essential. Usually, conventional solvents are employed for the separation and recovery of ibuprofen. Due to environmental limitations, alternative green extracting agents need to be explored. Ionic liquids (ILs), emerging and greener alternatives, can also serve this purpose. It is essential to explore ILs that are effective for recovering ibuprofen, among millions of ILs. The conductor-like screening model for real solvents (COSMO-RS) is an efficient tool that can be used to screen ILs specifically for ibuprofen extraction. The main objective of this work was to identify the best IL for the extraction of ibuprofen. A total of 152 different cation-anion combinations consisting of eight aromatic and non-aromatic cations and nineteen anions were screened. The evaluation was based upon activity coefficients, capacity, and selectivity values. Furthermore, the effect of alkyl chain length was studied. The results suggest that quaternary ammonium (cation) and sulfate (anion) have better extraction ability for ibuprofen than the other combinations tested. An ionic liquid-based green emulsion liquid membrane (ILGELM) was developed using the selected ionic liquid as the extractant, sunflower oil as the diluent, Span 80 as the surfactant, and NaOH as the stripping agent. Experimental verification was carried out using the ILGELM. The experimental results indicated that the predicted COSMO-RS and the experimental results were in good agreement. The proposed IL-based GELM is highly effective for the removal and recovery of ibuprofen.

Multiscale molecular simulations for the solvation of lignin in ionic liquids

Lignin, the second most abundant biopolymer found in nature, has emerged as a potential source of sustainable fuels, chemicals, and materials. Finding suitable solvents, as well as technologies for efficient and affordable lignin dissolution and depolymerization, are major obstacles in the conversion of lignin to value-added products. Certain ionic liquids (ILs) are capable of dissolving and depolymerizing lignin but designing and developing an effective IL for lignin dissolution remains quite challenging. To address this issue, the COnductor-like Screening MOdel for Real Solvents (COSMO-RS) model was used to screen 5670 ILs by computing logarithmic activity coefficients (ln(γ)) and excess enthalpies (H^E) of lignin, respectively. Based on the COSMO-RS computed thermodynamic properties (ln(γ) and H^E) of lignin, anions such as acetate, methyl carbonate, octanoate, glycinate, alaninate, and lysinate in combination with cations like tetraalkylammonium, tetraalkylphosphonium, and pyridinium are predicted to be suitable solvents for lignin dissolution. The dissolution properties such as interaction energy between anion and cation, viscosity, Hansen solubility parameters, dissociation constants, and Kamlet-Taft parameters of selected ILs were evaluated to assess their propensity for lignin dissolution. Furthermore, molecular dynamics (MD) simulations were performed to understand the structural and dynamic properties of tetrabutylammonium [TBA]⁺-based ILs and lignin mixtures and to shed light on the mechanisms involved in lignin dissolution. MD simulation results suggested [TBA]⁺-based ILs have the potential to dissolve lignin because of their higher contact probability and interaction energies with lignin when compared to cholinium lysinate.

Screening of ionic liquids as green entrainers for ethanol water separation by extractive distillation: COSMO-RS prediction and aspen plus simulation

Ionic liquids (ILs) have been demonstrated as promising alternatives to conventional entrainers in separation of azeotropic mixtures mostly investigating phase equilibrium and process design scenarios. However, proper selection of ILs for a specific task always remains challenging. Hence a simulation tool, i.e. conductor like screening model for real solvents (COSMO-RS) was applied to address this challenge. Furthermore, screened ILs were simulated as entrainers for ethanol water separation by extractive distillation. The current study also aims to demonstrate a systematic approach to retrofit existing processes, by employing ILs as green entrainers. Screening of twenty-five (25) ILs was carried out using COSMO-RS to select suitable ILs as green entrainers based on activity coefficient, capacity and selectivity. Results illustrated that tetramethylammonium chloride ([TMAm][Cl]) due to its strong hydrogen bonding ability was found to be the best ILs entrainer. Moreover, in order to reduce the operating costs without compromising desired product purity (ethanol purity ≥99.5% in top product), the selected ILs (8 kg/h) in a mixture with ethylene glycol (72 kg/h) were simulated using Aspen plus v.11. The simulation results revealed that by combining tetramethylammonium chloride (2 kg/h) with ethylene glycol (78 kg/h) reduced 7.26 tons of CO2 emissions/year through heat integration by saving 1.49*108 kJ/year energy besides minimizing operating costs. In conclusion, the systematic selection of ILs as green entrainers in combination with ethylene glycol and then the appropriate simulation of the whole system will ultimately reduce the cost of the separation process and reduce the emission of greenhouse gases as well utilization of toxic conventional entrainers.

Cross-Linked Ionic Liquid Polymer for the Effective Removal of Ionic Dyes from Aqueous Systems: Investigation of Kinetics and Adsorption Isotherms

In the current study, we have synthesized an imidazolium based cross-linked polymer, namely, 1-vinyl-3-ethylimidazolium bis(trifluoromethylsulfonyl)imide (poly[veim][Tf2N]-TRIM) using trimethylolpropane trimethacrylate as cross linker, and demonstrated its efficiency for the removal of two extensively used ionic dyes—methylene blue and orange-II—from aqueous systems. The detailed characterization of the synthesized poly[veim][Tf2N]-TRIM was performed with the help of 1H NMR, TGA, FT-IR and FE-SEM analysis. The concentration of dyes in aqueous samples before and after the adsorption process was measured using an UV-vis spectrophotometer. The process parameters were optimised, and highest adsorption was obtained at a solution pH of 7.0, adsorbent dosage of 0.75 g/L, contact time of 7 h and dye concentrations of 100 mg/L and 5.0 mg/L for methylene blue and orange-II, respectively. The adsorption kinetics for orange-II and methylene blue were well described by pseudo-first-order and pseudo−second-order models, respectively. Meanwhile, the process of adsorption was best depicted by Langmuir isotherms for both the dyes. The highest monolayer adsorption capacities for methylene blue and orange-II were found to be 1212 mg/g and 126 mg/g, respectively. Overall, the synthesized cross-linked poly[veim][Tf2N]-TRIM effectively removed the selected ionic dyes from aqueous samples and provided >90% of adsorption efficiency after four cycles of adsorption. A possible adsorption mechanism between the synthesised polymeric adsorbent and proposed dyes is presented. It is further suggested that the proposed ionic liquid polymer adsorbent could effectively remove other ionic dyes and pollutants from contaminated aqueous systems.

Vegetable Oil-Ionic Liquid-Based Emulsion Liquid Membrane for the Removal of Lactic Acid from Aqueous Streams: Emulsion Size, Membrane Breakage, and Stability Study

In this study, we present a highly stable vegetable oil ionic liquid (IL)-based emulsion liquid membrane (VOILELM) for the removal of lactic acid from water streams. The system developed as a part of this work comprises a non-ionic surfactant Span 80, sodium hydroxide as an internal stripping agent, sunflower canola oil as a green diluent, and IL-tetramethylammonium acetate [TMAm][Ac]-as a carrier. VOILELM stability was evaluated in terms of breakage, emulsion diameter, and standalone stability. The effect of various parameters, namely, concentration of the surfactant, concentration of the internal stripping agent, concentration of the carrier, phase ratio, homogenizer speed, and homogenization time, on the VOILELM stability was studied. The results revealed that VOILELM was highly stable, with 1.34% minimum breakage, 1.16 μm emulsion diameter, and 131 min standalone stability. The optimal process parameters were 0.1 wt % Span 80, 0.1 M NaOH, 0.3 wt % IL, 0.25 phase ratio, 5000 rpm homogenizer speed, and 5 min homogenization time. At these optimized conditions, 96.08% lactic acid extraction efficiency was achieved. Thus, a highly effective VOILELM was developed, with minimal breakage and emulsion diameter and maximum stability.

Firm Sustainable Development Goals and Firm Financial Performance through the Lens of Green Innovation Practices and Reporting: A Proactive Approach

The current global economy demands synergy between ecological responsiveness and proactive business models. To analyze these dynamics, the objective of this study is to simultaneously investigate the effects of green innovation practices concerning the sustainable development goals (SDG) and financial performance of firms. This study also advocates for the injection of green innovation reporting into sustainable reporting for greater disclosure. Data from sixty-seven companies from five continents and the top five blue chip firms for each country are collected through content analysis, with the generalized least squares (GLS) approach used to test a causal relationship hypothesis. The results indicate mixed findings, with green product innovation showing positive relationships with returns on equity (ROE) and returns on investments (ROI). At the same time, green process innovation shows negative relationships with returns on assets (ROA) but shows a positive impact on returns on investments (ROI) and firm SDGs. In contrast, green service innovation shows an insignificant relationship with financial performance and SDGs. On the other hand, non-operational green innovation variables and green marketing positively affect returns on assets and investment, showing significant negative impacts on returns on equity. However, green organizational innovation shows an insignificant relationship with firm financial performance and SDGs. In addition, this study also shows that the Australia/New Zealand region is the leader in green innovation reporting, followed by Europe, Asia, Africa, and lastly, North America.

The Nexus between Proactive Eco-Innovation and Firm Financial Performance: A Circular Economy Perspective

Eco-innovation has gained considerable attention in the academic and corporate world due to its potential in mitigating a firm’s sustainability issues. Most previous studies focused on the reactive approaches of eco-innovation using primary data. This study mitigates the existing research gap by highlighting proactive eco-innovation and using a secondary panel dataset. The prime objective of this study is to investigate the relationship between proactive eco-innovation and firms’ financial performance. Hence, the study will introduce the proactive eco-innovation index with the help of secondary panel data. In addition to that, the paper will also explore how proactive eco-innovation relates to circular economy. The theory of Resource-Based View (RBV) was used to explain the relationship among the variables. This study was conducted on 31 Malaysian public listed energy companies from 2015 to 2019. A proactive eco-innovation index was inferred by adapting three dimensions of eco-innovation (product, process, and technology) which is applicable for the energy sector. By applying random-effects GLS regression equation modeling, it was found that proactive eco-innovation (product eco-innovation, process eco-innovation, and technology eco-innovation) has a direct effect on firm financial performance. Furthermore, product and process eco-innovation is directly related to a circular economy through a sustainable product development process. The findings suggest that policymakers in the firm should proactively adopt eco-innovative practices. It will positively affect the circular economy as it will be cost-effective and help to reduce potential industrial pollution in the environment.

How to select ionic liquids as extracting agents systematically: a special case study for extractive denitrification processes

Extractive denitrification (EDN) of shale oil using ionic liquids (ILs) as the extracting agent has good industrial prospects.

Firm’s Sustainability and Societal Development from the Lens of Fishbone Eco-Innovation: A Moderating Role of ISO 14001-2015 Environmental Management System

Eco-innovation has gained considerable attention in academia as well as in industry due to its potential in mitigating environmental challenges and its positive correlation with firm performance. However, there are limited studies which have investigated the moderating relation of International Organization for Standardization (ISO) 14001:2015 between eco-innovation and firm sustainability in their contribution to societal development. This research is supported by a resource-based theory which explores the core-competencies of firms and challenges the resources creating the competitive advantage of the firm without compromising on the social responsibility aspect of the firm. This study proposes a fishbone eco-innovation business model, which includes production (product, process, and technology) and non-production (organization and marketing) business activities mapped with the 17 Sustainable Development Goals (SDGs) for societal development. This fishbone eco-innovation business model signals to the stakeholders about the organization’s innovation in their green implementation, which goes beyond mere compliance. The contribution of the fishbone eco-innovation business model to societal development will create a unique competitive edge and green goodwill amongst the external stakeholders, which will attract sustainably responsible investors for investment. This article draws propositions and develops a conceptual model for future empirical research on eco-innovation and societal development.