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Despite offering remarkable advantages as solvents, double salt ionic liquids (DSILs) have been scarcely studied for extractive dearomatization from hydrocarbons as well as many other applications, thus urging a theoretical guidance method. In this work, a systematic framework combining the rational screening validation and mechanistic analysis is proposed for tailoring DSILs for the o‐xylene/n‐octane separation. From an initial pool of commercially available ionic liquids (ILs), key thermodynamic properties of paired DSILs are predicted by COSMO‐RS while their important physical properties are estimated from those of corresponding parent ILs (retrieved from experimental database or predicted by a deep learning model). Promising DSILs are tested by liquid–liquid equilibrium experiments, wherein the effect of ion ratio is also evaluated. The mechanism underlying the tunability of DSIL thermodynamic properties is disclosed by quantum chemistry calculation and molecular dynamics simulation. This work can be a valuable reference for guiding the design of DSILs for diverse applications. [ABSTRACT FROM AUTHOR]

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 with the Selexol process. [ABSTRACT FROM AUTHOR]

For the ionic liquid (IL)‐solute systems of broad interest, a deep neural network based recommender system (RS) for predicting the infinite dilution activity coefficient (γ∞) is proposed and applied for a large extension of the UNIFAC model. In the RS, neural network entity embeddings are employed for mapping each IL and solute, and neural collaborative filtering is utilized to handle the nonlinearities of IL‐solute interactions. A comprehensive experimental γ∞ database covering 215 ILs and 112 solutes (totally 41,553 data points) is established for training the RS, where the cross‐validation and test are performed based on a rigorous dataset split by IL‐solute combinations. The obtained RS shows superior performance than the state‐of‐the‐art γ∞ prediction models and is thus taken to complete the solute‐in‐IL γ∞ matrix. Based on the completed γ∞ database, a large extension of the UNIFAC‐IL model is finally presented, filling all the parameters between involved groups. [ABSTRACT FROM AUTHOR]

• [BMIm][HSO 4 ] was employed as dual catalyst-solvent for BuHE formation. • Effect of [BMIm][HSO 4 ] as extractant on esterification was demonstrated by LLE. • Effect of [BMIm][HSO 4 ] as catalyst on esterification was experimentally investigated. • Reactive extraction conditions for BuHE formation were optimized. • Intensification mechanism of [BMIm][HSO 4 ] on reactive extraction was proposed. Butyl hexanoate (BuHE) is currently synthesized through the Fischer esterification with mineral acid as catalyst, which suffers from the problems of side reaction, difficult recycling, and corrosion. To overcome these disadvantages, ionic liquid 1-butyl-3-methylimidazolium hydrogen sulfate ([BMIm][HSO 4 ]) is employed as dual catalyst-solvent for the esterification of hexanoic acid (HeAc) with n-butanol (BuOH) in a reactive extraction process. The dual functions of [BMIm][HSO 4 ], extraction and catalysis, were confirmed by liquid-liquid equilibria for the two systems {[BMIm][HSO 4 ] + HeAc + BuHE} and {[BMIm][HSO 4 ] + BuOH + BuHE}, and by the comparison of esterifications with or without [BMIm][HSO 4 ], respectively. Moreover, the optimal reactive extraction conditions for BuHE formation were obtained. Finally, the possible mechanism of intensification of [BMIm][HSO 4 ] on BuHE formation in reactive extraction process was proposed. [ABSTRACT FROM AUTHOR]

Although ionic liquids (ILs) have been widely explored as solvents for extractive desulfurization (EDS) of fuel oils, systematic studying of the optimal design of ILs for this process is still scarce. The UNIFAC‐IL model is extended first to describe the EDS system based on exhaustive experimental data. Then, based on the obtained UNIFAC‐IL model and group contribution models for predicting the melting point and viscosity of ILs, a mixed‐integer nonlinear programming (MINLP) problem is formulated for the purpose of computer‐aided ionic liquid design (CAILD). The MINLP problem is solved to optimize the liquid‐liquid extraction performance of ILs in a given multicomponent model EDS system, under consideration of constraints regarding the IL structure, thermodynamic and physical properties. The top five IL candidates preidentified from CAILD are further evaluated by means of process simulation using ASPEN Plus. Thereby, [C5MPy][C(CN)3] is identified as the most suitable solvent for EDS. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1013–1025, 2018 [ABSTRACT FROM AUTHOR]

When applying ionic liquids (ILs) in extractive and oxidative desulfurization of fuel oils, the potential solubility of IL in fuel phase is an important concern whereas research particularly on this issue is still scarce. In this work, COSMO-RS was first employed to predict the solubilities of 220 imidazolium-based ILs (11 cations and 20 anions) in 7 model fuel hydrocarbons (namely, n -hexane, n -heptane, n -octane, i -octane, cyclohexane, benzene and toluene), which cover different characters of ILs and hydrocarbons. To understand the effect of IL and hydrocarbon on the IL-in-hydrocarbon solubility, different types of molecular interactions between IL and hydrocarbon were further analyzed from COSMO-RS point of view. Finally, the solubilities of 5 representative ILs in the studied hydrocarbons were experimentally determined by nitrogen analyzer, demonstrating the good qualitative and acceptable quantitative ability of COSMO-RS for predicting IL-in-hydrocarbon solubilities. [ABSTRACT FROM AUTHOR]

When selecting ionic liquid (IL) as solvent for extraction processes, the cation alkyl chain length is an important structural variation, while research particularly concerning its effect is lacking. In this work, the effect of cation alkyl chain length on the liquid-liquid equilibria of {IL + thiophene + heptane}, an example for extractive desulfurization, was systematically investigated. The COSMO-RS model was employed to calculate the distributional coefficient (β ∞ ) and selectivity (S ∞ ) at infinite dilution for thiophene of the combinations of 17 cations and 63 anions. Two different anion-dependent tendencies of the β ∞ with increasing the cation alkyl chain length were identified and analyzed by COSMO-RS theory. To verify the scarcely-reported decreasing β ∞ with longer cation alkyl chain, acetate ([OAc] − ) was selected as representative and liquid-liquid equilibria {[C n MIM][OAc] + thiophene + heptane} (n = 2, 4, 6, 8) were experimentally determined, which validate the anion-dependency and demonstrate the highest extraction performance of [C 2 MIM][OAc]. [ABSTRACT FROM AUTHOR]

When applying ionic liquids (ILs) for solvent-sensitive extraction systems, ILs dissolved in the raffinate may lead to severe subsequent problems or a significant reduction in product quality, and thus should be particularly concerned. To screen qualified IL solvent for such systems, a rigorous criterion considering both its solubility in the raffinate and extractive ability is established. The COSMO-RS model is used to evaluate the effect of anions and cations, and suggest potential ILs meeting the criterion. Afterwards, the solubility and extractive ability of candidate ILs are investigated by experiments to further confirm their suitability. The proposed solvent screening method is exemplified for the extractive desulfurization process. [C 4 mim][H 2 PO 4 ] is pre-selected by the screening method, and its high extractive performance is experimentally verified. [ABSTRACT FROM AUTHOR]

• Different solvent options are compared for vitamin E extraction. • Organic solvent, ionic liquids, and their binary combinations are covered. • Thermodynamic evaluation is performed using the COSMO-RS model. • Physical and environmental, health, and safety (EHS) properties are assessed. • Two IL-OS binary systems are identified as the best solvent options. Although it is well known that solvent is one of the most important decision variables in liquid-liquid extraction processes, many previous studies focused on a specific class of solvents while neglecting alternatives. This work presents a comparative screening of two types of most extensively studied solvents, i.e., organic solvents (OS) and ionic liquids (ILs), as well as their binary systems for the extraction of vitamin E from methylated oil deodorizer distillates (modelled as a mixture of α-tocopherol and methyllinoleate). For this practically relevant task, the ternary liquid-liquid equilibria (LLE) of {OS or IL + α-tocopherol + methyllinoleate} are first calculated by use of the COnductor-like Screening Model for Real Solvents (COSMO-RS), after which the physical and environmental, health, and safety (EHS) properties of solvents are assessed to identify the top-ranked OS and ILs. To intensify the separation performance, binary solvent systems are also explored, where one of the pre-selected ILs is taken as the first solvent for α-tocopherol and an OS is screened as the second solvent for methyllinoleate. Then, the IL-OS combinations are investigated regarding their binary immiscibility and ranked with respect to the LLE performance in the quaternary system {IL + α-tocopherol + methyllinoleate + OS}. By comparing the extraction distribution coefficient and the selectivity of the top-ranked OS, ILs and IL-OS systems, the notable intensified performance of binary solvent system is proven. [Display omitted] [ABSTRACT FROM AUTHOR]

The separation of 1,3-butadiene (1,3-C4H6) and 1-butene (n-C4H8) is quite challenging due to their close boiling points and similar molecular structures. Extractive distillation (ED) is widely regarded as a promising approach for such a separation task. For ED processes, the selection of suitable entrainer is of central importance. Traditional ED processes using organic solvents suffer from high energy consumption. To tackle this issue, the utilization of ionic liquids (ILs) can serve as a potential alternative. In this work, a high-throughput computational screening of ILs is performed to find proper entrainers, where 36,260 IL candidates comprising of 370 cations and 98 anions are involved. COSMO-RS is employed to calculate the infinite dilution extractive capacity and selectivity of the 36,260 ILs. In doing so, the ILs that satisfy the prespecified thermodynamic criteria and physical property constraints are identified. After the screening, the resulting IL candidates are sent for rigorous process simulation and design. 1,2,3,4,5-pentamethylimidazolium methylcarbonate is found to be the optimal IL solvent. Compared with the benchmark ED process where the organic solvent N-methyl-2-pyrrolidone is adopted, the energy consumption is reduced by 26%. As a result, this work offers a new IL-based ED process for efficient 1,3-C4H6 production. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• Multilevel IL screening for simultaneous CO 2 and H 2 S removal from NG is presented. • IL separation performances are evaluated from both H -based ASDI and VLE based ASDI ′. • Physical properties and stability are considered to search ILs suitable for practical application. • Evaluate the prescreened ILs in rate-based acidic gas removal process by Aspen Plus. For the selection of practically attractive ionic liquids (ILs) as absorbents for simultaneous CO 2 and H 2 S removal from natural gas (NG), a multilevel screening method combining Henry′s law constant (H) and vapor–liquid equilibria (VLE) based prediction of thermodynamic properties, physical properties estimation, and process simulation is presented. To begin with, an H -based Absorption-Selectivity-Desorption index (ASDI) is employed to prescreen potential ILs that have promising target properties at infinite dilution condition. Following this, their simultaneous CO 2 and H 2 S removal performances are further evaluated from the VLE of {IL + NG} systems at the specific composition of interest. After the thermodynamic screening, key physical properties of the obtained ILs are estimated by group contribution methods and the IL stability is assessed empirically to find out solvents suitable for practical application. Finally, continuous acidic gas removal processes based on the remaining ILs are simulated and compared by Aspen Plus, thereby identifying the best ILs from the process point of view. [ABSTRACT FROM AUTHOR]

• A dataset containing 10,116 CO 2 solubilities in ionic liquids is collected. • Two machine learning models, ANN-GC and SVM-GC, are developed. • Both of the models can give reliable predictions on the CO 2 solubility. • The ANN-GC model performs slightly better than the SVM-GC model. A comprehensive database containing 10,116 CO 2 solubility data measured in various ionic liquids (ILs) at different temperatures and pressures is established. Based on this database, the relationship between CO 2 solubility and IL structure, temperature and pressure is correlated using group contribution (GC) methods. Two different machine learning algorithms, namely artificial neural network (ANN) and support vector machine (SVM), are employed to develop the GC models. For the 2023 test-set data, the estimated MAE and R2 are 0.0202 and 0.9836, respectively for the ANN-GC model and for the SVM-GC model they are 0.0240 and 0.9783, respectively. The distributions of prediction errors are plotted for both models to provide more comprehensive knowledge on the model performance. The results indicate that both of the models can give reliable predictions on the CO 2 solubilities in ILs and the ANN-GC model performs slightly better than the SVM-based model. [ABSTRACT FROM AUTHOR]

Considering that the predictive UNIFAC model is highly valuable for the solvent selection, process design and optimization of separation tasks, a large extension of this model to ionic liquid (IL)–solute systems is presented by combining experimental and COSMO‐RS derived databases. The experimental infinite dilution activity coefficient (γ∞) data of different solutes in ILs are first collected exhaustively to extend UNIFAC‐IL to cover all involved IL and conventional functional groups. Afterwards, the experimental and COSMO‐RS calculated γ∞ are compared for different types of solutes to evaluate the potential of using COSMO‐RS predictions as quasi‐experimental data for further UNIFAC‐IL extension. In the cases where COSMO‐RS can provide quantitatively accurate predictions after calibration, additional γ∞ database is specifically generated to regress more group interaction parameters in the UNIFAC‐IL model. Finally, a large experimental liquid–liquid and vapor–liquid equilibria database is collected and employed to evaluate the predictive performance of the obtained γ∞‐based UNIFAC‐IL model. [ABSTRACT FROM AUTHOR]

Although double salt ionic liquids (DSILs) offer significant advantages over classical two‐ion ionic liquids as separation solvents, relevant studies are still scarce and a systematic DSIL selection method is thus highly desirable. In this contribution, a rational method for designing DSILs as extraction solvents is proposed and exemplified by the thiophene/n‐octane separation. The effects of additional degrees of freedom for DSIL design (i.e., double cations and/or anions and the ion ratio) on the thermodynamic properties are first analyzed by COSMO‐RS. Then, a multilevel DSIL design method combining the prediction of infinite dilution thermodynamic properties, the estimation of physical properties, the evaluation of phase equilibrium behavior, and the experimental validation is proposed. By applying this method, [C2MIm][OAc]x[NO3]1‐x (x = [0, 1]) and [C2MIm][OAc]x[SCN]1‐x (x = [0.70, 1]) are identified as promising DSIL solvents for the thiophene/n‐octane separation. Correspondingly, the liquid–liquid equilibria of {DSILs + thiophene + n‐octane} with the designed DSILs are experimentally studied. [ABSTRACT FROM AUTHOR]

As a volatile organic compound (VOC), styrene can pose significant risks to human health and environment if released into the air without proper treatment. Absorption based on ionic liquids (ILs) has been widely regarded as a promising VOC treatment approach, whereas there is limited research on capturing styrene by ILs. In this work, a multilevel framework was proposed to screen IL absorbents from the largest number of cation-anion combinations in the latest COSMObase. The COSMO-RS model is applied to estimate the absorption and desorption potentials of all IL candidates for styrene capture based on solubility prediction, while important physical properties of them namely melting point, viscosity, and toxicity are estimated by a recently-reported deep learning model. A parallel screening specific to the commercially available ILs in the initial candidate database was also performed. The top-ranked three ILs, identified in both scenarios with and without limiting the commercially availability, were further evaluated in a simulated absorption-desorption process in Aspen Plus. The most promising ILs in each scenario were figured out, which vividly demonstrates the value of discovering novel ILs. [Display omitted] • Propose a multilevel framework for screening ionic liquid (IL) absorbents. • Present two parallel scenarios with and without limiting commercial availability. • Find top 3 ILs from 347406 hypothetical and 108 available candidates, respectively. • Demonstrate the value of discovering novel ILs guided by large-scale screening. [ABSTRACT FROM AUTHOR]

When applying COSMO-based models in Computer-Aided Ionic Liquid Design (CAILD), the generation of surface charge density profiles ( σ -profiles) and cavity volumes ( V COSMO ) of ILs is particularly important but too computationally expensive with quantum chemical calculations. In this work, a modified group contribution methodology, the COSMO-GC-IL method, is proposed for quick prediction of IL σ -profiles and V COSMO based on σ -profiles of IL groups in their reference states (COSMO descriptors), together with two modification parameters (stretch and translation parameters). The influence of molecular environment on target groups can be well described and IL isomers are thereby distinguishable. To verify the method, σ -profiles and V COSMO generated from the present method and from the DMol 3 database are employed to calculate activity coefficients of 28,644 binary systems and 3410 liquid-liquid equilibria of ternary mixtures. Their close results in most cases demonstrate the reliability of the COSMO-GC-IL method. [ABSTRACT FROM AUTHOR]

The use of hydrogen as clean energy has attracted significant attention because conventional industrial hydrogen production processes show negative environmental impact, require intensive energy, and/or are dependent on natural gas. The main objective of this study is to develop an innovative and environment-friendly hydrogen production process utilizing biogas as an alternative to natural gas. Ionic liquid [Bmim][PF 6 ] shows high potential for the replacement of aqueous amine solutions for CO 2 absorption and are employed for biogas upgrading, while thermal plasma (TP), which is beneficial for converting electrical energy to chemical energy, is employed for the simultaneous production of clean "turquoise" hydrogen and solid carbon. In addition, an intercooler is used to improve CO 2 removal in the absorber. Heat and power integration are employed to enhance the performance of the upgrading process and thermal-plasma-assisted hydrogen production. All simulations were conducted using Aspen Plus V10.0 software. The simulated results show that the solid carbon production from biomethane increases compared to that in the proposed base case. The savings in both the heater used to preheat the TP reactor and the third flash drum are 100%, while the saving in power consumption in the compression section is 62.0%. Furthermore, sensitivity is investigated to determine the effect of biomethane composition on the performance of the proposed configuration. [Display omitted] • An attractive solution for both renewable hydrogen and solid carbon production. • The process employing [Bmim][PF6] with intercooler affords 99.7% pure biomethane. • The heating and power requirement can be saved 100% and 62%, respectively. • Increasing the methane composition in biogas increases hydrogen productivity. [ABSTRACT FROM AUTHOR]

[Display omitted] • A quantification method proposed for chemi- and physisorption in reactive absorption. • Chemi- and physisorption of CO 2 in [Emim][OAc] are quantified as example. • Solubility of CO 2 in [Emim][OAc] at low pressures are experimentally measured. • Rational thermodynamic analyses made with quantified chemi- and physisorption. Although chemisorptive ionic liquids (ILs) are widely expected as promising CO 2 absorbents, rigorous thermodynamic analyses for such systems remain challenging due to the inevitable co-existence of chemisorption and physisorption. In this work, an experimental approach combining quantitative NMR (qNMR) spectroscopy and mass balance is proposed to straightforwardly quantify the chemisorption and physisorption of CO 2 in chemisorptive absorbent, and 1-ethyl-3-methylimidazolium acetate ([Emim][OAc]) is selected for an exemplary study. The total CO 2 solubility in [Emim][OAc] is measured by the pressure drop method, of which the chemisorption part is quantified by qNMR and the physisorption part is then determined by mass balance. Correspondingly, a large set of CO 2 solubilities at four temperatures (298.15 K, 313.15 K, 323.15 K, and 348.15 K) covering the low pressure range below 100 kPa are determined, where the chemisorption and physisorption contribution are distinguished quantitatively. Following that, thermodynamic analyses for the CO 2 absorption by [Emim][OAc] are made from chemisorption and physisorption point of view, respectively. [ABSTRACT FROM AUTHOR]

• Ionic liquid and deep eutectic solvent are compared as alternative CO 2 absorbent. • Multilevel screening of ionic liquid and deep eutectic solvent are performed. • Top three ionic liquids and deep eutectic solvents are screened from a large space. • CO 2 absorption experiments are performed to validate the top deep eutectic solvent. • QC calculations are performed to gain microscopic insight into CO 2 absorption. Because of the high energy consumption and volatility of organic amine solvents in conventional CO 2 capture processes, ionic liquids (ILs) and deep eutectic solvents (DESs) have been widely expected as alternative CO 2 absorbents. In this work, promising ILs and DESs are identified through a comparative, multi-level absorbent screening method proposed for the first time from a large space of cation–anion combinations and potential DES components, respectively. Important physical properties (namely melting point, viscosity, and toxicity) of potential ILs and salt components of DESs are estimated by a recently-reported deep learning model. Key thermodynamic properties including physically-based absorption and desorption potentials as well as eutectic behaviors between DES component combinations are predicted by the COSMO-RS model. Five EHS (environment, health, and safety) related properties of non-salt components of DESs are assessed by the VEGA platform. From above, the top three ILs and DESs are identified from 5,440 and 38,389 candidates, respectively. The CO 2 capture processes based on the retained ILs and DESs are simulated in Aspen Plus in rate-based mode, identifying 1-methyl-1-propylpyrrolidinium bromide: methylimidazole (1:2) as the absorbent with the highest process performance. The experiments shows that the molality-based Henry constant of CO 2 in DES is as low as 1.32, validating the competitive absorption performance of this potential DES. Finally, quantum chemistry calculations are conducted to unveil the microscopic absorption mechanism of this DES. [ABSTRACT FROM AUTHOR]

• UNIFAC-IL model is extended to cover R410A refrigerant blend (R-32 and R-125). • CAILD is performed to rationally design ILs for separating R410A blend. • MD simulations are conducted to elucidate the rationality of CAILD results. The selective separation of refrigerants could facilitate their reclamation and reduce emissions of hydrofluorocarbons (HFC) with high global warming potential. R410A, a near azeotropic mixture comprising equimass difluoromethane (R-32) and pentafluoroethane (R-125), is required to be phased out and shortly replaced by more efficient and sustainable refrigerants. Under this background, the recovery of R-32 and R-125 by using ionic liquids (ILs) as the solvent is considered as a promising approach. In this work, the rational selection of ILs for enhancing the R410A separation is presented. To this end, 873 refrigerant-in-IL solubility data (573 for R-32, 300 for R-125) are firstly adopted for the extension of the UNIFAC-IL model to cover the R410A system. With the obtained UNIFAC-IL model, a computer-aided IL design (CAILD) task is cast as a mixed-integer nonlinear programming (MINLP) problem, which is solved to identify three top-ranked ILs. Following that, molecular dynamics (MD) simulations of the selected IL-refrigerant systems are conducted, which well elucidate the reliability of the CAILD results. [ABSTRACT FROM AUTHOR]

[Display omitted] • A two-stage process is reported for CO 2 capture in 1,2,4-triazolate ionic liquids. • Physi- and chemi-sorption species are identified by experimental and computational studies. • The transition between physi- and chemi-sorption is elucidated at a molecular level. • The transition is tuned by adjusting the absorption conditions and from the addition of co-solvents. Capture of CO 2 is a crucial process to achieve carbon neutrality. High-performance CO 2 capture involves both physi- and chemi-sorption, with a transition between them. However, the underlying mechanistic insights required to produce the methods to tune the transition are poorly understood. Here, we describe a series of 1,2,4-triazolate ionic liquids (TZ ILs) that capture > 0.7 mol CO 2 /mol TZ IL in a two-stage absorption process. Physi- and chemi-sorption were studied by spectroscopy using 13CO 2 and the transition between the two sorption modes has been identified. UV–Vis, FT-IR and NMR spectroscopy as well as density and viscosity measurements demonstrate that physisorption is initially the dominant process whereas later chemisorption predominates. Based on the identification of key species combined with theoretical modelling, a plausible molecular-level mechanism is proposed for the transition between the two sorption modes. These mechanistic insights enable the transition of CO 2 capture to be tuned. [ABSTRACT FROM AUTHOR]