Mark A. Stadtherr

Octanol-water partition coefficients of imidazolium-based ionic liquids

Ionic liquids (ILs) are low melting organic salts that are being vigorously investigated as possible replacements for volatile organic solvents. While they cannot contribute to air pollution due to their negligible vapor pressure, they do have significant solubility in water. As a result, this is the most likely medium through which ILs will enter the environment. Therefore, it is important to understand how ILs will influence aquatic ecosystems. A simple thermodynamic measurement that has been extremely useful in estimating effects of chemical pollutants on aquatic environments is the octanol–water partition coefficient (KOW). It is an extremely important quantity because it describes the hydrophobicity or hydrophilicity of a compound and has been correlated with bioaccumulation and toxicity in fish, as well as sorption to soils and sediments. Here we present measurements of the KOW of twelve imidazolium-based ILs at room temperature, using the slow-stirring method. For the butylmethylimidazolium cation, KOW values range from 0.003 to 11.1, depending on the choice of anion. In addition, we find that the KOW values increase with increasing alkyl chain length on the cation and that replacing the acidic hydrogen on the carbon between the two nitrogens in the imidazolium ring with a methyl group has negligible effect on the KOW. However, all of the KOW values measured, even for the most “hydrophobic” imidazolium-based ILs, are less than 15 so these ILs will not accumulate or concentrate in the environment.

Robust process simulation using interval methods

Ideally, for the needs of robust process simulation, one would like a nonlinear equation solving technique that can find any and all roots to a problem, and do so with mathematical certainty. In general, currently used techniques do not provide such rigorous guarantees. One approach to providing such assurances can be found in the use of interval analysis, in particular the use of interval Newton methods combined with generalized bisection. However, these methods have generally been regarded as extremely inefficient. Motivated by recent progress in interval analysis, as well as continuing advances in computer speed and the availability of parallel computing, we consider here the feasibility of using an interval Newton/generalized bisection algorithm on process simulation problems. An algorithm designed for parallel computing on an MIMD machine is described, and results of tests on several problems are reported. Experiments indicate that the interval Newton/generalized bisection method works quite well on relatively small problems, providing a powerful method for finding all solutions to a problem. For larger problems, the method performs inconsistently with regard to efficiency, at least when reasonable initial bounds are not provided.

Extraction of alcohols from water with 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide

Ethanol production in the U. S. has increased 36% between 2006 and 2007 (J. M. Urbanchuk, Contribution of the Ethanol Industry to the Economy of the United States, LECG, LLC, Renewable Fuels Association, 2008) in response to a growing demand for its use as a commercial transportation fuel. 1-Butanol also shows potential as a liquid fuel but both alcohols require high energy consumption in separating them from water. 1-Butanol, in particular, is considered an excellent intermediate for making other chemical compounds from renewable resources, as well as being widely used as a solvent in the pharmaceutical industry. These alcohols can be synthesized from bio-feedstocks by fermentation, which results in low concentrations of the alcohol in water. To separate alcohol from water, conventional distillation is used, which is energetically intensive. The goal of this study is to show that, using an ionic liquid, extraction of the alcohol from water is possible. Through the development of ternary diagrams, separation coefficients are determined. The systems studied are 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide/ethanol/water, which exhibits Type 1 liquid–liquid equilibrium (LLE) behavior, and 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide/1-butanol/water, which exhibits Type 2 LLE behavior. Based on the phase diagrams, this ionic liquid (1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide) can easily separate 1-butanol from water. It can also separate ethanol from water, but only when unreasonably high solvent/feed ratios are used. In addition, we use four excess Gibbs free energy (gE) models (NRTL, eNRTL, UNIQUAC and UNIFAC), with parameters estimated solely using binary data and/or pure component properties, to predict the behavior of the ternary LLE systems. None of the models adequately predicts the Type 1 system, but both UNIQUAC and eNRTL aptly predict the Type 2 system.

Reliable Phase Stability Analysis for Excess Gibbs Energy Models

Because models used to represent the Gibbs energy of mixing are typically highly nonlinear, the reliable prediction of phase stability from such models is a challenging computational problem. The phase stability problem can be formulated either as a minimization problem or as an equivalent nonlinear equation solving problem. However, conventional solution methods are initialization dependent, and may fail by converging to trivial or nonphysical solutions or to a point that is a local but not global minimum. Since the correct prediction of phase stability is critical in the design and analysis of separation processes, there has been considerable recent interest in developing more reliable techniques for stability analysis. Recently we have demonstrated a technique that can solve the phase stability problem with complete reliability. The technique, which is based on interval analysis, is initialization independent, and if properly implemented provides a mathematical guarantee that the correct solution to the phase stability problem has been found. In this paper, we demonstrate the use of this technique in connection with excess Gibbs energy models. The NRTL and UNIQUAC models are used in examples, and larger problems than previously considered are solved. We also consider two means of enhancing the efficiency of the method, both based on sharpening the range of interval function evaluations. Results indicate that by using the enhanced method, computation times can be substantially reduced, especially for the larger problems.

Extraction of biofuels and biofeedstocks from aqueous solutions using ionic liquids

Abstract The production from biomass of chemicals and fuels by fermentation, biocatalysis, and related techniques implies energy-intensive separations of organics from relatively dilute aqueous solutions, and may require use of hazardous materials as entrainers to break azeotropes. We consider the design feasibility of using ionic liquids as solvents in liquid–liquid extractions for separating organic compounds from dilute aqueous solutions. As an example, we focus on the extraction of 1-butanol from a dilute aqueous solution. We have recently shown ( Chapeaux et al., 2008 ) that 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide shows significant promise as a solvent for extracting 1-butanol from water. We will consider here two additional ionic liquids, 1-(6-hydroxyhexyl)-3-methylimidazolium bis-(trifluoromethylsulfonyl)imide and 1-hexyl-3-methylimidazolium tris(pentafluoroethyl)trifluorophosphate, as extraction solvents for 1-butanol. Preliminary design feasibility calculations will be used to compare the three ionic liquid extraction solvents considered. The ability to predict the observed ternary liquid–liquid equilibrium behavior using selected excess Gibbs energy models, with parameters estimated solely using binary data and pure component properties, will also be explored.

Reliable prediction of phase stability using an interval Newton method

Abstract A key step in phase equilibrium calculations is determining if, in fact, multiple phases are present. Reliably solving the phase stability and, ultimately the phase equilibrium problem, is a significant challenge for high pressure vapor/liquid, liquid/liquid and vapor/liquid/liquid equilibrium. We present the first general-purpose computational method, applicable to any arbitrary equation of state or activity coefficient model, that can mathematically guarantee a correct solution to the phase stability problem. In this paper, we demonstrate the use of this new method, which uses techniques from interval mathematics, for the van der Waals equation of state to determine liquid/liquid and liquid/vapor phase stability for a variety of representative systems. Specifically, we describe and test interval methods for phase stability computations for binary mixtures that exhibit Type I and Type II behavior, as well as for a relatively simple ternary mixture. This shows that interval techniques can find with absolute certainy all stationary points, and thus solve the phase stability problem with complete reliability.

Reliable nonlinear parameter estimation in VLE modeling

Abstract The reliable solution of nonlinear parameter estimation problems is an important computational problem in the modeling of vapor–liquid equilibrium (VLE). Conventional solution methods may not be reliable since they do not guarantee convergence to the global optimum sought in the parameter estimation problem. We demonstrate here a technique that is based on interval analysis, which can solve the nonlinear parameter estimation problem with complete reliability, and provides a mathematical and computational guarantee that the global optimum is found. As an example, we consider the estimation of parameters in the Wilson equation, using VLE data sets from a variety of binary systems. Results indicate that several sets of parameter values published in the DECHEMA VLE Data Collection correspond to local optima only, with new globally optimal parameter values found by using the interval approach. When applied to VLE modeling, the globally optimal parameters can provide significant improvements in predictive capability. For example, in one case, when the previously published locally optimal parameters are used, the Wilson equation does not predict experimentally observed homogeneous azeotropes, but, when the globally optimal parameters are used, the azeotropes are predicted.

Reliable Computation of Phase Stability Using Interval Analysis: Cubic Equation of State Models

The reliable prediction of phase stability is a challenging computational problem in chemical process simulation, optimization and design. The phase stability problem can be formulated either as a minimization problem or as an equivalent nonlinear equation solving problem. Conventional solution methods are initialization dependent, and may fail by converging to trivial or non-physical solutions or to a point that is a local but not global minimum. Thus there has been considerable recent interest in developing more reliable techniques for stability analysis. In this paper we demonstrate, using cubic equation of state models, a technique that can solve the phase stability problem with complete reliability. The technique, which is based on interval analysis, is initialization independent, and if properly implemented provides a mathematical guarantee that the correct solution to the phase stability problem has been found.

Reliable nonlinear parameter estimation using interval analysis: error-in-variable approach

Abstract Parameter estimation is a key problem in the development of process models, both steady- and unsteady-state, and thus is an important issue in both process design and control. The error-in-variable (EIV) approach differs distinctly from the standard approach in that measurement errors in both dependent and independent system variables are taken into account when formulating the objective function in the parameter estimation problem. It is not uncommon for the objective function in nonlinear parameter estimation problems to have multiple local optima. However, the usual methods used to solve these problems are local methods that offer no guarantee that the global optimum, and thus the best set of model parameters, has been found. We demonstrate here a technique, based on interval analysis, that can solve the EIV parameter estimation problem with complete reliability, providing a mathematical and computational guarantee that the global optimum is found. As examples, we consider the estimation of parameters in both steady and unsteady-state models, including a vapor—liquid equilibrium (VLE) model, a CSTR model, and a reaction kinetics model.

Systems Study of the Petrochemical Industry.

Abstract The modern petrochemical industry is the result of the action over decades of incompletely understood economic, technical, and political forces. It is to be hoped that this complex industrial system has evolved into an efficient and flexible provider of the needs of the economy. We seek to determine the strengths and weaknesses of the industry and to perceive opportunities for further development. A systems model of the industry provides the necessary insight. A criterion of efficient feedstock utilization on the model of the industry reproduces the dominant structure of the actual industry, thereby lending credence to the model and the performance criterion. Fourteen of the twenty chemicals for which the current production practices differ from those proposed by the model are the subject of current development interest. The remaining six chemicals are produced in the model by currently obsolete processes that may be revived. The response of the verified model to scenerios of potential future developments provides points of departure for planning the long-range development of the industry.