Solvent Design Using a Quantum Mechanical Continuum Solvation Model

Sheldon, T.J.; Folić, and M.; Adjiman, Claire S.

doi:10.1021/ie050416r

Cited by 23 publications

(12 citation statements)

References 48 publications

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“…Similar rules have been previously developed for molecular compounds. 23 Ã , in each side chain l. In other words, Eq. 19 can be used to make sure that a certain main group such as aldehyde or alcohol not being present more than a certain number of times in each side chain of the cation, and Eq.…”

Section: Il Structural Constraintsmentioning

confidence: 99%

Computer‐aided design of tailor‐made ionic liquids

Karunanithi

Mehrkesh

2013

AIChE Journal

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in Wiley Online Library (wileyonlinelibrary.com) Ionic liquids (IL), with their negligible vapor pressure, have the potential to replace volatile organic solvents in several processes. They also exhibit other unique characteristics, such as high thermal stability, wide liquid range, and wide electrochemical window, which make them attractive for many important applications. In addition, millions of ILs can be formed through different combination of cations, anions, and other functional groups. Till now, majority of work on IL selection, for a given application, is guided by trial and error experimentation. In this article, we present a computer-aided IL design framework, based on semiempirical structure-property models and optimization methods, which can consider several IL candidates and design optimal structures for a given application. This powerful methodology has great potential to act as a knowledge-based framework to aid synthetic chemists and engineers develop new ILs.

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Section: Il Structural Constraintsmentioning

confidence: 99%

Computer‐aided design of tailor‐made ionic liquids

Karunanithi

Mehrkesh

2013

AIChE Journal

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“…A surrogate model is a simplified model that must have two key properties: (i) it must be applicable to a very large number of solvents; (ii) it must be inexpensive to evaluate, thereby alleviating the computational cost of embedding QM calculations directly in the solvent design algorithm. 42 Here, we use the solvatochromic equation, 43,44 a well-recognized and widely used linear free energy relationship that can be applied to a range of properties, including reaction rate constants. The solvatochromic equation used relates the logarithm of the rate constant k to five properties of the solvent via six coefficients that are characteristic of the reaction being investigated: Every time the algorithm passes through Step 3, the reaction-specific coefficients, c i , are re-estimated using all known k QM values at that point.…”

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confidence: 99%

Computer-aided molecular design of solvents for accelerated reaction kinetics

et al. 2013

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ABSTRACT:Solvents crucially alter the rates and selectivity of liquid-phase organic reactions, often hindering the development of new synthetic routes or, if chosen wisely, facilitating routes by improving rates and selectivities. To address this challenge, a systematic methodology is proposed that quickly identifies improved reaction solvents by combining quantum mechanical computations of the reaction rate constant in a few solvents with a computer-aided molecular design (CAMD) procedure. The approach allows the identification of a high-performance solvent within a very large set of possible molecules. The validity of our CAMD approach is demonstrated through application to a classical nucleophilic-substitution reaction for the study of solvent effects, the Menschutkin reaction. The results are successfully validated via in-situ kinetic experiments. A space of 1341 solvents is explored in silico, but requiring quantum mechanical calculations of the rate constant in only 9 solvents, and uncovering a solvent that increases the rate constant by 40%.What is the best solvent for a given chemical reaction? Given that the rate and selectivity of chemical reactions can vary by several orders of magnitude in different solvents, 1,2 this question has important ramifications for the exploration of novel reaction routes and the development of industrial processes. 3,4 When investigating new liquid-phase reactions, it is essential to find a solvent that promotes the desired reaction without excessive catalyst deactivation, side-product formation, or solubility limitations. Indeed, a poor solvent choice can result in a missed opportunity to investigate novel chemistry or catalysts. At the process-development level, the problem of solvent choice is 2 compounded by the numerous safety, environmental and process constraints that must be satisfied.Yet, few tools exist to support this decision, especially when it affects reaction kinetics, and researchers are often left to choose on the basis of qualitative chemical knowledge and/or extensive and costly experimental investigations.Advances in the understanding of liquid-phase reactions remain a topic of intense academic interest 5 and practical relevance, as illustrated by identification of the development of solvent selection techniques as a key priority area by the ACS Green Chemistry roundtable. 6 A very promising avenue of research in this direction is the development of Computer-Aided Molecular Design (CAMD) techniques. CAMD offers systematic methodologies, typically in the form of algorithms, to identify chemical species/molecular structures that perform a chosen function best (e.g., maximize the rate of a given reaction). The resulting molecular designs can be used to guide experiments in an otherwise huge space of possibilities. CAMD techniques have been widely applied in the context of solvent design for separations, and have had a significant impact on academic and industrial practice. 7 In a batch extractive distillation for fine chemicals processing, for example, ...

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Section: Modeling Approachesmentioning

confidence: 99%

“…The main objectives of the CAM b D framework focus on optimizing the physical properties of mixtures or compounds 47,48 and/or on optimizing process performance, such as minimizing process cost 49 or maximizing production. 50,51 As discussed in the introduction, most existing CAM b D methods involve formulating and solving a problem using mathematical programming techniques; usually a MINLP problem.…”

Section: Introductionmentioning

confidence: 99%

The formulation of optimal mixtures with generalized disjunctive programming: A solvent design case study

et al. 2016

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Systematic approaches for the design of mixtures, based on a computer-aided mixture/blend design (CAM b D) framework, have the potential to deliver better products and processes. In most existing methodologies the number of mixture ingredients is fixed (usually a binary mixture) and the identity of at least one compound is chosen from a given set of candidate molecules. A novel CAM b D methodology is presented for formulating the general mixture design problem where the number, identity and composition of mixture constituents are optimized simultaneously. To this end, generalized disjunctive programming is integrated into the CAM b D framework to formulate the discrete choices. This generic methodology is applied to a case study to find an optimal solvent mixture that maximizes the solubility of ibuprofen. The best performance in this case study is obtained with a solvent mixture, showing the benefit of using mixtures instead of pure solvents to attain enhanced behavior. V C 2016 The Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers AIChE J, 62: [1616][1617][1618][1619][1620][1621][1622][1623][1624][1625][1626][1627][1628][1629][1630][1631][1632][1633] 2016 Keywords: computer-aided mixture design, generalized disjunctive programming, optimal mixture design, ibuprofen, solubility IntroductionMixtures play an important role in the process industries and blends of refrigerants, 1-3 polymers, 4,5 and solvents 6 are used in a wide range of applications. Solvent mixtures, for example, are used in separation processes, such as extraction, 7,8 absorption, 9 and crystallisation, 10,11 and in chemical reactions. 12,13 In product design, the desired performance can often only be achieved with a mixture or formulation (e.g., pesticide formulation, crude oils blended into a single product).14,15 The current regulatory environment is making mixtures increasingly relevant as restrictions are placed on the use of a growing number of compounds. Some common compounds are thus being removed from use as a result of changing regulations (e.g., REACH regulations 16 ). Given this context, the formulation of mixtures offers a potential route to enhanced performance, because mixtures can exhibit properties that equate or even surpass those of pure compounds. Some of the benefits of using mixtures have been demonstrated by Granberg and Rasmuson 17 who studied the solubility of paracetamol in a binary mixture of water and acetone. The results of their study are shown in Figure 1, where it can be seen that, at 308C, mixtures containing up to 75% water by mass achieve at least as high a solubility as pure acetone, with a 30:70 mixture of water and acetone achieving the highest solubility. A fivefold increase in solubility relative to pure acetone is observed, although paracetamol is poorly water-soluble. This nonlinear behavior, which is commonly observed in solubility experiments (e.g., the work of Pacheco et al. 18 ), arises from the nonideal thermodynamics of...

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Solvent Design Using a Quantum Mechanical Continuum Solvation Model

Cited by 23 publications

References 48 publications

Computer‐aided design of tailor‐made ionic liquids

Computer‐aided design of tailor‐made ionic liquids

Computer-aided molecular design of solvents for accelerated reaction kinetics

The formulation of optimal mixtures with generalized disjunctive programming: A solvent design case study

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