Optimal solvent design for batch separation based on economic performance

Giovanoglou, Apostolos; Barlatier, Julie; Adjiman, Claire S.; Pistikopoulos, Efstratios N.; Cordiner, Joan

doi:10.1002/aic.690491211

Cited by 69 publications

(37 citation statements)

References 47 publications

(23 reference statements)

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“…7 In a batch extractive distillation for fine chemicals processing, for example, CAMD has been shown to identify a solvent that makes it possible to meet purity requirements, and that minimizes the time required for separation, with gains in throughput/productivity of at least 15%. 8 The extension of CAMD techniques to reactions has the potential to facilitate the task of finding good solvents, and to uncover unexpected choices. The key objective in using such an approach is to identify choices of solvent molecules that offer good overall performance and meet the plethora of criteria that constrain solvent choice.…”

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confidence: 45%

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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confidence: 45%

Computer-aided molecular design of solvents for accelerated reaction kinetics

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“…This allows the quick evaluation of the separating agent put forward by the master problem, before the solution of the primal problem. This work has been applied to absorption processes and extended to dynamic models (Giovanoglou, Barlatier, Adjiman, Pistikopoulos & Cordiner, 2003). Another approach has been developed by Marcoulaki & Kokossis (2000), who have used a simulated annealing approach to integrate solvent and process design.…”

Section: Introductioncontrasting

confidence: 40%

Integrated solvent and process design using a SAFT-VR thermodynamic description: High-pressure separation of carbon dioxide and methane

Pereira¹,

Keskes²,

Galindo³

et al. 2011

Computers & Chemical Engineering

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“…44 To handle more general design problems, one can adopt the approach of Buxton et al 8 who modified the generalized Benders decomposition (GBD) algorithm 45 : they introduced several steps prior to the solution of the primal problem, including a series of property tests that form a subset of the CAMD problem constraints, the initialization of various sets of equations in the process model, and mass-transfer feasibility tests, in which the process operating conditions were assumed to be fixed a priori. This approach was extended to tackle mixed-integer dynamic optimization problems, 46 to enable the simultaneous design of a batch process and the associated solvent. In these studies, the highly-nonlinear UNI-FAC model 15 was combined with the ideal gas equation to represent the relevant phase equilibria.…”

Section: Introductionmentioning

confidence: 48%

“…Several novel tests are embedded within a modified outerapproximation (OA) 49,50 algorithm to solve the MINLP, akin to the general principle of integrating tests into a modified GBD algorithm deployed by Buxton et al 8 and Giovanoglou et al 46 The tests we develop differ from these earlier approaches, however, as the feasibility of the process is assessed for combinations of the values of the process and molecular variables, rather than for values of the molecular variables alone. When a new solvent is generated at a major iteration of the modified OA algorithm, the tests help to ascertain the feasibility of using the solvent in the process, before solving the process optimization problem (primal problem) for the fixed solvent.…”

Section: Introductionmentioning

confidence: 49%

Outer approximation algorithm with physical domain reduction for computer‐aided molecular and separation process design

et al. 2016

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Integrated approaches to the design of separation systems based on computer-aided molecular and process design (CAMPD) can yield an optimal solvent structure and process conditions. The underlying design problem, however, is a challenging mixed integer nonlinear problem, prone to convergence failure as a result of the strong and nonlinear interactions between solvent and process. To facilitate the solution of this problem, a modified outer-approximation (OA) algorithm is proposed. Tests that remove infeasible regions from both the process and molecular domains are embedded within the OA framework. Four tests are developed to remove subdomains where constraints on phase behavior that are implicit in process models or explicit process (design) constraints are violated. The algorithm is applied to three case studies relating to the separation of methane and carbon dioxide at high pressure. The process model is highly nonlinear, and includes mass and energy balances as well as phase equilibrium relations and physical property models based on a group-contribution version of the statistical associating fluid theory (SAFT-c Mie) and on the GC 1 group contribution method for some pure component properties. A fully automated implementation of the proposed approach is found to converge successfully to a local solution in 30 problem instances. The results highlight the extent to which optimal solvent and process conditions are interrelated and dependent on process specifications and constraints. The robustness of the CAMPD algorithm makes it possible to adopt higher-fidelity nonlinear models in molecular and process design.

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Optimal solvent design for batch separation based on economic performance

Cited by 69 publications

References 47 publications

Computer-aided molecular design of solvents for accelerated reaction kinetics

Computer-aided molecular design of solvents for accelerated reaction kinetics

Integrated solvent and process design using a SAFT-VR thermodynamic description: High-pressure separation of carbon dioxide and methane

Outer approximation algorithm with physical domain reduction for computer‐aided molecular and separation process design

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