A QM-CAMD approach to solvent design for optimal reaction rates

Struebing, Heiko; Obermeier, Stephan; Siougkrou, Eirini; Adjiman, Claire S.; Galindo, Amparo

doi:10.1016/j.ces.2016.09.032

Cited by 41 publications

(16 citation statements)

References 58 publications

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“…35 Recently, Struebing et al have proposed a method based on quantum mechanics calculations and computer-aided molecular design (CAMD) to make a screening in a space of 1341 solvents. 41,42 Their approach is a combination of continuum solvation calculation, using the SMD model for five or six solvents, 41 and the solvatochromic equation in conjunction with group-contribution methods to predict the solvent effect for a large set of solvents. However, the procedure was not widely tested to predict solvation free energy of neutral and ionic solutes as the SMD model was, 24,33,35,37 and the diversity of solvents is rather limited.…”

Section: Introductionmentioning

confidence: 99%

Solvent selection for chemical reactions: automated computational screening of solvents using the SMD model

Dalessandro¹,

Pliego²

2018

Quim. Nova

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Finding the most efficient solvent for a chemical reaction can demand costly experimental procedure and the screening is usually limited to few solvents. The use of theoretical methods could accelerate the search for the best solvent, able to promote most effective kinetics and thermodynamics of a reaction. In this work, it was proposed an automated procedure that calculates the solvent effect for a chemical reaction using all the 179 solvents available in SMD (solvation model density). The reaction of 2-bromoacetophenone with pyridine was used as a test. The SMD model correctly predicts the reactivity trends for five solvents, which experimental data are available. We have found that sulfolane, a less usual solvent, is the best one for this reaction. The present study points out that computational screening of large set of solvents using the SMD model is a viable approach and could be useful for chemical reactions optimization.

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Section: Introductionmentioning

confidence: 99%

Solvent selection for chemical reactions: automated computational screening of solvents using the SMD model

Dalessandro¹,

Pliego²

2018

Quim. Nova

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“…The CAMD formulation allows the design of novel molecular structures y S as a degree of freedom of the optimization problem. Structural feasibility is ensured by additional equality and inequality CAMD constraints ( F 1 , F 2 , e.g., octet rule) …”

Section: Framework For Integrated Design Of Molecules Processes Equmentioning

confidence: 99%

Integrating superstructure‐based design of molecules, processes, and flowsheets

2020

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The key to many chemical and energy conversion processes is the choice of the right molecule, for example, used as working fluid. However, the choice of the molecule is inherently coupled to the choice of the right process flowsheet. In this work, we integrate superstructure‐based flowsheet design into the design of processes and molecules. The thermodynamic properties of the molecule are modeled by the PC‐SAFT equation of state. Computer‐aided molecular design enables considering the molecular structure as degree of freedom in the process optimization. To consider the process flowsheet as additional degree of freedom, a superstructure of the process is used. The method results in the optimal molecule, process, and flowsheet. We demonstrate the method for the design of an organic Rankine cycle considering flowsheet options for regeneration, reheating, and turbine bleeding. The presented method provides a user‐friendly tool to solve the integrated design problem of processes, molecules, and process flowsheets.

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“…For the prediction of EHS properties, other techniques common to the machine learning community are more frequently applied, e.g., k -nearest neighbor methods . Molecular design methods for solvent selection have been applied to some specific applications such as reactions − and separations in general, the latter including adsorption and absorption, , extraction, , and crystallization …”

Section: Introductionmentioning

confidence: 99%

Systematic Green Solvent Selection for the Hydroformylation of Long-Chain Alkenes

Linke

McBride

Sundmacher

2020

ACS Sustainable Chem. Eng.

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When selecting solvents, not only thermodynamic criteria but also environmental, health, and safety (EHS) properties should be considered. To this end, we present a fully automated solvent selection approach for the homogeneous catalyzed hydroformylation of 1-decene in a temperature-dependent thermomorphic multicomponent system (TMS) using the conductor-like screening model for real solvents (COSMO-RS). The state-of-the-art TMS uses N,N-dimethylformamide (DMF) as the catalyst carrier, which is developmentally toxic, thereby demanding replacement. In order to evaluate the EHS properties holistically, 30 predictive EHS models for 15 different properties are considered in the solvent selection framework, as well as the reliability of the predictions. From a database containing approximately 7800 molecules, the most promising candidates are identified. The best solvent among them, diethyl sulfoxide (DESO), is predicted as outperforming DMF as a catalyst solvent in the hydroformylation. The evidence suggests that DESO may be a broadly applicable environmentally benign substitute solvent for DMF.

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A QM-CAMD approach to solvent design for optimal reaction rates

Cited by 41 publications

References 58 publications

Solvent selection for chemical reactions: automated computational screening of solvents using the SMD model

Solvent selection for chemical reactions: automated computational screening of solvents using the SMD model

Integrating superstructure‐based design of molecules, processes, and flowsheets

Systematic Green Solvent Selection for the Hydroformylation of Long-Chain Alkenes

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