Computer‐aided design of tailor‐made ionic liquids

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. © 2013 American Institute of Chemical Engineers AIChE J, 59: 4627–4640, 2013     

COSMO‐based computer‐aided molecular/mixture design: A focus on reaction solvents

In this article, we investigate reaction solvent design using COSMO‐RS thermodynamics in conjunction with computer‐aided molecular design (CAMD) techniques. CAMD using COSMO‐RS has the distinct advantage of being a method based in quantum chemistry, which allows for the incorporation of quantum‐level information about transition states, reactive intermediates, and other important species directly into CAMD problems. This work encompasses three main additions to our previous framework for solvent design (Austin et al., Chem Eng Sci. 2017;159:93–105): (1) altering the group contribution method to estimate hydrogen‐bonding and non‐hydrogen‐bonding σ‐profiles; (2) ab initio modeling of strong solute/solvent interactions such as H‐bonding or coordinate bonding; and (3) solving mixture design problems limited to common laboratory and industrial solvents. We apply this methodology to three diverse case studies: accelerating the reaction rate of a Menschutkin reaction, controlling the chemoselectivity of a lithiation reaction, and controlling the chemoselectivity of a nucleophilic aromatic substitution reaction. We report improved solvents/mixtures in all cases. © 2017 American Institute of Chemical Engineers AIChE J, 63: 104–122, 2018     

Computer‐aided design of ionic liquids as solvents for extractive desulfurization

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     

Effective solvent system selection in the recrystallization purification of pharmaceutical products

This treatment describes the details of a methodical three step algorithm for determining the best operating conditions for the recrystallization separations of solid mixtures for the chosen targeted solvent systems. Our algorithm was applied to effectively separate a representative pharmaceutical product (caffeine) from a related pharmaceutical product (theophylline). The limitations of such calculations with currently available, widely used predictive methods for computing solution thermodynamics without experimental data are directly examined. Also presented here is a novel two stage recrystallization procedure which can potentially dramatically improve the overall recovery yields of the desired products. These systematic selection calculations described herein should enable researchers to quickly screen many potential solvent systems and operating conditions and concentrate experimental efforts only on the most promising candidates for such purifications.     

通过模型为基础的溶液选择来调控药品化合物的形貌

In this paper we present a strategy for tuning the crystal morphology of pharmaceutical compounds by the appropriate choice of solvent via an optimization model. A three-stage approach involving a pre-design stage, a product design stage and a post-design experimental verification stage is presented. The pre-design stage addresses the tormulation of the property constraint tor crystal morphology. This involves crystallization experiments aria development of property models and constraints for morphology. In the design stage various property requirements for the solvent along with crystal morphology are considered and the product design problem is formulated as a mixed integer nonlinear programming model.The design stage provides an optimal solvent/list of candidate solvents. Similar to the pre-design stage, in the post design experimental verification stage, the morphology of the crystals （precipitated from the designed solvent） is verified through crystallization experiments followed by product characterization via scanni＇ng electron microscopy, powder X-ray diffraction imaging and Fourier transform spectra analysis.     

溶剂极性响应型丁基-环四联吡啶提锂分子的合成及性能研究

盐湖卤水提锂已逐渐成为我国锂及锂产品的生产途径之一,而我国盐湖卤水高镁锂比的特点导致锂离子提取难度大。传统溶剂萃取提锂过程中需使用大量协萃剂和高浓度酸,产品纯度低、危险度高。设计合成了一种具有溶剂极性响应性分子结构“异构互变”的丁基-环四联吡啶提锂分子,实现极性条件下“络合”锂,非极性条件下“释放”锂。核磁共振氢谱和高分辨质谱证实了目标分子结构的准确性,通过对比Li⁺和Mg²⁺存在时目标分子的光谱性质表明丁基-环四联吡啶分子对锂离子具有较强的选择性。此外,支撑液膜的离子跨膜传输结果进一步表明,丁基-环四联吡啶分子在不同极性溶剂条件下可以实现对锂离子的高选择性提取。     

Integrated solvent and process design for continuous crystallization and solvent recycling using PC‐SAFT

Solvent usage is a major source of environmental waste in pharmaceutical industry. The current paradigm shift toward continuous manufacturing in pharmaceutical industry has renewed the interest in continuous crystallization, which offers the prospect of easy solvent recycling. However, the selection of solvents for an integrated crystallization processes is nontrivial due to the likely trade‐off between optimal solvent properties for crystallization and solvent separation and recycling. A systematic approach for the simultaneous optimization of process conditions and solvent selection for continuous crystallization including solvent recycling is presented. A unified perturbed‐chain statistical associating fluid theory model framework is applied to predict thermodynamic properties related to solubility and vapor‐liquid equilibrium, which is integrated with a process model. A continuous mapping procedure is adopted to solve the optimization problem effectively. A case study based on continuous antisolvent crystallization of paracetamol with solvent separation via flash demonstrates the approach. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1205–1216, 2018     

Optimization‐based framework for computer‐aided molecular design

A new framework to automate, augment, and accelerate steps in computer‐aided molecular design is presented. The problem is tackled in three stages: (1) composition design, (2) structure determination, and (3) extended design. Composition identification and structure determination are decoupled to achieve computational efficiency. Using approximate group‐contribution methods in the first stage, molecular compositions that fit design targets are identified. In the second stage, isomer structures of solution compositions are determined systematically, and structure‐based property corrections are used to refine the solution pool. In the final stage, the design is extended beyond the scope of group‐contribution methods by using problem‐specific property models. At each design stage, novel optimization models and graph theoretic algorithms generate a large and diverse pool of candidates using an assortment of property models. The wide applicability and computational efficiency of the proposed methodology are illustrated through three case studies. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3686–3701, 2013     

Optimal design of solvents for extractive reaction processes

It is well known that solvents can have significant effects on rates and equilibrium compositions of chemical reactions. The computer‐aided molecular design (CAMD) of solvents for heterogeneous liquid phase reactions is challenging due to multiple solvent effects on reaction and phase equilibria. In this work, we propose a CAMD methodology based on a genetic algorithm (GA) for identifying optimal solvents for liquid phase reactions where the objective is to maximize the reaction equilibrium conversion. In particular, a novel molecular encoding method is introduced to facilitate the construction and evaluation of solvent molecules in a defined structure space. The reliability of the method for fast identification of optimal reaction solvents is demonstrated for a selected biphasic esterification reaction. The proposed approach opens up new perspectives for intensifying extractive reaction processes via the purposeful design of solvent molecules. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3238–3249, 2016     

Model‐based design of a plant‐wide control strategy for a continuous pharmaceutical plant

The design of an effective plant‐wide control strategy is a key challenge for the development of future continuous pharmaceutical processes. This article presents a case study for the design of a plant‐wide control structure for a system inspired by an end‐to‐end continuous pharmaceutical pilot plant. A hierarchical decomposition strategy is used to classify control objectives. A plant‐wide dynamic model of the process is used to generate parametric sensitivities, which provide a basis for the synthesis of control loops. Simulations for selected disturbances illustrate that the critical quality attributes (CQAs) of the final product can be kept close to specification in the presence of significant and persistent disturbances. Furthermore, it is illustrated how selected CQAs of the final product can be brought simultaneously to a new setpoint while maintaining the remaining CQAs at a constant value during this transition. The latter result shows flexibility to control CQAs independently of each other. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3671–3685, 2013     

Efficient ant colony optimization for computer aided molecular design: Case study solvent selection problem

In this paper, we propose a novel computer-aided molecular design (CAMD) methodology for the design of optimal solvents based on an efficient ant colony optimization (EACO) algorithm. The molecular design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a solvent performance measure is maximized (solute distribution coefficient) subject to structural feasibility, property, and process constraints. In developing the EACO algorithm, the better uniformity property of Hammersley sequence sampling (HSS) is exploited. The capabilities of the proposed methodology are illustrated using a real world case study for the design of an optimal solvent for extraction of acetic acid from waste process stream using liquid–liquid extraction. The UNIFAC model based on the infinite dilution activity coefficient is used to estimate the mixture properties. New solvents with better targeted properties are proposed.     

A new bubbling extraction tower: Toward liquid–liquid solvent extraction at large aqueous‐to‐oil phase ratios

Enrichment and recovery of valuable components in industrial waste waters by traditional liquid–liquid solvent extraction is not economic due to extremely low concentrations of those targets. Large‐phase‐ratio extraction exhibits potential advantages for recovery of small quantities of target components from large volume of aqueous solutions. A novel bubbling extraction tower is proposed toward performing solvent extraction at large aqueous‐to‐oil phase ratios in this work. Organic extractants were covered onto surface of gas bubbles to form a layer of organic liquid membrane and the dispersed organic phase in tower could be small enough. The target components are extracted from aqueous feed solution onto the surface of the bubbles, and the enrichment ratios could be extremely high. We develop a feasible methodology to calculate tower height and operation phase ratios of the bubbling extraction tower, which is essential for future industrial scale‐up. Experimental results in pilot test are highly consistent with calculations. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3889–3897, 2015     

21世纪的计算机辅助橡胶配方设计

分析了计算机辅助橡胶配方设计实现信息化所面临的问题,指出建立适合橡胶工业特点的数据库积极采用并改进橡胶配方优化设计的各种方法,结合神经网络技术及计算机软件工业的软件开发工具和思想,最络实现配方设计的智能化,网络化,是现代配方优化设计的发展方向。     

A hierarchical method to integrated solvent and process design of physical CO2 absorption using the SAFT‐γ Mie approach

Molecular‐level decisions are increasingly recognized as an integral part of process design. Finding the optimal process performance requires the integrated optimization of process and solvent chemical structure, leading to a challenging mixed‐integer nonlinear programming (MINLP) problem. The formulation of such problems when using a group contribution version of the statistical associating fluid theory, SAFT‐γ Mie, to predict the physical properties of the relevant mixtures reliably over process conditions is presented. To solve the challenging MINLP, a novel hierarchical methodology for integrated process and solvent design (hierarchical optimization) is presented. Reduced models of the process units are developed and used to generate a set of initial guesses for the MINLP solution. The methodology is applied to the design of a physical absorption process to separate carbon dioxide from methane, using a broad selection of ethers as the molecular design space. The solvents with best process performance are found to be poly(oxymethylene)dimethylethers. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3249–3269, 2015