A systematic methodology for optimal mixture design in an integrated biorefinery

Biomass is a sustainable source of energy which can be utilised to produce value-added products such as biochemical products and biomaterials. In order to produce a sustainable supply of such value-added products, an integrated biorefinery is required. An integrated biorefinery is a processing facility that integrates multiple biomass conversion pathways to produce value-added products. To date, various biomass conversion pathways are available to convert biomass into a wide range of products. Due to the large number of available pathways, various systematic screening tools have been developed to address the process design aspect of an integrated biorefinery. Process design however, is often inter-linked with product design as it is important to identify the optimal molecule (based on desired product properties) prior to designing its optimal production routes. In cases where the desired product properties cannot be met by a single component chemical product, a mixture of chemicals would be required. In this respect, product and process design decisions would be a challenging task for an integrated biorefinery. In this work, a novel two-stage optimisation approach is developed to identify the optimal conversion pathways in an integrated biorefinery to convert biomass into the optimal mixtures in terms of target product properties. In the first stage, the optimal mixture is designed via computer-aided molecular design (CAMD) technique. CAMD technique is a reverse engineering approach which predicts the molecules with optimal properties using property prediction models. Different classes of property models such as group contribution (GC) models and quantitative structure property relationship (QSPR) are adapted in this work. The main component of the mixture is first determined from the target product properties. This is followed by the identifying of additive components to form an optimal mixture with the main component based on the desired product properties. Once the optimal mixture is determined, the second stage identifies the optimal conversion pathways via superstructural mathematical optimisation approach. With such approach, the optimal conversion pathways can be determined based on different optimisation objectives (e.g. highest product yield, lowest environmental impact etc.). To illustrate the proposed methodology, a case study on the design of fuel additives as a mixture of different molecules from palm-based biomass is presented. With the developed methodology, optimal fuel additives are designed based on optimal target properties. Once the optimal fuel additives are designed, the optimal conversion pathways in terms of highest product yield and economic performance that convert biomass into the optimal fuel additives are identified.     

基于模型的化工产品设计方法——综述与展望

近年来,化学工业的重点持续向亟需大宗化学品及高附加值化工产品的生产转化。这些化工产品的开发不仅需要相应的产品筛选与设计方法,同时需要对其可持续的生产过程、经济效益以及环境影响加以考虑。因此,化工产品的开发是一个系统性的多尺度问题。本文对基于模型的化工产品设计方法进行了综述与展望。基于模型的化工产品设计可以对大量可能的设计结果进行快速的虚拟筛选,从而大大降低实验成本。然而,对于不同的产品类型,准确的模型、数据以及规则方法通常难以获取,从而限制了基于模型方法的大规模应用。另外,产品开发的多尺度、跨学科特性也使得产品设计问题变得非常复杂。因此,为获得创新的设计结果,能够降低产品设计问题复杂度的系统性的建模方法的开发已成为近年来的研究热点。本文综述了近年来化工产品设计方法及应用的研究热点问题,对基于实验、经验规则、数学模型等方法的产品设计模型与相关软件开发进行了系统的回顾,对化工产品设计未来的挑战与机遇进行了讨论。     

An Overview of Computer-aided Molecular and Process Design

Identifying sustainable chemical processes often depends on the choice of enabling materials that directly influence the overall performance. Matching property targets while incorporating adequate process knowledge is essential for optimal material selection. Multi-scale decisions need to be taken simultaneously to determine the optimal process configurations, operating conditions, and material structures. Integrating molecular to process scale decisions within an equation-oriented optimization framework leads to large-scale mixed-integer nonlinear programs (MINLP). Over the years, several solution approaches have been suggested to tackle this issue. Here, the current state-of-the-art in the field of computer-aided molecular and process design (CAMPD) is discussed and key challenges and open questions are highlighted that may stimulate future research.     

A computational toolbox for molecular property prediction based on quantum mechanics and quantitative structure-property relationship

Chemical industry is always seeking opportunities to efficiently and economically convert raw materials to commodity chemicals and higher value-added chemicalbased products.The life cycles of chemical products involve the procedures of conceptual product designs,experimental investigations,sustainable manufactures through appropriate chemical processes and waste disposals.During these periods,one of the most important keys is the molecular property prediction models associating molecular structures with product properties.In this paper,a framework combining quantum mechanics and quantitative structure-property relationship is established for fast molecular property predictions,such as activity coefficient,and so forth.The workflow of framework consists of three steps.In the first step,a database is created for collections of basic molecular information;in the second step,quantum mechanics-based calculations are performed to predict quantum mechanics-based/derived molecular properties(pseudo experimental data),which are stored in a database and further provided for the developments of quantitative structure-property relationship methods for fast predictions of properties in the third step.The whole framework has been carried out within a molecular property prediction toolbox.Two case studies highlighting different aspects of the toolbox involving the predictions of heats of reaction and solid-liquid phase equilibriums are presented.     

A conceptual model for chemical product design

The fundamental principles of chemical product design and associated systematic tools, within a broad domain of chemical products including molecules, formulations, and devices, are still under development. In this article, we propose a simple and fundamental conceptual model that defines the chemical product design problem as the inversion of three central design functions: quality, property, and process functions. The classic iterative cycles of product design problems may be envisioned as alternating between inversion and evaluation of these three functions, or in other words alternating between synthesis and analysis of solutions. On top of the proposed basic structure of the overall design problem, we then discuss the formulation of some subproblems as optimization problems and describe some useful solution tools. Three application examples are provided, including a more detailed case of formulation of a pharmaceutical ointment. © 2014 American Institute of Chemical Engineers AIChE J, 61: 802–815, 2015     

Graph machine learning for design of high-octane fuels

Fuels with high-knock resistance enable modern spark-ignition engines to achieve high efficiency and thus low CO₂ emissions. Identification of molecules with desired autoignition properties indicated by a high research octane number and a high octane sensitivity is therefore of great practical relevance and can be supported by computer-aided molecular design (CAMD). Recent developments in the field of graph machine learning (graph-ML) provide novel, promising tools for CAMD. We propose a modular graph-ML CAMD framework that integrates generative graph-ML models with graph neural networks and optimization, enabling the design of molecules with desired ignition properties in a continuous molecular space. In particular, we explore the potential of Bayesian optimization and genetic algorithms in combination with generative graph-ML models. The graph-ML CAMD framework successfully identifies well-established high-octane components. It also suggests new candidates, one of which we experimentally investigate and use to illustrate the need for further autoignition training data.     

Triggers for chemical product design: A systematic literature review

The product design project is a complex problem because objectives and constraints must be considered simultaneously, the sustainability context is highly relevant and specific, decision-making involves not only customer needs but also of other stakeholders, especially the organization in which the design project takes place. This work presents a systematic literature review of design methodologies for chemical products to identify how that problem has been addressed and which are the future challenges to be met. The review involved the analysis of 262 research papers and 336 patents, classified according to the chemical product type, the design phase studied, and whether they consider association with a business context. The study highlights the need for holistic product design methodologies applicable from the early design stages, covering the assessment of customer needs and the requirements of other stakeholders, as well as the business context where the design process is carried out.     

基于高阶基团贡献法与COSMO-SAC模型的溶剂设计方法

提出了一种基于高阶基团贡献法与类导体屏蔽片段活度系数模型（conductor like screening model-segment activity coefficient, COSMO-SAC）的计算机辅助溶剂设计方法（computer-aided molecular design, CAMD）。首先,基于高阶基团贡献法（higher-order group contribution, GC⁺）与COSMO-SAC模型构建GC⁺-COSMO方法,关联分子基团组合与表面屏蔽电荷密度分布[σ-profiles, p(σ)]、分子空腔体积V_c,实现对二者的高通量预测;然后结合基于简化分子线性输入系统（simplified molecular input line entry system, SMILES）的异构体生成算法与GC⁺-COSMO方法实现CAMD技术对异构体的识别及性质区分;最后,通过目标函数与约束方程组成的混合整数非线性规划模型（mixed integer nonlinear programming, MINLP）来建立溶剂设计问题,进一步采用分解式算法优化求解,实现溶剂优化设计目标。基于以上模型和方法开展了狄尔斯-阿尔德（Diels-Alder, DA）竞争性反应溶剂设计,验证了提出的方法的可行性与有效性。     

Product design – Molecules,devices, functional products,and formulated products

Chemical product design is a multidisciplinary and diverse subject. This article provides an overview of product design while focusing on product conceptualization. Four product types are considered – molecular products, formulated products, devices and functional products. For molecular products, computer-aided design tools are used to predict the physicochemical properties of single molecules and blends. For formulated products, an integrated experiment-modeling approach is used to generate the formula with the specified product attributes. For devices and functional products, conceptual product design is carried out by modeling the product based on thermodynamics, kinetics and transport processes, by performing experiments, and by decision making based on rule-based methods The results are product specifications in terms of the type of ingredients, composition, and the structure, form, shape or configuration of the product.     

基于生命周期评价的离子液体产品设计

离子液体因其优良的物化性质受到越来越多的关注,而生命周期评价(LCA)和生命周期产品设计(LCPD)是实现离子液体产品和过程绿色生产的两大重要工具.本文分别介绍了生命周期评价和生命周期产品设计的内涵和特征,初步建立了离子液体产品生命周期设计评价体系,提出了离子液体产品设计的实施步骤,有助于离子液体设计人员开发出环境友好...     

Computer aided product design tool for sustainable product development

A computer aided product design (CAPD) tool is proposed that finds mixtures matching target properties. Genetic algorithm crossover and mutation operators are completed with insertion or deletion operators adapted for side branches. A new substitution operator is devised for cyclic molecules. The mixture fitness is evaluated by a weighted sum of property performances. Molecules are represented by molecular graphs. They are split into molecular fragments which are built from polyatomic groups. Molecules or molecular fragments can be fixed, constrained or left free for building a new molecule. Building blocks are chemical functional groups or bio-sourced synthons. A specific coding of hydrogen-suppressed atoms is devised that can be used with various property estimation models where atom connectivity information is required. Illustration is provided through three case studies to find levulinic, glycerol and bio-based derivatives as substitute for chlorinated paraffin, methyl p-coumarate ester solvent and blanket wash solvent, respectively.     

Generic mathematical programming formulation and solution for computer-aided molecular design

This short communication presents a generic mathematical programming formulation for computer-aided molecular design (CAMD). A given CAMD problem, based on target properties, is formulated as a mixed integer linear/non-linear program (MILP/MINLP). The mathematical programming model presented here, which is formulated as an MILP/MINLP problem, considers first-order and second-order molecular groups for molecular structure representation and property estimation. It is shown that various CAMD problems can be formulated and solved through this model.     

Type II Polyketide Synthases: A Bioinformatics-Driven Approach

Bioinformatics has become an indispensable tool for natural products research in the genomic era. One of the key challenges is to accurately convert sequence data of a biosynthetic gene cluster into chemical information such as the enzymatic function or the biosynthetic product structure. Type II polyketide synthase is the most bioinformatically well-studied class of non-modular biosynthetic machinery and represents a model system to showcase bioinformatic applications in natural products research. This review takes a bioinformatics-centered perspective and summarizes the past advances and future opportunities of bioinformatics-guided research on type II polyketide synthases. How bioinformatics has contributed to deepen the chemical understanding of type II PKSs will be discussed with the focus on enzymology, evolution, structural prediction of the biosynthetic products, genome mining, and the global analyses of their polyketide products.     

煤大分子结构的计算机模拟

对计算机辅助分子设计在煤科学研究中的应用进行了回顾，介绍了计算机模拟原理、结构模拟和物理性质模拟的过程，并对未来的发展趋势进行了展望．     

基于分子表面电荷密度分布与机器学习的混合物设计方法研究

由于混合物性能的可调控性,当前市场对其关注与日俱增。对于这类产品,基于模型的设计方法由于具有高效性以及普适性,相较于其他产品设计方法得到了更快的发展。但是对于很多性质,如气味、颜色等,准确且普适的模型尚不可得。因此,本文提出了一种基于分子表面电荷密度分布描述符（S描述符）和机器学习模型的混合物设计方法,采用描述符表征产品、再通过机器学习模型将其与性质关联,直接用于混合物产品设计。具体地,根据给定的产品性质需求,机器学习模型直接预测/设计混合物产品的S描述符;然后以欧几里德距离为指标,在给定的数据库中筛选出S描述符满足要求的候选混合物组成。最后,对候选混合物及其组分性质进行实验验证,完成设计。本文以香精的混合替代物设计作为算例,设计得到丙酸叶醇酯的两种混合香精替代物,通过实验对混合物进行了验证。结果表明,混合替代物的气味及其组分的各理化性质均与丙酸叶醇酯相近,证实本文所提出方法的有效性。     

化工产品生命周期设计的研究进展和挑战

通过分析化学工业的现状和化学工程研究的发展趋势,探讨拓宽化工系统工程的研究范畴,基于这种现状的分析,文章探讨了未来的研究应向微观和宏观两个方向扩展,即微观方面扩展到分子模拟为手段的产品设计,宏观方面扩展到适应可持续发展的过程建模。对整个化学供应链的集成进行产品全生命周期分析和评价,对深化过程系统工程的研究提供了机会和挑战。     

煤化工企业新产品开发的方向和对策探讨

总结了煤化工企业新产品开发的经验,指出新产品开发需研究该产品在世界范围内的市场容量、产业规模和原料路线,弄清其政策因素,并考虑环保成本及是否符合国家的产业发展方向。论述了新产品开发的方向与机遇,提出煤制烯烃、煤制二甲醚和煤制油为煤化工几个热点领域,开发有机胺、硫精细化学品及碳一精细化学品将具有好的市场机遇。     

可持续的多功能纳米涂层的设计:一种目标驱动的多尺度系统论方法(英文)

Polymer nanocomposites have a great potential to be a dominant coating material in a wide range of applications in the automotive,aerospace,ship-making,construction,and pharmaceutical industries.However,how to realize design sustainability of this type of nanostructured materials and how to ensure the true optimality of the product quality and process performance in coating manufacturing remain as a mountaintop area.The major challenges arise from the intrinsic multiscale nature of the material-process-product system and the need to manipulate the high levels of complexity and uncertainty in design and manufacturing processes.In this work,the challenging objectives of sustainable design and manufacturing are simultaneously accomplished by resorting to multiscale systems theory and engineering sustainability principles.The principal idea is to achieve exceptional system performance through concurrent characterization and optimization of materials,product and associated manufacturing processes covering a wide range of length and time scales.Multiscale modeling and simulation techniques ranging from microscopic molecular modeling to classical continuum modeling are seamlessly coupled.The integration of different methods and theories at individual scales allows the quantitative prediction of macroscopic system performance from the fundamental molecular behavior.Furthermore,mathematically rigorous and methodologically viable approaches are pursued to achieve sustainability-goal-oriented design of material-process-product systems.The introduced methodology can greatly facilitate experimentalists in novel material invention and new knowledge discovery.At the same time,it can provide scientific guidance and reveal various new opportunities and effective strategies for achieving sustainable manufacturing.The methodological attractiveness will be fully demonstrated by a detailed case study on the design of thermoset nanocomposite coatings.     

Design of formulated products: Experimental component

A systematic methodology for the design and verification of chemical‐based products is proposed. By integrating modeling, and experiments, the search space is efficiently scanned to identify the feasible product candidates. The product design (or verification) problem consists of three stages: computer‐aided design (Stage 1), which generates a list of feasible candidates, experimental planning (Stage 2), which generates a list of experiments and checks the available experimental set‐ups, and experimental testing (Stage 3), which measures the necessary data and verifies the desirable attributes of the final product. The first stage (Stage 1) has been covered in previous publications, along with detailed case studies. The development of Stage 2 and Stage 3 is considered in this article and highlighted through two case studies involving the design and validation of an insect repellent lotion and a sunscreen lotion. © 2011 American Institute of Chemical Engineers AIChE J, 2012