Design of formulated products: A systematic methodology

In chemical product design one tries to find a product which exhibits the desired (target) behavior specified a priori. The identity of the ingredients of chemical‐based products maybe unknown at the start, but some of their desired qualities and functions are usually known. A systematic model‐based computer‐aided methodology for design and verification of a class of chemical‐based products (liquid formulations) is presented. This methodology is part of an integrated three‐stage approach for design/verification of liquid formulations where stage‐1 generates a list of feasible product candidates and/or verifies a specified set through a sequence of predefined activities (work‐flow). Stage‐2 and stage‐3 (not presented here) deal with the planning and execution of experiments, for product validation. Four case studies have been developed to test the methodology. The computer‐aided design (stage‐1) of a paint formulation and an insect repellent lotion are presented. © 2011 American Institute of Chemical Engineers AIChE J, 2011     

Product design in price‐competitive markets: A case study of a skin moisturizing lotion

In this article, we apply a recently developed method for product design to the formulation of skin lotions and extend its application to consider price‐competitive markets. The method is based on the use of consumer preference functions that are in turn parameters of price‐demand relations. These relationships are then embedded in a business model that aims at determining the optimal lotion formulation from the profitability point of view. The model allows to distinguish the formulation that leads to the consumer most preferred skin lotion from the most profitably one in a quantitative fashion. In the latter case, the selling price is also determined simultaneously with the optimal formulation. The example analyzed shows that the consumer most preferred lotion is not profitable, whereas a slightly less preferred lotion is very profitable. We then extend the new product design procedure to consider a competitive environment in which prices of all competitors, change dynamically until equilibrium is established. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

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.     

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 formulation of the property constraint for crystal morphology. This involves crystallization experiments and 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 productcharacterization via scanning electron microscopy, powder X-ray diffraction imaging and Fourier transform spectra analysis.     

洗手液市场透视

随着人们生活水平的提高及消费观念的转变，洗手液已逐渐成为传统洁手用品的替代品，市场前景十分广阔。目前国内的洗手液市场仍处于启蒙认知阶段，产品的生命周期长，因而进入市场的机会更多。从洗手液的产品特性和市场前景来看，它是一个蕴藏着丰富市场潜力的产品。对目前洗手液市场的领先品牌进行了分析。     

仿生乳霜呵护沐浴露

采用类似健康皮肤脂质、皮脂和天然保湿因子NMF的乳霜 ,将其添加于混合型沐浴露中 ,探讨了乳霜用量对产品泡沫、粘度、pH值、稳定性的影响 ,进而确定了仿生乳霜呵护沐浴露的配方 ,并对最终产品进行了人体实洗评价 ,从而得到了一种能对皮肤提供良好滋润的仿生乳霜呵护沐浴露     

洗手液市场略览

随着人们生活水平的提高及消费观念的转变，洗手液已逐渐成为传统洗手用品用替代品，市场前景十分广阔，但市场刚刚启动，目前尚未被人们广泛认知和使用。因此，从洗手液的产品特性、市场前景来看，它是一个市场生命周期长、蕴藏着丰富市场潜力的产品。洗手液的产品定位应是“个人日常清洁护理用品”，功能诉求应以“清除污垢、消毒杀菌”、“使用卫生、方便”为主。同时“辟味、止手汗、滋润、保湿、防脱皮、抗皱、防衰老和美白”等也是应考虑的辅助诉求点。     

An Integrated Approach for the Design of Emulsified Products

Consumer-oriented chemical-based products, including emulsified ones, are structured products constituted by numerous chemicals, and they are used every day by millions of people. They are still mainly designed through trial-and-error-based experimental techniques. A systematic approach, integrating model- and experiment-based techniques, for design of these products could significantly reduce both time and cost connected to product development by doing only the necessary experiments and ensuring chances for innovation. In this work, we present an integrated methodology for the design of emulsified formulated products. The methodology consists of three stages: the problem definition stage, the model-based design stage, and the experiment-based verification stage. In the problem definition stage, the consumer needs are translated into a set of target thermophysical properties and into a list of categories of ingredients, which are to be included in the formulation via a robust knowledge base. In the model-based design stage, structured databases, dedicated algorithms, and a property model library are employed for designing a candidate base case formulation. Finally, in the experiment-based verification stage, the properties and performances of the proposed formulation are measured by means of tailor-made experiments. The formulation is then validated or, if necessary, refined thanks to a systematic list of actions. All these tools have been implemented as a new template in our in-house software called the Virtual Product-Process Design Laboratory and have been illustrated via a case study (a hand wash detergent) where the complete methodology (all three stages) is for the first time applied. © 2018 American Institute of Chemical Engineers AIChE J, 65: 75–86, 2019     

Experimental evaluation of an approach to online redesign of experiments for parameter determination

The online redesign of experiments for parameter determination of nonlinear dynamic systems has been studied recently by different research groups. In this article, this technique is assessed in a real case study for the first time. The presented algorithm adopts well‐known concepts from model‐based control. Compared to previous studies, special attention is given to the efficient treatment of the underlying nonlinear and possibly ill‐conditioned parameter estimation and experiment design problems. These problems are solved with single shooting and gradient‐based nonlinear programming (NLP) solvers. We use an initial value solver, which generates first‐ and second‐order sensitivities to compute exact derivatives of the problem functions. As a special feature, we propose the integration of a local parameter identifiability analysis and a corresponding algorithm that generates well‐conditioned problems. The practical applicability is demonstrated by experimental application to a chromatography column system where A, D, and E optimal experiments are performed. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1981–1995, 2013     

A grand model for chemical product design

Chemical engineering has been expanding its focus from primarily business-to-business products (B2B) to business-to-consumer (B2C) products. The production of B2B products generally emphasizes on process design and optimization, whereas the production of B2C products focuses on product quality, ingredients and structure. Market and competitive analysis, government policies and regulations have to be explicitly considered in product design. All these considerations are accounted for in the Grand Product Design Model, which consists of a process model, a property model, a quality model, a cost model, a pricing model, an economic model as well as factors such as company strategy, government policies and regulations. This article introduces the model and highlights selected aspects of the model with two case studies. One is a die attach adhesive that illustrates how pricing affects profitability, and how product composition changes with market conditions. Another is a hand lotion that illustrates how product quality affects the profit.     

Design of polymeric materials: Experiences and prescriptions

As process engineering has matured, research interest has shifted towards polymer product quality. In the past 20 years or so, the shift has progressed even further, as interest in polymer product quality has morphed into polymer product design. Product design is intended to be a targeted pursuit of optimal conditions that will yield polymers with desirable properties for a specific application. This can be achieved by following a systematic design framework that employs sequential, iterative steps informed by prior knowledge and experience. This overview provides some background information regarding the need for design (including some examples from previous experience), especially in terms of structure‐property relationships. When links between kinetics (synthesis conditions), polymer structure, and application properties are well‐understood, it becomes possible to essentially reverse‐engineer the polymeric material; the researcher can start with known application requirements and synthesize polymers with tailor‐made properties using an optimized recipe (according to the polymerization kinetics). A suggested design approach is presented herein, followed by the application of the design approach to two large case studies. The number of applications for polymeric materials is essentially limitless; the current work provides typical examples of a systematic polymeric material design framework (and related case studies).     

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     

南美蟛蜞菊洗手液的研制

以南美蟛蜞菊为原料提取制备叶绿素铜钠盐,添加相关试剂后制成具有清洁、杀菌的洗手液。通过正交试验,确定了洗手液的最佳配方:19 g复合表面活性剂、4.05 g羧甲基维生素钠、9 mL甘油、3 mL叶绿素铜钠盐、220 mL蒸馏水、3.51 g柠檬酸、适量香精。     

Product color emotional design adaptive to product shape feature variation

When a user selects a product, he/she considers the emotional experience induced by the product color. However, when affected by product shape feature, the color image perception space of a user becomes more complex and dynamic. To address this problem, a product color emotional design method adaptive to product shape feature variation is proposed in this article. Based on psychological means, factor analysis and semantic differential methods are used to elucidate the mechanism for the formation of a color image perception space of a user influenced by product shape feature. Using support vector regression, a product color image evaluation model adaptive to product shape feature variation is constructed, and is then optimized via a genetic algorithm. A corresponding design system is constructed based on the method proposed in this article. A case study involving the design of a thermos for children is presented to demonstrate the operational procedure involved in the proposed method and to verify its performance. The results of the verification experiments confirm that the design scheme from system recommendation essentially meets the anticipated image target and assists the designer effectively. The method and system proposed in this study can generate a product color design scheme, which is unconstrained by shape feature and can satisfy user emotional preferences and needs, and have a certain applicability and practicability.     

Probabilistic Design space determination in pharmaceutical product development: A Bayesian/latent variable approach

To find the design space (DS) of a pharmaceutical process, quantification of the “assurance of quality” for the product under development is required. In this study, latent‐variable modeling is combined with multivariate Bayesian regression to identify a subset of input combinations (process operating conditions and raw materials properties) within which the DS of the product will lie at a probability equal to, or greater than, an assigned threshold. Partial least‐squares regression is used to obtain a linear transformation between the original multidimensional input space and a low‐dimensional latent space. The input domain is then discretized on its lower dimensional representation and a Bayesian posterior predictive approach is used to quantify the probability that the critical quality attributes of the product will meet their specifications for each discretization point. The methodology is tested on two case studies taken from the literature, one of which involving experimental data. The ability of the proposed approach to obtain a probabilistic identification of the DS, while simultaneously reducing the computational burden for the discretization of the input domain and providing a simple graphical representation of the DS, is shown. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2438–2449, 2018     

A new approach to batch process optimization using experimental design

Empirical and mechanistic experimental design methods are combined to construct partial models, which are, thus, used to design a process. The grid algorithm restricts the next experimental point to potential process optima, according to the confidence intervals around the optimal points, and works with any experimental design algorithm such as D‐optimal. Two case studies show the advantages of implementing the grid algorithm. On average the improvement due to the grid algorithm was 15–20% in the first case study. The second case study is based on thin film growth using four potential models, with the most probable model used for experimental design. The grid algorithm balances the trade‐off between two extremes: D‐optimal designs and sampling at the predicted optimal point. The methodology presented shows that the experimenter does not have to decide ahead of time on purely empirical or mechanistic experimental design methods, since both may be useful. © 2008 American Institute of Chemical Engineers AIChE J, 2009     

Transfer of a nanoparticle product between different mixers using latent variable model inversion

An experimental nanoparticle preparation process by solvent displacement in passive mixers is considered. The problem under investigation is to estimate the operating conditions in a target device (Mixer B) in order to obtain a product of assigned properties that has already been manufactured in a source device of different geometry (Mixer A). A large historical database is available for Mixer A, whereas a limited historical database is available for Mixer B. The difference in device geometries causes a different mixing performance within the devices, which is very difficult to capture using mechanistic models. The problem is further complicated by the fact that Mixer B can only be run under an experimental setup that is different from the one under which the available historical dataset was obtained. A joint‐Y projection to latent structures (JY‐PLS) model inversion approach is used to transfer the nanoparticle product from Mixer A to Mixer B. The Mixer B operating conditions estimated by the model are tested experimentally and confirm the model predictions within the experimental uncertainty. Since the inversion of the JY‐PLS model generates an infinite number of solutions that all lie in the so‐called null space, experiments are carried out to provide (to the authors' knowledge) the first experimental validation of the theoretical concept of null space. Finally, by interpreting the JY‐PLS model parameters from first principles, the understanding of the system physics is improved. © 2013 American Institute of Chemical Engineers AIChE J, 60: 123–135, 2014     

Product design: Nanoparticle‐Loaded polyvinyl butyral interlayer for solar control

A systematic procedure for the design of nanoparticle‐loaded polyvinyl butyral (PVB) interlayer for solar control applications is developed. Desirable product attributes—transparency, energy savings, pleasant color, and so on and the related product specifications—transmittance of visible light, solar heat gain coefficient, color coordinates, and so on are met by properly selecting the type(s) of nanoparticles, their volume fraction in the PVB interlayer, and so on. The selection is based on the Maxwell Garnett relation to account for the localized surface plasmon resonance of the nanoparticles, Beer–Lambert's law, various international standards, and a database of transmittance and reflectance developed in our laboratory. The final product that meets all the product specifications as verified by prototypes is obtained by iterating between predictions and experiments. A causal table is provided to guide the verification step. Two examples of preparing solar control PVB interlayers with different specifications are provided to illustrate this design procedure. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3614–3624, 2018     

The role of individual colour preferences in consumer purchase decisions

The purpose of this study is to test whether consumers' personal colour preferences (in an abstract sense rather than for a particular product) affect their intended product purchase decisions if they are given various colour choices. This work employs two experiments with visual components to investigate which colour a participant would choose if asked to select a product to purchase when there is a range of colours available. Two experiments were also designed to elicit a response about which colour each participant prefers (in an abstract sense). The study finds that personal colour preferences affect intended product‐colour purchase decisions but that the extent of this varies from one product category to the next. Further analysis reveals that personal colour preferences are secondary to factors such as colour functionality and colour performance. This work presents new experimental data about the role of colour in product and product packaging on intended consumer purchase decisions. A conceptual framework, supported by the experimental findings, are understanding the relationship between individual colour preferences and product‐choice colours, and more functional aspects of colour itself (such as the effect of colour on product's performance or functionality).