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For optimization of production processes and product quality, often knowledge of the factors influencing the process outcome is compulsory. Thus, process analytical technology (PAT) that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality. The present study aims at characterizing a well-known industrial process, the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters (FAME) for usage as biodiesel in a continuous micro reactor set-up. To this end, a design of experiment approach is applied, where the effects of two process factors, the molar ratio and the total flow rate of the reactants, are investigated. The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield. The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression. The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis. A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination (R²) of 0.9608. Thus, we applied a PAT approach to generate further insight into this established industrial process.
Monodisperse porous poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate) particles are widely applied in different fields, as their pore properties can be influenced and functionalization of the epoxy group is versatile. However, the adjustment of parameters which control morphology and pore properties such as pore volume, pore size and specific surface area is scarcely available. In this work, the effects of the process factors monomer:porogen ratio, GMA:EDMA ratio and composition of the porogen mixture on the response variables pore volume, pore size and specific surface area are investigated using a face centered central composite design. Non-linear effects of the process factors and second order interaction effects between them were identified. Despite the complex interplay of the process factors, targeted control of the pore properties was possible. For each response a response surface model was derived with high predictive power (all R2 predicted > 0.85). All models were tested by four external validation experiments and their validity and predictive power was demonstrated.
Allyls
(2022)
This chapter addresses the importance and usage of the commercially low-volume thermoset plastics group known as allyls. The three significant subelements of this group are poly(diallylphthalates), poly(diallylisophthalates), and poly(allyldiglycol carbonate). Chemistry, processing, and properties are also described. Allyl polymers are synthesized by radical polymerizations of allyl monomers that usually do not produce high-molecular-mass macromolecules. Therefore only a few specific monomers can produce thermosetting materials. Diallyldiglycolcarbonate (CR-39) and diallylphthalates are the most significant examples that have considerably improved our everyday life.
Unsaturated polyester resins (UPR) and vinyl ester resins (VER) are among the most commercially important thermosetting matrix materials for composites. Although comparatively low cost, their technological performance is suitable for a wide range of applications, such as fiber-reinforced plastics, artificial marble or onyx, polymer concrete, or gel coats. The main areas of UPR consumption include the wind energy, marine, pipe and tank, transportation, and construction industries.
This chapter discusses basic UPR and VER chemistry and technology of manufacturing, and consequent applications. Some important properties and performance characteristics are discussed, such as shrinkage behavior, flame retardance, and property modification by nanoparticles. Also briefly introduced and described are the practical aspects of UPR and VER processing, with special emphasis on the most widely used technological approaches, such as hand and spray layup, resin infusion, resin transfer molding, sheet and bulk molding, pultrusion, winding, and centrifugal casting.
Cross-linked thermoplastics
(2022)
Cross-linked thermoplastics represent an important class of materials for numerous applications such as heat-shrinkable tubing, rotational molded parts, and polyolefin foams. By cross-linking olefins, their mechanical performance can be significantly enhanced. This chapter covers the three main methods for the cross-linking of thermoplastics: radiation cross-linking, chemical cross-linking with organic peroxides, and cross-linking using silane-grafting agents. It also considers the major effects of the cross-linking procedure on the performance of the thermoplastic materials discussed.
Silicones
(2022)
Silicones are found in a variety of applications with requirements that range from long life at elevated temperatures to fluidity at low temperatures. This chapter first considers silicone elastomers and their application in room temperature vulcanizing (RTV) and heat curing systems (HTV). Also, new technologies for UV curing are introduced. Coverage of RTVs includes both one-component and two-component systems and the different cure chemistries of each and is followed by a separate discussion of silicone laminates. Due to the high importance of silicone fluids, they are also discussed. Fluids include polishes, release agents, surfactants, and dielectric fluids.
Cyanate ester resins
(2022)
Cyanate ester resins are an important class of thermosetting compounds that experience an ever-increasing interest as matrix systems for advanced polymer composite materials, which among other application fields are especially suitable for highly demanding applications in the aerospace or microelectronics industries. Other names for cyanate ester resins are cyanate resins, cyanic esters, or triazine resins. The various types of cyanate ester monomers share the –OCN functional group that trimerizes in the course of resin formation to yield a highly branched heterocyclic polymeric network based on the substituted triazine core structure.
Process analysis and process control have attracted increasing interest in recent years. The development and application of process analytical methods are a prerequisite for the knowledge-based manufacturing of industrial goods and allow for the production of high-value products of defined, constantly good quality. Discussed in this chapter are the measurement principle and some relevant aspects and illustrative examples of online monitoring tools as the basis for process control in the manufacturing and processing of thermosetting resins. Optical spectroscopy is featured as one of the main process analytical methods applicable to, among other applications, online monitoring of resin synthesis. In combination with chemometric methods for multivariate data analysis, powerful process models can be generated within the framework of feedback and feed-forward control concepts. Other analytical methods covered in this chapter are those frequently used to control further processing of thermosets to the final parts, including dielectric analysis, ultrasonics, fiber optics, and Fiber Bragg Grating sensors.
Self-healing thermosets
(2022)
This chapter discusses the basic extrinsic, intrinsic, and combined extrinsic/intrinsic strategies for equipping thermosetting polymers with self-healing properties. The main focus will be on the presentation of a holistic optimization of thermosetting materials, that is, on a simultaneous optimization of both self-healing and other, specialized material properties. Due to their very rigid, highly cross-linked three-dimensional structure, thermosetting polymers require special chemical strategies to achieve self-healing properties. The main chemical strategies available for this will be briefly outlined. The examples given illustrate interesting and/or typical procedures and serve as an inspiration to find solutions for your own applications. They summarize important recent development in research and technology aiming toward multifunctional truly smart self-healing thermosetting materials. An important aspect in this topic area is also how precisely the self-healing effects are analytically checked, quantified, and evaluated. A range of measuring methods is available for this purpose. In this chapter, the most important analytical tools for testing self-healing properties are briefly introduced and highlighted with some illustrative examples.
Metalworking fluids (MWFs) are widely used to cool and lubricate metal workpieces during processing to reduce heat and friction. Extending a MWF’s service life is of importance from both economical and ecological points of view. Knowledge about the effects of processing conditions on the aging behavior and reliable analytical procedures are required to properly characterize the aging phenomena. While so far no quantitative estimations of ageing effects on MWFs have been described in the literature other than univariate ones based on single parameter measurements, in the present study we present a simple spectroscopy-based set-up for the simultaneous monitoring of three quality parameters of MWF and a mathematical model relating them to the most influential process factors relevant during use. For this purpose, the effects of MWF concentration, pH and nitrite concentration on the droplet size during aging were investigated by means of a response surface modelling approach. Systematically varied model MWF fluids were characterized using simultaneous measurements of absorption coefficients µa and effective scattering coefficients µ’s. Droplet size was determined via dynamic light scattering (DLS) measurements. Droplet size showed non-linear dependence on MWF concentration and pH, but the nitrite concentration had no significant effect. pH and MWF concentration showed a strong synergistic effect, which indicates that MWF aging is a rather complex process. The observed effects were similar for the DLS and the µ’s values, which shows the comparability of the methodologies. The correlations of the methods were R2c = 0.928 and R2P = 0.927, as calculated by a partial least squares regression (PLS-R) model. Furthermore, using µa, it was possible to generate a predictive PLS-R model for MWF concentration (R2c = 0.890, R2P = 0.924). Simultaneous determination of the pH based on the µ’s is possible with good accuracy (R²c = 0.803, R²P = 0.732). With prior knowledge of the MWF concentration using the µa-PLS-R model, the predictive capability of the µ’s-PLS-R model for pH was refined (10 wt%: R²c = 0.998, R²p = 0.997). This highlights the relevance of the combined measurement of µa and µ’s. Recognizing the synergistic nature of the effects of MWF concentration and pH on the droplet size is an important prerequisite for extending the service life of an MWF in the metalworking industry. The presented method can be applied as an in-process analytical tool that allows one to compensate for ageing effects during use of the MWF by taking appropriate corrective measures, such as pH correction or adjustment of concentration.