A variety of techniques exist to study the curing behavior of wood adhesives throughout the hot-pressing. Nonetheless, correlating these techniques is challenging, primarily due to the inherent differences in their operational principles and measurement conditions. This study correlates the chemical, rheological and mechanical aspects of adhesive curing using differential scanning calorimetry (DSC), rheometry and Automated Bonding Evaluation System (ABES), respectively. DSC determines the chemical curing degree, and rheometry captures both chemical and physical aspects of curing, while ABES simulates adhesive bond strength development by focusing on mechanical changes. Results reveal that the rheological curing degree exhibits a higher reaction rate than the mechanical curing degree from ABES. DSC was also used to measure the residual enthalpy of adhesives after isothermal curing using rheometry or ABES. The results suggest that the tested adhesives cannot be considered fully chemically cured when complex viscosity and shear strength reach their maximum values. Dynamic DSC analyses were used for the prediction of the curing degree at isothermal conditions. At higher curing temperatures, the differences between the resulting conversion degrees from DSC, rheometry, and ABES techniques decrease. DSC is highly sensitive to reaction onset, while rheometry more accurately tracks curing progress through viscosity changes. ABES lacks sensitivity to chemical progression but offers practical mechanical insights. Furthermore, the time to reach the minimum activation energy was determined using the isoconversional principle. It was found that the activation energy achieves its minimum in the immediate vicinity of the gel and the storage and loss moduli crossover point for tested amino resins.

Miniaturization of liquid chromatography (LC) systems offers numerous advantages. Nevertheless, miniaturized LC is still not widely used. Here, we present the additive manufacturing of hierarchically structured macro- and mesoporous functionalized polymer monoliths and their application for miniaturized reversed-phase chromatographic separations. A CAD-predesigned macroporous structure was generated by 3D printing of a repetitive design of Schoen gyroids from a photoresin via two-photon polymerization. For this, a photoresin formulation was developed containing a porogenic solvent to induce the formation of mesopores and a hydrophobic monomer to achieve a surface functionality suitable for reversed-phase chromatography. This strategy enables independent tuning of macropore geometry and mesoporosity, which is not readily achievable by conventional polymer monolith synthesis. Successful fabrication of hierarchically structured polymer monoliths was demonstrated by scanning electron microscopy and nano-computed tomography. The monolithic stationary phase was connected to a microfluidic system, and chromatographic separation of the nonpolar analytes naphthalene and fluoranthene was demonstrated. This highlights the applicability of the hierarchically structured porous functionalized polymer monolith as a reversed-phase stationary phase.

Monodisperse porous polymer spheres are functional materials with attractive properties such as high cohesive strength, strong adsorptivity, and a high degree of surface functionalization due to their large specific surface area. They are widely used in various fields, including biomedicine, instrumental analytics as stationary phases in HPLC columns, and sensor technology. In this work, the formation mechanism of porous poly(glycidyl methacrylate-co-ethylene dimethacrylate) (p(GMA-co-EDMA)) particles was investigated in a time-resolved experiment using scanning electron microscopy (SEM) and two-dimensional confocal Raman spectroscopy. Data analysis revealed that the particles are formed via rapidly reacting anisotropic Janus-like intermediates that assemble into large agglomerates of different morphologies. Spectral unmixing of the Raman data enabled the determination of relative concentration changes in the reactants over time. This study uncovers a pool of previously unknown anisotropic particle species that offer new opportunities for subsequent functionalization and material design.

The curing process of urea-formaldehyde (UF) resins consists of parallel, consecutive, and competitive reactions, which complicates defining a single activation energy or reaction type. Differential Scanning Calorimetry (DSC) was used to measure reaction enthalpy in joules per gram (J g-1). By conducting DSC experiments at three heating rates, the activation energy, expressed in joules per mole (J mol-1), was determined as a function of conversion degree using the model-free Friedman method. For such multistep reactions, the calculated activation energy represents an average of several reaction steps. The complex composition of UF resin samples further complicates the quantification of “one mole” of adhesive, raising the question of how many moles correspond to the measured enthalpy. To address this, dimethylolurea (DMU) was selected as a simplified model compound. The methylol group, a reactive unit in DMU with known enthalpy and defined molar mass, allowed the establishment of a relationship between activation energy and enthalpy in UF reactions. Since methylol groups are key participants in UF resin curing, they served as representative units for analysis. The results showed that activation energy is considerably higher than reaction enthalpy, emphasizing the dominant role of kinetic barriers in UF curing. These findings provide new insights into UF resin reaction kinetics.

The in-line control of curing during the molding process significantly improves product quality and ensures the reliability of packaging materials with the required thermo-mechanical and adhesion properties. The choice of the morphological and thermo-mechanical properties of the molded material, and the accuracy of their determination through carefully selected thermo-analytical methods, play a crucial role in the qualitative prediction of trends in packaging product properties as process parameters are varied. This work aimed to verify the quality of the models and their validation using a highly filled molding resin with an identical chemical composition but 10 wt% difference in silica particles (SPs). Morphological and mechanical material properties were determined by dielectric analysis (DEA), differential scanning calorimetry (DSC), warpage analysis and dynamic mechanical analysis (DMA). The effects of temperature and injection speed on the morphological properties were analyzed through the design of experiments (DoE) and illustrated by response surface plots. A comprehensive approach to monitor the evolution of ionic viscosity (IV), residual enthalpy (dHrest), glass transition temperature (Tg), and storage modulus (E) as a function of the transfer-mold process parameters and post-mold-cure (PMC) conditions of the material was established. The reliability of Tg estimation was tested using two methods: warpage analysis and DMA. The noticeable deterioration in the quality of the analytical signal for highly filled materials at high cure rates is discussed. Controlling the temperature by increasing the injection speed leads to the formation of a polymer network with a lower Tg and an increased storage modulus, indicating a lower density and a more heterogeneous structure due to the high heating rate and shear heating effect.

Monitoring of molding processes is one of the most challenging future tasks in polymer processing. In this work, the in situ monitoring of the curing behavior of highly filled EMCs (silica filler content ranging from 73 to 83 wt%) and the effect of filler load on curing kinetics are investigated. Kinetic modelling using the Friedman approach was applied using real-time process data obtained from in situ DEA measurements, and these online kinetic models were compared with curing analysis data obtained from offline DSC measurements. For an autocatalytic fast-reacting material to be processed above the glass transition temperature Tg and for an autocatalytic slow-reacting material to be processed below Tg, time–temperature–transformation (TTT) diagrams were generated to investigate the reaction behavior regarding Tg progression. Incorporating a material containing a lower silica filler content of 10 wt% enabled analysis of the effects of filler content on sensor sensitivity and curing kinetics. Lower silica particle content (and a larger fraction of organic resin, respectively) favored reaction kinetics, resulting in a faster reaction towards Tg1. Kinetic analysis using DEA and DSC facilitated the development of highly accurate prediction models using the Friedman model-free approach. Lower silica particle content resulted in enhanced sensitivity of the analytical method, leading, in turn, to more precise prediction models for the degree of cure.

Comparative analysis of the chemical and rheological curing kinetics of formaldehyde-based wood adhesives is crucial for assessing their respective performance. Differential scanning calorimetry (DSC) and rheometry are the conventional techniques used for monitoring the curing processes leading to crosslinking polymerization of the adhesives. However, the direct comparison of these techniques is inappropriate due to the intrinsic differences in their underlying procedures. To address this challenge, the two adhesive samples were sequentially cured, firstly with rheometry and followed by DSC. The observed higher curing degree in the subsequent DSC procedure underpins the incomplete curing of the samples during initial rheometry. Furthermore, the comparative assessment of the activation energies, molar ratios, and active groups of the two adhesives highlights the importance of the pre-exponential factor in addition to the activation energies, as it attributes to the probability of active groups coinciding at the appropriate spatial arrangement.

An epoxy compound’s polymer structure can be characterized by the glass transition temperature (Tg) which is often seen as the primary morphological characteristic. Determining the Tg after manufacturing thermoset-molded parts is an important objective in material characterization. To characterize quantitatively the dependence of Tg on the degree of cure, the DiBenedetto equation is usually used. Monitoring polymer network formation during molding processes is therefore one of the most challenging tasks in polymer processing and can be achieved using dielectric analysis (DEA). In this study, the morphological properties of an epoxy resin-based molding compounds (EMC) were optimized for the molding process using response surface analysis. Processing parameters such as curing temperature, curing time, and injection rate were investigated according to a DoE strategy and analyzed as the main factors affecting Tg as well as the degree of cure. A new method to measure the Tg at a certain degree of cure was developed based on warpage analysis. The degree of cure was determined inline via dielectric analysis (DEA) and offline using differential scanning calorimetry (DSC). The results were used as the response in the DoE models. The use of the DiBenedetto equation to refine the response characteristics for a wide range of process parameters has significantly improved the quality of response surface models based on the DoE approach.

Determining the instant of gelation of formaldehyde-basedwoodadhesives as an assessment parameter for their curing rate is importantfor optimizing the curing behavior. Due to the stoichiometricallyimbalanced networks of formaldehyde-based adhesives, the crossoverpoint of storage G & PRIME; and loss modulus G & DPRIME; cannot unconditionally be assumed as the gel pointin oscillatory time sweeps as the material response is frequency-dependent.This study aims to determine the gel point of selected adhesives bythe isothermal multiwave oscillatory shear test. A thorough comparisonbetween the gel and the crossover point of G & PRIME;and G & DPRIME; is performed. Rheokinetic analysisshowed no significant difference between the activation energies calculatedat the gel point determined by a multiwave test and the crossoverpoint obtained by the time sweep test. Hence, for resins with similarcuring reactions, a reliable determination of gel point by applyinga multiwave test is needed for a comparison of their reactivity.

For optimization of production processes and product quality, often knowledge of the factors influencing the pro-cess 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 impor-tant process factors can help to achieve higher production efficiency and quality. The present study aims at char-acterizing 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 frac-tion 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.

Rapid and robustquality monitoring of the composition of meatpastes is of fundamental importance in processing meat and sausageproducts. Here, an in-line near-infrared spectroscopy/micro-electro-mechanical-system-(MEMS)-basedapproach, combined with multivariate data analysis, was used for measuringthe constituents fat, protein, water, and salt in meat pastes withina typical range of meat paste recipes. The meat pastes were spectroscopicallycharacterized in-line with a novel process analyzer prototype. Byintegrating salt content in the calibration set, robust predictivePLSR models of high accuracy (R (2) >0.81)were obtained that take interfering matrix effects of the minor andNIR-inactive meat paste recipe component "salt" intoaccount as well. The nonlinear blending behavior of salt concentrationon the spectral features of meat pastes is discussed based on a designedmixture experiment with four systematically varied components.

Mesoporous silica microspheres (MPSMs) find broad application as separation materials in high liquid chromatography (HPLC). A promising preparation strategy uses p(GMA-co-EDMA) as hard templates to control the pore properties and a narrow size distribution of the MPMs. Here six hard templates were prepared which differ in their porosity and surface functionalization. This was achieved by altering the ratio of GMA to EDMA and by adjusting the proportion of monomer and porogen in the polymerization process. The various amounts of GMA incorporated into the polymer network of P1-6 lead to different numbers of tetraethylene pentamine in the p(GMA-co-EDMA) template. This was established by a partial least squares regression (PLS-R) model, based on FTIR spectra of the templates. Deposition of silica nanoparticles (SNP) into the template under Stoeber conditions and subsequent removal of the polymer by calcination result in MPSM1-6. The size of the SNPs and their incorporation depends on the pore parameters of the template and degree of TEPA functionalization. Moreover, the incorporated SNPs construct the silica network and control the pore parameters of the MPSMs. Functionalization of the MPSMs with trimethoxy (octadecyl) silane allows their use as a stationary phase for the separation of biomolecules. The pore characteristics and the functionalization of the template determine the pore structure of the silica particles and, consequently, their separation properties.

High-performance liquid chromatography is one of the most important analytical tools for the identification and separation of substances. The efficiency of this method is largely determined by the stationary phase of the columns. Although monodisperse mesoporous silica microspheres (MPSM) represent a commonly used material as stationary phase their tailored preparation remains challenging. Here we report on the synthesis of four MPSMs via the hard template method. Silica nanoparticles (SNPs) which form the silica network of the final MPSMs were generated in situ from tetraethyl orthosilicate (TEOS) in the presence of (3-aminopropyl) triethoxysilane (APTES) functionalized p(GMA-co-EDMA) as hard template. Methanol, ethanol, 2-propanol, and 1-butanol were applied as solvents to control the size of the SNPs in the hybrid beads (HB). After calcination, MPSMs with different sizes, morphology and pore properties were obtained and characterized by scanning electron microscopy, nitrogen adsorption and desorption measurements, thermogravimetric analysis, solid state NMR and DRIFT IR spectroscopy. Interestingly, the 29Si NMR spectra of the HBs show T and Q group species which suggests that there is no covalent linkage between the SNPs and the template. The MPSMs were functionalized with trimethoxy (octadecyl) silane and used as stationary phases in reversed-phase chromatography to separate a mixture of eleven different amino acids. The separation characteristics of the MPSMs strongly depend on their morphology and pore properties which are controlled by the solvent during the preparation of the MPSMs. Overall, the separation behavior of the best phases is comparable with those of commercially available columns. The phases even achieve faster separation of the amino acids without loss of quality.& COPY; 2023 Published by Elsevier B.V.

The hard template method for the preparation of monodisperse mesoporous silica microspheres (MPSMs) has been established in recent years. In this process, in situ-generated silica nanoparticles (SNPs) enter the porous organic template and control the size and pore parameters of the final MPSMs. Here, the sizes of the deposited SNPs are determined by the hydrolysis and condensation rates of different alkoxysilanes in a base catalyzed sol–gel process. Thus, tetramethyl orthosilicate (TMOS), tetraethyl orthosilicate (TEOS), tetrapropyl orthosilicate (TPOS) and tetrabutyl orthosilicate (TBOS) were sol–gel processed in the presence of amino-functionalized poly (glycidyl methacrylate-co-ethylene glycol dimethacrylate) (p(GMA-co-EDMA)) templates. The size of the final MPSMs covers a broad range of 0.5–7.3 µm and a median pore size distribution from 4.0 to 24.9 nm. Moreover, the specific surface area can be adjusted between 271 and 637 m2 g−1. Also, the properties and morphology of the MPSMs differ according to the SNPs. Furthermore, the combination of different alkoxysilanes allows the individual design of the morphology and pore parameters of the silica particles. Selected MPSMs were packed into columns and successfully applied as stationary phases in high-performance liquid chromatography (HPLC) in the separation of various water-soluble vitamins.

Mesoporous silica microspheres (MPSMs) represent a promising material as a stationary phase for HPLC separations. The use of hard templates provides a preparation strategy for producing such monodisperse silica microspheres. Here, 15 MPSMs were systematically synthesized by varying the sol-gel reaction parameters of water-to-precursor ratio and ammonia concentration in the presence of a porous p(GMA-co-EDMA) polymeric hard template. Changing the sol-gel process factors resulted in a wide range of MPSMs with varying particle sizes from smaller than one to several micrometers. The application of response surface methodology allowed to derive quantitative predictive models based on the process factor effects on particle size, pore size, pore volume, and specific surface area of the MPSMs. A narrow size distribution of the silica particles was maintained over the entire experimental space. Two larger-scale batches of MPSMs were prepared, and the particles were functionalized with trimethoxy(octadecyl) silane for the application as stationary phase in reversed-phases liquid chromatography. The separation of proteins and amino acids was successfully accomplished, and the effect of the pore properties of the silica particles on separation was demonstrated.

Film formation of self synthesized Polymer EPM-g-VTMDS (ethylene-propylene rubber, EPM, grafted with vinyltetramethyldisiloxane, VTMDS) was studied regarding bonding to adhesion promoter vinyltrimethoxysilane (VTMS) on oxidized 18/10 chromium/nickel-steel (V2A) stainless steel surfaces. Polymer films of different mixed solutions including commercial siloxane and silicone, dimethyl, vinyl group terminated crosslinker (HANSA SFA 42100, CAS# 68083-19-2, 0.35 mmol Vinyl/g) and platinum, 1,3-diethenyl-1,1,3,3-tetramethyldi-siloxane complex Karstedt's catalyst (ALPA-KAT 1, CAS# 68478-92-2) were spin coated on V2A stainless steel surfaces with adsorbed VTMS thin layers in order to analyze film formation of EPM-g-VTMDS at early stages. Surface topography and chemical bonding of the high performance polymers on different oxidized V2A surfaces were investigated with X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), scanning electron microscopy (SEM) and surface enhanced Raman spectroscopy (SERS). AFM and SEM as well as XPS results indicated that the formation of the polymer film proceeds via growth of polymer islands. Chemical sig-natures of the essential polymer contributions, linker and polymer backbones, could be identified using XPS core level peak shape analysis and also SERS. The appearance of signals which are related to Si-O-Si can be seen as a clear indication of lateral crosslinking and silica network formation in the films on the V2A surface.

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 R2predicted > 0.85). All models were tested by four external validation experiments and their validity and predictive power was demonstrated.

Hybrid organic/inorganic nanocomposites combine the distinct properties of the organic polymer and the inorganic filler, resulting in overall improved system properties. Monodisperse porous hybrid beads consisting of tetraethylene pentamine functionalized poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate) particles and silica nanoparticles (SNPs) were synthesized under Stoeber sol-gel process conditions. A wide range of hybrid organic/silica nanocomposite materials with different material properties was generated. The effects of n(H2O)/n(TEOS) and c(NH3) on the hybrid bead properties particle size, SiO2 content, median pore size, specific surface area, pore volume and size of the SNPs were studied. Quantitative models with a high robustness and predictive power were established using a statistical and systematic approach based on response surface methodology. It was shown that the material properties depend in a complex way on the process factor settings and exhibit non-linear behaviors as well as partly synergistic interactions between the process factors. Thus, the silica content, median pore size, specific surface area, pore volume and size of the SNPs are non-linearly dependent on the water-to-precursor ratio. This is attributed to the effect of the water-to-precursor ratio on the hydrolysis and condensation rates of TEOS. A possible mechanism of SNP incorporation into the porous polymer network is discussed.

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.