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Polyamide 11 (PA11) and copolyester (TPC-E) were compounded through melt extrusion with low levels (below 10%) of expanded graphite (EG), aiming at the manufacturing of a thermally and electrically conductive composite resistant to friction and with acceptable mechanical properties. Thermal characterisation showed that the EG presence had no influence on the onset degradation temperature or melting temperature. While the specific density of the produced composite materials increased linearly with increasing levels of EG, the tensile modulus and flexural modulus showed a significant increase already at the introduction of 1 wt% EG. However, the elongation at break decreased significantly for higher loadings, which is typical for composite materials. We observed the increase in the dielectric and thermal conductivity, and the dissipated power displayed a much larger increase where high frequencies (e.g., 10 GHz) were taken into account. The tribological results showed significant changes at 4 wt% for the PA11 composite and 6 wt% for the TPC-E composite. Morphological analysis of the wear surfaces indicated that the main wear mechanism changed from abrasive wear to adhesive wear, which contributes to the enhanced wear resistance of the developed materials. Overall, we manufactured new composite materials with enhanced dielectric properties and superior wear resistance while maintaining good processability, specifically upon using 4–6 wt% of EG., QC 20240425

The three-dimensional arrangement of natural and synthetic network materials determines their application range. Control over the real-time incorporation of each building block and functional group is desired to regulate the macroscopic properties of the material from the molecular level onwards. Here we report an approach combining kinetic Monte Carlo and molecular dynamics simulations that chemically and physically predicts the interactions between building blocks in time and in space for the entire formation process of three-dimensional networks. This framework takes into account variations in inter- and intramolecular chemical reactivity, diffusivity, segmental compositions, branch/network point locations and defects. From the kinetic and three-dimensional structural information gathered, we construct structure–property relationships based on molecular descriptors such as pore size or dangling chain distribution and differentiate ideal from non-ideal structural elements. We validate such relationships by synthesizing organosilica, epoxy–amine and Diels–Alder networks with tailored properties and functions, further demonstrating the broad applicability of the platform.

The strength of combining experimental design and advanced kinetic Monte Carlo (kMC) modeling to understand step-growth network synthesis, commencing with a linear/star polymeric precursor, is illustrated considering three chemistries: (i) para-fluoro-thiol reaction (PFTR); (ii) nitrile imine-mediated tetrazole-ene cycloaddition (NITEC); and (iii) star poly(ethylene oxide-stat-propylene oxide) (sPEG)-amine-epoxy click reaction. Chemical parameters are determined based on small-molecule systems (monofunctional analogues) and diffusion parameters based on literature data and higher-network-yield data. Overall model validation is performed considering molar mass and spectroscopic experimental data. As basic support, kMC modeling provides the evolution of the complete size exclusion chromatography trace for both the soluble and the insoluble fraction at any time. In more detail, kMC modeling allows one to construct, whenever desired, two-dimensional traces such as the distribution of species with a given molar mass and number of cross-linking points (CPs) of a given type (e.g., with at least three cross-links), still differentiating between the soluble and insoluble fractions. Ultimately, postprocessing of kMC modeling results allows one to calculate distributions regarding distances between specific functional groups and the molecular pore size distribution upon considering a three-dimensional representation of the molecular buildup of individual network molecules. Also, the (relative) importance of reaction pathways can be assessed. It is, for instance, shown that diffusional limitations on intermolecular reactions determine how far a polymer network yield can be pushed, with a strong effect due to an intrinsically fast maleimide incorporation step, specifically for NITEC. Too long linear precursor building blocks should be avoided as they induce too prominent diffusional limitations. Too short linear precursor building blocks promote intramolecular reactions. With

The [4+4] photocycloaddition of anthracene is one of most relevant photoreactions and is widely applied in materials science, as it allows to remote-control soft matter material properties by irradiation. However, highly energetic UV irradiation is commonly applied, which limits its application. Herein, the wavelength dependence of the photodimerization of anthracene is assessed for the first time, revealing that the reaction is induced just as effectively with mild visible light (410 nm). To fully establish [4+4] cycloadditions within defined chemical environments, a conceptual framework for the solution kinetics of the photo-dimerization up to long reaction times is established by developing a novel photoreaction rate law that is dependent on individual rate coefficients of the key reaction steps. These coefficients can be determined based on low conversion photochemical experiments. Both differential and integral quantum yields can subsequently be predicted that are strongly time-dependent, highlighting the need for a detailed reaction pathway analysis. The presented approach simplifies a complex photochemical scenario, making the photochemical anthracene dimerization, or potentially any other photochemical dimerization, amenable to a time-dependent understanding at the elementary reaction level.

A detailed kinetic study on the para-fluoro-thiol reaction (PFTR) using experimental analysis and kinetic Monte Carlo modeling is introduced, covering the difference in reactivity of a selected variety of structurally different thiols, uniquely including polymeric thiols. The impact of solvent polarity is evaluated by comparing the results obtained using THF and DMF, with the latter giving the fastest reaction rates. As PFTR involves the formation of a thiolate ion, potential side reactions such as disulfide bond formation are studied both isolated (determination of disulfide rate coefficients) and in competition with PFTR (determination of PFTR rate coefficients and selectivities). It is demonstrated that for star polymer synthesis-employing a polymeric thiol and a trifunctional fluorinated linker-the PFTR reacitivity is influenced by diffusional limitations and that the disulfide formation needs to be considered. Different reaction conditions (e.g. addition of reducing agent) are explored to limit the disulfide bond formation, providing the user a guideline for optimizing PFTR upon application for macromolecular design at high reaction rate.

Free-radical polymerization (FRP) processes are extensively applied for the production of macromolecular materials, since they allow the synthesis of a large variety of vinyl polymers under mild reaction conditions and with a high tolerance toward impurities.[1] Despite the high industrial importance of FRP, the quantitative understanding of radical polymerization kinetics is still incomplete. Accurate knowledge of Arrhenius parameters and rate coefficients for key reactions such as chain initiation, propagation, and termination is a prerequisite for FRP design, particularly when conducted in large-scale reactors, in which temperature control is a key issue.

Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the key areas of chemical engineering, their mathematical foundations, and corresponding modeling techniques. Modern industrial production is based on solid scientific methods, many of which are part of chemical engineering. To produce new substances or materials, engineers must devise special reactors and procedures, while also observing stringent safety requirements and striving to optimize the efficiency jointly in economic and ecological terms. In chemical engineering, mathematical methods are considered to be driving forces of many innovations in material design and process development.Presents the main mathematical problems and models of chemical engineering and provides the reader with contemporary methods and tools to solve themSummarizes in a clear and straightforward way, the contemporary trends in the interaction between mathematics and chemical engineering vital to chemical engineers in their daily workIncludes classical analytical methods, computational methods, and methods of symbolic computationCovers the latest cutting edge computational methods, like symbolic computational methods

Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the key areas of chemical engineering, their mathematical foundations, and corresponding modeling techniques. Modern industrial production is based on solid scientific methods, many of which are part of chemical engineering. To produce new substances or materials, engineers must devise special reactors and procedures, while also observing stringent safety requirements and striving to optimize the efficiency jointly in economic and ecological terms. In chemical engineering, mathematical methods are considered to be driving forces of many innovations in material design and process development.Presents the main mathematical problems and models of chemical engineering and provides the reader with contemporary methods and tools to solve themSummarizes in a clear and straightforward way, the contemporary trends in the interaction between mathematics and chemical engineering vital to chemical engineers in their daily workIncludes classical analytical methods, computational methods, and methods of symbolic computationCovers the latest cutting edge computational methods, like symbolic computational methods

Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the key areas of chemical engineering, their mathematical foundations, and corresponding modeling techniques. Modern industrial production is based on solid scientific methods, many of which are part of chemical engineering. To produce new substances or materials, engineers must devise special reactors and procedures, while also observing stringent safety requirements and striving to optimize the efficiency jointly in economic and ecological terms. In chemical engineering, mathematical methods are considered to be driving forces of many innovations in material design and process development.Presents the main mathematical problems and models of chemical engineering and provides the reader with contemporary methods and tools to solve themSummarizes in a clear and straightforward way, the contemporary trends in the interaction between mathematics and chemical engineering vital to chemical engineers in their daily workIncludes classical analytical methods, computational methods, and methods of symbolic computationCovers the latest cutting edge computational methods, like symbolic computational methods

The "one-pot" "two-step" synthesis of well-defined poly(ethylene oxide-b-N-isopropylacrylamide-b-acrylamido-2-methyl-1-propane sodium sulfonate) (P[EO-b-NIPAm-b-AMPSNa]) triblock copolymers is reported in aqueous medium using atom transfer radical polymerization (ATRP) with Cu(I)Cl.Me6TREN (Me6TREN: tris[(2-dimethylamino) ethyl]amine) as catalyst and N,N-dimethylformamide (DMF) as cosolvent. Polymerization conditions leading to a high end-group functionality (EGF) during the first synthesis step, i.e. the formation of the P(EO-b-NIPAM) diblock copolymer, are selected based on kinetic modeling insights for the corresponding NIPAm ATRP homopolymerization. For these conditions, the significant influence of viscosity effects on the NIPAm ATRP kinetics is illustrated based on dynamic viscosity measurements of the saturated monomer solution and measured William-Landel-Ferry parameters for the polymer. The importance of cyclization and termination reactions for the loss of EGF is shown to be limited. Only at very high conversions, cyclization reactions can lead to a decrease of EGF to a minimal value of ca. 80%.

A detailed kinetic modeling study of the atom transfer radical polymerization (ATRP) of isobornyl acrylate (iBoA) is presented. This study combines a detailed reaction scheme with a systematic approach to account for diffusional limitations. Calculated values for diffusion coefficients and the Williams-Landel-Ferry parameters for poly(iBoA) are based on rheological measurements. A good agreement with experimental data is obtained for the polymerization rate, average chain length, and polydispersity index in conditions ranging from 323 to 348 K for targeted chain lengths varying from 50 to 100 and initial activator/deactivator concentrations between 10-50/0-2.5 mol m(-3). In these conditions, beta C-scission reactions are insignificant and backbiting reactions result in a slight decrease of the polymerization rate and level of control at high conversions only. Termination is subject to diffusional limitations during the whole ATRP, while diffusional limitations on deactivation cannot be neglected at higher conversion. Diffusional limitations are shown to be codetermined by the evolution of the chain length distribution of both the end-chain and mid-chain macromolecular species.