Optimization of batch solution polymerizations: Simulation studies using an inhibitor and a chain-transfer agent

Multiobjective constrained optimizations are carried out to compute optimal operation policies for batch solution polymerizations of styrene. It is shown by simulations how specified values for conversion, average molecular weight, and polydispersity may be achieved through the proper manipulation of the temperature profile and the initial amounts of the initiator, chain-transfer agent (modifier), and inhibitor. The optimizations show that the use of inhibitors and/or modifiers is seldomly required, unless the process economics is taken into consideration or the high-molecular weight chain fraction of the final polymer resin is to be minimized. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 69: 1137–1152, 1998     

Molecular and Biochemical Basis of Fluoroquinolones-Induced Phototoxicity—The Study of Antioxidant System in Human Melanocytes Exposed to UV-A Radiation

Phototoxicity of fluoroquinolones is connected with oxidative stress induction. Lomefloxacin (8-halogenated derivative) is considered the most phototoxic fluoroquinolone and moxifloxacin (8-methoxy derivative) the least. Melanin pigment may protect cells from oxidative damage. On the other hand, fluoroquinolone–melanin binding may lead to accumulation of drugs and increase their toxicity to skin. The study aimed to examine the antioxidant defense system status in normal melanocytes treated with lomefloxacin and moxifloxacin and exposed to UV-A radiation. The obtained results demonstrated that UV-A radiation enhanced only the lomefloxacin-induced cytotoxic effect in tested cells. It was found that fluoroquinolones alone and with UV-A radiation decreased superoxide dismutase (SOD) activity and SOD1 expression. UV-A radiation enhanced the impact of moxifloxacin on hydrogen peroxide-scavenging enzymes. In turn, lomefloxacin alone increased the activity and the expression of catalase (CAT) and glutathione peroxidase (GPx), whereas UV-A radiation significantly modified the effects of drugs on these enzymes. Taken together, both analyzed fluoroquinolones induced oxidative stress in melanocytes, however, the molecular and biochemical studies indicated the miscellaneous mechanisms for the tested drugs. The variability in phototoxic potential between lomefloxacin and moxifloxacin may result from different effects on the antioxidant enzymes.     

Evaluation of biogenic amines and microbial counts throughout the ripening of goat cheeses from pasteurized and raw milk

The effect of the hygienic quality of milk on changes in microbial counts and biogenic amine content was evaluated during ripening of goat cheeses manufactured from pasteurized and raw milks at 1, 14, 30, 60 and 90 d. The original milk, rennet, curd and whey were also included in the study. The pH, salt content and extent of proteolysis in the cheese were also evaluated. Spermidine and spermine were the main amines in raw milk, while they were minor amines in cheeses. Other amines increased markedly during ripening, tyramine being the main amine in cheese made from raw milk and cadaverine and putrescine in those produced from pasteurized milk. Enterobacteriaceae counts decreased during ripening whereas those of lactic acid bacteria increased, especially lactobacilli and enterococci. Cheese made from raw milk showed higher microbial counts during ripening than those made from pasteurized milk, especially for Enterobacteriaceae and enterococci, counts being 2 or 3 log units higher. Raw milk cheese showed remarkably higher biogenic amines compared with pasteurized milk cheeses. Therefore, pasteurization of milk causes a decrease in final biogenic amine content of cheese as a result of the reduction of its microbial counts.     

On the origin of emission and thermal quenching of SRSO:Er3+ films grown by ECR-PECVD

Silicon nanocrystals embedded in a silicon-rich silicon oxide matrix doped with Er³⁺ ions have been fabricated by electron cyclotron resonance plasma-enhanced chemical vapor deposition. Indirect excitation of erbium photoluminescence via silicon nanocrystals has been investigated. Temperature quenching of the photoluminescence originating from the silicon nanocrystals and the erbium ions has been observed. Activation energies of the thermally activated quenching process were estimated for different excitation wavelengths. The temperature quenching mechanism of the emission is discussed. Also, the origin of visible emission and kinetic properties of Er-related emission have been discussed in details.     

Safe reuse in modelling language engineering using model subtyping with OCL constraints

Software and Systems Modeling - Low-code software development promises rapid delivery of software cloud applications by employing domain-specific languages (DSLs), requiring minimal traditional...     

Investigations on the polymorphism of K4CaSi6O15 at elevated temperatures

In the present study, single crystals and polycrystalline material of K₄CaSi₆O₁₅ were prepared from solid-state reactions between stoichiometric mixtures of the corresponding oxides/carbonates. Heat capacity (C_p) measurements above room temperature using a differential scanning calorimeter indicated that two thermal effects occurred at approximately T₁ = 462 K and T₂ = 667 K, indicating the presence of structural phase transitions. The standard third-law entropy of K₄CaSi₆O₁₅ was determined from low-temperature C_p’s measured by relaxation calorimetry using a Physical Properties Measurement System and amounts to S°(298K) = 524.3 ± 3.7 J·mol⁻¹·K⁻¹. For the 1^st transition, the enthalpy change ΔH^tr1 = 1.48 kJ·mol and the entropy change ΔS^tr1 = 3.25 J·mol⁻¹·K⁻¹, whereas ΔH^tr2 = 3.33 kJ·mol⁻¹ and ΔS^tr2 = 5.23 J·mol⁻¹·K⁻¹ were determined for the 2^nd transition. The compound was further characterized by in-situ single-crystal X-ray diffraction between ambient temperature and 1063 K. At 773 K, the high-temperature phase stable above T₂ has the following basic crystallographic data: monoclinic symmetry, space group P2₁/c, a = 6.9469(4) Å, b = 9.2340(5) Å, c = 12.2954(6) Å, β = 93.639(3)°, V = 787.13(7) ų, Z = 2. It belongs to the group of interrupted framework silicates and is based on tertiary (Q³-type) [SiO₄]-tetrahedra. Together with the octahedrally coordinated Ca-cations, a three-dimensional mixed polyhedral network structure is formed, in which the remaining K-ions provide charge balance by occupying voids within the net. The intermediate temperature modification stable between T₁ and T₂ shows a (3+2)-dimensional incommensurately modulated structure that is characterized by the following q-vectors: q₁ = (0.057, 0.172, 0.379), q₂ = (-0.057, 0.172, -0.379). The crystal structures of the high- and the previously studied ambient temperature polymorph (space group Pc) are topologically equivalent and show a group-subgroup relationship. The index of the low- in the high-symmetry group is six and involves both, losses in translation as well as point group symmetry. The distortion is based on shifts of the different atom species and tilts of the 4- and 6-fold coordination polyhedra. Actually, for some of the oxygen atoms, the displacements exceed 0.5 Å. A more detailed analysis of the distortions relating to both structures has been performed using mode analysis, which revealed that the primary distortion mode transforms according to the Λ₁ irreducible representation of P2₁/c. However, other modes with smaller distortion amplitudes are also involved.     

Improving Biocatalytic Properties of an Azoreductase via the N-Terminal Fusion of Formate Dehydrogenase

Azoreductases require NAD(P)H to reduce azo dyes but the high cost of NAD(P)H limits its application. Formate dehydrogenase (FDH) allows NAD(P)⁺ recycling and therefore, the fusion of these two biocatalysts seems promising. This study investigated the changes to the fusion protein involving azoreductase (AzoRo) of Rhodococcus opacus 1CP and FDH (FDH_C23S and FDH_{C23SD195QY196H}) of Candida boidinii in different positions with His-tag as the linker. The position affected enzyme activities as AzoRo activity decreased by 20-fold when it is in the N-terminus of the fusion protein. FDH_C23S+AzoRo was the most active construct and was further characterized. Enzymatic activities of FDH_C23S+AzoRo decreased compared to parental enzymes but showed improved substrate scope – accepting bulkier dyes. Moreover, pH has an influence on the stability and activity of the fusion protein because at pH 6 (pH that is suboptimal for FDH), the dye reduction decreased to more than 50 % and this could be attributed to the impaired NADH supply for the AzoRo part.     

Flowsheet generation through hierarchical reinforcement learning and graph neural networks

Process synthesis experiences a disruptive transformation accelerated by artificial intelligence. We propose a reinforcement learning algorithm for chemical process design based on a state-of-the-art actor-critic logic. Our proposed algorithm represents chemical processes as graphs and uses graph convolutional neural networks to learn from process graphs. In particular, the graph neural networks are implemented within the agent architecture to process the states and make decisions. We implement a hierarchical and hybrid decision-making process to generate flowsheets, where unit operations are placed iteratively as discrete decisions and corresponding design variables are selected as continuous decisions. We demonstrate the potential of our method to design economically viable flowsheets in an illustrative case study comprising equilibrium reactions, azeotropic separation, and recycles. The results show quick learning in discrete, continuous, and hybrid action spaces. The method is predestined to include large action-state spaces and an interface to process simulators in future research.     

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.     

Monte Carlo simulation of terpolymerization: Optimizing the simulation and post-processing times

Monte Carlo simulations are a useful and easy way to understand a polymerization reaction process properly. However, achieving reliable results with Monte Carlo simulations can also lead to prohibitive computational times and a considerable amount of data to be processed afterward. The present study analyses the Monte Carlo simulation of a steady-state terpolymerization process to reduce the overall computational time of the simulation and the post-processing of its results. Different sorting algorithms (Bubble, Insertion, Selection, and Tim) and Python libraries (Joblib and Numba) were used. The chain composition distribution and the micro-structures resultant of different scenarios were assessed by processing the simulated mechanism results. The simulation time results indicate the Tim sorting algorithm as the best to use in the post-processing step and the Numba library as the best suited for both the simulation and the post-processing step.