To efficiently harness resources from Pinus koraiensis seed scales, a type of forestry waste, rigorous studies on the extraction, purification, stability, and free radical scavenging capacity of the proanthocyanidins derived from these seed scales were conducted. Kinetic models showed that under ultrasonic conditions, the proanthocyanidins content reached 2.66 mg/g within 0.5 h. The optimal storage parameters include darkness, 4 °C, and pH 4. The degrees of polymerization of the mixture and the high- and low-polymer components were 4.89, 7.42 and 3.07, respectively, with the low-polymer component exhibiting the highest radical scavenging activity. Through HPLC-QE-MS/MS, 1H NMR, and FT-IR analyses, we identified proanthocyanidin B1, proanthocyanidin B2, (-)-epicatechin, and polymeric trimer esters. The Pinus koraiensis proanthocyanidins exhibited a high molecular weight, a complex internal molecular structure, and commendable stability, with crystallization requiring elevated temperatures. Therefore, the proanthocyanidins from Pinus koraiensis seed scales have emerged as highly promising novel natural antioxidants.

The investigation of the reaction\'s kinetics is one of the most crucial aspects of the design of a commercial process. The current research investigates the kinetics of Fischer-Tropsch synthesis using a perovskite catalyst. The LaFe0.7 Co0.3 O3 perovskite catalyst was prepared via the thermal sol-gel technique and characterized using BET, XRD, SEM, and H2-TPR techniques. According to operating conditions (e.g. H2/CO: 1-2, pressure: 10-20 barg, temperature: 240-300 °C, and GHSV: 3000 1/h), Fischer-Tropsch reaction kinetics (CO conversion) were carried out in a fixed-bed reactor. Using the framework of Langmuir-Hinshelwood-Hougen-Watson (LHHW) theories, 18 kinetic expressions for CO conversion were derived, and all were fitted to experimental data one by one to determine the optimum condition. The correlation was derived from experimental data and well-fitted using LHHW form (according to the enol mechanism, carbon monoxide and dissociated hydrogen atoms are adsorbed and reacted on the surface of the catalyst) -rCO = kpbCOPCO(bH2PH2)0.5/(1 + bCOPCO + (bH2PH2)0.5)2. Finally, the activation energy of the optimum kinetic model was determined with respect to the Arrhenius equation under various operating conditions. The activation energy of perovskite catalyst is about 106.25 kJ/mol at temperatures 240-300 °C, pressures 10-20 barg, and H2/CO ratios 1-2, which is lower than other types of catalyst. Therefore, the catalyst was activated at a high temperature and demonstrated stable performance without any temperature runaway and coking issues.

In this work, a bioprocess for the fermentation of A. succinogenes for the production of succinic acid from glycerol was developed, employing a continuous bioreactor with recycle. Moreover, a new bioprocess model was constructed, based on an existing double substrate limitation model, which was validated with experimental results for a range of operating parameters. The model was used to successfully predict the dynamics of the continuous fermentation process and was subsequently employed in optimisation studies to compute the optimal conditions, dilution rate, reflux rate and feed glycerol concentration, that maximise the productivity of bio-succinic acid. In addition, a Pareto front for optimal volumetric productivity and glycerol conversion combinations was computed. Maximum volumetric productivity of 0.518 g/L/h, was achieved at the optimal computed conditions, which were experimentally validated. This is the highest bio-succinic acid productivity reported so far, for such a continuous bioprocess.

Modern people spend more and more time in cars in their daily lives, and the pollution of formaldehyde in the car may directly affect people\'s health. Thermal catalytic oxidation technology by solar light is a potential way to purify formaldehyde in cars. MnOx-CeO2 was prepared by the modified co-precipitation method as the main catalyst, and the basic characteristic (SEM, N2 adsorption, H2-TPR, UV-visible absorbance) were also analyzed in detail. The experimental study was set up to simulate the solar photothermal catalysis of formaldehyde in-car environment. The results showed that the higher the temperature in the experimental box (56.7 ± 0.2°C, 62.6 ± 0.2°C, 68.2 ± 0.2°C), the better the formaldehyde degradation by catalytic effect (formaldehyde degradation percentage: 76.2%, 78.3%, 82.1%). With increase of the initial formaldehyde concentration (200 ppb, 500 ppb, 1000 ppb), the catalytic effect first increased and then decreased (formaldehyde degradation percentage: 63%, 78.3%, 70.6%). The catalytic effect risen gradually with the increase of load ratio (10g/m2, 20g/m2, and 40g/m2), and the formaldehyde degradation percentages were 62.8%, 78.3%, and 81.1%, respectively. According to the expressions of the Eley-Rideal (ER) model, the Langmuir-Hinshelwood (LH) model, and the Mars-Van Krevelen (MVK) model, the experimental results were fitted and verified, and it was found that the ER model had a high degree of fit. It is more suitable to explain the catalytic mechanism of formaldehyde by MnOx-CeO2 catalyst in the experimental cabin, where formaldehyde is in the adsorption state and oxygen is in the gas phase.Implications: Judging from the current research status, vehicles have become an indispensable mode of travel for people, and the air quality in the vehicle is not optimistic. Most vehicles generally have the phenomenon of excessive formaldehyde. The characteristic of formaldehyde in the car is the continuous release, especially in the hot summer, the temperature inside the car rises sharply under the sun radiation. At this time, the formaldehyde concentration exceeds the standard by 4 to 5 times, which can cause great damage to the health of the passengers. In order to improve the air quality in the car, it is necessary to adopt the correct purification technology to degrade formaldehyde. The problem brought by this situation is how to effectively use solar radiation and high temperature in the car to degrade formaldehyde in the car. Therefore, this study uses the thermal catalytic oxidation technology to catalyze the degradation of formaldehyde in the high temperature environment of the car in summer. The selected catalyst is MnOx-CeO2, mainly because manganese oxide (MnOx) itself is the most effective catalyst for volatile organic compounds (TCO) among transition metal oxides, and CeO2 has excellent oxygen storage and release capacity and Oxidation activity, which helps to improve the activity of MnOx. Finally, the effects of temperature, initial concentration of formaldehyde and catalyst loading on the experiment were explored, and the kinetic model of thermal catalytic oxidation of formaldehyde with MnOx-CeO2 catalyst was analyzed to provide technical support for the future application of this research in practice.

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

In the present study, biomass from the Chromolaena odorata plant\'s stem was activated using sulfuric acid to adsorb crystal violet (CV) dye. The adsorption operation of CV dye was studied considering the effect of variables like pH, initial dye concentration, time, adsorbent dosage, and temperature. The pseudo-second-order equation best fitted the kinetic study. The thermodynamic parameters such as activation energy (9.56 kJ/mol), change in Gibbs energy (81.43 to 96.7 kJ/mol), enthalpy change (6.89 kJ/mol), and entropy change (-254.4 J/mol K) were calculated. Response surface methodology estimated that at pH (4.902), adsorbent dosage (8.33 g/L), dye concentration (82.30 ppm), and temperature (300.13 K) dye removal of 97.53% is possible. FTIR, SEM, XRD, BJH, and BET confirmed adsorption operation. The adsorbent can be reused for 3 cycles effectively. Langmuir isotherm which best fitted the adsorption operation was used for designing a theoretical single-stage batch adsorber for large-scale operation.

An innovative strategy to control nitrogen oxide emission from flue gas was developed using the wet flue gas denitrification technology. The use of cyclodextrin (CD) as an additive facilitated NO2 absorption by the sulfite absorbent. Compared with absorption by a sulfite solution (59.12%), the instantaneous absorption efficiencies employing CD improved to 94.57%. Moreover, 48 h of continuous absorption indicated cyclic utilization of CD. The favorable role of CD was ascribed to facilitating the limiting step for the entire NO2 absorption-dissolution process which included both water solubility and gas-liquid mass transfer. Furthermore, we propose a potential mechanism of CD/sulfite mixed solution absorbing NO2, among which the favorable role of the additive is related to its amphiphilic behavior toward gas and liquid phases. Additionally, a kinetic model describing the rates of gas-liquid transfer and macro absorption was established based on various operating conditions. This model explains the absorption improvement in the kinetic aspect and provides theoretical guidance for practical applications.

Eversa® Transform 2.0 lipase used as biocatalyst to biodiesel (fatty acid methyl esters - FAME) synthesis has been the target of interesting studies due to its thermostability and cost-effectiveness. In these researches, data about reaction conditions that result in satisfactory yields were investigated. Nevertheless, kinetic and thermodynamic parameters considering this enzyme are scarce. This paper presents an estimation of kinetic and thermodynamic parameters for the Eversa® Transform 2.0-mediated hydroesterification to FAME synthesis. Kinetic studies were performed for different methanol, water and lipase loads in distinct temperatures. Parameters adjusted by the thermodynamic model indicate that the hydrolysis is decisive in the overall hydroesterification reaction rate and the esterification reaction is endothermic (ΔHe = 38.98 kJ/mol). Formation of enzymatic complexes is favored by increasing the temperature, especially the enzyme-methanol inhibition complex. Statistical analysis showed that the model was not overparameterized, and the small confidence interval indicated good reliability of the estimated parameters.

In vitro digestibility of starch is a common analysis in human nutrition research, and generally consists of performing the hydrolysis of starch by α-amylase in specific conditions. Similar in vitro assays are also used in other research fields, where different methods can be used. Overall, the in vitro hydrolysis of native starch is a bridge between all of these methods. In this literature review, we examine the use of amylolysis assays in recent publications investigating the complex starch structure-amylolysis relation. This review is divided in two parts: (1) a brief review of the factors influencing the hydrolysis of starch and (2) a systematic review of the experimental designs and methods used in publications for the period 2016-2020. The latter reports on starch materials, factors investigated, characterization of the starch hydrolysis kinetics and data analysis techniques. This review shows that the dominant research strategy favors the comparison between a few starch samples most frequently described through crystallinity, granule type, amylose and chain length distribution with marked characteristics. This strategy aims at circumventing the multifactorial aspect of the starch digestion mechanism by focusing on specific features. An alternative strategy relies on computational approaches such as multivariate statistical analysis and machine learning techniques to decipher the role of each factor on amylolysis. While promising to address complexity, the limited use of a computational approach can be explained by the small size of the experimental datasets in most publications. This review shows that key steps towards the production of larger datasets are already available, in particular the generalization of rapid hydrolysis assays and the development of quantification approaches for most analytical results.

Spirulina platensis has been considered a promising source of food supplement to combat malnutrition worldwide. Numerous investigations have stated its immune activity, ability to absorb CO2 during the growth period, and antioxidant potential. Well-known theoretical biomass kinetic model sheds are capable of qualitative analysis of the fast microalgae growth. In this regard, we considered eight popular biomass models: Monod, Haldane, Andrews & Noack, Teissier, Hinshelwood, Yano & Koga, Webb and, Aiba model comprising analytical investigation within the numerical simulation. Besides, in this study, we establish a new mathematical biomass growth model by merging the well-known Hinshelwood and Yano & Koga models. We explored the most suitable Spirulina growth model to minimize the overstated and understated growth trends in the assorted eight biomass kinetic models. Our findings show microalgae biomass growth and substrate diminishes along with time, and these results were compared with available experimental data. Results present a high value of R2(0.9862), a low value of RSS (0.0813), AIC (-9.7277), and BIC (-8.2148) implied significantly fitted with the investigated data for the growth of Spirulina platensis compared with popular eight studied models.