Hasil untuk "Chemical industries"

W. Dhifi, Sana Bellili, S. Jazi et al.

This review covers literature data summarizing, on one hand, the chemistry of essential oils and, on the other hand, their most important activities. Essential oils, which are complex mixtures of volatile compounds particularly abundant in aromatic plants, are mainly composed of terpenes biogenerated by the mevalonate pathway. These volatile molecules include monoterpenes (hydrocarbon and oxygenated monoterpens), and also sesquiterpenes (hydrocarbon and oxygenated sesquiterpens). Furthermore, they contain phenolic compounds, which are derived via the shikimate pathway. Thanks to their chemical composition, essential oils possess numerous biological activities (antioxidant, anti-inflammatory, antimicrobial, etc…) of great interest in food and cosmetic industries, as well as in the human health field.

Afia Yasmin, Bristy Biswas, Md. Lutfor Rahman et al.

CoFe2O4 was synthesized at 150 °C, 180 °C, and 210 °C temperatures using hydrothermal method to find the effect on its structural, magnetic, electric, and optical properties. The saturation magnetization, coercivity and magnetic anisotropy was found using Vibrating Sample Magnetometer (VSM), ranging from 50.36 to 53.66 emu/g. XRD (X-ray Diffraction Analysis) and SEM (Scanning Electron Microscopy), FTIR (Fourier Transform Infrared Spectroscopy) was used for structural analysis verifying the spinel ferrite structure with a single phase. The crystalline size and lattice strain was found using Size-Strain Plot (SSP) and Debye-Scherrer (D-S) method which proved that as the synthesis temperature increased, the crystallite size also increased. The crystalline size ranges from 39.40 to 82.24 nm as observed by XRD. SEM analysis found the crystal size range to be from 9 to 12 nm. It was found that the optimum temperature to synthesize cobalt ferrite nanoparticles are at 180 °C for sample H2 with a crystal size of 82.24 nm and band gap energy of 2.60 eV. The Ms value was determined to be 50.36 emu/g for H2 sample with Rs value of 0.31.

Preetom Borah, Elif Irem Senyurt, Rohit Berlia et al.

The development of advanced diagnostic systems to measure and optimize emerging energetic material performance is critical for the defeat of Chemical Warfare Agents (CWA). This study presents an integrated multi-spectroscopic approach to monitor the interaction between a CWA simulant, Diisopropyl Methyl Phosphonate (DIMP), and combusting composite metal particles. A custom benchtop Polygonal Rotating Mirror Infrared Spectrometer (PRiMIRS), equipped with a customizable experimental chamber, is employed to observe DIMP decomposition. Tunable Diode Laser Absorption Spectroscopy (TDLAS) is used to measure path-averaged gas temperature profiles during combustion. In the experiment, the chamber is preheated to evaporate liquid DIMP. Various composite metal powders (Al-8Mg):3Zr, (Al-8Mg):Zr, 2(Al-8Mg):Zr, and 4(Al-8Mg):Zr are placed on a stainless steel mount and ignited using 3Al-2Ni sputter-deposited nanolayered foils. The combusting metal particles mix with the DIMP vapor, initiating chemical and thermal interactions. PRiMIRS captures DIMP spectral evolution, while TDLAS simultaneously monitors gas temperature. A spectral defeat parameter was developed to enable quantitative real-time assessment of the DIMP destruction. It uses infrared light absorption by both from DIMP and its immediate decomposition products Isopropyl Methyl Phosphonate (IMP) and Isopropyl Alcohol (IPA). Fourier Transform Infrared Spectroscopy (FTIR) serves as a secondary verification tool quantifying the decomposition products over extended timeframes, and Transmission Electron Microscopy (TEM) confirms the expected metal oxide dispersion within the reaction space. This study reports variability in DIMP defeat as a function of metal powder stoichiometry, metal powder loading, and path-averaged gas temperature profiles, offering critical insights into optimizing reactive materials for effective CWA neutralization.

Dean Brandner, Sergio Lucia

Optimal operation of chemical processes is vital for energy, resource, and cost savings in chemical engineering. The problem of optimal operation can be tackled with reinforcement learning, but traditional reinforcement learning methods face challenges due to hard constraints related to quality and safety that must be strictly satisfied, and the large amount of required training data. Chemical processes often cannot provide sufficient experimental data, and while detailed dynamic models can be an alternative, their complexity makes it computationally intractable to generate the needed data. Optimal control methods, such as model predictive control, also struggle with the complexity of the underlying dynamic models. Consequently, many chemical processes rely on manually defined operation recipes combined with simple linear controllers, leading to suboptimal performance and limited flexibility. In this work, we propose a novel approach that leverages expert knowledge embedded in operation recipes. By using reinforcement learning to optimize the parameters of these recipes and their underlying linear controllers, we achieve an optimized operation recipe. This method requires significantly less data, handles constraints more effectively, and is more interpretable than traditional reinforcement learning methods due to the structured nature of the recipes. We demonstrate the potential of our approach through simulation results of an industrial batch polymerization reactor, showing that it can approach the performance of optimal controllers while addressing the limitations of existing methods.

Sanghyeon Park, Yuseung Hong, Hyunseo Choi

The use of chemical warfare agents (CWAs) in modern warfare cannot be disregarded due to their ease of use and potential for large-scale incapacitation. An effective countermeasure involves the physical adsorption of these agents, preventing their entry through the respiratory tract by non-specific adsorption. In this study, we investigate the physical interaction between potential adsorbents and model gases mimicking CWAs, thereby identifying sufficient conditions for higher physical adsorption performance. Our findings reveal that the physical adsorption capacity is highly sensitive to the surface properties of the adsorbents, with uniform development of micropores, rather than solely high surface area, emerging as a critical factor. Additionally, we identified the potential of porous organic polymers as promising alternatives to conventional activated carbon-based adsorbents. Through a facile introduction of polar sulfone functional groups on the polymer surface, we demonstrated that these polar surface polymers exhibit physical adsorption capabilities for formaldehyde under ambient conditions comparable to high-performance activated carbons. Notably, the superior activated carbon possessed a high BET surface area of 2400 m^2/g and an exceptionally uniform micropore structure with an average pore size of approximately 11 Angstroms. This research paves the way for designing adsorbents with high physical adsorption capacities tailored for CWAs protection, offering a significant advancement in developing next-generation protective materials.

Chen Bin, Ge Liu

The turbulence characteristics of the oil pulsation flow may be influenced by the concentration of particles. In this research, an NI PXI data acquisition system is utilized to experimentally analyze the flow pressure signal of the oil pulsation containing various concentrations of particles. To decompose the signal of the oil pressure, a wavelet basis function called sym8 was selected, and a 4-layer decomposition was performed. In this way, the wavelet coefficients of each node can be obtained. By utilizing wavelet packet decomposition, we investigated the impact of varying concentrations of particles on the energy distribution and values of the signal of the oil pressure. The findings indicate that the first three nodes of the signal of the oil pressure, regardless of the concentration of particles, play a significant influence on the signal of the oil pressure frequency band. The Euclidean distance between these nodes ranges from 0.6723 to 1.9786, showing considerable variability. As the concentration of particles increases, the Euclidean distance between these nodes decreases. Moreover, the primary frequency corresponding to nodes with even sequence numbers gradually decreases with increasing concentration of particles, while nodes with odd sequence numbers experience an opposite trend of gradual increase. Additionally, the primary frequency of the signal of the oil pressure gradually decreases with increasing the concentration of particles.

Marina Grubišić, Ines Peremin, Elvis Djedović et al.

Microalgal biomass is an excellent platform for producing food, feed, nutraceuticals, pharmaceuticals, and biofuels. This study aimed to investigate the effect of the trophic mode of cultivation (phototrophic, heterotrophic, and mixotrophic) on the growth and biomass composition of <i>Chlorella vulgaris</i> S2. The contents of lipids and carbohydrates, as well as the fatty acid composition of total lipids, were studied. The effects of the carbon-to-nitrogen ratio (C:N) and the organic carbon concentration of the growth media under mixotrophic and heterotrophic conditions were also investigated. The C:N ratio of 30 mol mol⁻¹ favoured lipid synthesis, and the C:N ratio of 10 mol mol⁻¹ favoured carbohydrate synthesis. Maximal lipid and biomass productivities (2.238 and 0.458 g L⁻¹ d⁻¹, respectively) were obtained under mixotrophic conditions at the C:N ratio of 50 mol mol⁻¹ and glucose concentration of 50 g L⁻¹. Fed-batch cultivation conducted in a stirrer tank bioreactor under heterotrophic growth conditions increased biomass (2.385 g L⁻¹ d⁻¹, respectively) and lipid (0.339 L⁻¹ d⁻¹) productivities ~50 and ~60 times compared to the fed-batch phototrophic cultivation, respectively. The trophic mode, growth phase, and growth medium composition significantly influenced the fatty acid composition. Under mixotrophic and heterotrophic growth conditions, lipid accumulation is associated with an increase in oleic acid (C18:1) content. Mixotrophically grown biomass of <i>Chlorella vulgaris</i> S2 under optimised conditions is a suitable source of lipids for biodiesel production.

Mahfujul Alam, Mir Meahadi Hasan, Mrinal Kanti Debnath et al.

Papaya fruits different edible and non-edible portions are valued for the abundance of numerous nutrients and therapeutic benefits. The study was aimed to examine the physico-chemical properties, bioactive compounds (total phenolics and total flavonoids), antioxidant activity and microstructure analysis of the peel, pulp and seed flour of both ripe and unripe papaya. The results demonstrated the different portions of both ripe and unripe papaya fruit flour differed significantly with respect to almost all quality attributes within them. The physico-chemical variations have been evaluated through evaluation of the pH, moisture content, TSS, and ascorbic acid content of the papaya fruits during both ripening stages. Statistically significant variations (p < 0.05) were observed between two distinct stages of ripening. The concentration of ascorbic acid in the fruit revealed a notable increase as it matured, while the pH, moisture, and TSS all exhibited a substantial decrease (p < 0.05) during the immature stage. The unripe peel showed the most significant level of bulk density, tapped density, swelling capacity, crude fiber, and TFC whereas the unripe seed showed the highest value of ash, crude fat, and TPC. For the rest of the value, ripe pulp and seed flour showed a significantly higher value than others. The total phenolic content in seed flour and the total flavonoid content of peel flour were 196.9 ± 0.03 and 164.9 ± 0.08 mgQE/100 g, respectively, at unripe conditions. An immense amount of antioxidant activity was found in ripe (20.48 ± 0.54%) and unripe (16.05 ± 0.32%) peels flour. The flour granules' diverse morphological forms and particle sizes were identified by SEM analysis. The versatility of papaya and its various components provides opportunities for applications in the food, pharmaceutical, cosmetic, and agricultural industries. The papaya fruit flour of different portions have unique functional, nutritional, and morphological characteristics that may contribute to the development of gluten free flour based value added baked products.

Nicolas Hayer, Thomas Specht, Justus Arweiler et al.

In this work, we introduce a novel approach for predicting thermodynamic properties of binary mixtures, which we call the similarity-based method (SBM). The method is based on quantifying the pairwise similarity of components, which we achieve by comparing quantum-chemical descriptors of the components, namely $σ$-profiles. The basic idea behind the approach is that mixtures with similar pairs of components will have similar thermodynamic properties. The SBM is trained on a matrix that contains some data for a given property for different binary mixtures; the missing entries are then predicted by the SBM. As an example, we consider the prediction of isothermal activity coefficients at infinite dilution ($γ^\infty_{ij}$) and show that the SBM outperforms the well-established physical methods modified UNIFAC (Dortmund) and COSMO-SAC-dsp. In this case, the matrix is only sparsely occupied, and it is shown that the SBM works also if only a limited number of data for similar mixtures is available. The SBM idea can be transferred to any mixture property and is a powerful tool for generating essential data for many applications.

Yuqi Zhang, Heng Guo, Chunying Zhu et al.

The flow behavior of bubbles in the expansion of the microchannel is studied. Four stable flow patterns are observed: Double-Layer-Bubble Coalescence (DLBC), Hamburger-Double-Layer-Bubble Coalescence (HDLBC), Hamburger Flow Coalescence (HFC), and Non-Coalescence Hamburger Flow (NCHF). With the increase of gas velocity, the flow pattern changes gradually from DLBC to HDLBC, HFC, and UHFC. The experimental results show that the liquid film drainage time increases with the bubble length. The location of bubble coalescence is away from the inlet with the increase of bubble length and bubble velocity but moves towards the inlet with the increase of liquid slug length. A prediction equation of bubble coalescence position is proposed, which has a good prediction effect.

Christian Schäfer, Jakub Fojt, Eric Lindgren et al.

Altering chemical reactivity and material structure in confined optical environments is on the rise, and yet, a conclusive understanding of the microscopic mechanisms remains elusive. This originates mostly from the fact that accurately predicting vibrational and reactive dynamics for soluted ensembles of realistic molecules is no small endeavor, and adding (collective) strong light-matter interaction does not simplify matters. Here, we establish a framework based on a combination of machine learning (ML) models, trained using density-functional theory calculations, and molecular dynamics to accelerate such simulations. We then apply this approach to evaluate strong coupling, changes in reaction rate constant, and their influence on enthalpy and entropy for the deprotection reaction of 1-phenyl-2-trimethylsilylacetylene, which has been studied previously both experimentally and using ab initio simulations. While we find qualitative agreement with critical experimental observations, especially with regard to the changes in kinetics, we also find differences in comparison with previous theoretical predictions. The features for which the ML-accelerated and ab initio simulations agree show the experimentally estimated kinetic behavior. Conflicting features indicate that a contribution of dynamic electronic polarization to the reaction process is more relevant then currently believed. Our work demonstrates the practical use of ML for polaritonic chemistry, discusses limitations of common approximations and paves the way for a more holistic description of polaritonic chemistry.

Thorsten Weimar, Christian Hammer

The method of fibre optic strain measurement based on Rayleigh signal analysis enables the detection of the deformation behaviour of laminated glass and the modelling of its load-bearing characteristics. The measurement system is already calibrated for glass surfaces by studies of Institute of Structural Design at Universität Siegen. In addition to discretely measuring systems, such as strain gauges, the distributed measurement system is particularly suitable for determining the interlaminar shear modulus. The sensors used in bending tests on laminated glass supplement the deformation measurements taken with strain gauges and inductive displacement sensors. The study describes the results of the shear modulus of viscoelastic interlayers made of polyvinyl butyral and provides the basis to define and evaluate a model for the finite element analysis.

Xingxun Bao, Yanan Zhang, Hairong Zhang et al.

β-Sitosterol (SIT), a white powdery organic substance with a molecular formula of C29H50O, is one of the most abundant naturally occurring phytosterols in plants. With a chemical composition similar to that of cholesterol, SIT is applied in various fields such as medicine, agriculture, and chemical industries, owing to its unique biological and physicochemical properties. Modern pharmacological studies have elucidated good anti-tumor therapeutic effect activity of SIT, which mainly manifests as pro-apoptotic, anti-proliferative, anti-metastatic, anti-invasive, and chemosensitizing on tumor cells. In addition, SIT exerts an anti-tumor effect on multiple malignant tumors such as breast, gastric, lung, kidney, pancreatic, prostate, and other cancers. Further, SIT derivatives with structural modifications are promising anti-tumor drugs with significant anti-tumor effects. This review article focuses on recent studies relevant to the anti-tumor effects of SIT and summarizes its anti-tumor mechanism to provide a reference for the clinical treatment of malignant tumors and the development of novel anti-tumor drugs.

William Poole, Thomas Ouldridge, Manoj Gopalkrishnan et al.

Can a micron sized sack of interacting molecules understand, and adapt to a constantly-fluctuating environment? Cellular life provides an existence proof in the affirmative, but the principles that allow for life's existence are far from being proven. One challenge in engineering and understanding biochemical computation is the intrinsic noise due to chemical fluctuations. In this paper, we draw insights from machine learning theory, chemical reaction network theory, and statistical physics to show that the broad and biologically relevant class of detailed balanced chemical reaction networks is capable of representing and conditioning complex distributions. These results illustrate how a biochemical computer can use intrinsic chemical noise to perform complex computations. Furthermore, we use our explicit physical model to derive thermodynamic costs of inference.

Johan S. Høye, Dirk Gillespie

The Mean Spherical Approximation (MSA) is a commonly-used thermodynamic theory for computing the energetics of ions in the primitive model (i.e., charged hard-sphere ions in a background dielectric). For the excess chemical potential, however, the early MSA formulations (which were widely adopted) only included the terms needed to compute the mean excess chemical potential (or the mean activity coefficient). Other terms for the chemical potential $μ_i$ of individual species $i$ were not included because they sum to $0$ in the mean chemical potential. Here, we derive these terms to give a complete MSA formulation of the chemical potential. The result is a simple additive term for $μ_i$ that we show is a qualitative improvement over the previous MSA version. In addition, our derivation shows that the MSA's assumption of global charge neutrality is not strictly necessary, so that the MSA is also valid for systems close to neutrality.

P. Shwethambika, J. Ishwara Bhat

Matured Cocoa Pod Extract (MCPE) is prepared using Soxhlet extraction and is then characterized using Fourier Transform-Infra Red Spectroscopy (FT-IR), Gas Chromatography-Mass Spectroscopy (GC-MS). The thermal decomposition characteristics are studied using Thermo Gravimetric Analysis- Differential Thermal Analysis (TGA-DTA) method. FT-IR study confirmed the presence of hetero atoms like O, N, and GC-MS showed the presence of 15 chemical constituents of which 1,2-bis (trimethylsilyl) benzene is the major constituent present. TGA-DTA studies showed the thermal decomposition of chemical constituents which was supported by GC-MS data. The inhibition efficiency of MCPE is tested in 0.5M HCl medium taking aluminum as the target metal by Weight loss method (303K-308K). The anticorrosive property of MCPE was also tested using Electrochemical Impedance Spectroscopy and Potentiodynamic Polarization methods (303K). In all the methods, the inhibition efficiency of MCPE was found to increase with an increase in % volume of the MCPE exhibiting good agreement with each other. Also, inhibition efficiency decreased with an increase in temperature, showing adsorption of inhibitor is by physisorption and thermodynamic parameters are measured. Tafel plots showed MCPE could retard both anodic and cathodic reactions, predominantly acting as an anodic type of inhibitor. Surface morphological changes of the metal were studied using Scanning Electron Microscopy which confirmed that MCPE acted as an inhibitor by adsorption mechanism.

Rachid El Brychy, Mohamed Moutie Rguiti, Nadia Rhazzane et al.

Today, organic wastes (paints, pigments, etc.) are considered to be a major concern for the pollution of aqueous environments. Therefore, it is essential to find new methods to solve this problem. This research was conducted to study the use of electrochemical processes to remove organic pollutants (e.g., crystal violet (CV)) from aqueous solutions. The galvanostatic electrolysis of CV by the use of Ti/Pt/SnO₂ anode, were conducted in an electrochemical cell with 100 mL of solution using Na₂SO₄ and NaCl as supporting electrolyte, the effect of the important electrochemical parameters: current density (20–60 mA cm⁻²), CV concentration (10–50 mg L⁻¹), sodium chloride concentration (0.01–0.1 g L⁻¹) and initial pH (2 to 10) on the efficiency of the electrochemical process was evaluated and optimized. The electrochemical treatment process of CV was monitored by the UV-visible spectrometry and the chemical oxygen demand (COD). After only 120 min, in a 0.01 mol L⁻¹ NaCl solution with a current density of 50 mA cm⁻² and a pH value of 7 containing 10 mg L⁻¹ CV, the CV removal efficiency can reach 100%, the COD removal efficiency is up to 80%. The process can therefore be considered as a suitable process for removing CV from coloured wastewater in the textile industries.

Salman Hajian Ghayemi, Abdolreza Samimi, Masoud Nematollahi

In this investigation, fresh and regenerated Ni-W-Alumina-Zeolite industrial hydrocracking catalysts are characterized via several analyzing methods, including XRF, XRD, BET adsorption, FT-IR, FESEM-EDS, and TGA-DTA to understand the phenomena affecting trend towards their deactivation. The XRD patterns represented the presence of main phases of Al2O3/Y-zeolite as support and NiWO4/WO3 as active compounds. For the catalysts subjected to a three-year reactor operation/regeneration cycle, the XRF analysis revealed elemental enhancement of Fe, Na, V, Pb, Sb, and S, mostly from an outsourced environment. The BET and BJH analyses represented cylindrical shape mesoporosity for the samples, while the total pore-specific surface area and volume were reduced from 287.73 m2/g  and 0.46 cm3/g to 160.84 m2/g and 0.40 cm3/g for fresh and regenerated samples, respectively. The latter results indicated possibly filling the pores with impurities and/or sintering of pores. By considering FESEM images, the smooth surface of the fresh sample and indented/corroded characteristics of the regenerated one were seen. The variety of analyses portrayed the increasing trend of the poisoning factors and the structural malfunction of the catalysts towards irreversible deactivation.

Anandlogesh R R, Breasha Gupta, Divika Agarwal et al.

The story of the Chemical Industry in India is one of outperformance and promise. A consistent value creator, the chemical industry remains an attractive hub of opportunities, even in an environment of global uncertainty. This paper aims to analyze the various driving factors, the performance of the key players over fundamental analysis, and the various trends that would shape the performance of the industry due to the various geopolitical and macroeconomic trends in the post-pandemic world.

Carlos Allende Prieto

The Sun provides a standard reference against which we compare the chemical abundances found anywhere else in the Universe. Nevertheless, there is not a unique 'solar' composition, since the chemical abundances found in the solar interior, the photosphere, the upper atmosphere, or the solar wind, are not exactly the same. The composition of the solar photosphere, usually preferred as a reference, changes with time due to diffusion, convection, and probably accretion. In addition, we do not know the solar photospheric abundances, inferred from the analysis of the solar spectrum using model atmospheres, with high accuracy, and uncertainties for many elements exceed 25%. This paper gives an overview of the methods and pitfalls of spectroscopic analysis, and discusses the chemistry of the Sun in the context of the solar system.