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Records added in 2021
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Showing records 26 to 50 of 798. [First] Page: 1 2 3 4 5 6 Last
Development of Poly(L-Lactic Acid)/Chitosan/Basil Oil Active Packaging Films via a Melt-Extrusion Process Using Novel Chitosan/Basil Oil Blends
Constantinos E. Salmas, Aris E. Giannakas, Maria Baikousi, Areti Leontiou, Zoe Siasou, Michael A. Karakassides
October 14, 2021 (v1)
Subject: Materials
Keywords: active packaging, antioxidant properties, barrier properties, basil oil, chitosan, films, PLLA
Following the global trend toward a cyclic economy, the development of a fully biodegradable active packaging film is the target of this work. An innovative process to improve the mechanical, antioxidant, and barrier properties of Poly(L-Lactic Acid)/Chitosan films is presented using essential basil oil extract. A Chitosan/Basil oil blend was prepared via a green evaporation/adsorption method as a precursor for the development of the Poly(L-Lactic Acid)/Chitosan/Basil Oil active packaging film. This Chitosan/Basil Oil blend was incorporated directly in the Poly(L-Lactic Acid) matrix with various concentrations. Modification of the chitosan with the Basil Oil improves the blending with the Poly(L-Lactic Acid) matrix via a melt-extrusion process. The obtained Poly(L-Lactic Acid)/Chitosan/Basil Oil composite films exhibited advanced food packaging properties compared to those of the Poly(L-Lactic Acid)/Chitosan films without Basil Oil addition. The films with 5%wt and 10%wt Chitosan/Basil... [more]
Pyrometallurgical Lithium-Ion-Battery Recycling: Approach to Limiting Lithium Slagging with the InduRed Reactor Concept
Stefan Windisch-Kern, Alexandra Holzer, Christoph Ponak, Harald Raupenstrauch
October 14, 2021 (v1)
Subject: Materials
Keywords: carbothermal reduction, lithium-ion-batteries, pyrometallurgical recycling
The complexity of the waste stream of spent lithium-ion batteries poses numerous challenges on the recycling industry. Pyrometallurgical recycling processes have a lot of benefits but are not able to recover lithium from the black matter since lithium is slagged due to its high oxygen affinity. The presented InduRed reactor concept might be a promising novel approach, since it does not have this disadvantage and is very flexible concerning the chemical composition of the input material. To prove its basic suitability for black matter processing, heating microscope experiments, thermogravimetric analysis and differential scanning calorimetry have been conducted to characterize the behavior of nickel rich cathode materials (LiNi0.8Co0.15Al0.05O2 and LiNi0.33Mn0.33Co0.33O2) as well as black matter from a pretreatment process under reducing conditions. Another experimental series in a lab scale InduRed reactor was further used to investigate achievable transfer coefficients for the metals... [more]
State-of-the-Art Char Production with a Focus on Bark Feedstocks: Processes, Design, and Applications
Ali Umut Şen, Helena Pereira
October 14, 2021 (v1)
Keywords: bark, charcoal, gasification, hydrothermal carbonization, pyrolysis, torrefaction
In recent years, there has been a surge of interest in char production from lignocellulosic biomass due to the fact of char’s interesting technological properties. Global char production in 2019 reached 53.6 million tons. Barks are among the most important and understudied lignocellulosic feedstocks that have a large potential for exploitation, given bark global production which is estimated to be as high as 400 million cubic meters per year. Chars can be produced from barks; however, in order to obtain the desired char yields and for simulation of the pyrolysis process, it is important to understand the differences between barks and woods and other lignocellulosic materials in addition to selecting a proper thermochemical method for bark-based char production. In this state-of-the-art review, after analyzing the main char production methods, barks were characterized for their chemical composition and compared with other important lignocellulosic materials. Following these steps, previ... [more]
Fault Monitoring of Chemical Process Based on Sliding Window Wavelet DenoisingGLPP
Fan Yang, Yuancun Cui, Feng Wu, Ridong Zhang
October 14, 2021 (v1)
Keywords: global local preserving projections, principal component analysis, process monitoring, sliding window, Tennessee Eastman, wavelet denoising
In industrial process fault monitoring, it is very important to collect accurate data, but in the actual process, there are often various noises that are difficult to eliminate in the collected data due to sensor accuracy, measurement errors, or human factors. Existing statistical process monitoring methods often ignore the problem of data noise. To solve this problem, a sliding window wavelet denoising-global local preserving projections (SWWD-GLPP) process monitoring method is proposed. In the offline stage, the wavelet denoising method is used to denoise the offline data, and then, the GLPP method is used for offline modeling, and then, the control limit is obtained by the kernel density estimation method. In the online phase, the sliding window wavelet denoising method is used to denoise the online data in real time. Then, use the model of the GLPP method to find the statistics, compare them with the control limit, judge the fault situation, and finally, use the contribution graph... [more]
Integration of Artificial Intelligence into Biogas Plant Operation
Samet Cinar, Senem Onen Cinar, Nils Wieczorek, Ihsanullah Sohoo, Kerstin Kuchta
October 14, 2021 (v1)
Keywords: anaerobic digestion, Artificial Intelligence, automation, biogas plant, predictive monitoring, process monitoring, process optimization
In the biogas plants, organic material is converted to biogas under anaerobic conditions through physical and biochemical processes. From supply of the raw material to the arrival of the products to customers, there are serial processes which should be sufficiently monitored for optimizing the efficiency of the whole process. In particular, the anaerobic digestion process, which consists of sequential complex biological reactions, requires improved monitoring to prevent inhibition. Conventional implemented methods at the biogas plants are not adequate for monitoring the operational parameters and finding the correlation between them. As Artificial Intelligence has been integrated in different areas of life, the integration of it into the biogas production process will be inevitable for the future of the biogas plant operation. This review paper first examines the need for monitoring at the biogas plants with giving details about the process and process monitoring as well. In the follow... [more]
Research on the Dynamic Responses of Simply Supported Horizontal Pipes Conveying Gas-Liquid Two-Phase Slug Flow
Gang Liu, Zongrui Hao, Yueshe Wang, Wanlong Ren
October 14, 2021 (v1)
Subject: Other
Keywords: dynamic responses, intermittent, simply supported pipe, two-phase slug flow
The dynamic responses of simply supported horizontal pipes conveying gas-liquid two-phase slug flow are explored. The intermittent characteristics of slug flow parameters are mainly considered to analyze the dynamic model of the piping system. The results show that the variations of the midpoint transverse displacement could vary from periodic-like motion to a kind of motion whose amplitude increases as time goes on if increasing the superficial gas velocity. Meanwhile, the dynamic responses have certain relations with the vibration acceleration. By analyzing the parameters in the power spectrum densities of vibration acceleration such as the number of predominant frequencies and the amplitude of each peak frequency, the dynamic behaviors of the piping system like periodicity could be calculated expediently.
Films and Materials Derived from Aminomalononitrile
Helmut Thissen, Richard A. Evans, Vincent Ball
October 14, 2021 (v1)
Subject: Materials
Keywords: aminomalononitrile, biomaterials, prebiotic chemistry, versatile coatings
In recent years major advances in surface chemistry and surface functionalization have been performed through the development, most often inspired by living organisms, of versatile methodologies. Among those, the contact of substrates with aminomalononitrile (AMN) containing solutions at pH = 8.5 allows a conformal coating to be deposited on the surface of all known classes of material. Since AMN is a molecule probably formed in the early atmosphere of our planet and since HCN-based compounds have been detected on many comets and Titan (Saturn’s largest moon) it is likely that such molecules will open a large avenue in surface functionalization mostly for bio-applications. This mini review describes the state of the art of AMN-based coatings from their deposition kinetics, composition, chemical reactivity, hypothetical structure to their first applications as biomaterials. Finally, the AMN-based versatile coatings are compared to other kinds of versatile coating based on catecholamines... [more]
Influence of the Ni-Co/Al-Mg Catalyst Loading in the Continuous Aqueous Phase Reforming of the Bio-Oil Aqueous Fraction
Pablo Lozano, Ana I. Simón, Lucía García, Joaquín Ruiz, Miriam Oliva, Jesús Arauzo
October 14, 2021 (v1)
Keywords: acetic acid, acetol, aqueous fraction, aqueous phase reforming, bio-oil, Butanol, Ni catalyst
The effect of catalyst loading in the Aqueous Phase Reforming (APR) of bio-oil aqueous fraction has been studied with a Ni-Co/Al-Mg coprecipitated catalyst. Because of the high content of water in the bio-oil aqueous fraction, APR could be a useful process to convert this fraction into valuable products. Experiments of APR with continuous feeding of aqueous solution of acetol, butanol and acetic acid as the only compound, together with a simulated and a real aqueous fraction of bio-oil, were carried out. Liquid products in the liquid effluent of the APR model compounds were quantified and the reaction pathways were revised. The increase of catalyst loading produced an increase of gas production and a gas with higher alkanes content. Acetol was the compound with the highest reactivity while the conversion of acetic acid was very low. The presence of acetic acid in the feed caused catalyst deactivation.
Experimental and Numerical Analysis of the Mechanical Properties of a Pretreated Shape Memory Alloy Wire in a Self-Centering Steel Brace
Bo Zhang, Sizhi Zeng, Fenghua Tang, Shujun Hu, Qiang Zhou, Yigang Jia
October 14, 2021 (v1)
Keywords: energy dissipation capacity, initial strain, loading rate, shape memory alloy (SMA), strain amplitude
As a stimulus-sensitive material, the difference in composition, fabrication process, and influencing factors will have a great effect on the mechanical properties of a superelastic Ni-Ti shape memory alloy (SMA) wire, so the seismic performance of the self-centering steel brace with SMA wires may not be accurately obtained. In this paper, the cyclic tensile tests of a kind of SMA wire with a 1 mm diameter and special element composition were tested under multi-working conditions, which were pretreated by first tensioning to the 0.06 strain amplitude for 40 cycles, so the mechanical properties of the pretreated SMA wires can be simulated in detail. The accuracy of the numerical results with the improved model of Graesser’s theory was verified by a comparison to the experimental results. The experimental results show that the number of cycles has no significant effect on the mechanical properties of SMA wires after a certain number of cyclic tensile training. With the loading rate incre... [more]
Computational Fluid Dynamics Modeling of Rotating Annular VUV/UV Photoreactor for Water Treatment
Minghan Luo, Wenjie Xu, Xiaorong Kang, Keqiang Ding, Taeseop Jeong
October 14, 2021 (v1)
Keywords: Computational Fluid Dynamics, MB, photoreactor, VUV, water treatment
The ultraviolet photochemical degradation process is widely recognized as a low-cost, environmentally friendly, and sustainable technology for water treatment. This study integrated computational fluid dynamics (CFD) and a photoreactive kinetic model to investigate the effects of flow characteristics on the contaminant degradation performance of a rotating annular photoreactor with a vacuum-UV (VUV)/UV process performed in continuous flow mode. The results demonstrated that the introduced fluid remained in intensive rotational movement inside the reactor for a wide range of inflow rates, and the rotational movement was enhanced with increasing influent speed within the studied velocity range. The CFD modeling results were consistent with the experimental abatement of methylene blue (MB), although the model slightly overestimated MB degradation because it did not fully account for the consumption of OH radicals from byproducts generated in the MB decomposition processes. The OH radical... [more]
Green Synthesis of Copper Oxide Nanoparticles Using Protein Fractions from an Aqueous Extract of Brown Algae Macrocystis pyrifera
Karla Araya-Castro, Tzu-Chiao Chao, Benjamín Durán-Vinet, Carla Cisternas, Gustavo Ciudad, Olga Rubilar
October 14, 2021 (v1)
Subject: Biosystems
Keywords: brown seaweed, copper oxide nanoparticles, green synthesis, proteins, size exclusion chromatography
Amongst different living organisms studied as potential candidates for the green synthesis of copper nanoparticles, algal biomass is presented as a novel and easy-to-handle method. However, the role of specific biomolecules and their contribution as reductant and capping agents has not yet been described. This contribution reports a green synthesis method to obtain copper oxide nanoparticles (CuO-NPs) using separated protein fractions from an aqueous extract of brown algae Macrocystis pyrifera through size exclusion chromatography (HPLC-SEC). Proteins were detected by a UV/VIS diode array, time-based fraction collection was carried out, and each collected fraction was used to evaluate the synthesis of CuO-NPs. The characterization of CuO-NPs was evaluated by Dynamic Light Scattering (DLS), Z-potential, Fourier Transform Infrared (FTIR), Transmission Electron Microscope (TEM) equipped with Energy Dispersive X-ray Spectroscopy (EDS) detector. Low Molecular Weight (LMW) and High Molecular... [more]
Microemulsion vs. Precipitation: Which Is the Best Synthesis of Nickel−Ceria Catalysts for Ethanol Steam Reforming?
Cristina Pizzolitto, Federica Menegazzo, Elena Ghedini, Arturo Martínez Arias, Vicente Cortés Corberán, Michela Signoretto
October 14, 2021 (v1)
Keywords: coke resistance, ethanol steam reforming, lanthanum doping, microemulsion, Ni/CeO2
Ethanol steam reforming is one of the most promising ways to produce hydrogen from biomass, and the goal of this research is to investigate robust, selective and active catalysts for this reaction. In particular, this work is focused on the effect of the different ceria support preparation methods on the Ni active phase stabilization. Two synthetic approaches were evaluated: precipitation (with urea) and microemulsion. The effects of lanthanum doping were investigated too. All catalysts were characterized using N2-physisorption, temperature programmed reduction (TPR), XRD and SEM, to understand the influence of the synthetic approach on the morphological and structural features and their relationship with catalytic properties. Two synthesis methods gave strongly different features. Catalysts prepared by precipitation showed higher reducibility (which involves higher oxygen mobility) and a more homogeneous Ni particle size distribution. Catalytic tests (at 500 °C for 5 h using severe Ga... [more]
Investigation of Ni−Fe−Cu-Layered Double Hydroxide Catalysts in Steam Reforming of Toluene as a Model Compound of Biomass Tar
David Díez, Ana Urueña, Gregorio Antolín
October 14, 2021 (v1)
Keywords: gasification, hydrogen production, hydrotalcite, layered double hydroxide, Ni-based catalyst, tar, toluene steam reforming
This work focused on the synthesis of a catalyst based on layered double hydroxides with a molar cation concentration Ni/Cu/Fe/Mg/Al of 30/5/5/40/20 and its performance in the steam reforming of toluene as a model compound of biomass tar. Its performance at different temperatures (500, 600, 700, 800, and 900 °C) and steam/carbon molar ratios (S/C ratios) (1, 2, 4, 6, 8) was studied. The contact time used was 0.32 g h mol−1. The catalyst obtained allowed us to reach 98−99.87% gas conversion of toluene with a low carbon deposition on catalyst surface (1.4 wt %) at 800 °C and S/C = 4. In addition, conversions in the range of 600−700 °C were higher than 80% and 90%, respectively, and the type of carbon deposited on the catalyst was found to be filamentous, which did not significantly reduce the performance of the catalyst.
Research on Optimization of Coal Slime Fluidized Bed Boiler Desulfurization Cooperative Operation
Yangjian Xiao, Yudong Xia, Aipeng Jiang, Xiaofang Lv, Yamei Lin, Hanyu Zhang
October 14, 2021 (v1)
Keywords: boiler thermal efficiency, cooperative optimization, mechanism model, Simulation, slime fluidized bed
The semi-dry desulfurization of slime fluidized bed boilers (FBB) has been widely used due to its advantages of low cost and high desulfurization efficiency. In this paper, the cooperative optimization of a two-stage desulfurization processes in the slime fluidized bed boiler was studied, and a model-based optimization strategy was proposed to minimize the operational cost of the desulfurization system. Firstly, a mathematical model for the FBB with a two-stage desulfurization process was established. The influences of coal slime elements on combustion flue gas and the factors that may affect the thermal efficiency of the boiler were then analyzed. Then, on the basis of the developed model, a number of parameters affecting the SO2 concentration at the outlet of the slime fluidized bed boiler were simulated and deeply analyzed. In addition, the effects of the sulfur content of coal slime, excess air coefficient, and calcium to sulfur ratio were also discussed. Finally, according to the... [more]
Using Neural Networks to Obtain Indirect Information about the State Variables in an Alcoholic Fermentation Process
Anca Sipos, Adrian Florea, Maria Arsin, Ugo Fiore
October 14, 2021 (v1)
Keywords: fermentation process, neural network, prediction application
This work provides a manual design space exploration regarding the structure, type, and inputs of a multilayer neural network (NN) to obtain indirect information about the state variables in the alcoholic fermentation process. The main benefit of our application is to help experts reduce the time needed for making the relevant measurements and to increase the lifecycles of sensors in bioreactors. The novelty of this research is the flexibility of the developed application, the use of a great number of variables, and the comparative presentation of the results obtained with different NNs (feedback vs. feed-forward) and different learning algorithms (Back-Propagation vs. Levenberg−Marquardt). The simulation results show that the feedback neural network outperformed the feed-forward neural network. The NN configuration is relatively flexible (with hidden layers and a number of nodes on each of them), but the number of input and output nodes depends on the fermentation process parameters.... [more]
Encapsulation of Lactoferrin for Sustained Release Using Particles from Gas-Saturated Solutions
Kento Ono, Hiroki Sakai, Shinichi Tokunaga, Tanjina Sharmin, Taku Michael Aida, Kenji Mishima
October 14, 2021 (v1)
Subject: Biosystems
Keywords: enteric polymer, gastric digestion, lactoferrin, PGSS, shellac
The particles from gas saturated solutions (PGSS) process were performed to encapsulate lactofer-rin, an iron-binding milk glycoprotein, using supercritical carbon dioxide (scCO2). A natural en-teric polymer, shellac, was used as a coating material of lactoferrin carried out by the PGSS pro-cess. Conditions were optimized by applying different temperatures (20−50 °C) and pressures (8−10 MPa) and the particles were evaluated for particle shape and size, lactoferrin encapsulation ef-ficiency, Fourier transform infrared (FTIR) spectroscopy to confirm lactoferrin entrapment and in vitro dissolution studies at different pH values. Particles with an average diameter of 75.5 ± 7 μm were produced with encapsulation efficiency up to 71 ± 2%. Furthermore, particles that showed high stability in low pH (pH 1.2) and a sustained release over time (t2h = 75%) in higher pH (pH 7.4) suggested an effective encapsulation process for the protection of lactoferrin from gastric di-gestion.
Snapse: A Visual Tool for Spiking Neural P Systems
Aleksei Dominic C. Fernandez, Reyster M. Fresco, Francis George C. Cabarle, Ren Tristan A. de la Cruz, Ivan Cedric H. Macababayao, Korsie J. Ballesteros, Henry N. Adorna
October 14, 2021 (v1)
Keywords: membrane computing, spiking neural P systems, visual simulator
Spiking neural P (SN P) systems are models of computation inspired by spiking neurons and part of the third generation of neuron models. SN P systems are equivalent to Turing machines and are able to solve computationally hard problems using a space-time trade-off. Research in SN P systems theory is especially active, more so in recent years as more efforts are directed towards their real-world applications. Usually, SN P systems are represented visually as a directed graph and simulated through mainly text-based simulations or tables. Thus, there is a need for tools that can simulate and create SN P Systems in a visual and easy-to-use manner. Snapse is such a tool which aims to hasten the speed and ease at which researchers may create and experiment with SN P systems. Furthermore, visual tools such as Snapse can help further bring SN P systems outside of theoretical computer science.
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
Outi M. H. Salo-Ahen, Ida Alanko, Rajendra Bhadane, Alexandre M. J. J. Bonvin, Rodrigo Vargas Honorato, Shakhawath Hossain, André H. Juffer, Aleksei Kabedev, Maija Lahtela-Kakkonen, Anders Støttrup Larsen, Eveline Lescrinier, Parthiban Marimuthu, Muhammad Usman Mirza, Ghulam Mustafa, Ariane Nunes-Alves, Tatu Pantsar, Atefeh Saadabadi, Kalaimathy Singaravelu, Michiel Vanmeert
October 14, 2021 (v1)
Subject: Biosystems
Keywords: binding free energy, computational pharmaceutics, computer-aided drug design, conformational ensemble, drug formulations, drug targets, enhanced sampling methods, ligand binding kinetics, membrane interactions, protein flexibility
Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels a... [more]
Optimization Studies of AC4CH Material in the Cylinder Block of a Diesel Engine Application
Bum Youl Park, Youngkun Kim, Kihyung Lee
October 14, 2021 (v1)
Subject: Materials
Keywords: AC4CH, diesel engine, refinement, weight reduction
The reduction of the weight of the engine of a vessel or an automobile can result in improved engine efficiency and lower CO2 emissions. Therefore, this study was conducted to improve the mechanical properties of the AC4CH alloy, an alternative to cast iron for engine fabrication, through the addition of Si and Mg to aluminum. The mechanical properties of the alloy were improved through refinement of the Si structure, grain refinement, and heat treatment. In addition, the applicability of a cylinder block fabricated with the modified AC4CH alloy to a diesel engine was validated through a 300 h durability test.
Research on Rotating Machinery Fault Diagnosis Method Based on Energy Spectrum Matrix and Adaptive Convolutional Neural Network
Yiyang Liu, Yousheng Yang, Tieying Feng, Yi Sun, Xuejian Zhang
October 14, 2021 (v1)
Keywords: convolutional neural network, dynamic adjustment of the learning rate, energy spectrum matrix, hierarchical fault diagnosis, rotating machinery
Traditional intelligent fault diagnosis methods focus on distinguishing different fault modes, but ignore the deterioration of fault severity. This paper proposes a new two-stage hierarchical convolutional neural network for fault diagnosis of rotating machinery bearings. The failure mode and failure severity are modeled as a hierarchical structure. First, the original vibration signal is transformed into an energy spectrum matrix containing fault-related information through wavelet packet decomposition. Secondly, in the model training method, an adaptive learning rate dynamic adjustment strategy is further proposed, which adaptively extracts robust features from the spectrum matrix for fault mode and severity diagnosis. To verify the effectiveness of the method, the bearing fault data was collected using a rotating machine test bench. On this basis, the diagnostic accuracy, convergence performance and robustness of the model under different signal-to-noise ratios and variable load env... [more]
Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case Study
Stefanie Hering, Nico Schäuble, Thomas M. Buck, Brigitta Loretz, Thomas Rillmann, Frank Stieneker, Claus-Michael Lehr
October 14, 2021 (v1)
Keywords: 3D simulation modeling and analysis, bottleneck analysis, model implementation, production costs, resource conservation
Increasing regulatory demands are forcing the pharmaceutical industry to invest its available resources carefully. This is especially challenging for small- and middle-sized companies. Computer simulation software like FlexSim allows one to explore variations in production processes without the need to interrupt the running process. Here, we applied a discrete-event simulation to two approved film-coated tablet production processes. The simulations were performed with FlexSim (FlexSim Deutschland—Ingenieurbüro für Simulationsdienstleistung Ralf Gruber, Kirchlengern, Germany). Process visualization was done using Cmap Tools (Florida Institute for Human and Machine Cognition, Pensacola, FL, USA), and statistical analysis used MiniTab® (Minitab GmbH, Munich, Germany). The most critical elements identified during model building were the model logic, operating schedule, and processing times. These factors were graphically and statistically verified. To optimize the utilization of employees,... [more]
The Influence of Hydrodynamic Changes in a System with a Pitched Blade Turbine on Mixing Power
Jacek Stelmach, Czesław Kuncewicz, Szymon Szufa, Tomas Jirout, Frantisek Rieger
October 14, 2021 (v1)
Subject: Other
Keywords: impeller, Mixing, pitched blade turbine, power consumption
This paper presents an analysis of hydrodynamics in a tank with a 45° and 60° pitched blade turbine impeller operating while emptying the mixer and with an axial agitator working during axial pumping-down of water at different water levels above the impeller. Measurements made with the PIV method confirmed the change in direction of pumping liquid after the level dropped below the critical value, with an almost unchanged liquid stream flowing through the mixer. It was found that an increase in the value of the tangential velocity in the area of the impeller took place and the quantity of this increase depended on the angle of the blade pitch and the rotational frequency of the impeller. Change in this velocity component increased the mixing power.
Graphitic Carbon Nitride-Based Composite in Advanced Oxidation Processes for Aqueous Organic Pollutants Removal: A Review
Yu Shen, Antonio J. Dos santos-Garcia, María José Martín de Vidales
October 14, 2021 (v1)
Subject: Materials
Keywords: advanced oxidation processes, aqueous organic pollutants removal, graphitic carbon nitride
In recent decades, a growing number of organic pollutants released have raised worldwide concern. Graphitic carbon nitride (g-C3N4) has drawn increasing attention in environmental pollutants removal thanks to its unique electronic band structure and excellent physicochemical stability. This paper reviews the recent progress of g-C3N4-based composites as catalysts in various advanced oxidation processes (AOPs), including chemical, photochemical, and electrochemical AOPs. Strategies for enhancing catalytic performance such as element-doping, nanostructure design, and heterojunction construction are summarized in detail. The catalytic degradation mechanisms are also discussed briefly.
Machine Learning for Ionic Liquid Toxicity Prediction
Zihao Wang, Zhen Song, Teng Zhou
October 14, 2021 (v1)
Keywords: ionic liquid, Machine Learning, neural network, support vector machine, toxicity
In addition to proper physicochemical properties, low toxicity is also desirable when seeking suitable ionic liquids (ILs) for specific applications. In this context, machine learning (ML) models were developed to predict the IL toxicity in leukemia rat cell line (IPC-81) based on an extended experimental dataset. Following a systematic procedure including framework construction, hyper-parameter optimization, model training, and evaluation, the feedforward neural network (FNN) and support vector machine (SVM) algorithms were adopted to predict the toxicity of ILs directly from their molecular structures. Based on the ML structures optimized by the five-fold cross validation, two ML models were established and evaluated using IL structural descriptors as inputs. It was observed that both models exhibited high predictive accuracy, with the SVM model observed to be slightly better than the FNN model. For the SVM model, the determination coefficients were 0.9289 and 0.9202 for the training... [more]
LC-UV and UPLC-MS/MS Methods for Analytical Study on Degradation of Three Antihistaminic Drugs, Ketotifen, Epinastine and Emedastine: Percentage Degradation, Degradation Kinetics and Degradation Pathways at Different pH
Anna Gumieniczek, Izabela Kozak, Paweł Żmudzki, Urszula Hubicka
October 14, 2021 (v1)
Subject: Biosystems
Keywords: degradation in solutions, epinastine and emedastine, ketotifen, LC-UV and UPLC-MS/MS methods, new degradation products, pH and high temperature
Evaluation of pH-dependent reactivity of drugs is an essential component in the pharmaceutical industry. Thus, the stability of three antihistaminic drugs, i.e., ketotifen, epinastine and emedastine, was tested, in solutions of five pH values, i.e., 1.0, 3.0, 7.0, 10.0 and 13.0, at high temperature (70 °C). LC-UV isocratic methods were developed to estimate percentage degradation as well as the kinetics of degradation. Generally, epinastine was shown to be the most stable compound with degradation below 14%. Emedastine was labile in all pH conditions, with degradation in the range 29.26−51.88%. Ketotifen was moderately stable at pH 1−7 (degradation ≤ 14.04%). However, at pH ≥ 10, its degradation exceeded 30%. The kinetics of degradation of ketotifen, epinastine and emedastine was shown as a pseudo-first-order reaction with the rate constants in the range 10−4−10−3 min−1 Finally, the UPLC-MS/MS method was applied to identify the main degradants and suggest degradation pathways. Degradat... [more]
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