Multicomponent adsorption isotherm modeling using thermodynamically inconsistent and consistent models

In this work, the multicomponent adsorption modeling of the experimental adsorption data of ternary system consisting of nitrobenzene (NI), phenol (PH) and aniline (AN) onto granulated activated carbon (GAC) was performed. The Redlich–Peterson and Freundlich isotherm models provided better fitting of the single component experimental data than the Langmuir isotherm model. The adsorption preference of GAC was found to be: NI > PH > AN. The ternary adsorption equilibrium data were analyzed by using thermodynamically consistent and inconsistent isotherm models as well as an artificial neural network model. Modified Redlich–Peterson and LeVan–Vermeulen models, and real adsorbed solution theory model provided satisfactory fit of the ternary system. Levenberg–Marquardt back-propagation or scaled conjugate gradient back-propagation algorithm with two neurons, either logsig or tansig transfer function in the hidden layer, and purelin transfer function in output layer were found to be the best network and gave an excellent prediction of experimental data.     

A comparison of isotherm and kinetic models for binary-solute adsorption to affinity membranes

Single-solute isotherms for pepsin (EC 3.4.23.1) and chymosin (EC 3.4.23.4) adsorption to affinity membranes were fitted using five of the most popular isotherm models. It was found that the single-solute Langmuir isotherm was the best two-parameter model, although the three-parameter models gave even better fitting. Experimental binary-solute adsorption isotherms were compared with four different types of binary-solute Langmuir models using the single-solute parameters. The results showed that the difference in the saturation capacities affected the adsorption equilibrium. Furthermore, three types of binary-solute Langmuir models were converted into the kinetic form and used to calculate the association rate constants of pepsin and chymosin from experimental data. The best-fitted rate constant values were found to be identical for different kinetic models. However, the model predictions of association curves were significantly influenced when the values of association rate constants were changed.     

A new approach for modeling adsorption kinetics and transport of methane and carbon dioxide in shale

In this article, a new approach is proposed to investigate adsorption kinetics and transport of gases in shale. Due to co-existence of pores with different size in the shale, a set of adsorption processes happened in pores of different sizes are considered. A first-order multi-process model is developed, which can perfectly fit the adsorption kinetic data of CH₄ and CO₂ obtained at different temperatures. The modeling and pore characterization results indicate that an adsorption process happens in micropores/mesopores (<50 nm) and another adsorption process happens in macropores (>50 nm) in the Wufeng shale. Gas diffusion mechanism is dominant in micropores/mesopores, and gas seepage mechanism is dominant in macropores. The effective diffusivity of CO₂ is smaller than that of CH₄, because the adsorption of large amount of CO₂ in the pores hinders its diffusion. The coefficients related to the diffusion and seepage have no obvious trend with temperature.     

Synthesis and adsorption properties of metal ions of novel azacrown ether crosslinked chitosan

Azacrown ether chitosan (CTSC) was synthesized by the reaction of chitosan with N‐allyl benzo 15‐crown‐5 crown ether. Azacrown ether crosslinked chitosan (CCTSC) was prepared by the crosslinked reaction of CTSC and epichlorodydrin. Their structures were confirmed by infrared spectral analysis and X‐ray diffraction analysis. The adsorption properties of CTSC and CCTSC for metal ions were also investigated. The experimental results showed that the two chitosan derivatives not only had a good capacity to adsorb Pd²⁺ and Ag⁺ but also was highly selective for Pd²⁺ and Ag⁺ in the coexistence system containing other metal ions. At 20°C ± 1°C and pH = 4, the adsorption capacity of CTSC and CCTSC for Pd²⁺ was 186.1 and 173.1 mg/g, respectively; and for Ag⁺ was 90.2 and 56.5 mg/g, respectively. The selectivity coefficients were K = 6.99, K = ∞, K = 35.38, K = ∞ for CTSC and K = 10.66, K = ∞, K = 85.45, K = ∞ for CCTSC. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 2705–2709, 2006     

Effect of Zn substitution on the structural and magnetic properties of nanocrystalline NiFe2O4 ferrites

Nanocrystalline Ni_1?xZn_xFe₂O₄ (where, x = 0.0, 0.2, 0.4, 0.6, 0.8 & 1) samples were synthesized through solution combustion technique using oxylyl de-hydrazide (ODH) as a fuel and the effect of dopant and its concentration on the structural and magnetic properties was investigated. As-prepared samples were characterized using different characterization techniques such as, XRD, SEM-EDS, TEM and Raman spectroscopy for their phase-purity, crystallinity, surface morphology and elemental composition; also magnetic properties were investigated through EPR, Mossbauer spectroscopy and vibrating sample magnetometer (VSM). Rietveld fitted XRD and Raman studies confirm the formation of cubic spinel structured ferrites and substitution of Zn ion at Ni site without formation of impurity phases. No other structural changes were observed and the structure remains in cubic phase with increase of Zn concentration. SEM and TEM micrographs reveal that the particles are agglomerated and the particles size were found in the nano range. Also good stoichiometric composition was observed in all the compositions of Zn substituted Ni ferrite samples. Magnetic measurements (VSM) reveal that pure Ni ferrites exhibits soft magnetic behaviour. Further the ferromagnetic behaviour suppressed with the substitution of diamagnetic Zn ion and with increase of its concentration in Ni ferrites, which was further evidenced in the Mossbauer spectroscopic results. At room temperature, electronic paramagnetic resonance spectra exhibits a broad resonance signal with Lande's g factor varies from 2.23 to 1.95 with increase in Zn content, which is attributed to spin exchange interactions between Fe³⁺, Ni²⁺ and Zn²⁺ ions also asymmetric EPR spectra was observed. The investigated results show that, Zn substitution has greater impact on the magnetic properties of Ni ferrites due to the diamagnetic nature of Zn, which inturn alters the cationic distribution and the exchange interactions between Ni-Fe and Fe-Fe.     

Application of convolutional neural networks to large-scale naphtha pyrolysis kinetic modeling

System design and optimization problems require large-scale chemical kinetic models. Pure kinetic models of naphtha pyrolysis need to solve a complete set of stiff ODEs and is therefore too computational expensive. On the other hand, artificial neural networks that completely neglect the topology of the reaction networks often have poor generalization. In this paper, a framework is proposed for learning local representations from large-scale chemical reaction networks. At first, the features of naphtha pyrolysis reactions are extracted by applying complex network characterization methods. The selected features are then used as inputs in convolutional architectures. Different CNN models are established and compared to optimize the neural network structure. After the pre-training and fine-tuning step, the ultimate CNN model reduces the computational cost of the previous kinetic model by over 300 times and predicts the yields of main products with the average error of less than 3%. The obtained results demonstrate the high efficiency of the proposed framework.     

Structure and adsorption properties of activated carbon aerogels

Activated carbon aerogels (ACAs) with excellent microporosity (e.g., 0.44 cm³/g) and mesoporosity (e.g., 1.72 cm³/g) were prepared by CO₂ activation. Their structures were investigated with transmission electron microscopy and N₂ adsorption–desorption analysis. Subsequently, their adsorption properties toward organic vapors were studied with static and dynamic adsorption experiments. The micropores of the ACAs had stronger adsorption ability than those of normal porous carbons. Furthermore, the condensation of organic vapors in the mesopores of ACAs greatly enhanced their equilibrium adsorption at high relative pressures. As a result, the adsorption capacities of organic vapors on the typical ACAs prepared were about 2–3 times greater than those on normal porous carbons. In addition, they also possessed excellent adsorption dynamics and outstanding desorption and regeneration properties. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci, 2006     

Synthesis and adsorption properties for metal ions of crosslinked chitosan acetate crown ethers

Two novel chitosan derivatives—crosslinked chitosan dibenzo‐16‐c‐5 acetate crown ether (CCTS‐1) and crosslinked chitosan 3,5‐di‐tert‐butyl dibenzo‐14‐c‐4 diacetate crown ether (CCTS‐2)—were synthesized by the reaction of crosslinked chitosan with dibenzo‐16‐c‐5 chloracetate crown ether and 3,5‐di‐tert‐butyl dibenzo‐14‐c‐4 dichloracetate crown ether with the intent of forming polymers that could be used in hazardous waste remediation as toxic metal‐binding agents in aqueous environments. Their structures were confirmed with elemental analysis, infrared spectral analysis, and X‐ray diffraction analysis. In the infrared spectra of CCTS‐1 and CCTS‐2, the characteristic peaks of aromatic backbone vibration appeared at 1595 cm⁻¹ and 1500 cm⁻¹; the intensity of the N H and O H stretching vibration in the region of 3150–3200 cm⁻¹ decreased greatly. The X‐ray diffraction analysis showed that the peak at 2θ = 20° decreased greatly in CCTS‐1 and CCTS‐2. The adsorption and selectivity properties of CCTS‐1 and CCTS‐2 for Pb²⁺, Cu²⁺, Cr³⁺, and Ni²⁺ were studied. Experimental results showed that the two crosslinked chitosan derivatives had not only good adsorption capacities for Pb²⁺, Cu²⁺, but also high selectivity for Pb²⁺, Cu²⁺ in the coexistence of Ni²⁺. For aqueous systems containing Pb²⁺, Ni²⁺, or Cu²⁺, Ni²⁺, CCTS‐1 only adsorbed Pb²⁺ or Cu²⁺. For aqueous systems containing Pb²⁺, Cr²⁺ and Ni²⁺, CCTS‐2 had high adsorption and selectivity properties for Pb²⁺. © 1999 John Wiley & Sons, Inc. J Appl Polym Sci 71: 2069–2074, 1999     

Ammonia synthesis kinetics: Surface chemistry,rate expressions,and kinetic analysis

The results of surface science studies of nitrogen adsorption and desorption on iron single crystals are summarized with respect to ammonia synthesis reaction kinetics. Analytical rate expressions for ammonia synthesis on high surface iron catalysts at industrial reaction conditions are presented and compared to the behavior of microkinetic models based on the surface science results. Microkinetic models based on uniform surfaces are successful in extrapolating results from surface science studies at low surface coverages to describe the performance of iron catalysts at industrial ammonia synthesis reaction conditions. We suggest that the value of rate constant for recombination of nitrogen atoms on the surface is a weak function of surface coverage. Furthermore, modest variations in the heat of N₂ adsorption are sufficient to achieve fractional ammonia orders that are relatively insensitive to the ammonia pressure.     

Preparation of electrodes for hybrid capacitive deionization and its influence on the adsorption behaviour

ABSTRACT

The influence of the ratio of poly(vinyl chloride) in electrode composition into their surface energetics, hybrid capacitive deionization performance as well as adsorption kinetics and isotherms was evaluated. The electrodes were comprised of lithium manganese titanium oxide or activated carbon. Electrodes were tested by used hybrid capacitive deionization. To testing surface energetic the goniometer measurements were applied. It was possible to calculate free surface energy with its components. For investigated the adsorption kinetics the pseudo first order, pseudo second order, Weber–Morris intraparticle diffusion, Elovich models were chosen. While for the detection of adsorption isotherms Temkin and Harkins–Jura models were examined.     

A new approach for kinetic modeling and optimization of rubber molding

Although extensive research has been carried out on the understanding of the complex vulcanization process, the influence of reversion through exposure time and temperature on the vulcanization degree remains unclear. Therefore, the main aim of this study was a novel optimization approach that can help the industrial practitioners to select the optimal operating parameters, exposure time, and molding temperature, to achieve desired vulcanization degree of selected product. Spheres of four different diameters (2.5, 5, 10, and 20 cm) were selected as test geometry for simulation and optimization of rubber molding. Obtained vulcanization rheometer data for commercially available rubber blend (NR/SBR) were fitted by a new modeling approach, dividing vulcanization curve into two fitting sets: curing and reversion. The heat transfer equations for chosen geometry were coupled with proposed kinetic model. A new temperature-dependent kinetic parameter x, as the maximal reversion degree, was introduced, enabling determination of the lowest operating molding temperature (T_min = 132.36 °C), preventing high reversion and overheating of the rubber product. The final optimization goal was assessment of the optimal temperature and vulcanization time dependence on the rubber products dimensions. Proposed models have precise prediction with R² values greater than 0.8328 and MAPE less than 2.3099%.     

Automatic data-driven stoichiometry identification and kinetic modeling framework for homogeneous organic reactions

Data-driven and knowledge-driven methods are two approaches used in studying reaction kinetics. This article proposes a hybrid-modeling framework for homogeneous synthesis reactions, which combines the advantages of high level of automation in the data-driven approach and improved accuracy in the knowledge-driven approach. A constrained enumeration method is proposed to generate possible candidate stoichiometries, and dynamic response surface methodology, target factor analysis, and mass balance are used together for identifying stoichiometries one-by-one, without the necessity of an expert-generated candidate list. Then, the previously screened stoichiometries are formed into different groups that represent candidate reaction systems, and the group (or groups) with the greatest likelihood will be identified, based on kinetic fitting and reaction dynamic criteria. This framework has been demonstrated by several examples of different reaction systems. The true reaction stoichiometries are all correctly identified, and the accurate kinetic models are obtained, showing satisfactory performance of the proposed method.     

Removal of divalent nickel from aqueous solution using blue-green marine algae: adsorption modeling and applicability of various isotherm models

Adsorption of Ni(II) onto blue-green marine algae (BGMA) is investigated under batch condition. Under optimum experimental conditions, the initial Ni(II) metal ion concentration is varied from 25 to 250 ppm and the maximum adsorption capacity of BGMA is found to be 42.056 mg/g. The optimum pH, biomass loading, and an agitation rate on maximum removal of Cu(II) ion are found to be 6, 2 g, and 120 rpm, respectively. 24 h of contact time is allowed to achieve equilibrium condition. All the experiments are carried out at room temperature. The equilibrium experimental data infer that the isotherm is L-shaped. It is the indication of no strong competition between solvent and Ni(II) to occupy the active sites of BGMA. Also, it indicates that the BGMA has a limited sorption capacity for adsorption of Ni(II). The experimental data are tested with various isotherm models; subsequently, the mechanism of adsorption is identified and the characteristic parameters for process design are established. Fritz–Schlunder-V isotherm model is highly significant in establishing the mechanism of adsorption of Ni(II) under the conditions employed in this investigation followed by Freundlich. The q_max of 41.89 mg/g obtained by this model indicates its relevance more precisely with experimental data.     

Equilibrium,kinetic, diffusion and thermodynamic applications for dye adsorption with pine cone

ABSTRACT

In the present study, the adsorption of methylene blue onto pine cone was investigated. Adsorbent was characterized by XRD and SEM. The adsorption data follow the Langmuir isotherm model. Maximum adsorption capacity was calculated 125 mg.g^?1 . It was determined that the pseudo-second-order model was the best choice among all the available kinetic models to describe the adsorption behaviour. E_a was found to be 19.57 kJ mol^?1. This confirms the fact that the adsorption was a physical process. The negative free energy values indicate the feasibility of the adsorption process and its spontaneous nature.     

表面活性素集成生产过程(Ⅲ)吸附柱的模型

The study is focused on modeling of separation process and optimization.An adsorption separation process is simulated.The surfactin production process by Bacillus subtilis ATCC 21332 followed by surfactin adsorption in a fixed-bed column packed with commercial active carbon is studied in laboratory.The adsorption column achieves high surfactin recovery(94%)by up-flow methanol elution at 25°C.The adsorption column is simulated with a complex one-dimensional plug flow dispersion model coupled with nonlinear adsorption equilibrium,based on the assumption that the adsorption of surfactin is monomolecular layer and no micelle is formed.The molecular diffusion coefficient of surfactin in water solution with electric neutrality is estimated to be 0.428×10 -5 cm 2 ·s -1 by molecular dynamics simulation.The model developed can describe the complex interplay of adsorption kinetics,fluid dynamics,and mass-transfer phenomena based on the assumption of no radial temperature and concentration gradients,and is of adequate precision.The work involved in this paper is valuable for the optimization of the production process of surfactin.     

Optimization of multicomponent photopolymer formulations using high‐throughput analysis and kinetic modeling

While high throughput and combinatorial techniques have played an instrumental role in materials development and implementation, numerous problems in materials science and engineering are too complex and necessitate a prohibitive number of experiments, even when considering high throughput and combinatorial approaches, for a comprehensive approach to materials design. Here, we propose a unique combination of high throughput experiments focused on binary formulations that, in combination with advanced modeling, has the potential to facilitate true materials design and optimization in ternary and more complex systems for which experiments are never required. Extensive research on the development of photopolymerizable monomer formulations has produced a vast array of potential monomer/comonomer, initiator and additive combinations. This array dramatically expands the range of material properties that are achievable; however, the vast number of potential formulations has eliminated any possibility of comprehensive materials design or optimization. This limitation is addressed by maximizing the benefits and unique capabilities of high throughput experimentation coupled with predictive models for material behavior and properties. The high throughput experimentation‐model combination is useful to collect a limited amount of data from as few as 11 experiments on binary combinations of 10 analyzed monomers, and then use this limited data set to predict and optimize formulation properties in ternary resins that would have necessitated at least 1000 high throughput experiments and several orders of magnitude greater numbers of traditional experiments. A data analysis approach is demonstrated, and the model development and implementation for one model application in which a range of material properties are prescribed, and an optimal formulation that meets those properties is predicted and evaluated. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

Optimization of kinetic data for two‐stage batch adsorption of Pb(II) ions onto tripolyphosphate‐modified kaolinite clay

BACKGROUND: Most adsorption studies consider only the adsorption of pollutants onto low cost adsorbents without considering how equilibrium and kinetic data can be optimized for the proper design of adsorption systems. This study considers the optimization of kinetic data obtained for the removal of Pb(II) from aqueous solution by a tripolyphosphate modified kaolinite clay adsorbent. RESULTS: Modification of kaolinite clay with pentasodium tripolyphosphate increases its cation adsorption capacity (CEC) and specific surface area (SSA) from 7.81 to 78.9 meq (100 g)^?1 and 10.56 to 13.2 m² g^?1 respectively. X‐ray diffraction patterns for both unmodified and tripolyphosphate‐modified kaolinite clay suggest the modification is effective on the surface of the clay mineral. Kinetic data from the batch adsorption of Pb(II) onto the tripolyphosphate‐modified kaolinite clay adsorbent were optimized to a two‐stage batch adsorption of Pb(II) using the pseudo‐second‐order kinetic model. Mathematical model equations were developed to predict the minimum operating time for the adsorption of Pb(II). Results obtained suggest that increasing temperature and decreasing percentage Pb(II) removal by the adsorbent enhanced operating time of the adsorption process. The use of two‐stage batch adsorption reduces contact time to 6.7 min from 300 min in the single‐stage batch adsorption process for the adsorption of 2.5 m³ of 500 mg L^?1 Pb(II) under the same operating conditions. CONCLUSION: Results show the potential of a tripolyphosphate‐modified kaolinite clay for the adsorption of Pb(II) from aqueous solution and the improved efficiency of a two‐stage batch adsorption process for the adsorption of Pb(II) even at increased temperature. Copyright © 2009 Society of Chemical Industry     

Synthesis,characterization, and adsorption properties of chitosan azacrown ethers bearing hydroxyl group

Two new chitosan azacrown ethers bearing hydroxyl groups (CTS‐DH and CTS‐DO) were synthesized by the reaction of 3‐hydroxyl‐1,5‐diaza‐cycloheptane and 3‐hydroxyl‐1,5‐diaza‐cyclooctane with epoxy‐activated chitosan. Their structures were characterized by elemental analysis, infrared spectra analysis, and X‐ray diffraction analysis. The adsorption and selectivity properties of the hydroxyl azacrown ethers chitosan derivatives for Ag⁺, Cr³⁺, Cd²⁺, and Pb²⁺ were also investigated. The experimental results showed that the two novel chitosan azacrown ethers have good adsorption capacity for Ag⁺, and also showed that the grafted chitosan azacrown ethers have high selectivity for the adsorption of Ag⁺ in the presence of Pb²⁺ and Cd²⁺. The selectivity coefficients of CTS‐DH and CTS‐DO were K = 21, K = 42, K = 20.5, K = 41, respectively. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 81: 1793–1798, 2001     

3D打印用聚丙烯复合材料的制备及性能研究

将碳酸钙和滑石粉按质量比为1∶1混合,与聚丙烯(PP)共混,制备可用于熔融沉积法(FDM)打印的PP材料,研究填料用量对3D打印试样力学性能和微观结构的影响。结果表明,随着填料用量的增大,3D打印制品的力学性能下降,PP材料的收缩率显著降低,试样内部纤维之间无空隙。当碳酸钙和滑石粉质量各占配方总质量的20%时,3D打印的PP制品性能最好。