Multi-fluid modeling biomass fast pryolysis with particle shrinkage model for complex reaction kinetics

This numerical study investigates the effects of operating conditions on the product yields of a biomass fast pyrolysis reactor. A numerical approach that combines a multifluid model and pyrolysis reaction kinetics was applied to simulate the biomass fast pyrolysis process in a bubbling fluidized-bed reactor. The model was first validated using experimental data, and a parametric study was conducted. Operating parameters were varied to characterize their effects on the final product yields. For the reactor studied, it was found that the maximum tar yield could be obtained by maintaining both the wall temperature and the inlet temperature of nitorgen at approximately 800 K. The inlet velocity of nitrogen at about 0.6 m/s also produced favorable results. Simulations indicated that the optimal biomass particle diameter and the feeding rate were 900 μm and 1.92 kg/h, respectively, for tar production. Larger sand particle diameter and deeper initial sand bed also favored the tar yield.

Development of a generalized numerical framework for simulating biomass fast pyrolysis in fluidized-bed reactors

Canadian report voices concern over PVC plasticizer

The present work belongs to a bigger project whose main goal is to study the technical feasibility of the application of a relatively new heat treating concept, called Quenching and Partitioning (Q&P), as an alternative to the processing of high strength ductile cast irons. The aim of the Q&P process is to obtain multiphase microstructures consisting of martensite and carbon enriched retained austenite. Martensite confers high strength, whereas austenite confers ductility. In the Q&P process, after total or partial austenitization of the alloy, the material is quenched in a quenching temperature T Q between the Ms and Mf temperatures to produce a controlled mixture of martensite and austenite. Next, at the partitioning step, the material is isothermally held at a either equal or higher temperature (so called partitioning temperature T P ) in order to promote the carbon diffusion (partitioning) from martensite to austenite. The present work focus on the study of phase transformations aspects -with emphasis on the microstructural evolution and kinetics of the reactions -of the Q&P process applied to a ductile cast iron alloy (Fe-3,47%C-2,47%Si-0,2%Mn). Heat treatments consisted of austenitization at 880 C for 30 min, followed by quenching at 140, 170, and 200 C and partitioning at 300, 375 e 450 C up to 2 h. The microstructural characterization was carried out by optical microscopy (OM), scanning electron microscopy (SEM), electron backscattered diffraction (EBSD), and electron probe microanalysis (EPMA). The kinetic analysis was studied by high resolution dilatometry tests and in situ X-ray diffraction using a synchrotron light source. Results showed that competitive reactions -bainite reaction and carbides precipitation in martensite -is unavoidable during the Q&P process. The bainite reaction kinetics is accelerated by the presence of martensite formed in the quenching step. The bainite reaction occurs at low temperatures without carbides precipitation and contributes to the carbon enrichment of austenite and its stabilization. Due to carbides precipitation in martensite, growth of bainitic ferrite is the main mechanism of carbon enrichment of austenite. Microsegregation inherited from the casting process is present in the heat treated material and affects the martensite distribution and the kinetics of the bainite reaction. In regions corresponding to eutectic cell boundaries less martensite is observed and the kinetics of bainite reaction is slower. The final microestructure produced by the Q&P process applied to the ductile cast iron consists of tempered martensite with carbides, bainitic ferrite, and carbon enriched austenite. Additionally, a computational model was developed to calculate the local kinetics of carbon redistribution during the partitioning step, considering the ef-fects of carbides precipitation and bainite reaction. The model showed that the kinetics of carbon partitioning from martensite to austenite is slower when the tempering carbides are more stable and that, when the carbides free energy is sufficiently low, the carbon diffuses from austenite to martensite. The model is not limited to the studied conditions and can be applied to the development of Q&P heat treatments to steels.

Reaction kinetics for the hydrothermal carbonisation of cellulose in a two-phase pathway

In-situ Fourier transform infrared (FT-IR) spectroscopy has been recognized as an important technology for online monitoring of chemical reactions. However, analysis of the real-time IR data for identification and quantification of uncertain reactants or intermediates is often ambiguous and difficult. Here, we propose an analysis algorithm based on reaction kinetic modeling and the chemometric method of partial least squares (PLS) to comprehensively and quantitatively study reaction processes. Concentration profiles and apparent kinetic parameters can be simultaneously calculated from the spectral data, without the demand of complicated analysis on characteristic absorbance peaks or tedious sampling efforts for multivariate modeling. Paal-Knorr reactions and glyoxylic acid synthesis reactions were selected as typical reactions to validate the algorithm. A lack of fit of the Paal-Knorr reaction spectra was less than 2.5% at various conditions, and the absolute errors between the predicted values and HPLC measurement of glyoxylic acid synthesis were less than 6% during the reaction process. Moreover, the reaction kinetic models extracted from FT-IR data were used to simulate reaction processes and optimize the conditions in order to maximize product yields, which proved that this analysis method could be used for process optimization.

A fluidized sand bed reactor was used to study the production of gases from scrap tires at four nominal temperatures (ranging from 600 to 900 °C). Yields of 17 pyrolysis products (methane, ethane, ethylene, propane, propylene, acetylene, butane, butylene, 1,3-butadiene, pentane, benzene, toluene, xylenes + styrene, hydrogen, carbon monoxide, carbon dioxide, and hydrogen sulfide) were analyzed as a function of the operating conditions. The results are compared with the data obtained by pyrolysis of tires in a Pyroprobe 1000, where secondary tar cracking is small. Correlations between the products analyzed with those of methane are discussed.

Organic synthesis facilitates the conversion of raw materials into high‐value chemicals. Computer‐assisted synthetic planning plays a vital role in designing synthetic pathways, which are usually evaluated by the reaction probability using deep learning models. However, this criterion is generally hard to describe real reaction behaviors such as reaction kinetics. Therefore, this article aims to establish a reaction kinetics‐based retrosynthesis planning framework to design synthetic pathways with well‐performed reaction kinetics. The key contribution of this work is developing a method for the GENeration of initial guesses of Transition States based on Reactive Sites (GENiniTS‐RS) to automatically and fast generate the initial guesses of transition states for the transition state theory‐based reaction kinetic model without sampling the minimum energy path from reactants to products. Finally, two case studies involving the design of synthetic pathways for aspirin and ibuprofen are presented to demonstrate the feasibility and effectiveness of the proposed framework.

Although natural gas hydrates and hydrate exploration have been extensively studied for decades, the reaction kinetics and nucleation mechanism of hydrate formation is not fully understood. In its early stage, gas hydrate formation can be assumed to be an autocatalytic kinetic reaction with nucleation and initial growth. In this work, a reaction kinetics model has been established to form structure II methane–propane hydrate in an isochoric reactor. The computational model consists of six pseudo-elementary reactions for three dynamic processes: (1) gas dissolution into the bulk liquid, (2) a slow buildup of hydrate precursors for nucleation onset, and (3) rapid and autocatalytic hydrate growth after onset. The model was programmed using FORTRAN, with initiating parameters and rate constants that were derived or obtained from data fitted using experimental results. The simulations indicate that the length of nucleation induction is determined largely by an accumulation of oligomeric hydrate precursors up to a threshold value. The slow accumulation of precursors is the rate-limiting step for the overall hydrate formation, and its conversion into hydrate particles is critical for the rapid, autocatalytic reaction. By applying this model, the memory effect for hydrate nucleation was studied by assigning varied initial amounts of precursor or hydrate species in the simulations. The presence of pre-existing precursors or hydrate particles could facilitate the nucleation stage with a reduced induction time, and without affecting hydrate growth. The computational model with the performed simulations provides insight into the reaction kinetics and nucleation mechanism of hydrate formation.

A kinetic approach to the mathematical model of fixed bed gasifiers

Kinetic model for modern double-layered Pd/Rh TWC as a function of metal loadings and mileage

Modeling of the liquefaction reaction kinetics for the low-input high-diversity mixtures of native grassland perennials was studied. The highest liquid yield of 82% was achieved within a short residence time of 1 minute at 374°C and 22.1 MPa. Seven possible reaction schemes and kinetic models were developed and compared. The unknown kinetic parameters of each model were estimated by nonlinear least square method. Model 3, assuming that biomass first decomposes to condensable hydrocarbons or tars (liquid products), gaseous products, and solid chars via three competitive reactions and then tars are subjected to a second cracking reaction producing gases, is found to be the best one closely matching the experimental yield data obtained from liquefaction of prairie grasses. The effects of temperature on reaction rate constants for all the reactions except the biomass conversion to char were best described by Arrhenius-type equations. The model developed here in addition to helping better understand the fundamentals of reaction kinetics of biomass liquefaction is also helpful for prediction of three lumped products—liquid products, gaseous products, and solid chars, and rough design of biomass liquefaction reactors and subsequent techno-economic analysis of the process.

Multiscale analysis and modeling of multiphase chemical reactors

CFD-DEM simulation of fluorination reaction in fluidized beds with local grid and time refinement method

Multicomponent reaction kinetics for the ozonation of [formula omitted]-nitrophenol and its decomposition products under acidic conditions at constant pH