Time factors pyrolysis

As shown in Fig. 3 for different pyrolysis kinetics and a spherical particle which is exposed to a raAation flux from a blackbody dose to Ae isokinetic temperature, Ae time for pyrolysis may vary by a factor of 3. The Afference between Ae different kinetics increases wiA increasing diameter, because of Ae higher temperature difference over Ae particle. 

The pyrolysis of CR NH (<1 mbar) was perfomied at 1.3 atm in Ar, spectroscopically monitoring the concentration of NH2 radicals behind the reflected shock wave as a fiinction of time. The interesting aspect of this experiment was the combination of a shock-tube experiment with the particularly sensitive detection of the NH2 radicals by frequency-modulated, laser-absorption spectroscopy [ ]. Compared with conventional narrow-bandwidth laser-absorption detection the signal-to-noise ratio could be increased by a factor of 20, with correspondingly more accurate values for the rate constant k T). 

The Du Pont HaskeU Laboratory for Toxicology and Industrial Medicine has conducted a study to determine the acute inhalation toxicity of fumes evolved from Tefzel fluoropolymers when heated at elevated temperatures. Rats were exposed to decomposition products of Tefzel for 4 h at various temperatures. The approximate lethal temperature (ALT) for Tefzel resins was deterrnined to be 335—350°C. AH rats survived exposure to pyrolysis products from Tefzel heated to 300°C for this time period. At the ALT level, death was from pulmonary edema carbon monoxide poisoning was probably a contributing factor. Hydrolyzable fluoride was present in the pyrolysis products, with concentration dependent on temperature. 

ZnO displays similar redox and alloying chemistry to the tin oxides on Li insertion [353]. Therefore, it may be an interesting network modifier for tin oxides. Also, ZnSnOs was proposed as a new anode material for lithium-ion batteries [354]. It was prepared as the amorphous product by pyrolysis of ZnSn(OH)6. The reversible capacity of the ZnSn03 electrode was found to be more than 0.8 Ah/g. Zhao and Cao [356] studied antimony-zinc alloy as a potential material for such batteries. Also, zinc-graphite composite was investigated [357] as a candidate for an electrode in lithium-ion batteries. Zinc parhcles were deposited mainly onto graphite surfaces. Also, zinc-polyaniline batteries were developed [358]. The authors examined the parameters that affect the life cycle of such batteries. They found that Zn passivahon is the main factor of the life cycle of zinc-polyaniline batteries. In recent times [359], zinc-poly(anihne-co-o-aminophenol) rechargeable battery was also studied. Other types of batteries based on zinc were of some interest [360]. 

There have been a number of studies of magnetic fields upon radical recombination using steady-state techniques of photolysis or pyrolysis. They have variously found large or small effects, which are not always consistent with the theoretical predictions [304—306]. However, using laser flash photolysis techniques to provide fast time resolution, Turro et al. [307] followed the combination of benzyl radicals within hexadecyltrimethyl ammonium chloride micelles in water. The combination occurs over times < 100 ns. A magnetic field of 0.04 T reduces the rate of recombination by almost a factor of two. Such a magnetic field... 

The response of the cotton fiber to heat is a function of temperature, time of heating, moisture content of the fiber and the relative humidity of the ambient atmosphere, presence or absence of oxygen in the ambient atmosphere, and presence or absence of any finish or other material that may catalyze or retard the degradative processes. Crystalline state and DP of the cotton cellulose also affect the course of thermal degradation, as does the physical condition of the fibers and method of heating (radiant heating, convection, or heated surface). Time, temperature, and content of additive catalytic materials are the major factors that affect the rate of degradation or pyrolysis. 

It is essential to determine the yield of each major product rather precisely and at different values of the various operating parameters, mainly temperature, residence time, and pressure. Many studies are incompletely documented, considering only gas or liquid phase products, without mention of residues or mass balances. Moreover, in practice the product yield of pyrolysis is reduced by losses inherent to consecutive purification. Inevitable losses occur further during storage, transfer, and separation. Moreover, each raw material as a rule contains nonproductive constituents, such as some moisture, metal inserts, coatings, reinforcement agents, or fillers. These loss factors explain why laboratory data may lead to overly optimistic views regarding possible industrial yields ... 

Computer modeling of hydrocarbon pyrolysis is discussed with respect to industrial applications. Pyrolysis models are classified into four groups mechanistic, stoichiometric, semi-kinetic, and empirical. Selection of modeling schemes to meet minimum development cost must be consistent with constraints imposed by factors such as data quality, kinetic knowledge, and time limitations. Stoichiometric and semi-kinetic modelings are further illustrated by two examples, one for light hydrocarbon feedstocks and the other for naphthas. The applicability of these modeling schemes to olefins production is evidenced by successful prediction of commercial plant data. 

Another possible correlation between coal structure and pyrolysis behavior is indicated by the temperature dependence of the evolution of pyrolytic water being strikingly different for the two coals. Figure 5 shows pyrolytic water evolution data for experiments in which the sample was heated at 1000°C/sec to the peak temperature indicated on the abscissa and then immediately allowed to cool at around 200°C/sec. The smooth curves are based on a single reaction, first-order decomposition model (7,8) and on the stated temperature-time history. Parameters used for the lignite have been published (8) while for the bituminous coal the Arrhenius frequency factor and activation energy were taken as 1013 sec"1 and 35 kcal/mol, respectively, with the yield of pyrolytic water ultimately attainable estimated from experimental measurements as 4.6 wt % of the coal (as-received). 

The objective of sca)ing-up a vacuum pyrolysis reactor is to achieve the desired capacity and conversion of feedstock by defermining the dimension of the reactor. The feedstock conversion in a vacuum pyrolysis reactor mainly depends on three factors the heat transfer coefficient from the reactor to the feedstock the residence time of the feedstock in the reactor and the kinetics of the feedstock pyrolysis reactions. The heat transfer coefficient and the residence time determine the quantity of energy transferred and thus the temperature distribution throughout the feedstock in the reactor. The tert erature distribution and the kinetics determine the final conversion achieved at the reactor outlet. 

As regards adjustments, the following factors ii proved combustion and flame clean nozzle, strong swirl, intense symmetrical flame, pressure air atomisation compared to steam), increase of air coefticient and combustion power (having enough residence time though), suitable atomisation viscosity (abt 15-20 cSt). At the optimum adjustments of this combustion system, the mean conibustion results and emission values of typical pyrolysis oils were as follows O2 3 5 vol%, NO 88 mg/MJ, CO 4.6 mg/MJ, hydrocarbons 0.1 mg/MJ, soot 2.4 Bac., and particles 86 ing/MJ. 

The following discussion shows how the chemical composition, rate of formation, and heat of combustion of the pyrolysis products are affected by the variations in the composition of the substrate, the time and temperature profile, and the presence of inorganic additives or catalysts. The latter aspect, however, is discussed in more detail in Chapter 14. Combustion may be defined as complex interactions among fuel, energy, and the environment. Consequently, the combustion process is controlled not only by the above chemical factors, but also by the physical properties of the substrate and other prevailing conditions affecting the phenomena of heat and mass transport. Discussion of this phenomenon is beyond the scope of this chapter. 

The ways to eliminate variability in quantitative work using Py-GC/MS include the use of small sample size and of instruments with the temperature profile well calibrated. The analysis of a standard polymer at specified intervals of time (or number of samples) helps to verify reproducibility, and careful evaluation of the factors that may influence variability followed by their elimination may improve the results. One other procedure to improve reproducibility is the use of an internal standard during pyrolysis. The addition of a standard is not always simple when the sample weight is below 1 mg, and the standard must represent only a small part of the sample. A solution to this problem is to pyrolyze simultaneously with the sample a measured amount of standard diluted in a solid matrix, an example being alumina containing 1% of 1,4-dibromobenzene [40]. 

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