Transient kinetics of <i>n</i>‐butane partial oxidation at elevated pressure

Shekari, Ali; Patience, Gregory S.

doi:10.1002/cjce.21637

Cited by 10 publications

(6 citation statements)

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“…[25] We advocate that words and text be concise (limit redundancy) and precise (rather than vague), that verbs be active (not passive) and vigorous (avoid delexical verbs and verb mutilation). Metadiscourse often adds unnecessary words like hedges, boosts, and signposts: [11] feeble verb, verb mutilation estimate were applied to analyze [12] [13] feeble verb characterize enable the characterization feeble verb, verb mutilation characterize experienced fragmentation feeble verb, verb mutilation fragment give good agreement [14] delexical, verb mutilation agree have an effect delexical, verb mutilation affect make an assessment delexical, verb mutilation assess observations have been made [15] verb mutilation, passive observe obtain a clear understanding delexical, verb mutilation, redundant understand accumulation of ions does not occur [16] verb mutilation, feeble verb ions do not accumulate perform an operation delexical, verb mutilation operate provide an explanation delexical, verb mutilation explain predictions show close agreement [17] feeble verb, verb mutilation, vague agree take into consideration delexical, verb mutilation consider by trying to minimize [18] hedging minimizing used for comparing feeble verb compare 5. 'Revise Sentences over 30 Words Long' [26] Identify metadiscourse in the following paragraph:…”

Section: -Hedging B)mentioning

confidence: 98%

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How do you write and present research well? Answers to the 20 questions

2016

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At the beginning of this series on how to write and present research,[1,2] we repeated Whitesides's[3] message that working in the laboratory, modelling, designing, and troubleshooting constitute only part of the research effort. Discovery, development, analysis, and reviewing literature is work which is incomplete until you publish it and others cite it.[4] Our questions address specifically how to write and present with greater clarity, which is only one element in the process and includes: (a) acknowledging that you should write and present better; (b) deciding that you want to improve; (c) identify means to achieve this goal—courses and books, for example; (d) dedicating time to practice; (e) finding a coach or some way to get feedback on how you are doing; and (f) implementing what you learn in all written and oral communication. Writing and presenting are indispensable skills for researchers, but for many of us, formal instruction on communication ended in high school or the first year of university. However, universities are now implementing soft skill workshops as part of the offering to new graduate students. Funding agencies recognize the importance of these skills and now require programs in grant proposals (NSERC CREATE, European RECHIND). These resources are most effective when students recognize that they need to improve their skills and also want to improve them. Great musicians, athletes, and Go players practice continually. Furthermore, they have coaches to give them feedback and help them develop strategies. Writing is as complex as these activities and, like with them, we can improve at it continually.[5,6]

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Section: -Hedging B)mentioning

confidence: 98%

“…The numbers in the graph represent the impact factor (N IF ) of the journal that published the article. 18. 'Publish and Flourish' [54] WoS categorizes arts and sciences into 250 disciplines.…”

Section: Papers and Postersmentioning

confidence: 99%

How do you write and present research well? Answers to the 20 questions

2016

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“…Shekari and Patience studied experimentally the effect of the oxidation period in cyclic CFB operation, and found that longer oxidation times were beneficial to MA yield. A further study by the same authors at elevated pressure showed that higher pressures improved the yield of MA, by maintaining the catalyst in a higher oxidation state and thus increasing catalytic activity, which more than compensated for the decrease in MA selectivity. Shekari and Patience proposed transient kinetics for n ‐butane oxidation for high pressure conditions.…”

Section: Introductionmentioning

confidence: 93%

n‐butane partial oxidation in a fixed bed: A resolved particle computational fluid dynamics simulation

Partopour

Dixon

2018

Can J Chem Eng

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Maleic anhydride (MA) is an important chemical intermediate, which is mainly produced by the highly exothermic partial oxidation of n-butane in fixed bed reactors. Production of maleic anhydride is limited by problems of temperature control and loss of selectivity. Here we present threedimensional resolved-particle computational fluid dynamics (CFD) simulations of n-butane partial oxidation in a randomly packed bed of 807 spherical catalyst particles. We used a semi-empirical two-site surface mechanism from the literature and obtained distributions of temperature, gas phase species, and surface species in the bed. The local selectivity patterns are strongly controlled by the changes in the gas phase flow field, the temperature in the fixed bed, and the weakly adsorbed oxygen surface coverage fraction (l O ) profiles inside the particles. Most of the selectivity loss due to product combustion happens in the interior of the catalyst particles, as opposed to the production of MA, which is mainly in the near-surface layers. We observed loss of selectivity and yield in the centre of the bed at increased bed depths, because of the temperature increase and decrease in gas phase oxygen there. The simulations show sharp l O gradients inside the particles. Near the cooled tube wall l O is strongly affected by the temperature, while at the bed centre gas phase oxygen diffusion limitations contribute to a depleted oxygen surface resulting in lower selectivity.

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“…The kinetics of this reaction has been the subject of many investigations [47][48][49][50][51][52][53][54][55][56][57][58]. A particular kinetic model for this reaction system is the widely cited work of Centi et al [48] in which the authors developed the model from the empirical data Table 2: General mass balance and mass transfer equations.…”

Section: Kinetic Modelmentioning

confidence: 98%

Performance of a Catalytic Gas–Solid Fluidized Bed Reactor in the Presence of Interparticle Forces

Shabanian

Chaouki

2015

International Journal of Chemical Reactor Engineering

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The influence of interparticle forces (IPFs) on the hydrodynamics of a gas-solid fluidized bed was experimentally investigated with the help of a polymer coating approach. The results showed that the presence of IPFs in the bed can considerably change the hydrodynamic parameters. The tendency of the fluidizing gas passing through the bed in the emulsion phase increased with IPFs in the bubbling regime. The performance of a fluidized bed reactor was then studied through simulation of a reactive catalytic system using three different hydrodynamic models: (a) a simple two-phase flow model, (b) a dynamic two-phase flow model, and (c) a dynamic two-phase flow model, integrating the effects of superficial gas velocity and IPFs. The simple two-phase flow model was found to underestimate the reactor performance for catalytic reaction most likely due to the oversimplified assumptions involved in this model. Also, the simulation results showed that modification of the bed hydrodynamics due to IPFs resulted in a better performance for a bubbling fluidized bed reactor. This suggests that the hydrodynamic models should take into account the effects of superficial gas velocity and variation in the ratio of the magnitude of IPFs/hydrodynamic forces, due to any operational reason, to yield a more reliable evaluation of the performance of the fluidized bed reactor.

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Transient kinetics of n‐butane partial oxidation at elevated pressure

Cited by 10 publications

References 33 publications

How do you write and present research well? Answers to the 20 questions

How do you write and present research well? Answers to the 20 questions

n‐butane partial oxidation in a fixed bed: A resolved particle computational fluid dynamics simulation

Performance of a Catalytic Gas–Solid Fluidized Bed Reactor in the Presence of Interparticle Forces

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