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In this paper, we demonstrate the utility of combining multicomponent ligand synthesis and catalytic performance studies with predictive modelling for catalyst discovery and optimization.
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A model for catalyst layer (CL) performance is used to determine optimal shapes of electrolyte content and catalyst loading through the CL thickness.
This leads to difficulty in developing simple models for catalyst washcoat effectiveness based upon any parameter such as a Thiele modulus.
A similar sensitivity analysis was used to derive a reduced model for catalyst deactivation, by using data recorded in the dual non-isothermal integral reactor system.
In this work, a model for catalyst deactivation in terms of fouling because of blockage of micropores of the catalyst is used to estimate activity independently of reaction rates; later cracking kinetic rates of a model compound are estimated.
A mathematical model for catalyst regenerator of fluidized bed catalytic cracking process, including thermal effects, has been developed to simulate a regenerator having characteristics similar to that of the unit operated by Petrobras (Brazilian Oil Company).
A multiscale model is subsequently established to quantify the two types of reaction rate and simulate the catalyst leaching from a cross-coupling catalyst, PdEncat™ 30; including: (1) a multi-particle sizes model for catalyst scale; and (2) a dispersion model for reactor scale.
Using the sedimentation-diffusion model for catalyst dispersion the steady-state performance of semi-batch bubble column reactors has been studied over a wide range of mass transfer and reaction groups for reactions that are described by power law and Langmuir-Hinshelwood (L-H) type of kinetics.
The experimental data was successfully modeled for the three catalysts.
A methodology for estimating deactivation models for catalysts in industrial application is proposed.
A numerical model for catalyst-aided carbon dioxide (CO2) desorption from CO2-loaded aqueous amines solution has been developed.
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