Results 201 to 210 of about 108,324 (309)

Synthesis of Hydrocarbon Fuels From Dimethyl Ether Through Co‐Oligomerization of Olefins

open access: yesChemie Ingenieur Technik, EarlyView.
This work investigates the impact of higher olefins and typical impurities from a preceding Dimethyl ether‐to‐Olefins (DtO) process on olefin oligomerization for sustainable fuel production. Several key properties of the kerosene fraction comply with the ASTM D7566 22a standard for sustainable aviation fuels, whereas some important properties of the ...
Marc Pfennings   +5 more
wiley   +1 more source

Hydroprocessing of synthetic kerosene over a non‐sulphided Ni/Al2O3 catalyst: Impact of alcohols and ketones on alkene conversion

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract Synthetic jet fuel containing non‐petroleum‐derived kerosene can be produced from synthetic kerosene obtained through processes that include a hydroprocessing step. The potential use of non‐sulphided (reduced) nickel supported on alumina (Ni/Al2O3) was evaluated as an alternative to sulphided catalysts to saturate alkenes in sulphur‐free ...
Garima Chauhan   +3 more
wiley   +1 more source

Innovative electrospun geopolymer/zeolite/PVA composite membranes

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Proposed scheme of gas adsorption mechanisms on electrospun geopolymer/zeolite/PVA composite membranes. Abstract Innovative electrospun poly(vinyl alcohol) (PVA)–geopolymer–zeolite 13X composite membranes were successfully fabricated and systematically characterized.
Mariana Schneider   +7 more
wiley   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos   +3 more
wiley   +1 more source

Hybrid machine learning and genetic algorithm approach for catalyst and process optimization in Fischer–Tropsch synthesis toward sustainable fuel production

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Graphical representation of a data‐driven framework for Fischer‐Tropsch synthesis (FTS) modelling and optimization. Abstract This study presents a data‐driven approach for predicting the relationships between catalyst design, process conditions, and product selectivity in Fischer–Tropsch synthesis (FTS).
Doaa M. Hassan   +2 more
wiley   +1 more source

Home - About - Disclaimer - Privacy