CJCE May Issue

The Editor’s Choice article from the May issue of CJCE is the latest addition to the Experimental Methods in Chemical Engineering Special Series, and is also an open access article: “Experimental methods in chemical engineering–Validation of steady-state simulation” by Caroline Brucel, Émilie Thibault, Gregory S. Patience, and Paul Stuart of Polytechnique Montréal. In this article, the authors “present strategies to validate steady-state simulations against plant data and expectations from operators”, provide a bibliometric review showing the “limited focus on steady-state simulation validation in the field of process engineering”, and include a case study that “demonstrates how to implement data treatment and validation for Kraft mill brownstock washing department: Applying multiple validation techniques increases the value and confidence in the simulation.” Within this issue, be sure to also read the preface for CJCE’s recent Experimental Methods in Chemical Engineering virtual issue. This virtual issue is currently free-to-read. Within the preface, the Guest Editor of the special series, Gregory S. Patience, outlines the inspiration for the Experimental Methods special series and identifies topics for future additions to this series.

The second issue highlight from the May issue is another open access article: “Potassium sulphate production from an aqueous sodium sulphate from lead-acid battery recycling: Impact of feedstock impurities on products yields” by Barialo Zorzor, Michael Fabrik, and Hussameldin Ibrahim of University of Regina. In this study, waste management of Na₂SO₄, which is generated as a waste product from lead-acid battery recycling, is examined and “HSC Chemistry software was used to model K₂SO₄ and NaCl production from impure Na₂SO₄ and KCl, considering feed impurities.” Ultimately, “Under ideal conditions—a 1 bar pressure, 25°C feed temperature, and 40°C reactor temperature—over 90% yield of K₂SO₄ and NaCl was achieved in the absence of impurities.” Read this article for more of the results!

The next issue highlight, an open access article titled “ML-driven models for predicting CO₂ uptake in metal–organic frameworks (MOFs)” by Sofiene Achour and Zied Hosni, “advances the discourse on the application of machine learning (ML) algorithms for the predictive analysis of CO₂ uptake in metal–organic frameworks (MOFs), with a nuanced focus on the CATBoost model’s capability to navigate the complexities inherent in MOFs’ heterogeneous landscape.” The authors note that “our investigation underscores the CATBoost model’s remarkable prediction robustness, characterized by a significant reduction in root mean square error (RMSE) and an enhanced R-squared (R²) value, thereby affirming its superior accuracy and reliability in forecasting CO₂ adsorption.”

The final issue highlight is an open access article from authors Armin Moniri, Sandeep Badoga, Mohamed Ali, and Jinwen Chen of Natural Resources Canada: “CrMn-based catalysts for oxidative dehydrogenation of propane to propylene with CO2”. This article “investigates the catalytic oxidative dehydrogenation of propane with carbon dioxide (ODH-CO₂) as a promising route for propylene production, an avenue yet to be commercially developed.” Within this study, “Utilizing the incipient wetness catalyst preparation method, CrMn catalysts were synthesized on three supports (γ-Al2O3, ZSM-5, and SBA-15). Comprehensive characterization through Brunauer–Emmett–Teller (BET) analysis, X-ray diffraction (XRD), thermogravimetric analysis (TGA), transmission electron microscopy (TEM)/scanning transmission electron microscopy (STEM)-energy-dispersive X-ray spectroscopy (EDS), and hydrogen temperature programmed reduction (H2-TPR) was conducted to comprehend catalyst behaviour.”