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ChemEngineering
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Catalytic Reactions and Development of (Bio)Chemical Processes for Synthesizing Value...
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Catalytic Reactions and Development of (Bio)Chemical Processes for Synthesizing Value Added Compounds

A special issue of ChemEngineering (ISSN 2305-7084).

Deadline for manuscript submissions: 31 July 2024 | Viewed by 3395

Special Issue Editor

Dr. Ionut Banu

E-Mail Website
Guest Editor
Department of Chemical and Biochemical Engineering, Polytechnic University of Bucharest, Bucharest, Romania
Interests: chemical reaction engineering and kinetics; chemical engineering process optimization; modeling and simulation of chemical processes

Special Issue Information

Dear Colleagues,

This Special Issue of ChemEngineering will aim the publication of original manuscripts and critical reviews dealing with the application of the process development principles both at industrial and laboratory scales. Manuscripts emphasizing highly active catalyst preparation and testing, process design, modeling,  optimization  and their economic efficiency assesment, with the end-goal of producing value added (bio)chemical products will be welcome.

In order to produce value added chemical and biochemical products, an increasing number of processes, involving both homogeneous and heterogeneous catalytic materials, are proposed nowadays in different engineering fields. The development of an industrial process requires extensive laboratory studies, and then an appropriate scale-up to provide a sufficient level of know-how. Manufacturing a catalyst with good activity and selectivity for a specific product plays a crucial role in increasing the economic efficiency of a process, whereas this step requires developing appropriate operating conditions for catalyst synthesis with a strong correlation between these aspects and the chemical structure of the catalyst. Given the global environmental requirements, a special emphasis should be conferred to the use of renewable raw materials as well as the minimization of wastes in the proposed alternatives.

Dr. Ionut Banu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ChemEngineering is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • homogeneous catalysis
  • heterogeneous catalysis
  • catalyst deactivation
  • value added chemicals
  • catalytic processes
  • organic and bioactive compounds
  • process engineering
  • renewable raw materials

Published Papers (2 papers)

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Research

16 pages, 4367 KiB  
Article
Simultaneous Environmental Waste Management through Deep Dewatering of Alum Sludge Using Waste-Derived Cellulose
by Manasik M. Nour and Maha A. Tony
ChemEngineering 2024, 8(2), 40; https://doi.org/10.3390/chemengineering8020040 - 3 Apr 2024
Viewed by 859
Abstract
To simultaneously solve problems in an eco-friendly manner, introducing a waste residual as a sustainable conditioner to aid alum sludge dewatering is suggested as a cradle-to-cradle form of waste management. In this regard, the superiority of deep dewatering alum sludge with a powdered [...] Read more.
To simultaneously solve problems in an eco-friendly manner, introducing a waste residual as a sustainable conditioner to aid alum sludge dewatering is suggested as a cradle-to-cradle form of waste management. In this regard, the superiority of deep dewatering alum sludge with a powdered wood chip composite residual as a novel conditioner was explored, whereby traditional conventional conditioners, i.e., polyelectrolytes and lime, were substituted with powdered wood chips. Initially, Fe3O4 was prepared at the nanoscale using a simple co-precipitation route. Next, wooden waste was chemically and thermally treated to attain cellulosic fine powder. Subsequently, the resultant wood powder and Fe3O4 nanoparticles were mixed at 50 wt % to attain a wood powder augmented with iron, and this conditioner was labeled nano-iron-cellulose (nIC-Conditioner). This material (nIC-Conditioner) was mixed with hydrogen peroxide to represent a dual oxidation and skeleton builder conditioning substance. Characterization of the resultant conditioner was carried out using transmission electron microscopy (TEM) and Fourier transform infrared (FT-IR) transmittance spectrum analysis. The feasibility of the experimental results revealed that the moisture content in the sludge cake was lower after conditioning, and the capillary suction time (CST) was reduced to 78% compared to that of raw alum sludge after 5 min of dewatering time. Moreover, the optimal system parameters, including nIC-Conditioner and H2O2 concentrations, as well as the working pH, were optimized, and optimal values were recorded at 1 g/L and 200 mg/L for nIC-Conditioner and H2O2, respectively, with a pH of 6.5. Additionally, scanning electron microscope (SEM) analyses of the sludge prior to and after conditioning were conducted to verify the change in sludge molecules due to this conditioning technique. The results of this study confirm the sustainability of an alum sludge and waste management facility. Full article
(This article belongs to the Special Issue Catalytic Reactions and Development of (Bio)Chemical Processes for Synthesizing Value Added Compounds)
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19 pages, 6644 KiB  
Article
Process Optimization of Biodiesel from Used Cooking Oil in a Microwave Reactor: A Case of Machine Learning and Box–Behnken Design
by Achanai Buasri, Phensuda Sirikoom, Sirinan Pattane, Orapharn Buachum and Vorrada Loryuenyong
ChemEngineering 2023, 7(4), 65; https://doi.org/10.3390/chemengineering7040065 - 21 Jul 2023
Cited by 6 | Viewed by 1965
Abstract
In the present investigation, response surface methodology (RSM) and machine learning (ML) are applied to the biodiesel production process via acid-catalyzed transesterification and esterification of triglyceride (TG). In order to optimize the production of biodiesel from used cooking oil (UCO) in a microwave [...] Read more.
In the present investigation, response surface methodology (RSM) and machine learning (ML) are applied to the biodiesel production process via acid-catalyzed transesterification and esterification of triglyceride (TG). In order to optimize the production of biodiesel from used cooking oil (UCO) in a microwave reactor, these models are also compared. During the process, Box–Behnken design (BBD) and an artificial neural network (ANN) were used to evaluate the effect of the catalyst content (3.0–7.0 wt.%), methanol/UCO mole ratio (12:1–18:1), and irradiation time (5.0–9.0 min). The process conditions were adjusted and developed to predict the highest biodiesel yield using BBD with the RSM approach and an ANN model. With optimal process parameters of 4.94 wt.% catalyst content, 16.76:1 methanol/UCO mole ratio, and 8.13 min of irradiation time, a yield of approximately 98.62% was discovered. The coefficient of determination (R2) for the BBD model was found to be 0.9988, and the correlation coefficient (R) for the ANN model was found to be 0.9994. According to the findings, applying RSM and ANN models is advantageous when optimizing the biodiesel manufacturing process as well as making predictions about it. This renewable and environmentally friendly process has the potential to provide a sustainable route for the synthesis of high-quality biodiesel from waste oil with a low cost and high acid value. Full article
(This article belongs to the Special Issue Catalytic Reactions and Development of (Bio)Chemical Processes for Synthesizing Value Added Compounds)
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