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Selected Papers from the 2nd International Electronic Conference on Processes: Process Engineering—Current State and Future Trends (ECP2023)

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A special issue of Processes (ISSN 2227-9717).

Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 6166

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Prof. Dr. Giancarlo Cravotto

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Department of Drug Science and Technology, University of Turin, Via P. Giuria 9, 10125 Turin, Italy
Interests: green chemistry; process intensification; green extraction; enabling technologies (ultrasound, microwaves, hydrodynamic cavitation, ball milling, flow chemistry); sustainable chemical processes
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Special Issue Information

Dear Colleagues,

This Special Issue comprises selected papers from the Proceedings of the 2nd International Electronic Conference on Processes: Process Engineering—Current State and Future Trends (ECP2023), hosted online from 17 to 31 May 2023, an online platform for hosting scholarly e-conferences and discussion groups (https://ecp2023.sciforum.net/).

ECP2023 will present the latest studies in process/system-related research in chemistry, biology, material, energy, environment, food and engineering fields. The goal is to show the current state, challenges, opportunities and future trends in process systems engineering. The 1st Electronic Conference Special Issue has published 12 papers and can be found at the following link: https://0-www-mdpi-com.brum.beds.ac.uk/journal/processes/special_issues/ECP2022.

All process/system-related scientists or researchers are welcome to join this event and share their findings around the following general and related themes including, but not limited to:

Green chemistry engineering and environment relevant process;
Experimental, theoretical, and computational research on process development and engineering;
Process modeling, simulation, optimization, and control;
Food-relevant processing and improvement of food quality;
Sustainable and renewable systems engineering;
Energy system and current demand and electricity market;
Supply chain management;
Circular economies;
Eco-friendly processes and methods.

Prof. Dr. Giancarlo Cravotto
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. Processes is an international peer-reviewed open access monthly 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 2400 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.

Related Special Issue

Selected Papers from the First International Electronic Conference on Processes: Processes System Innovation (ECP2022) in Processes (12 articles)

Published Papers (7 papers)

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Research

14 pages, 1585 KiB

Open AccessArticle

Hyperspectral and Microtomographic Analyses to Evaluate the Stability of Quercetin and Calcium Effervescent Tablets Exposed to Heat and Ultraviolet Radiation

by Beata Szulc-Musioł, Piotr Duda, Michał Meisner and Beata Sarecka-Hujar

Processes 2024, 12(3), 531; https://0-doi-org.brum.beds.ac.uk/10.3390/pr12030531 - 07 Mar 2024

Viewed by 541

Abstract

This study aimed to assess the changes occurring during the storage of tablets of three effervescent preparations available in Polish pharmacies containing calcium and quercetin from various manufacturers under stressful conditions (45 °C, UV radiation) using a hyperspectral Specim IQ camera (Finland), X-ray microtomography (Germany), and selected pharmacopoeial parameters. All measurements were made three times at the beginning of the experiment (day 0) and then on days 3 and 10. In general, for all analyzed preparations, the values of reflectance (within a range from visible light to near-infrared) were significantly higher on day 0 than after 10 days of heat and UV (p < 0.001 each). The hardness of the tablets of all analysed preparations was higher on days 3 and 10 compared to day 0. Significant differences were found in the density of the internal structure of the tested preparations (p < 0.001), but in Preparations 1 and 2 on day 10, the density was higher compared to the initial density. In contrast, the porosity was lower on day 10 than on day 0 for Preparations 1 and 2, while in Preparation 3, it remained the same. In conclusion, lower reflectance values indicate that more light passes through/into the tablet, and the increase in density and decrease in porosity may indicate changes in the microstructure of the tablets. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd International Electronic Conference on Processes: Process Engineering—Current State and Future Trends (ECP2023))

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26 pages, 697 KiB

Open AccessFeature PaperArticle

Using a Machine Learning Regression Approach to Predict the Aroma Partitioning in Dairy Matrices

by Marvin Anker, Christine Borsum, Youfeng Zhang, Yanyan Zhang and Christian Krupitzer

Processes 2024, 12(2), 266; https://0-doi-org.brum.beds.ac.uk/10.3390/pr12020266 - 26 Jan 2024

Viewed by 885

Abstract

Aroma partitioning in food is a challenging area of research due to the contribution of several physical and chemical factors that affect the binding and release of aroma in food matrices. The partition coefficient measured by the

K_{m g}

value refers to [...] Read more.

K_{m g}

value refers to the partition coefficient that describes how aroma compounds distribute themselves between matrices and a gas phase, such as between different components of a food matrix and air. This study introduces a regression approach to predict the

K_{m g}

value of aroma compounds of a wide range of physicochemical properties in dairy matrices representing products of different compositions and/or processing. The approach consists of data cleaning, grouping based on the temperature of

K_{m g}

analysis, pre-processing (log transformation and normalization), and, finally, the development and evaluation of prediction models with regression methods. We compared regression analysis with linear regression (LR) to five machine-learning-based regression algorithms: Random Forest Regressor (RFR), Gradient Boosting Regression (GBR), Extreme Gradient Boosting (XGBoost, XGB), Support Vector Regression (SVR), and Artificial Neural Network Regression (NNR). Explainable AI (XAI) was used to calculate feature importance and therefore identify the features that mainly contribute to the prediction. The top three features that were identified are log P, specific gravity, and molecular weight. For the prediction of the

K_{m g}

in dairy matrices,

R^{2}

scores of up to 0.99 were reached. For 37.0

°

C, which resembles the temperature of the mouth, RFR delivered the best results, and, at lower temperatures of 7.0

°

C, typical for a household fridge, XGB performed best. The results from the models work as a proof of concept and show the applicability of a data-driven approach with machine learning to predict the

K_{m g}

value of aroma compounds in different dairy matrices. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd International Electronic Conference on Processes: Process Engineering—Current State and Future Trends (ECP2023))

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19 pages, 5693 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Analyzing Local Shear Rate Distribution in a Dual Coaxial Mixing Bioreactor Handling Herschel–Bulkley Biopolymer Solutions through Computational Fluid Dynamics

by Forough Sharifi, Ehsan Behzadfar and Farhad Ein-Mozaffari

Processes 2023, 11(12), 3387; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11123387 - 07 Dec 2023

Viewed by 689

Abstract

For the aeration of highly viscous non-Newtonian fluids, prior studies have demonstrated the improved efficacy of dual coaxial mixing bioreactors fitted with two central impellers and a close clearance anchor. Evaluating the effectiveness of these bioreactors involves considering various mixing characteristics, with a specific emphasis on shear rate distribution. The study of shear rate distribution is critical due to its significant impact on the mixing performance, gas dispersion, and homogeneity in aerated mixing systems comprising shear-thinning fluids. Although yield-pseudoplastic fluids are commonly employed in various industries, there is a research gap when it comes to evaluating shear rate distribution in aerated mixing bioreactors that utilize this fluid type. This study aims to investigate shear rate distribution in an aerated double coaxial bioreactor that handles a 1 wt% xanthan gum solution, known as a Herschel–Bulkley fluid. To achieve this goal, we employed an experimentally validated computational fluid dynamics (CFD) model to assess the effect of different mixing configurations, including down-pumping and co-rotating (Down-Co), up-pumping and co-rotating (Up-Co), down-pumping and counter-rotating (Down-Counter), and up-pumping and counter-rotating (Up-Counter) modes, on the shear rate distribution within the coaxial mixing bioreactor. Our findings revealed that the Up-Co system led to a more uniform local shear distribution and improved mixing performance. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd International Electronic Conference on Processes: Process Engineering—Current State and Future Trends (ECP2023))

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10 pages, 893 KiB

Open AccessArticle

Microbial Pretreatment for Biogas: Analyzing Dairy Rumen Anaerobic Bacteria Inoculum’s Impact on Alfalfa Biomass and Energy Value

by Bronius Žalys, Kęstutis Venslauskas and Kęstutis Navickas

Processes 2023, 11(12), 3384; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11123384 - 06 Dec 2023

Viewed by 759

Abstract

Lignocellulose is a complex and abundant biomass source, and finding ways to efficiently break it down is essential for various applications, including bioenergy production and waste management. Biogas production can be significantly enhanced by adding rumen fluid to the anaerobic digestion process, which contains a variety of microorganisms with the enzyme activity necessary to breakdown complex lignocellulosic materials. This study examined the influence of rumen anaerobic bacteria inoculum on alfalfa biomass biogas yield and quality. Inoculation experiments were performed, and the higher biogas yield from organic matter was gained in experiment (A), with a rumen fluid addition of 340 ± 3.2 L/kg_VS, compared to the utilization of a digestate alone in (B), 238 ± 1.2 L/kg_VS. The results demonstrated that a pretreatment temperature of 37 °C (experiment D) yielded the highest biogas production, 381 ± 3.9 L/kg_VS, and maintained a high methane content of 63.9 ± 1.9%. Notably, pretreatment at 25 °C resulted in only a 3% increase over the raw sample and a pretreatment at 50 °C (respectively, experiments C and E) showed no significant changes, emphasizing the sensitivity of pretreatment efficiency to temperature variations. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd International Electronic Conference on Processes: Process Engineering—Current State and Future Trends (ECP2023))

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22 pages, 18769 KiB

Open AccessArticle

Investigation of Surface Nanoclusters and Paramagnetic Centers of ZnO/Por-Si Structures as the Basis of Sensory Properties

by Danatbek Murzalinov, Tatyana Seredavina, Ainagul Kemelbekova, Yulia Spivak, Vyacheslav Moshnikov, Daniya Mukhamedshina, Kostantin Mit’, Nurzhan Ussipov, Elena Dmitriyeva, Sultan Zhantuarov, Sayora Ibraimova, Kazybek Aimaganbetov, Ekaterina Bondar and Anastasiya Fedosimova

Processes 2023, 11(12), 3332; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11123332 - 30 Nov 2023

Viewed by 687

Abstract

The detection of particles with uncompensated charge and the determination of the features of their interaction during the formation of nanocrystals on substrates with a developed surface are an interesting area of research. The porous surface formed via the electrochemical etching of silicon acquired fractal properties as a result of the deposition of zinc oxide layers. Microscopy methods using different resolutions revealed a hierarchical structure of the surface, where each of the three consecutive levels contains uniformly distributed formations. The deposition of 20 layers of ZnO maximizes the concentration of nanocrystals at the pore boundaries, while the deposition of 25 layers leads to the formation of a continuous layer. The increase in photoluminescence intensity with an increase in the number of deposited layers is due to the saturation of surface nanostructures with electrons through several mechanisms. Electron paramagnetic resonance (EPR) studies have shown that the main mechanism of radiation recombination is the capture of electrons on oxygen vacancies. The different nature of the EPR saturation of the signal of interconnected paramagnetic centers revealed the formation of zinc oxide particles at the boundaries of pores with different sizes. The results of these studies of surface-active structures effectively complement the knowledge about sensory materials. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd International Electronic Conference on Processes: Process Engineering—Current State and Future Trends (ECP2023))

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10 pages, 2569 KiB

Open AccessArticle

The Development of Advanced Fluorescent Tracers Aimed at Drill Cuttings Labelling and Depth Correlation via Injection with Oil-Based Drilling Mud

by Vladimir Khmelnitskiy, Hassan S. Alqahtani, Hyung Kwak and Vera Solovyeva

Processes 2023, 11(11), 3197; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11113197 - 09 Nov 2023

Viewed by 541

Abstract

Fast and precise geo-steering and geo-navigation upon well drilling are the key parameters for improved well targeting, optimal well placement, and maximal hydrocarbon recovery. To advance geo-steering parameters, we propose a new approach to on-site formation evaluation through the use of fluorescent tracers for drill cuttings tagging according to the depth of origin. Cuttings labelling at the drill bit site is followed by near-real-time drilling depth correlation at the well-head via a camera and AI image recognition systems. To suite the drilling process, the engineered tracers should match to the rheology of the utilized drilling mud. This study was performed to comprehensively investigate the effect of fluorescent tracers on the rheological properties of oil-based drilling mud (OBM) and to determine the optimal quantities of the tracers’ addition. We evaluated critical mud characteristics including electrical stability, thixotropic parameters, shear stress, gel strength, plastic viscosity, and yield point as prepared and in the presence of fluorescent tracers at the range of 1 to 20 wt.%. Additionally, the mud’s effects on the long-term stability of the fluorescent tracers were assessed via hot-rolling tests in conditions mimicking downhole conditions, with the aim of determining the tags’ feasibility for drill cuttings labelling applications. The study also examines the recovery potential of the tracers and their reusability in the drilling process. This investigation provides valuable insights into the potential application of fluorescent tracers for downhole drill cuttings depth correlation which will improve geo-steering works. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd International Electronic Conference on Processes: Process Engineering—Current State and Future Trends (ECP2023))

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17 pages, 1424 KiB

Open AccessCommunication

Insights into the Potential Role of Gordonia alkanivorans Strains in Biotechnologies

by Ekaterina Frantsuzova, Alexander Bogun, Lidiya Shishkina, Anna Vetrova, Inna Solyanikova and Yanina Delegan

Processes 2023, 11(11), 3184; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11113184 - 08 Nov 2023

Viewed by 1098

Abstract

Members of many species of the genus Gordonia are known for their significant metabolic potential, including the ability to utilize compounds of different structures. The aim of the work was to study the ability of nine G. alkanivorans strains to degrade persistent organic pollutants and to analyze the genomic peculiarities of these strains. The genomes of nine Gordonia alkanivorans strains were sequenced and assembled. The utilization of these strains as alkane and benzoate degraders in environmental biotechnologies, coupled with their capacity to potentially produce diverse secondary metabolites, holds promising prospects for both environmental and pharmaceutical applications. Full article

(This article belongs to the Special Issue Selected Papers from the 2nd International Electronic Conference on Processes: Process Engineering—Current State and Future Trends (ECP2023))

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