Pub Date : 2023-10-16DOI: 10.3389/fceng.2023.1144115
Tahar Nabil, Mohamed Noaman, Tatiana Morosuk
With new materials, objectives or constraints, it becomes increasingly difficult to develop optimal processes using conventional heuristics-based or superstructure-based methods. Hence, data-driven alternatives have emerged recently, to increase creativity and accelerate the development of innovative technologies without requiring extensive industrial feedback. However, beyond these proof-of-concepts and the promise of automation they hold, a deeper understanding of the behaviour and use of these advanced algorithms by the process engineer is still needed. In this paper, we provide the first data-driven solution for designing supercritical CO 2 power cycle for waste heat recovery, a challenging industrial use case with lack of consensus on the optimal layout from the field literature. We then examine the issue of artificial intelligence acceptance by the process engineer, and formulate a set of basic requirements to foster user acceptance - robustness, control, understanding of the results, small time-to-solution. The numerical experiments confirm the robustness of the method, able to produce optimal designs performing as well as a set of selected expert layouts, yet only from the specification of the unit operations (turbomachinery and heat exchangers). We provide tools to exploit the vast amount of generated data, with pattern mining techniques to extract heuristic rules, thereby explaining the decision-making process. As a result, this paper shows how the process engineer can interact with the data-driven design approaches, by refocusing on the areas of domain expertise, namely, definition and analysis of the physical problem.
{"title":"Data-driven structural synthesis of supercritical CO2 power cycles","authors":"Tahar Nabil, Mohamed Noaman, Tatiana Morosuk","doi":"10.3389/fceng.2023.1144115","DOIUrl":"https://doi.org/10.3389/fceng.2023.1144115","url":null,"abstract":"With new materials, objectives or constraints, it becomes increasingly difficult to develop optimal processes using conventional heuristics-based or superstructure-based methods. Hence, data-driven alternatives have emerged recently, to increase creativity and accelerate the development of innovative technologies without requiring extensive industrial feedback. However, beyond these proof-of-concepts and the promise of automation they hold, a deeper understanding of the behaviour and use of these advanced algorithms by the process engineer is still needed. In this paper, we provide the first data-driven solution for designing supercritical CO 2 power cycle for waste heat recovery, a challenging industrial use case with lack of consensus on the optimal layout from the field literature. We then examine the issue of artificial intelligence acceptance by the process engineer, and formulate a set of basic requirements to foster user acceptance - robustness, control, understanding of the results, small time-to-solution. The numerical experiments confirm the robustness of the method, able to produce optimal designs performing as well as a set of selected expert layouts, yet only from the specification of the unit operations (turbomachinery and heat exchangers). We provide tools to exploit the vast amount of generated data, with pattern mining techniques to extract heuristic rules, thereby explaining the decision-making process. As a result, this paper shows how the process engineer can interact with the data-driven design approaches, by refocusing on the areas of domain expertise, namely, definition and analysis of the physical problem.","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136113754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-16DOI: 10.3389/fceng.2023.1256334
Giada Benedetti, Beatriz Fournon Berodia, Paolo De Coppi, Giovanni Giuseppe Giobbe
Gastrointestinal organ failure, from congenital or postnatally acquired pathologies, is a major cause of death across countries of all income levels. Organoids and engineered tissues have been widely investigated as tools to model organ functions and treat pathologies. In this review we aim to describe the progress in human organoid engineering applied to the gastrointestinal tract (namely esophagus, stomach, and intestine). Starting from the onset of the organoid culture technique, we illustrate genetic engineering, stem cell niche engineering, bioprinting, and microfluidics approaches used to integrate mechano-physiological parameters with human organoids. Thanks to these improvements, organoid technology allows disease modelling of patient-specific pathologies, and personalized treatment screening, also offering a cell source for autologous transplantation. We further present an overview of the advances of tissue engineering in animal systems, concerning novel materials and scaffolds to be combined with a variety of cell types to reconstitute a viable surrogate for implantation. The effort in this field sets organoids as an important tool in personalized and regenerative medicine. Their application combined with the advances in tissue engineering holds great potential for translational application.
{"title":"Human gastro-intestinal organoid engineering: a state of the art","authors":"Giada Benedetti, Beatriz Fournon Berodia, Paolo De Coppi, Giovanni Giuseppe Giobbe","doi":"10.3389/fceng.2023.1256334","DOIUrl":"https://doi.org/10.3389/fceng.2023.1256334","url":null,"abstract":"Gastrointestinal organ failure, from congenital or postnatally acquired pathologies, is a major cause of death across countries of all income levels. Organoids and engineered tissues have been widely investigated as tools to model organ functions and treat pathologies. In this review we aim to describe the progress in human organoid engineering applied to the gastrointestinal tract (namely esophagus, stomach, and intestine). Starting from the onset of the organoid culture technique, we illustrate genetic engineering, stem cell niche engineering, bioprinting, and microfluidics approaches used to integrate mechano-physiological parameters with human organoids. Thanks to these improvements, organoid technology allows disease modelling of patient-specific pathologies, and personalized treatment screening, also offering a cell source for autologous transplantation. We further present an overview of the advances of tissue engineering in animal systems, concerning novel materials and scaffolds to be combined with a variety of cell types to reconstitute a viable surrogate for implantation. The effort in this field sets organoids as an important tool in personalized and regenerative medicine. Their application combined with the advances in tissue engineering holds great potential for translational application.","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136114260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-02DOI: 10.3389/fceng.2023.1235125
Sutha Subbian, Pappa Natarajan, Chitra Murugan
Introduction: Water scarcity and water pollution are two major issues in India. Circular economy-based wastewater treatment technology provides the most sustainable solutions for solving these issues. In this paper, a novel multi-objective decentralized controller (MODC) is proposed for benchmarking a multi-input multi-output (MIMO) activated sludge wastewater treatment plant (WWTP) to achieve maximum effluent quality with minimum cost. WWTPs with conventional control schemes consume more energy to achieve the desired effluent quality. Methods: In this study, a MIMO model is developed for the activated sludge process (ASP) from a physics-based model, and relative gain array (RGA) analysis are carried out to determine the interaction between the loops to identify a suitable control scheme for the MIMO process. In addition, a multi-objective decentralized control problem is formulated to achieve the conflicting multiple objectives of improving effluent quality and minimizing operational costs by efficient usage of energy. Results and discussion: The desired quality and cost reduction are verified by comparing the integral square error (ISE) and control effort (CE) values of a closed-loop WWTP. A multi-objective evolutionary algorithm (MOEA), namely, the non-dominated sorting genetic algorithm (NSGA)-II, successfully solves the multi-objective control problem. NSGA-II provides several optimal solutions in the Pareto front. In order to demonstrate the feasibility of the proposed controller, three optimal solutions are selected from the Pareto-optimal front, and their closed-loop performances are evaluated qualitatively and quantitatively for both servo and regulatory operations. Improving the quality of effluent enhances active sludge production, which in turn increases the methane production in the anaerobic digester.
{"title":"Circular economy-based multi-objective decentralized controller for activated sludge wastewater treatment plant","authors":"Sutha Subbian, Pappa Natarajan, Chitra Murugan","doi":"10.3389/fceng.2023.1235125","DOIUrl":"https://doi.org/10.3389/fceng.2023.1235125","url":null,"abstract":"Introduction: Water scarcity and water pollution are two major issues in India. Circular economy-based wastewater treatment technology provides the most sustainable solutions for solving these issues. In this paper, a novel multi-objective decentralized controller (MODC) is proposed for benchmarking a multi-input multi-output (MIMO) activated sludge wastewater treatment plant (WWTP) to achieve maximum effluent quality with minimum cost. WWTPs with conventional control schemes consume more energy to achieve the desired effluent quality. Methods: In this study, a MIMO model is developed for the activated sludge process (ASP) from a physics-based model, and relative gain array (RGA) analysis are carried out to determine the interaction between the loops to identify a suitable control scheme for the MIMO process. In addition, a multi-objective decentralized control problem is formulated to achieve the conflicting multiple objectives of improving effluent quality and minimizing operational costs by efficient usage of energy. Results and discussion: The desired quality and cost reduction are verified by comparing the integral square error (ISE) and control effort (CE) values of a closed-loop WWTP. A multi-objective evolutionary algorithm (MOEA), namely, the non-dominated sorting genetic algorithm (NSGA)-II, successfully solves the multi-objective control problem. NSGA-II provides several optimal solutions in the Pareto front. In order to demonstrate the feasibility of the proposed controller, three optimal solutions are selected from the Pareto-optimal front, and their closed-loop performances are evaluated qualitatively and quantitatively for both servo and regulatory operations. Improving the quality of effluent enhances active sludge production, which in turn increases the methane production in the anaerobic digester.","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135901424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-20DOI: 10.3389/fceng.2023.1218668
Fabio Trigo Raya, Lucas Miguel de Carvalho, Juliana José, Larissa Prado da Cruz, Rafael Leonardo Almeida, Heliur Alves de Almeida Delevatti, Neidiquele Maria Silveira, Simone Ferreira da Silva, Maria Dolores Pissolato, Adriele Bárbara de Oliveira, Wagner José Villela dos Reis, Luís Guilherme Furlan de Abreu, Jesús Gutiérrez, Marcelo Falsarella Carazzolle, Ana Cristina Fermino Soares, Jorge Nieto Sotelo, Rafael Vasconcelos Ribeiro, Gonçalo Amarante Guimarães Pereira
Agaves have been a valuable resource in dryland areas for centuries, providing fibers (sisal), food, and beverages. However, the advent of synthetic fibers has led to a decrease in research on Agave , resulting in the cessation of breeding programs in Brazil. With the rise of climate change, there is renewed interest in Agave for its potential as a biofuel feedstock in semiarid regions. Since 2016, we have been collecting Agave accessions throughout the country and retrieving what is left of Brazil’s original breeding program to establish a new germplasm bank. Here, we evaluated 21 of those accessions growing in the field. We used molecular markers and morphophysiological traits to characterize the plants. Based on the Mayahuelin molecular marker, we were able to reconstruct a phylogeny for the Brazilian accessions. The morphophysiological traits explained 34.6% of the phenotypic variation in the dataset, with physiological traits such as leaf water content, effective quantum efficiency of photosystem II (Φ PSII ), and specific leaf mass (SLM) as the most significant traits. Specifically, we evaluated nine Agave species and found that the physiological traits, rather than the morphological ones, were the most significant. Leaf water content was negatively correlated with specific leaf mass, which could be used as a marker for selecting cultivars with higher biomass accumulation. Interestingly, Φ PSII and chlorophyll content were negatively correlated, suggesting photochemical adaptations throughout the rosette. Molecular and phenotypic data suggest that A. amaniensis , which is frequently considered a synonym of A. sisalana , is effectively another species. Overall, this study provides valuable information on the physiological traits of Brazilian Agave accessions and is a starting point for selecting more productive and climate-resilient cultivars for biorenewables production.
{"title":"Rescuing the Brazilian Agave breeding program: morphophysiological and molecular characterization of a new germplasm","authors":"Fabio Trigo Raya, Lucas Miguel de Carvalho, Juliana José, Larissa Prado da Cruz, Rafael Leonardo Almeida, Heliur Alves de Almeida Delevatti, Neidiquele Maria Silveira, Simone Ferreira da Silva, Maria Dolores Pissolato, Adriele Bárbara de Oliveira, Wagner José Villela dos Reis, Luís Guilherme Furlan de Abreu, Jesús Gutiérrez, Marcelo Falsarella Carazzolle, Ana Cristina Fermino Soares, Jorge Nieto Sotelo, Rafael Vasconcelos Ribeiro, Gonçalo Amarante Guimarães Pereira","doi":"10.3389/fceng.2023.1218668","DOIUrl":"https://doi.org/10.3389/fceng.2023.1218668","url":null,"abstract":"Agaves have been a valuable resource in dryland areas for centuries, providing fibers (sisal), food, and beverages. However, the advent of synthetic fibers has led to a decrease in research on Agave , resulting in the cessation of breeding programs in Brazil. With the rise of climate change, there is renewed interest in Agave for its potential as a biofuel feedstock in semiarid regions. Since 2016, we have been collecting Agave accessions throughout the country and retrieving what is left of Brazil’s original breeding program to establish a new germplasm bank. Here, we evaluated 21 of those accessions growing in the field. We used molecular markers and morphophysiological traits to characterize the plants. Based on the Mayahuelin molecular marker, we were able to reconstruct a phylogeny for the Brazilian accessions. The morphophysiological traits explained 34.6% of the phenotypic variation in the dataset, with physiological traits such as leaf water content, effective quantum efficiency of photosystem II (Φ PSII ), and specific leaf mass (SLM) as the most significant traits. Specifically, we evaluated nine Agave species and found that the physiological traits, rather than the morphological ones, were the most significant. Leaf water content was negatively correlated with specific leaf mass, which could be used as a marker for selecting cultivars with higher biomass accumulation. Interestingly, Φ PSII and chlorophyll content were negatively correlated, suggesting photochemical adaptations throughout the rosette. Molecular and phenotypic data suggest that A. amaniensis , which is frequently considered a synonym of A. sisalana , is effectively another species. Overall, this study provides valuable information on the physiological traits of Brazilian Agave accessions and is a starting point for selecting more productive and climate-resilient cultivars for biorenewables production.","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136264195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.3389/fceng.2023.1282418
Jingjie Luo, Wen Luo, Ning Wang, Kuang-Hsu Wu
{"title":"Editorial: Carbon-based catalytic engineering for sustainable industrial applications","authors":"Jingjie Luo, Wen Luo, Ning Wang, Kuang-Hsu Wu","doi":"10.3389/fceng.2023.1282418","DOIUrl":"https://doi.org/10.3389/fceng.2023.1282418","url":null,"abstract":"","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":"258 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139339496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-07DOI: 10.3389/fceng.2023.1228510
Kavery Elangovan, Prabhu Saravanan, Cristian H. Campos, Felipe Sanhueza-Gómez, Md. Maksudur Rahman Khan, Sim Yee Chin, Santhana Krishnan, Ramalinga Viswanathan Mangalaraja
The microbial fuel cells (MFCs) which demonstrates simultaneous production of electricity and wastewater treatment have been considered as one of the potential and greener energy production technology among the available bioelectrochemical systems. The air-cathode MFCs have gained additional benefits due to using air and avoiding any chemical substances as catholyte in the cathode chamber. The sluggish oxygen reduction reaction (ORR) kinetics at the cathode is one of the main obstacles to achieve high microbial fuel cell (MFC) performances. Platinum (Pt) is one of the most widely used efficient ORR electrocatalysts due to its high efficient and more stable in acidic media. Because of the high cost and easily poisoned nature of Pt, several attempts, such as a combination of Pt with other materials, and using non-precious metals and non-metals based electrocatalysts has been demonstrated. However, the efficient practical application of the MFC technology is not yet achieved mainly due to the slow ORR. Therefore, the review which draws attention to develop and choosing the suitable cathode materials should be urgent for the practical applications of the MFCs. In this review article, we present an overview of the present MFC technology, then some significant advancements of ORR electrocatalysts such as precious metals-based catalysts (very briefly), non-precious metals-based, non-metals and carbon-based, and biocatalysts with some significant remarks on the corresponding results for the MFC applications. Lastly, we also discussed the challenges and prospects of ORR electrocatalysts for the practical application of MFCs.
{"title":"Outline of microbial fuel cells technology and their significant developments, challenges, and prospects of oxygen reduction electrocatalysts","authors":"Kavery Elangovan, Prabhu Saravanan, Cristian H. Campos, Felipe Sanhueza-Gómez, Md. Maksudur Rahman Khan, Sim Yee Chin, Santhana Krishnan, Ramalinga Viswanathan Mangalaraja","doi":"10.3389/fceng.2023.1228510","DOIUrl":"https://doi.org/10.3389/fceng.2023.1228510","url":null,"abstract":"The microbial fuel cells (MFCs) which demonstrates simultaneous production of electricity and wastewater treatment have been considered as one of the potential and greener energy production technology among the available bioelectrochemical systems. The air-cathode MFCs have gained additional benefits due to using air and avoiding any chemical substances as catholyte in the cathode chamber. The sluggish oxygen reduction reaction (ORR) kinetics at the cathode is one of the main obstacles to achieve high microbial fuel cell (MFC) performances. Platinum (Pt) is one of the most widely used efficient ORR electrocatalysts due to its high efficient and more stable in acidic media. Because of the high cost and easily poisoned nature of Pt, several attempts, such as a combination of Pt with other materials, and using non-precious metals and non-metals based electrocatalysts has been demonstrated. However, the efficient practical application of the MFC technology is not yet achieved mainly due to the slow ORR. Therefore, the review which draws attention to develop and choosing the suitable cathode materials should be urgent for the practical applications of the MFCs. In this review article, we present an overview of the present MFC technology, then some significant advancements of ORR electrocatalysts such as precious metals-based catalysts (very briefly), non-precious metals-based, non-metals and carbon-based, and biocatalysts with some significant remarks on the corresponding results for the MFC applications. Lastly, we also discussed the challenges and prospects of ORR electrocatalysts for the practical application of MFCs.","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44760324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-17DOI: 10.3389/fceng.2023.1267210
V. Zambare, M. F. Md. Din
{"title":"Editorial: Saccharomyces cerevisiae as a model organism for biochemical engineering and bioprocesses","authors":"V. Zambare, M. F. Md. Din","doi":"10.3389/fceng.2023.1267210","DOIUrl":"https://doi.org/10.3389/fceng.2023.1267210","url":null,"abstract":"","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41627185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-07DOI: 10.3389/fceng.2023.1227620
C. Walther, Michael C. Martinetz, Anja Friedrich, Anne Tscheliessnig, M. Voigtmann, Alexander Jung, C. Brocard, E. Bluhmki, J. Smiatek
We present explainable machine learning approaches for gaining deeper insights into the solubilization processes of inclusion bodies. The machine learning model with the highest prediction accuracy for the protein yield is further evaluated with regard to Shapley additive explanation (SHAP) values in terms of feature importance studies. Our results highlight an inverse fractional relationship between the protein yield and total protein concentration. Further correlations can also be observed for the dominant influences of the urea concentration and the underlying pH values. All findings are used to develop an analytical expression that is in reasonable agreement with experimental data. The resulting master curve highlights the benefits of explainable machine learning approaches for the detailed understanding of certain biopharmaceutical manufacturing steps.
{"title":"Solubilization of inclusion bodies: insights from explainable machine learning approaches","authors":"C. Walther, Michael C. Martinetz, Anja Friedrich, Anne Tscheliessnig, M. Voigtmann, Alexander Jung, C. Brocard, E. Bluhmki, J. Smiatek","doi":"10.3389/fceng.2023.1227620","DOIUrl":"https://doi.org/10.3389/fceng.2023.1227620","url":null,"abstract":"We present explainable machine learning approaches for gaining deeper insights into the solubilization processes of inclusion bodies. The machine learning model with the highest prediction accuracy for the protein yield is further evaluated with regard to Shapley additive explanation (SHAP) values in terms of feature importance studies. Our results highlight an inverse fractional relationship between the protein yield and total protein concentration. Further correlations can also be observed for the dominant influences of the urea concentration and the underlying pH values. All findings are used to develop an analytical expression that is in reasonable agreement with experimental data. The resulting master curve highlights the benefits of explainable machine learning approaches for the detailed understanding of certain biopharmaceutical manufacturing steps.","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49240909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-02DOI: 10.3389/fceng.2023.1266904
Jie-jie Dong, Daehwan Kim, C. Yoo
{"title":"Editorial: Biochemical/biomaterial production from lignocellulosic biomass","authors":"Jie-jie Dong, Daehwan Kim, C. Yoo","doi":"10.3389/fceng.2023.1266904","DOIUrl":"https://doi.org/10.3389/fceng.2023.1266904","url":null,"abstract":"","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47297266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-20DOI: 10.3389/fceng.2023.1153795
Alexander Mendoza-Acosta, Suleyka Torres-Romero, Martín Orozco, M. Cota, Ricarda L. Basurto, Luis L. Galaviz
There is currently great interest in photocatalytic degradation technologies of pollutants in industrial effluents. This is due to the need to reduce the environmental pollution generated by the textile industry’s high demand of clothing for fast fashion; in addition to severe environmental problems, this also generates social problems. Since the catalysts of this type of processes are usually nanoparticles of metal oxides such as zinc and titanium, it is necessary to promote research into the synthesis and evaluation of photocatalysts. Therefore, this article describes three free basic access tools for the academic analysis of nanoparticles, from experimental design to representation, using the study of kinetics and particle size analysis. After pre-selecting easily accessible software, it was found that RStudio, J-Image, and Vesta are very useful programs for the analysis of nanoparticles in the respective areas of statistical processing, image analysis, and three-dimensional representation.
{"title":"Three basic open access software tools for academic analysis of photocatalytic particles","authors":"Alexander Mendoza-Acosta, Suleyka Torres-Romero, Martín Orozco, M. Cota, Ricarda L. Basurto, Luis L. Galaviz","doi":"10.3389/fceng.2023.1153795","DOIUrl":"https://doi.org/10.3389/fceng.2023.1153795","url":null,"abstract":"There is currently great interest in photocatalytic degradation technologies of pollutants in industrial effluents. This is due to the need to reduce the environmental pollution generated by the textile industry’s high demand of clothing for fast fashion; in addition to severe environmental problems, this also generates social problems. Since the catalysts of this type of processes are usually nanoparticles of metal oxides such as zinc and titanium, it is necessary to promote research into the synthesis and evaluation of photocatalysts. Therefore, this article describes three free basic access tools for the academic analysis of nanoparticles, from experimental design to representation, using the study of kinetics and particle size analysis. After pre-selecting easily accessible software, it was found that RStudio, J-Image, and Vesta are very useful programs for the analysis of nanoparticles in the respective areas of statistical processing, image analysis, and three-dimensional representation.","PeriodicalId":73073,"journal":{"name":"Frontiers in chemical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42953818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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