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Crafting the future: Enhancing gas separation with nanoarchitectonics of bimetallic Ni–Co-ZIF-67 in polysulfone-based mixed matrix membranes

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Case Studies in chemical and Environmental engineering 2024年 9卷

作者： Sulistiono, Dety Oktavia Ali, Badrut Tamam Ibnu Widyanto, Alvin Rahmad Ediati, Ratna Widiastuti, Nurul Lestari, Witri Wahyu Akhlus, Syafsir Iqbal, Rendy Muhamad Senda, Semuel Pati Fansuri, Hamzah Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Sukolilo Surabaya 60111 Indonesia Automotive Engineering Engineering Department Politeknik Negeri Jember Jember 68101 Indonesia Center for Process and Manufacturing Industry Technology National Research and Innovation Agency Technology Energy Cluster PUSPIPTEK 625 Building South Tangerang Indonesia Department of Applied Chemistry Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo 135-8548 Japan Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Sebelas Maret Jl. Ir. Sutami No. 36A Kentingan Jebres Surakarta 57126 Indonesia Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Palangka Raya Kampus UPR Tunjung Nyaho Palangkaraya 73111 Indonesia Advanced Membrane Technology Research Center (AMTEC) Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia Johor Skudai 81310 Malaysia

In response to global clean energy demands, this study develops mixed matrix membranes (MMMs) for gas separation in renewable energy applications. MMMs are produced through phase inversion by employing polysulfone and bimetallic-ZIF (Ni–Co-ZIF-67). Bimetallic-ZIF, formed in-situ by Co and Ni metals in water solvent with triethylamine, enhances gas selectivity. MMMs with 4 wt% bimetallic-ZIF, Co: Ni ratio of 9:1 (4Ni10Z67), exhibit remarkable selectivity: CO₂/CH₄ (21.19), H₂/N₂ (1.47), H₂/CH₄ (44.82), and N₂/CH₄ (30.40). Strong interactions between bimetallic-ZIF and CO₂, facilitated by molecular sieving and Ni–Co sites, contribute to these results. © 2024 The Authors

关键词： Bimetallic-ZIF CO2 capture Gas emissions Metal substitution Renewable energy

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Efficient toluene degradation using Bacillus subtilis biofilm-supported Mn–Ce/zeolite catalysts

Green Synthesis and Catalysis

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Green Synthesis and Catalysis 2024年

作者： Mohsin, Muhammad Zubair Mohsin, Ali Zaman, Waqas Qamar Zhu, Xiaojuan Zhao, Xihua Abbas, Zain Hussain, Muhammad Hammad Shan, Ali Salim-ur-Rehman Nawaz, Muhammad Asif Omer, Rabia Zhuang, Yingping Guo, Meijin Huang, Jiaofang State Key Laboratory of Bioreactor Engineering East China University of Science and Technology Shanghai 200237 China Institute of Environmental Sciences and Engineering School of Civil and Environmental Engineering National University of Sciences and Technology (NUST) Islamabad 44000 Pakistan College of Life Science Jiangxi Normal University Nanchang 330022 China School of Resources and Environmental Engineering State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process East China University of Science and Technology Shanghai 200237 China College of Materials Science and Engineering Shenzhen Key Laboratory of Polymer Science and Technology Guangdong Research Center for Interfacial Engineering of Functional Materials Shenzhen University Shenzhen 518055 China Department of Food Science and Technology Riphah International University Faisalabad Campus Faisalabad 44000 Pakistan Institute of Materials Science of Seville (ICMS) University of Seville Seville 41092 Spain

This study investigated a new approach for synthesizing Bacillus subtilis biofilm-supported Mn–Ce/zeolite catalysts for the degradation of gaseous toluene. Four different metal oxide nano-catalysts (ZMn, ZMnCe-10%, ZMnCe-20%, and ZMnCe-30%) were synthesized with varying ratios of manganese (Mn) and cerium (Ce) on zeolite nanoparticles. TEM, SEM, XRD, BET, XPS, and EDX mapping were used to examine these four samples, as well as simple zeolite. Based on these analyses, the catalytic activity of the prepared samples ZMn, ZMnCe-10%, ZMnCe-20%, and ZMnCe-30% for the complete oxidation of toluene and toluene intermediate products were tested with Non-thermal plasma (NTP) technology in a dielectric barrier discharge (DBD) reactor. Among all, ZMnCe-20% showed the highest toluene degradation efficiency (89%) at low concentrations (200 ppm) and humidity (>50%). Later, highly efficient and hydrophobic nano-biocatalysts were prepared by combining B. subtilis biofilm wild-type (WT) and engineered B. subtilis biofilm EPS with ZMnCe-20% catalyst. EPS is the main component found in biofilm matrix and plays a key role in influencing properties such as biofilm stability, electron transfer, surface roughness and hydrophobicity. Compared to WT B. subtilis biofilm, EPS overexpressed B. subtilis biofilm showed stronger growth and development on ZMnCe-20% nanocatalyst. Moreover, the NTP system packed with ZMnCe-20%/biofilm (EPS+) nano-biocatalyst exhibited the highest toluene degradation activity (99%) with (83%) CO₂ selectivity, (up to 50%) reduction in NOx concentration and complete ozone decomposition at (250 ppm) toluene concentrations and increased humidity (>90%). High-energy electrons generated in the NTP system break the C–H and C–C bond between the rings of the toluene molecule, forming several byproducts which are later reacted with active radical species such as O[rad], OH[rad], and O₃ and further converted into final degradation products (CO₂

关键词： CO2 selectivity Engineered Bacillus subtilis biofilm Metal nanoparticles Toluene oxidation Zeolite

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In-Situ Raman Unveiled Nb-O-Bond-Dependency Selectivity for Methanol Electro-Oxidation at High Current Density

SSRN

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SSRN 2023年

作者： Wang, Xinlin Xiao, Chuqian Li, Yuhang Murayama, Toru Ishida, Tamao Lin, Mingyue Xiu, Guangli Shanghai Environmental Protection Key Laboratory on Environmental Standard and Risk Management of Chemical Pollutants East China University of Science and Technology Shanghai200237 China State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process School of Resources and Environmental Engineering East China University of Science and Technology Shanghai200237 China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China School of Materials Science and Engineering East China University of Science & Technology Shanghai200237 China Research Center for Hydrogen Energy-based Society Graduate School of Urban Environmental Sciences Tokyo Metropolitan University 1-1 Minami-Osawa Hachioji Tokyo192-0397 Japan School of Chemistry & Chemical Engineering Yantai University Yantai264005 China Department of Applied Chemistry for Environment Graduate School of Urban Environmental Sciences Tokyo Metropolitan University Hachioji Tokyo192-0397 Japan

Selective methanol oxidation reaction (MOR) to value-added formate can maximize the input energy utilization for water electrolysis by replacing the high onset-potential and kinetics sluggish oxygen evolution reaction. However, to date only first-row 3d transition metal oxides present the capacity of selective MOR, motivating the design of new kinds of electrocatalysts to further enhance the MOR performance. Herein, we show amorphous Nb2O5 as an efficient electrocatalyst, for the oxidation of methanol to formate, with a low operating potential of 1.47 V vs. RHE to achieve industry-relevant current densities (>100 mA cm-2) with a Faraday efficiency of ~100%. We demonstrate, via operando Raman measurements, this superior electrochemical MOR activity originated from the in-situ induced short Nb-O bonds from the amorphous structure, while the crystalline Nb2O5 fails to generate this active site resulting in a poor activity. This work may provide valuable insight for developing novel transition metal oxides for MOR catalysts. © 2023, The Authors. All rights reserved.

关键词： Electrocatalysis

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Recent advancements and challenges in emerging applications of biochar-based catalysts

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Biotechnology Advances 2023年 67卷 108181页

作者： Yuan, Xiangzhou Cao, Yang Li, Jie Patel, Anil Kumar Dong, Cheng-Di Jin, Xin Gu, Cheng Yip, Alex C.K. Tsang, Daniel C.W. Ok, Yong Sik Ministry of Education of Key Laboratory of Energy Thermal Conversion and Control School of Energy and Environment Southeast University Nanjing210096 China Korea Biochar Research Center APRU Sustainable Waste Management Program & Division of Environmental Science and Ecological Engineering Korea University Seoul02841 Korea Republic of Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong CAS Key Laboratory of Urban Pollutant Conversion Institute of Urban Environment Chinese Academy of Sciences Xiamen361021 China Institute of Aquatic Science and Technology College of Hydrosphere National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan State Key Laboratory of Pollution Control and Resource Reuse School of Environment Nanjing University Nanjing210023 China Department of Chemical and Process Engineering University of Canterbury Christchurch New Zealand Research Centre for Resources Engineering towards Carbon Neutrality The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong

The sustainable utilization of biochar produced from biomass waste could substantially promote the development of carbon neutrality and a circular economy. Due to their cost-effectiveness, multiple functionalities, tailorable porous structure, and thermal stability, biochar-based catalysts play a vital role in sustainable biorefineries and environmental protection, contributing to a positive, planet-level impact. This review provides an overview of emerging synthesis routes for multifunctional biochar-based catalysts. It discusses recent advances in biorefinery and pollutant degradation in air, soil, and water, providing deeper and more comprehensive information of the catalysts, such as physicochemical properties and surface chemistry. The catalytic performance and deactivation mechanisms under different catalytic systems were critically reviewed, providing new insights into developing efficient and practical biochar-based catalysts for large-scale use in various applications. Machine learning (ML)-based predictions and inverse design have addressed the innovation of biochar-based catalysts with high-performance applications, as ML efficiently predicts the properties and performance of biochar, interprets the underlying mechanisms and complicated relationships, and guides biochar synthesis. Finally, environmental benefit and economic feasibility assessments are proposed for science-based guidelines for industries and policymakers. With concerted effort, upgrading biomass waste into high-performance catalysts for biorefinery and environmental protection could reduce environmental pollution, increase energy safety, and achieve sustainable biomass management, all of which are beneficial for attaining several of the United Nations Sustainable Development Goals (UN SDGs) and Environmental, Social and Governance (ESG). © 2023 The Authors

关键词： Biodiversity

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Effect of high-frequency atmospheric plasma on the growth of mung bean sprouts 11

Effect of high-frequency atmospheric plasma on the growth of...

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11th International Conference on Simulation and Modelling in the Food and Bio-Industry, FOODSIM 2020

作者： Kozak, Dmytro S. Rodriguez, Estefanía Garcia Blundell, Renald Tsepelev, Vladimir S. Akkermans, Simen Van Impe, Jan F.M. Valdramidis, Vasilis Gatt, Ruben Chemical and Biochemical Process Technology and Control BioTeC+ Department of Chemical Engineering KU Leuven Belgium Metamaterials Unit Faculty of Science University of Malta Msida Malta 19 Mira Street Ekaterinburg620002 Russia Department of Food Sciences and Nutrition Faculty of Health Sciences University of Malta Msida Malta Department of Physiology and Biochemistry Faculty of Medicine and Surgery University of Malta Msida Malta Centre for Molecular Medicine Bio Banking University of Malta Msida Malta

ISBN: (纸本)9789492859136

A high-frequency AC plasma was applied during the germination of mung bean at extreme conditions in a closed system. A new laboratory design for emitting high-frequency plasma in the form of a single electrode directly in a closed system has been successfully tested. The current results demonstrated that plasma had both a growth promoting and inhibiting effect. Even though the growth of sprouts was mostly inhibited in the current study, it is expected that the plasma generation can be tuned in such a way that it has an overall positive effect on sprout growth. © 2020 EUROSIS. All Rights Reserved.

关键词： Germination

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Transfer learning soft sensor for product quality prediction in multi-grade processes 8

Transfer learning soft sensor for product quality prediction...

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8th IEEE Data Driven control and Learning Systems Conference, DDCLS 2019

作者： Yang, Chao Chen, Bocheng Wang, Zhiwen Yao, Yuan Liu, Yi Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

ISBN: (纸本)9781728114545

For multi-grade chemical processes, current data-driven soft sensor models built in a specific operating condition cannot be directly applied to predict product qualities of other conditions. A simple transfer learning method namely domain adaptation extreme learning machine (DAELM) is presented to construct a soft sensor model in multi-grade processes with limited labeled data. In addition, an effective strategy is developed to fast select the model parameters. By exploring and utilizing useful information from different operating conditions, the prediction accuracy can be improved. Compared with traditional soft sensors, the prediction results of two multi-grade chemical processes validate the advantages of DAELM. © 2019 IEEE.

关键词： Forecasting

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Orthogonal locality preserving projections thermography for subsurface defect detection 11

Orthogonal locality preserving projections thermography for ...

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11th CAA Symposium on Fault Detection, Supervision, and Safety for Technical processes, SAFEprocess 2019

作者： Liu, Kaixin Tang, Yuwei Yao, Yuan Liu, Yi Yang, Jianguo Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

ISBN: (纸本)9781728106816

In this work, the subspace learning technique for manifold learning is integrated into the application of subsurface defect detection to promote the performance of inspection and evaluation. Specifically, thermograms recorded by an infrared camera are analyzed by the proposed orthogonal locality preserving projections thermography (OLPPT) method. In detail, OLPPT constrains the primary functions' orthogonality on the basis of the LPP ground and studies the thermographic data by mapping the adjacency graph to retain the local features. After eliminating the majority of uneven backgrounds, the projections reveal more pronounced contours and locations of the defective areas. The performance of OLPPT is demonstrated by the defect analysis of a carbon fiber reinforced polymer sample. © 2019 IEEE.

关键词： Nondestructive examination

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How resistant is anammox biofilm against antibiotics: A special insight into anammox response towards fluoroquinolones

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Heliyon 2025年第1期11卷 e41339页

作者： Mamun, Faysal-Al Kumar, Rohit Anwuta, Kelvin Ugochukwu Das, Sovik Jaagura, Madis Herodes, Koit Kyrpel, Tetyana Borzyszkowska, Agnieszka Fiszka Zielińska-Jurek, Anna Vincevica-Gaile, Zane Burlakovs, Juris Krauklis, Andrey E. Azra, Mohamad Nor Salauddin, Md Zhong, Jiexi Tenno, Taavo Bester, Kai Zekker, Ivar Institute of Chemistry University of Tartu 14a Ravila St. Tartu 50411 Estonia Indian Institute of Technology Delhi Hauz Khas New Delhi 110 016 India Institute of Genomics University of Tartu Riia 23b Tartu 51010 Estonia Institute of Chemistry Chair of Analytics University of Tartu 14a Ravila St. Tartu 50411 Estonia Department of Environmental Toxicology Faculty of Health Sciences Medical University of Gdansk Dębowa Str. 23A Gdansk 80-204 Poland Department of Process Engineering and Chemical Technology Gdansk University of Technology Narutowicza 11/12 Gdansk 80-233 Poland Department of Environmental Science University of Latvia Jelgavas Street 1 Riga LV-1004 Latvia Faculty of Civil and Mechanical Engineering Riga Technical University Riga LV-1048 Latvia ASEMlab – Laboratory of Advanced and Sustainable Engineering Materials Department of Manufacturing and Civil Engineering NTNU – Norwegian University of Science and Technology Gjøvik 2815 Norway Institute of Climate Adaptation and Marine Biotechnology Universiti Malaysia Terengganu Terengganu Kuala Nerus 21030 Malaysia UCD Dooge Centre for Water Resources Research School of Civil Engineering University College Dublin Ireland Department of Environmental Science Aarhus University Frederiksborgvej 399 Roskilde 4000 Denmark WATEC – Centre for Water Technology Aarhus University Ny Munkegade 120 Aarhus 8000 Denmark

Elevated concentrations of pharmaceutically active compounds (PhACs) in the water bodies are posing a serious threat to the aquatic microbiota and other organisms. In this context, anaerobic ammonium oxidizing (anammox) bacteria carry a great potential to degrade PhACs through their innate metabolic pathways. This study investigates the influence of short-term exposure to lower and higher concentrations (0.8 mg L⁻¹, 0.06 mg L⁻¹, respectively) of antibiotics on the anammox process under distinct operational conditions (starvation/non-starvation) in moving bed biofilm reactor (MBBR). During batch operations that lasted for up to 6 h, the total nitrogen removal efficiency (TNRE) and total nitrogen conversion rate (TNCR) reached a maximum of 93 ± 5 % and 6.97 ± 1.30 mg N g⁻¹ TSS d⁻¹, respectively. Evidently, at higher PhAC levels, the anammox process was active, and up to 75 % PhAC removal efficiency was obtained within 6 h of the batch cycle. Most importantly, the anammox biofilm effectively eliminated the PhACs compounds, i.e., ciprofloxacin (CIP), ofloxacin (OFL), and norfloxacin (NOR) present at higher (0.8 mg L⁻¹) and lower (0.06 mg L⁻¹) total PhACs (sum of CIP, NOR, OFL) concentrations. Furthermore, 16S rRNA sequencing analyses showed a mixture of nitrifying, denitrifying, and anammox bacterial commodities enriched on the carriers' surface with a high relative abundance of Candidatus Brocadia, primarily responsible for catalyzing the anammox process. This study showed the intricate relationship between PhAC concentrations, TNCR, and antibiotic elimination in the wastewater treatment, and the results obtained set up a new breakthrough in wastewater treatment. Future research should investigate the mechanisms that underlie the anammox biofilms' resistance to various types of PhACs and investigate the long-term stability and scalability of this process with real wastewater influents. © 2024

关键词： Adsorption Anammox Moving bed biofilm reactor Nitrogen removal Pharmaceutically active compounds

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Artificial Intelligence Modelling Based Optimization of an Industrial Scale Steam Turbine for Moving Towards Net-Zero in the Energy Sector

SSRN

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SSRN 2022年

作者： Ashraf, Waqar Muhammad Uddin, Ghulam Moeen Tariq, Rasikh Ahmed, Afaq Farhan, Muhammad Nazeer, Muhammad Aarif Ul Hassan, Rauf Naeem, Ahmad Jamil, Hanan Krzywanski, Jaroslaw Sosnowski, Marcin Dua, Vivek Centre for Process Systems Engineering Department of Chemical Engineering University College London Torrington Place LondonWC1E 7JE United Kingdom Department of Mechanical Engineering University of Engineering & Technology Punjab Lahore54890 Pakistan Facultad de Ingeniería Universidad Autónoma de Yucatán Av. Industrias No Contaminantes por Anillo Periférico Norte Apdo. Postal 150 Cordemex Yucatán Mérida97203 Mexico Department of Automotive Engineering Technology Punjab Tianjin University of Technology Lahore54000 Pakistan Faculty of Science and Technology Jan Dlugosz University in Czestochowa 13/15 Armii Krajowej Av. Czestochowa42-200 Poland

Augmentation of energy efficiency in power generation processes can aid in the decarbonization of this sector which is also recognized by the International Energy Agency (IEA) as a solution to attain net-zero in the energy sector. With this reference, this article exploits a framework incorporating artificial intelligence (AI) for improving the isentropic efficiency of a high-pressure (HP) steam turbine installed at a supercritical power plant. The data of the operating parameters taken from a supercritical 660 MW coal-fired power plant is well distributed in the input and the output space of the operating parameters. Based on hyperparameters tuning, two advanced AI modelling algorithms, i.e., Artificial Neural Network (ANN) and Support Vector Machine (SVM) are trained, and subsequently, validated. ANN, as turned out to be a better performing model, is deployed for evaluating the impact of individual or combination of operating parameters on the HP (high pressure) turbine efficiency under three real power generation capacities of the power plant. The parametric study and nonlinear programming-based optimization techniques are applied to optimize the HP turbine efficiency. It is estimated that the HP turbine efficiency can be improved by 1.43 %, 5.09 %, and 3.40 % as compared to its average operational value for Half Load, Mid Load, and Full Load power generation modes. The annual reduction in CO2, SO2, CH4, N2O, and Hg emissions is also estimated for the three power generation modes of the power plant. It is concluded that AI algorithms are found to be useful in conducting complex industry-wide analytics, which can be applied on various operational levels of the energy systems for achieving higher energy efficiency that contributes to the net-zero target. © 2022, The Authors. All rights reserved.

关键词： Neural networks

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A federated data-driven evolutionary algorithm

arXiv

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arXiv 2021年

作者： Xu, Jinjin Jin, Yaochu Du, Wenli Gu, Sai Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom Department of Chemical and Process Engineering University of Surrey GuildfordGU27XH United Kingdom

Data-driven evolutionary optimization has witnessed great success in solving complex real-world optimization problems. However, existing data-driven optimization algorithms require that all data are centrally stored, which is not always practical and may be vulnerable to privacy leakage and security threats if the data must be collected from different devices. To address the above issue, this paper proposes a federated data-driven evolutionary optimization framework that is able to perform data driven optimization when the data is distributed on multiple devices. On the basis of federated learning, a sorted model aggregation method is developed for aggregating local surrogates based on radial-basis-function networks. In addition, a federated surrogate management strategy is suggested by designing an acquisition function that takes into account the information of both the global and local surrogate models. Empirical studies on a set of widely used benchmark functions in the presence of various data distributions demonstrate the effectiveness of the proposed framework. © 2021, CC BY.

关键词： Optimization

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