Green Chemical Engineering最新文献_第3页

Integration of physical information and reaction mechanism data for surrogate prediction model and multi-objective optimization of glycolic acid production 整合物理信息和反应机理数据，建立代用预测模型并对乙醇酸生产进行多目标优化

IF 9.1

Green Chemical Engineering Pub Date : 2024-06-12 DOI: 10.1016/j.gce.2024.06.002

Zhibo Zhang , Yaowei Wang , Dongrui Zhang , Deming Zhao , Huibin Shi , Hao Yan , Xin Zhou , Xiang Feng , Chaohe Yang

{"title":"Integration of physical information and reaction mechanism data for surrogate prediction model and multi-objective optimization of glycolic acid production","authors":"Zhibo Zhang , Yaowei Wang , Dongrui Zhang , Deming Zhao , Huibin Shi , Hao Yan , Xin Zhou , Xiang Feng , Chaohe Yang","doi":"10.1016/j.gce.2024.06.002","DOIUrl":"10.1016/j.gce.2024.06.002","url":null,"abstract":"<div><div>With the continuous development of the chemical industry, the concept of advocating green development has become increasingly popular. Glycolic acid (GA), serving as the monomer for biodegradable plastic polyglycolic acid, plays a crucial role in combating plastic pollution and fostering an eco-friendly society. The selective oxidation of ethylene glycol (EG) to produce GA represents a novel green production technology. Controlling reaction parameters to achieve multi-objective optimization of product distribution and direct CO<sub>2</sub> emissions is crucial for scaling up the process. With the advent of the big data era, the integration of the chemical industry with artificial intelligence to achieve engineering scale-up is an important trend. This study proposes a neural network model for production prediction and optimization. The model is trained using experimental data, reaction mechanism data, and physical information, enabling rapid prediction of GA production. After validating with 40% of experimental data and 16% of reaction mechanism data, the model's prediction error was within ±5%, and the linear correlation coefficient R<sup>2</sup> between the predicted values and actual values was 0.998. Furthermore, this study integrated a multi-objective optimization algorithm based on the model, enabling surrogate optimization of reaction parameters during production. After optimization, the direct CO<sub>2</sub> emissions were reduced by over 99% and overall greenhouse gas emissions were reduced by 4.6%. The research paradigm proposed in this research can offer guidance and technical support for the optimized operation of EG selective oxidation to GA.</div></div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"6 2","pages":"Pages 169-180"},"PeriodicalIF":9.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141391858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Progress in the design and performance evaluation of catalysts for low-temperature direct ammonia fuel cells 低温直接氨燃料电池催化剂的设计和性能评估进展

IF 9.1

Green Chemical Engineering Pub Date : 2024-06-04 DOI: 10.1016/j.gce.2024.06.001

Zhongbin Gong , Hao Wang , Chenhao Li , Qinqin Sang , Ying Xie , Xiaosa Zhang , Yanrong Liu

{"title":"Progress in the design and performance evaluation of catalysts for low-temperature direct ammonia fuel cells","authors":"Zhongbin Gong , Hao Wang , Chenhao Li , Qinqin Sang , Ying Xie , Xiaosa Zhang , Yanrong Liu","doi":"10.1016/j.gce.2024.06.001","DOIUrl":"10.1016/j.gce.2024.06.001","url":null,"abstract":"<div><div>Ammonia, a hydrogen-rich and carbon-free energy carrier, possesses advantages such as high energy density and convenient liquefaction storage and serves as an optimal medium for hydrogen storage. Low-temperature direct ammonia fuel cells (DAFCs) represent a highly promising pathway for the efficient utilization of ammonia energy. However, the sluggish kinetics of the low-temperature ammonia oxidation reaction (AOR), requires high loading of platinum-group metals (PGMs) catalysts, and their poisoning significantly hampers the performance of DAFCs, thereby limiting their large-scale commercial application. Therefore, it is crucial to design efficient, cost-effective, and stable catalysts. In this work, a detailed review of recent research efforts aimed at elucidating the mechanism underlying the AOR is presented. Building on this knowledge base, progress in the design and synthesis of both PGM and PGM-free catalysts for the AOR is discussed, as well as membrane electrode assembly (MEA) preparation processes for DAFCs. Furthermore, the results of the performance evaluation of AOR catalysts in single-cell tests are summarized. Finally, based on our findings from this research area thus far, potential design strategies for AOR catalysts that can promote the rapid development of low temperatures DAFCs are proposed.</div></div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"6 1","pages":"Pages 54-67"},"PeriodicalIF":9.1,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141403872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Switching from deep eutectic solvents to deep eutectic systems for natural product extraction 天然产品萃取从深共晶溶剂转向深共晶体系

IF 9.1

Green Chemical Engineering Pub Date : 2024-06-01 DOI: 10.1016/j.gce.2024.05.002

Zhaoyang Wang, Simin Wang, Yuan Zhang, Wentao Bi

{"title":"Switching from deep eutectic solvents to deep eutectic systems for natural product extraction","authors":"Zhaoyang Wang, Simin Wang, Yuan Zhang, Wentao Bi","doi":"10.1016/j.gce.2024.05.002","DOIUrl":"10.1016/j.gce.2024.05.002","url":null,"abstract":"<div><div>This article presents a comprehensive overview of recent advancements in natural product extraction, focusing on the evolution from deep eutectic solvents (DESs) to deep eutectic systems (DESys) for extraction. DESs, known for their environmentally friendly properties, have become crucial in extracting various natural products from plants, including micromolecules, lignin, and polysaccharides. Research into the extraction mechanism reveals that target compounds typically form hydrogen bonds with DESs, effectively becoming part of the solvent system. This insight has led to the development of the DESys extraction method, where hydrogen bond acceptors (HBAs) and hydrogen bond donors (HBDs) are directly mixed with the sample to form a DESys containing the target compounds. The shift from DES-based extraction to DESys-based extraction introduces innovative approaches where target compounds are integral to the solvent system, allowing for one-step dissolution and extraction. This methodology eliminates the need for pre-prepared DESs, simplifying processes and enhancing extraction efficiency. Additionally, strategies for DESs recycling and reuse contribute to sustainability efforts, offering cost-effective and environmentally friendly extraction solutions. The expanding applications of DES-based and DESys-based natural product extraction in cosmetics, food, industry, and environmental fields highlight their promising development potential. By delineating the transition from DES-based to DESys-based extraction of natural products, this review offers valuable insights for advancing the practice of green chemical engineering.</div></div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"6 1","pages":"Pages 36-53"},"PeriodicalIF":9.1,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141278624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A size shrinkable dendrimer-lipid hybrid nanoassembly for reversing tumor drug resistance 用于逆转肿瘤抗药性的尺寸可收缩树枝状聚合物-脂质混合纳米组件

IF 9.1

Green Chemical Engineering Pub Date : 2024-05-18 DOI: 10.1016/j.gce.2024.05.001

Xuanrong Sun , Tenghan Zhang , Zhao Lou , Yujie Zhou , Yuteng Chu , Dongfang Zhou , Juhong Zhu , Yue Cai , Jie Shen

引用次数: 0

Machine learning-assisted prediction and optimization of solid oxide electrolysis cell for green hydrogen production 用于绿色制氢的固体氧化物电解槽的机器学习辅助性能预测与优化

IF 9.1

Green Chemical Engineering Pub Date : 2024-05-15 DOI: 10.1016/j.gce.2024.04.004

Qingchun Yang , Lei Zhao , Jingxuan Xiao , Rongdong Wen , Fu Zhang , Dawei Zhang

{"title":"Machine learning-assisted prediction and optimization of solid oxide electrolysis cell for green hydrogen production","authors":"Qingchun Yang , Lei Zhao , Jingxuan Xiao , Rongdong Wen , Fu Zhang , Dawei Zhang","doi":"10.1016/j.gce.2024.04.004","DOIUrl":"10.1016/j.gce.2024.04.004","url":null,"abstract":"<div><div>The solid oxide electrolysis cell (SOEC) holds great promise to efficiently convert renewable energy into hydrogen. However, traditional modeling methods are limited to a specific or reported SOEC system. Therefore, four machine learning models are developed to predict the performance of SOEC processes of various types, operating parameters, and feed conditions. The impact of these features on the SOEC's outputs is explained by the Shapley additive explanations and partial dependency plot analyses. The preferred model is integrated with a genetic algorithm to determine the optimal values of each input feature. Results show the improved extreme gradient enhanced regression (XGBoost) algorithm is the core of the machine learning model of the process since it has the highest R<sup>2</sup> (> 0.95) in the three outputs. The electrolytic cell descriptors have a greater impact on the system performance, contributing up to 54.5%. The effective area, voltage, and temperature are the three most influential factors in the SOEC system, contributing 21.6%, 16.6%, and 13.0% to its performance. High temperature, high pressure, and low effective area are the most favorable conditions for H<sub>2</sub> production rate. After conducting multi-objective optimization, the optimal current intensity and hydrogen production rate were determined to be 1.61 A/cm<sup>2</sup> and 1.174 L/(h·cm<sup>2</sup>).</div></div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"6 2","pages":"Pages 154-168"},"PeriodicalIF":9.1,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141036786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tailored SrFeO3-δ for chemical looping dry reforming of methane 用于甲烷化学循环干式转化的定制 SrFeO3-δ

IF 9.1

Green Chemical Engineering Pub Date : 2024-04-23 DOI: 10.1016/j.gce.2024.04.003

Ao Zhu, Dongfang Li, Tao Zhu, Xing Zhu

{"title":"Tailored SrFeO3-δ for chemical looping dry reforming of methane","authors":"Ao Zhu, Dongfang Li, Tao Zhu, Xing Zhu","doi":"10.1016/j.gce.2024.04.003","DOIUrl":"10.1016/j.gce.2024.04.003","url":null,"abstract":"<div><div>Chemical looping dry reforming of methane (CL-DRM) is a highly efficient process that converts two major greenhouse gases (CH<sub>4</sub> and CO<sub>2</sub>) into syngas ready for the feedstock of liquid fuel production. One of the major obstacles facing this technology now is creating oxygen carriers that are stable and reactive. We fabricated high-performance Sr<sub>0.98</sub>Fe<sub>0.7</sub>Co<sub>0.3</sub>O<sub>3-δ</sub> perovskite-structured oxygen carrier by combining A-site defects and B-site doping of SrFeO<sub>3-δ</sub>. During isothermal CL-DRM tests at 850 °C, Sr<sub>0.98</sub>Fe<sub>0.7</sub>Co<sub>0.3</sub>O<sub>3-δ</sub> achieved 87% CH<sub>4</sub> conversion and 94% CO selectivity in the CH<sub>4</sub> partial oxidation reaction, followed by a syngas yield of 8.5 mmol/g, and CO yield of 4.2 mmol/g in CO<sub>2</sub> decomposition. A-site defect engineering of the perovskite creates abundant oxygen vacancies and enhances oxygen storage capacity (OSC). Co-doping of the B-site of Sr<sub>0.98</sub>FeO<sub>3-δ</sub> increases oxygen mobility and CH<sub>4</sub>/CO<sub>2</sub> activation, resulting in high activity in the CL-DRM process. This methodology resulted in high ionic mobility and facilitated the rapid diffusion of oxygen in the bulk phase, thereby increasing the redox properties of SrFeO<sub>3-δ</sub>. The oxygen carrier exhibits excellent structural stability and regeneration ability in successive redox cycles. This strategy offers a simple but very effective pathway to tailor OSC, oxygen mobility, and oxygen vacancies of perovskite-structured materials for chemical looping or redox-involved processes.</div></div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"6 1","pages":"Pages 102-115"},"PeriodicalIF":9.1,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140786370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep eutectic solvent-induced controllable synthesis of bifunctional Ni–Fe–P catalysts for electrochemical water splitting 深共晶溶剂诱导可控合成用于电化学水分离的双功能 Ni-Fe-P 催化剂

IF 9.1

Green Chemical Engineering Pub Date : 2024-04-10 DOI: 10.1016/j.gce.2024.04.002

Ruichang Xue , Rongrong Deng , Yan Li , Mengqiu Gao , Jiafu Wang , Qibo Zhang

{"title":"Deep eutectic solvent-induced controllable synthesis of bifunctional Ni–Fe–P catalysts for electrochemical water splitting","authors":"Ruichang Xue , Rongrong Deng , Yan Li , Mengqiu Gao , Jiafu Wang , Qibo Zhang","doi":"10.1016/j.gce.2024.04.002","DOIUrl":"10.1016/j.gce.2024.04.002","url":null,"abstract":"<div><div>Developing electrocatalysts with excellent activity, high stability, and low cost is vital for large-scale hydrogen production through electrochemical water splitting. Herein, a bifunctional Ni–Fe–P catalyst <em>in situ</em> grown on Fe foam (Ni–Fe–P/FF) is developed by a simple one-step solvothermal process in the deep eutectic solvent (DES) of ethylene glycol and choline chloride (named Ethaline). The unique solvent environment of Ethaline assisted with the regulating effect of the introduced Fe(III) ions shows an essential role in governing the preparation process. The developed Ni–Fe–P/FF acts as the efficient bifunctional electrocatalyst for water splitting in 1.0 M KOH, requiring overpotentials of 82 mV (229 mV) and 263 mV (370 mV) to deliver 10 mA cm<sup>−2</sup> (100 mA cm<sup>−2</sup>) for oxygen and hydrogen evolution reactions, respectively. Furthermore, the self-supported catalyst-assembled electrolyzer also exhibits good catalytic performance with a low voltage of 1.83 V to drive 100 mA cm<sup>−2</sup> and good stability over 100 h. This work offers a facile approach to fabricating high-performance bifunctional Ni–Fe–P electrocatalysts to catalyze water splitting.</div></div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"6 1","pages":"Pages 93-101"},"PeriodicalIF":9.1,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140776231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep eutectic solvents for fractionation and valorization of lignocellulose 用于木质纤维素分馏和增值的深度共晶溶剂

IF 9.1

Green Chemical Engineering Pub Date : 2024-04-06 DOI: 10.1016/j.gce.2024.04.001

Yansai Bao, Yang Wang, Chuanyu Yan, Zhimin Xue

引用次数: 0

The different structure and properties of protic ionic liquid in alcohol from acid and base: butylammonium butyrate mixing with butanol, butyric acid, and butylamine respectively 原离子液体在酒精中与酸和碱的不同结构和性质：丁酸丁铵分别与丁醇、丁酸和丁胺的混合物

IF 9.1

Green Chemical Engineering Pub Date : 2024-04-04 DOI: 10.1016/j.gce.2024.03.005

Xuan Zhang , Yue Zhang , Haoran Li , Jia Yao

{"title":"The different structure and properties of protic ionic liquid in alcohol from acid and base: butylammonium butyrate mixing with butanol, butyric acid, and butylamine respectively","authors":"Xuan Zhang , Yue Zhang , Haoran Li , Jia Yao","doi":"10.1016/j.gce.2024.03.005","DOIUrl":"10.1016/j.gce.2024.03.005","url":null,"abstract":"<div><div>Solvents are commonly added into protic ionic liquids (PILs) to reduce viscosity in practical applications. Understanding the relationship between the structure and properties of PILs mixed with solvents is also essential for tailoring specific applications, however, such research is limited. In this study, we measured and compared the density, viscosity, and conductivity of three mixed systems: <em>n</em>-butylammonium butyrate ionic liquid (PIL) mixing with <em>N</em>-butyric acid (PrCOOH), PIL-<em>N</em>-butylamine (BuNH<sub>2</sub>), and PIL-<em>N</em>-butanol (BuOH). Small- and wide-angle X-ray scattering (S/WAXS), molecular dynamics (MD) simulation, and electron paramagnetic resonance (EPR) techniques were used to explore their inherent structural differences. The results indicate that the properties of the PIL-BuOH and PIL-PrCOOH systems exhibit more overall similarity in trends compared to the PIL-BuNH<sub>2</sub> system. However, when the molar fraction of alcohol or acid exceeds 0.8, structural differences between the two systems lead to the differences in properties. The hydrogen bond network between the BuOH molecules outside the ion cluster leads to higher viscosity and conductivity than the PIL-PrCOOH system. However, the strong hydrogen bond between PrCOOH and anions will replace the position of cations and form spherical clusters. This research highlights how distinct structures influence diverse properties, providing deeper insights into the structure-property relationship.</div></div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"6 1","pages":"Pages 85-92"},"PeriodicalIF":9.1,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140789223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical study on performance optimization and flow mechanism of a new cyclone separator 新型旋风分离器性能优化和流动机理的数值研究

IF 9.1

Green Chemical Engineering Pub Date : 2024-03-29 DOI: 10.1016/j.gce.2024.03.006

Mengjing Feng , Chengmin Gui , Yangfan Zhou , Zhigang Lei

{"title":"Numerical study on performance optimization and flow mechanism of a new cyclone separator","authors":"Mengjing Feng , Chengmin Gui , Yangfan Zhou , Zhigang Lei","doi":"10.1016/j.gce.2024.03.006","DOIUrl":"10.1016/j.gce.2024.03.006","url":null,"abstract":"<div><div>This study proposed a new cyclone separator, using a designed nozzle inside the traditional cyclone separator, which significantly improved the efficiency of separating fine particles while maintaining an essentially unchanged pressure drop. Firstly, computational fluid dynamics (CFD) was used to compare the flow characteristics of the new cyclone separator with those of the traditional cyclone separator. On this basis, this study comprehensively investigated the pressure drop and separation efficiency of two separators under varying working conditions. The new separator achieved a separation efficiency for particles with a particle size of 1 μm that was approximately 45% higher than that of the traditional separator when the inlet velocity was 2–10 m/s. Besides, the pressure drop of the cyclone separator remained unchanged while the separation efficiency increased by 46% at an inlet flow rate of 2 m/s. The influence of the outlet area of the nozzle inside the new cyclone separator on the separation efficiency and pressure drop was analyzed, and the outlet area of the nozzle with the best overall performance was determined. It was found that the overall performance of the new cyclone separator is optimal when the nozzle outlet area is <em>S</em>/<em>f</em> = 2 cm. Finally, an energy-saving cyclone separator with high separation efficiency was developed through an in-depth study of the variation of particle motion configuration with time. It is worth noting that this study provides a guidance for the flow field analysis and geometry optimization of new gas-solid separators, not limited to cyclone separators.</div></div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"6 1","pages":"Pages 76-84"},"PeriodicalIF":9.1,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140403664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0