Green Chemical Engineering最新文献_第10页

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/S2666-9528(22)00092-9

引用次数: 0

Boosting the adsorption and removal of dye from water by COOH-functionalized carbon nanotubes 羧酸官能化碳纳米管对水中染料的吸附和去除

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/j.gce.2022.05.002

Binran Zhao , Yiyi Zhao , Peng Liu , Yu-Long Men , Yun-Xiang Pan

{"title":"Boosting the adsorption and removal of dye from water by COOH-functionalized carbon nanotubes","authors":"Binran Zhao , Yiyi Zhao , Peng Liu , Yu-Long Men , Yun-Xiang Pan","doi":"10.1016/j.gce.2022.05.002","DOIUrl":"10.1016/j.gce.2022.05.002","url":null,"abstract":"<div>Water pollution caused by dye is a serious challenge. Herein, we use a novel discharge process to functionalize carbon nanotube (CNT) by COOH groups to form CNT30 for removing methyl red (MR) from water. By pristine CNT, 75% MR is removed in 60 min, with an adsorption capacity of 68.44 mg g-1. By CNT30, 85% MR is fast removed in only 5 min, and the removal efficiency reaches to 95% after 30 min, with an adsorption capacity of 80.33 mg g-1. Thus, a higher MR removal efficiency is achieved in a much shorter time on CNT30. Moreover, CNT30 has an outstanding reusability, with the MR removal efficiency decreasing by only 7% after ten cycles. The COOH groups on CNT30 improve the hydrophilicity of CNT30, thus promoting the interaction of MR in water with CNT30. The hydrogen bonding and electrostatic interaction of MR with the COOH groups on CNT30 could be the force to drive MR adsorption on CNT30. The higher COOH content could be the origin for the better performance of CNT30 in removing dye from water. The discharge process developed herein is operated in O2, without using harmful substances, and the COOH content on CNT can be efficiently tuned by simply changing discharge time. This is different from the chemical modification widely used to functionalize CNT by strong oxidants, e.g., HNO3. The present work is of great significance to realize green construction of materials for more efficiently removing dye from water.</div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"4 1","pages":"Pages 88-98"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42751609","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}

引用次数: 8

Recent advances in hybrid water electrolysis for energy-saving hydrogen production 混合水电解节能制氢研究进展

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/j.gce.2022.11.001

Di Li , Jibing Tu , Yingying Lu , Bing Zhang

引用次数: 1

Electrochemical synthesis of Ni doped carbon quantum dots for simultaneous fluorometric determination of Fe3+ and Cu2+ ion facilely 电化学合成镍掺杂碳量子点用于同时荧光测定Fe3+和Cu2+离子

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/j.gce.2022.05.004

Siyuan Sun , Yang Sun , Fan Yang, Sai Che, Xiaoyun Zhang, Ge Zhang, Yongfeng Li

{"title":"Electrochemical synthesis of Ni doped carbon quantum dots for simultaneous fluorometric determination of Fe3+ and Cu2+ ion facilely","authors":"Siyuan Sun , Yang Sun , Fan Yang, Sai Che, Xiaoyun Zhang, Ge Zhang, Yongfeng Li","doi":"10.1016/j.gce.2022.05.004","DOIUrl":"https://doi.org/10.1016/j.gce.2022.05.004","url":null,"abstract":"<div>A novel Ni doped carbon quantum dots (Ni-CQDs) fluorescence probe was synthesized by facile electrolysis of monoatomic Ni dispersed porous carbon (Ni–N–C). The obtained Ni-CQDs showed a high quantum yield of 6.3% with the strongest excitation and emission peaks of 360 nm and 460 nm, and maintained over 90% of the maximum fluorescence intensity in a wide pH range of 3–12. The metal ions detectability of Ni-CQDs was enhanced by Ni doping and functional groups modification, and the rapid and selective detection of Fe3+ and Cu2+ ions was achieved with Ni-CQDs through dynamic and static quenching mechanism, respectively. On one hand, the energy band gap of Ni-CQDs was regulated by Ni doping, so that excited electrons in Ni-CQDs were able to transfer to Fe3+ easily. On the other hand, the abundant functional groups promoted the generation of static quenching complexation between Cu2+ and Ni-CQDs. In metal ions detection, the linear quantitation range of Fe3+ and Cu2+ were 100–1000 μM (R2 = 0.9955) and 300–900 μM (R2 = 0.9978), respectively. The limits of detection (LOD) were calculated as 10.17 and 7.88 μM, respectively. Moreover, the fluorescence quenched by Cu2+ could be recovered by EDTA2− due to the destruction of the static quenching complexation. In this way, Ni-CQDs showed the ability to identify the two metal ions to a certain degree under the condition of Fe3+ and Cu2+ coexistent. This work paves the way of facile multiple metal ion detection with high sensitivity.</div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"4 1","pages":"Pages 115-122"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50180860","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}

引用次数: 0

Understanding and optimizing the gasification of biomass waste with machine learning 利用机器学习理解和优化生物质废物的气化

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/j.gce.2022.05.006

Jie Li , Lanyu Li , Yen Wah Tong , Xiaonan Wang

{"title":"Understanding and optimizing the gasification of biomass waste with machine learning","authors":"Jie Li , Lanyu Li , Yen Wah Tong , Xiaonan Wang","doi":"10.1016/j.gce.2022.05.006","DOIUrl":"10.1016/j.gce.2022.05.006","url":null,"abstract":"<div>Gasification is a sustainable approach for biomass waste treatment with simultaneous combustible H2-syngas production. However, this thermochemical process was quite complicated with multi-phase products generated. The product distribution and composition also highly depend on the feedstock information and gasification condition. At present, it is still challenging to fully understand and optimize this process. In this context, four data-driven machine learning (ML) methods were applied to model the biomass waste gasification process for product prediction and process interpretation and optimization. The results indicated that the Gradient Boosting Regression (GBR) model showed good performance for predicting three-phase products and syngas compositions with test R2 of 0.82–0.96. The GBR model-based interpretation suggested that both feed and gasification condition (including the contents of feedstock ash, carbon, nitrogen, oxygen, and gasification temperature) were important factors influencing the distribution of char, tar, and syngas. Furthermore, it was found that a feedstock with higher carbon (> 48%), lower nitrogen (< 0.5%), and ash (1%–5%) contents under a temperature over 800 °C could achieve a higher yield of H2-rich syngas. It was shown that the optimal conditions suggested by the model could achieve an output containing 60%–62% syngas and achieve an H2 yield of 44.34 mol/kg. These valuable insights provided from the model-based interpretation could aid the understanding and optimization of biomass gasification to guide the production of H2-rich syngas.</div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"4 1","pages":"Pages 123-133"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45514134","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}

引用次数: 23

Visible light assisted enzyme-photocatalytic cascade degradation of organophosphorus pesticides 可见光辅助酶催化级联降解有机磷农药

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/j.gce.2022.02.001

Ying Zhang , Xue Cao , Yufeng Yang , Sumin Guan , Xiaotian Wang , Heyu Li , Xiaobing Zheng , Liya Zhou , Yanjun Jiang , Jing Gao

{"title":"Visible light assisted enzyme-photocatalytic cascade degradation of organophosphorus pesticides","authors":"Ying Zhang , Xue Cao , Yufeng Yang , Sumin Guan , Xiaotian Wang , Heyu Li , Xiaobing Zheng , Liya Zhou , Yanjun Jiang , Jing Gao","doi":"10.1016/j.gce.2022.02.001","DOIUrl":"10.1016/j.gce.2022.02.001","url":null,"abstract":"<div>The worldwide application of organophosphorus pesticides (OPs) has promoted agricultural development, but their gradual accumulation in soil and water can seriously affect the central nervous system of humans and other mammals. Organophosphorus hydrolase (OPH) is an effective enzyme that can catalyze the degradation of the residual OPs. However, the degradation products such as p-nitrophenol (p-NP) is still toxic. Thus, it is of great significance to develop a multi-functional support that can be simultaneously used for the immobilization of OPH and the further degradation of p-NP. Herein, a visible light assisted enzyme-photocatalytic integrated catalyst was constructed by immobilizing OPH on hollow structured Au-TiO2 (named OPH@H-Au-TiO2) for the degradation of OPs. The obtained OPH@H-Au-TiO2 can degrade methyl parathion to p-NP by OPH and then degrade p-NP to hydroquinone with low toxicity by using H-Au-TiO2 under visible light. OPH molecules were immobilized on H-Au-TiO2 through adsorption method to prepare OPH@H-Au-TiO2. After 2.5 h of reaction, methyl parathion is completely degraded, and about 82.64% of the generated p-NP is further degraded into hydroquinone. After reused for 4 times, the OPH@H-Au-TiO2 retains more than 80% of the initial degradation activity. This research presents a new insight in designing and constructing multi-functional biocatalyst, which greatly expands the application scenarios and industrial value of enzyme catalysis.</div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"4 1","pages":"Pages 30-38"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46444717","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}

引用次数: 8

Outside Back Cover 封底

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/S2666-9528(22)00099-1

引用次数: 0

Enzymes immobilized in wood-derived cellulose scaffold for constructing a novel modular bioreactor 木质纤维素支架固定化酶构建新型模块化生物反应器

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/j.gce.2022.03.001

Zhihong Zhang , Mengchen Jin , Guiru Chen , Jiandu Lei , Luying Wang , Jun Ge

{"title":"Enzymes immobilized in wood-derived cellulose scaffold for constructing a novel modular bioreactor","authors":"Zhihong Zhang , Mengchen Jin , Guiru Chen , Jiandu Lei , Luying Wang , Jun Ge","doi":"10.1016/j.gce.2022.03.001","DOIUrl":"10.1016/j.gce.2022.03.001","url":null,"abstract":"<div>Modular bioreactors can provide a flexible platform for constructing complex multi-step pathways, which may be a solution for maximizing reactions and overcoming the complexity of multi-enzyme systems. Here, we selected wood-derived cellulose scaffold as a support for enzyme immobilization and constructed the modular bioreactor. Cellulose scaffold was prepared after removing lignin from wood, followed by citric acid functionalization and the addition of glutaraldehyde finally allowed the cross-linking of enzymes. Three enzymes, horseradish peroxidase (HRP), glucose oxidase (GOD), and catalase (CAT), were separately immobilized, resulting in the immobilized enzyme amount to over 40 mg/g. The introduction of carboxyl groups from citric acid facilitated the rapid enzyme adsorption on the support surface and immobilized enzymes possess ∼65% expressed activity. Modular bioreactors were constructed by using the immobilized enzymes. With the immobilized HRP module, reactor showed desired catalytic performance with the phenol degradation rate of > 90%. Also, a pH regulation can occur in the bioreactors for preserving enzyme activities and neutralizing acid products. In the GOD/CAT modular bioreactor, the cascade reaction with adjusting pH values can achieve a 95% yield of sodium gluconate and exhibit a favorable reusability of 5 operation cycles.</div>","PeriodicalId":66474,"journal":{"name":"Green Chemical Engineering","volume":"4 1","pages":"Pages 39-48"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49163259","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}

引用次数: 2

Engineering 3D-printed aqueous colloidal ceramic slurry for direct ink writing 用于直接墨水书写的工程3d打印水性胶体陶瓷浆料

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/j.gce.2022.04.005

Jie Zhu , Jiangtao Yu , Yingcheng Wu , Yanhong Chao , Peiwen Wu , Linjie Lu , Linlin Chen , Jing He , Wenshuai Zhu

引用次数: 8

Recent developments of anti-plasticized membranes for aggressive CO2 separation 抗增塑膜在侵略性CO2分离中的最新进展

Green Chemical Engineering Pub Date : 2023-03-01 DOI: 10.1016/j.gce.2022.09.001

Yongchao Sun , Xiaoyu Wang , Xiangcun Li , Wu Xiao , Yan Dai , Canghai Ma , Gaohong He

引用次数: 4