Chemical upcycling of waste plastics represents an appealing way to achieve a circular economy and mitigate environmental problems but remains a huge challenge. Herein, we report a heterojunction photocatalyst (ZnInFe‐mixed metal oxide, denoted as ZnInFe‐MMO) for the rapid valorization of polylactic acid (PLA) via a developed alkali‐assisted photocatalysis system. The ZnInFe‐MMO featured with a double Z‐Scheme structure is favorable for light harvesting and electron‐hole separation. Moreover, the operando characterizations and theoretical simulations confirm that the ZnInFe‐MMO affords a remarkably decreased barrier for the rate‐determining step (formation of *LA intermediate) while inhibiting the CC breakage in the side reaction. As a result, the ZnInFe‐MMO attains a ~100% conversion and ~99% selectivity toward sodium lactate (NaLA), which is preponderant to the state‐of‐the‐art photocatalysts. In addition, such an effective route is also demonstrated in various real‐world PLA waste.
{"title":"Ultrafast and highly‐selective upcycling of plastic polylactic acid waste driven by ZnInFe‐mixed metal oxide","authors":"Jianchi Zhou, Jibo Qin, Biao Li, Congjia Luo, Jingbin Han, Yanqing Hu, Wenjing Zhang, Yibo Dou","doi":"10.1002/aic.18513","DOIUrl":"https://doi.org/10.1002/aic.18513","url":null,"abstract":"Chemical upcycling of waste plastics represents an appealing way to achieve a circular economy and mitigate environmental problems but remains a huge challenge. Herein, we report a heterojunction photocatalyst (ZnInFe‐mixed metal oxide, denoted as ZnInFe‐MMO) for the rapid valorization of polylactic acid (PLA) via a developed alkali‐assisted photocatalysis system. The ZnInFe‐MMO featured with a double Z‐Scheme structure is favorable for light harvesting and electron‐hole separation. Moreover, the operando characterizations and theoretical simulations confirm that the ZnInFe‐MMO affords a remarkably decreased barrier for the rate‐determining step (formation of *LA intermediate) while inhibiting the CC breakage in the side reaction. As a result, the ZnInFe‐MMO attains a ~100% conversion and ~99% selectivity toward sodium lactate (NaLA), which is preponderant to the state‐of‐the‐art photocatalysts. In addition, such an effective route is also demonstrated in various real‐world PLA waste.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work pursues the closure for the effective reaction rate based on fine‐grid two‐fluid model (TFM) simulations in reactive gas‐solid flows. It is found that the mesoscale mechanism in the solid‐catalyzed reaction is constrained by the kinetic regime (KR) and the external mass transfer‐controlled regimes (EMTR). Thus, a filtered reaction rate model ηsubgrid considered two different regimes is proposed. The mesoscale effectiveness factor proposed in previous work is adopted in KR. A filtered interphase mass transfer model QM, which is constructed by analogy to the interphase heat transfer model, is used in EMTR. ηsubgrid shows a good predictability in two regimes via a priori test. The fidelity of ηsubgrid is also assessed via a filtered TFM simulation. The results indicate that the simulations incorporating corrections for the drag force and reaction rate yield better agreement with the fine‐grid simulations for both mass fraction and reaction rate profiles.
{"title":"Filtered reaction rate and interphase mass transfer models in reactive gas‐solid flows","authors":"Zheqing Huang, Zheng Zhang, Lingxue Wang, Qiang Zhou","doi":"10.1002/aic.18521","DOIUrl":"https://doi.org/10.1002/aic.18521","url":null,"abstract":"This work pursues the closure for the effective reaction rate based on fine‐grid two‐fluid model (TFM) simulations in reactive gas‐solid flows. It is found that the mesoscale mechanism in the solid‐catalyzed reaction is constrained by the kinetic regime (KR) and the external mass transfer‐controlled regimes (EMTR). Thus, a filtered reaction rate model <jats:italic>η</jats:italic><jats:sub>subgrid</jats:sub> considered two different regimes is proposed. The mesoscale effectiveness factor proposed in previous work is adopted in KR. A filtered interphase mass transfer model <jats:italic>Q</jats:italic><jats:sub><jats:italic>M</jats:italic></jats:sub>, which is constructed by analogy to the interphase heat transfer model, is used in EMTR. <jats:italic>η</jats:italic><jats:sub>subgrid</jats:sub> shows a good predictability in two regimes via a priori test. The fidelity of <jats:italic>η</jats:italic><jats:sub>subgrid</jats:sub> is also assessed via a filtered TFM simulation. The results indicate that the simulations incorporating corrections for the drag force and reaction rate yield better agreement with the fine‐grid simulations for both mass fraction and reaction rate profiles.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adriane Simanke, Jacob Harrison, Priya Srinivasan, Mengyao Ouyang, Jiahan Xie, Nei Sebastiao Domingues
Biomass feedstocks are established as a key resource and a viable alternative for an economy less dependent on fossil inputs. This review offers an examination exemplified by fresh references covering strategies to reach a sustainable conversion of biomass to emerging chemicals and materials. Biobased chemicals lead to reduced climate change impacts compared with their fossil‐based counterparts. There is a broad range of products that can be targeted for biobased production, and it is important to select both the feedstocks and the target chemicals, which have a positive environmental impact and opportunity of commercial success. From the perspective of polymer science, we summarize emerging polymers that can be derived from biomass with promising properties. Furthermore, as challenges in the field of emerging biobased materials and chemicals are driven both by performance constraints and economic factors, we also examine recent progress in catalytic and biochemical process towards successful end products.
{"title":"Recent advances in biobased materials and value‐added chemicals","authors":"Adriane Simanke, Jacob Harrison, Priya Srinivasan, Mengyao Ouyang, Jiahan Xie, Nei Sebastiao Domingues","doi":"10.1002/aic.18506","DOIUrl":"https://doi.org/10.1002/aic.18506","url":null,"abstract":"Biomass feedstocks are established as a key resource and a viable alternative for an economy less dependent on fossil inputs. This review offers an examination exemplified by fresh references covering strategies to reach a sustainable conversion of biomass to emerging chemicals and materials. Biobased chemicals lead to reduced climate change impacts compared with their fossil‐based counterparts. There is a broad range of products that can be targeted for biobased production, and it is important to select both the feedstocks and the target chemicals, which have a positive environmental impact and opportunity of commercial success. From the perspective of polymer science, we summarize emerging polymers that can be derived from biomass with promising properties. Furthermore, as challenges in the field of emerging biobased materials and chemicals are driven both by performance constraints and economic factors, we also examine recent progress in catalytic and biochemical process towards successful end products.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141463959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eleni D. Koronaki, Luise F. Kaven, Johannes M. M. Faust, Ioannis G. Kevrekidis, Alexander Mitsos
Polymer particle size constitutes a crucial characteristic of product quality in polymerization. Raman spectroscopy is an established and reliable process analytical technology for in‐line concentration monitoring. Recent approaches and some theoretical considerations show a correlation between Raman signals and particle sizes but do not determine polymer size from Raman spectroscopic measurements accurately and reliably. With this in mind, we propose three alternative machine learning workflows to perform this task, all involving diffusion maps, a nonlinear manifold learning technique for dimensionality reduction: (i) directly from diffusion maps, (ii) alternating diffusion maps, and (iii) conformal autoencoder neural networks. We apply the workflows to a data set of Raman spectra with associated size measured via dynamic light scattering of 47 microgel (cross‐linked polymer) samples in a diameter range of 208–483 nm. The conformal autoencoders substantially outperform state‐of‐the‐art methods and results for the first time in a promising prediction of polymer size from Raman spectra.
{"title":"Nonlinear manifold learning determines microgel size from Raman spectroscopy","authors":"Eleni D. Koronaki, Luise F. Kaven, Johannes M. M. Faust, Ioannis G. Kevrekidis, Alexander Mitsos","doi":"10.1002/aic.18494","DOIUrl":"https://doi.org/10.1002/aic.18494","url":null,"abstract":"Polymer particle size constitutes a crucial characteristic of product quality in polymerization. Raman spectroscopy is an established and reliable process analytical technology for in‐line concentration monitoring. Recent approaches and some theoretical considerations show a correlation between Raman signals and particle sizes but do not determine polymer size from Raman spectroscopic measurements accurately and reliably. With this in mind, we propose three alternative machine learning workflows to perform this task, all involving diffusion maps, a nonlinear manifold learning technique for dimensionality reduction: (i) directly from diffusion maps, (ii) alternating diffusion maps, and (iii) conformal autoencoder neural networks. We apply the workflows to a data set of Raman spectra with associated size measured via dynamic light scattering of 47 microgel (cross‐linked polymer) samples in a diameter range of 208–483 nm. The conformal autoencoders substantially outperform state‐of‐the‐art methods and results for the first time in a promising prediction of polymer size from Raman spectra.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141462765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modulating lattice strain in intermetallic compounds could effectively alter their electronic structure and binding energy, thus impacting catalytic activity. Strain is usually induced through lattice mismatch, achieved by constructing core‐shell nanostructures or metal‐substrate interfaces with complex reciprocity and distractors. However, in situ induced strain without interface‐construction or lattice mismatch presents challenges. In this study, we precisely manipulate consecutive compressive strain from −0.5% to −0.8% in CoPt3Pd intermetallic compound by inducing interior atomic radius mismatch. Precise strain control results in a negative shift of d‐band center, dynamic charge distribution, and facilitates water dissociation, leading to enhanced electrocatalytic activity. The CoPt3Pd catalyst with −0.5% compressive strain exhibits exceptional hydrogen evolution activity, with an overpotential of 169 mV at 1 A cm−2. Our approach offers a straightforward method to manipulate compressive strain on intermetallic compounds by atomic size mismatch, with broad implications for catalytic processes.
调节金属间化合物的晶格应变可有效改变其电子结构和结合能,从而影响催化活性。应变通常通过晶格错配来诱导,通过构建具有复杂互易性和分心的核壳纳米结构或金属-基底界面来实现。然而,在没有界面构建或晶格错配的情况下进行原位诱导应变则面临挑战。在本研究中,我们通过诱导内部原子半径失配,在 CoPt3Pd 金属间化合物中精确控制 -0.5% 至 -0.8% 的连续压缩应变。精确的应变控制导致了 d 波段中心的负移和动态电荷分布,并促进了水的解离,从而提高了电催化活性。具有-0.5%压缩应变的 CoPt3Pd 催化剂表现出卓越的氢气进化活性,在 1 A cm-2 的过电位为 169 mV。我们的方法提供了一种通过原子尺寸失配来操纵金属间化合物压应变的直接方法,对催化过程具有广泛的影响。
{"title":"Atomic size mismatch induced consecutive compressive strain on intermetallic compound towards boosted hydrogen evolution","authors":"Jiankun Li, Zeyu Guan, Haoran Wu, Yixing Wang, Linfeng Lei, Minghui Zhu, Linzhou Zhuang, Zhi Xu","doi":"10.1002/aic.18522","DOIUrl":"https://doi.org/10.1002/aic.18522","url":null,"abstract":"Modulating lattice strain in intermetallic compounds could effectively alter their electronic structure and binding energy, thus impacting catalytic activity. Strain is usually induced through lattice mismatch, achieved by constructing core‐shell nanostructures or metal‐substrate interfaces with complex reciprocity and distractors. However, <jats:italic>in situ</jats:italic> induced strain without interface‐construction or lattice mismatch presents challenges. In this study, we precisely manipulate consecutive compressive strain from −0.5% to −0.8% in CoPt<jats:sub>3</jats:sub>Pd intermetallic compound by inducing interior atomic radius mismatch. Precise strain control results in a negative shift of d‐band center, dynamic charge distribution, and facilitates water dissociation, leading to enhanced electrocatalytic activity. The CoPt<jats:sub>3</jats:sub>Pd catalyst with −0.5% compressive strain exhibits exceptional hydrogen evolution activity, with an overpotential of 169 mV at 1 A cm<jats:sup>−2</jats:sup>. Our approach offers a straightforward method to manipulate compressive strain on intermetallic compounds by atomic size mismatch, with broad implications for catalytic processes.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141462799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shuangfei Zhao, Xin Hu, Huiyue Wang, Yihuan Liu, Zheng Fang, Kai Guo, Ning Zhu
The scale‐up of microreactor‐based flow chemical process represents a grand challenge in chemical engineering. The small characteristic size (<1000 μm) of a typical microreactor leads to not only microscale effect (process intensification) but also low throughput. Here, we report macro‐microreactor to achieve scale‐up of liquid–liquid chemical operation with process intensification. By incorporating the designed internals based on computational fluid dynamics, the characteristic size of the macro‐microreactor is expanded into 3000–4000 μm. The optimized design of macro‐microreactor with helical‐shaped internal exhibits both similar or even stronger microscale effect and high throughput in contrast to the typical microreactor. For the liquid–liquid chemical process, seven times higher mass transfer coefficient and about half reduction of the pressure drop are realized. These macro‐microreactors would find further applications in industrial chemical manufacturing.
{"title":"Optimized design of macro‐microreactor for scale‐up of liquid–liquid chemical processes","authors":"Shuangfei Zhao, Xin Hu, Huiyue Wang, Yihuan Liu, Zheng Fang, Kai Guo, Ning Zhu","doi":"10.1002/aic.18508","DOIUrl":"https://doi.org/10.1002/aic.18508","url":null,"abstract":"The scale‐up of microreactor‐based flow chemical process represents a grand challenge in chemical engineering. The small characteristic size (<1000 μm) of a typical microreactor leads to not only microscale effect (process intensification) but also low throughput. Here, we report macro‐microreactor to achieve scale‐up of liquid–liquid chemical operation with process intensification. By incorporating the designed internals based on computational fluid dynamics, the characteristic size of the macro‐microreactor is expanded into 3000–4000 μm. The optimized design of macro‐microreactor with helical‐shaped internal exhibits both similar or even stronger microscale effect and high throughput in contrast to the typical microreactor. For the liquid–liquid chemical process, seven times higher mass transfer coefficient and about half reduction of the pressure drop are realized. These macro‐microreactors would find further applications in industrial chemical manufacturing.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141448348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhengrun Chen, Hui Xu, Xiaoteng Zang, Hong Meng, Hongwei Fan, Yingzhou Lu, Chunxi Li
Calcium carbide (CaC2) is a valuable carbanion resource, but the reactivity is highly restricted by its insolubility and super-basicity. For this, the effect of solvent and mechanical forces on its reactivity is investigated extensively here via quantum chemistry calculation, molecular dynamic simulation, and experiments. The dissolution free energy of CaC2 in over 100 solvents has been evaluated. DMSO, CH3CN, and DMF can enhance the negative potential and reactivity of CaC2, especially DMSO. The electrostatic interaction of CaC2-solvent mainly originates from the interaction between Ca2+ and O or N atom. The increased electron density around