Pub Date : 2024-11-26DOI: 10.1021/acs.iecr.4c02125
Yu Zhang, Lixia Kang, Jing Wang, Yongzhong Liu
An optimal design approach for a modular production system (MPS) for producing renewable methanol is proposed, aming at mitigating carbon dioxide emissions from coal-fired power plants. A mathematical programming model is established to optimize the capacity configuration and material/energy scheduling scheme of the MPS. The coal-fired power plant serves as the variable carbon source, whereas the wind farm provides the fluctuating renewable energy supply. The optimal design parameters and scheduling strategies for the MPS are determined by solving the proposed model. Two scenarios are considered, i.e. one involving sole energy supply fluctuations, and another one encompassing fluctuations in both energy and carbon supplies. These scenarios are analyzed to understand their effects on the design and operational performances of the MPS. The influence of wind power prices on the total annual cost of the MPS is also examined to identify the optimal conditions for deploying the proposed system.
{"title":"Optimal Design of a Modular Production System for Renewable Methanol to Mitigate Carbon Dioxide Emissions from Coal-Fired Power Plants","authors":"Yu Zhang, Lixia Kang, Jing Wang, Yongzhong Liu","doi":"10.1021/acs.iecr.4c02125","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c02125","url":null,"abstract":"An optimal design approach for a modular production system (MPS) for producing renewable methanol is proposed, aming at mitigating carbon dioxide emissions from coal-fired power plants. A mathematical programming model is established to optimize the capacity configuration and material/energy scheduling scheme of the MPS. The coal-fired power plant serves as the variable carbon source, whereas the wind farm provides the fluctuating renewable energy supply. The optimal design parameters and scheduling strategies for the MPS are determined by solving the proposed model. Two scenarios are considered, i.e. one involving sole energy supply fluctuations, and another one encompassing fluctuations in both energy and carbon supplies. These scenarios are analyzed to understand their effects on the design and operational performances of the MPS. The influence of wind power prices on the total annual cost of the MPS is also examined to identify the optimal conditions for deploying the proposed system.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"23 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142718520","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}
Pub Date : 2024-11-26DOI: 10.1021/acs.iecr.4c02380
Joshua A. Powell, Jazmine Aiya D. Marquez, Giles A. Johnson, Ray O. K. Ozdemir, Qingsheng Wang
While metal–organic frameworks (MOFs) hold great promise for a wide range of industrial applications, the challenges of handling fine crystalline powders have limited their adoption. MOF–polymer composites are one solution to this challenge, as composites or membranes are substantially easier to handle; however, most existing MOF–polymer composites have low MOF loadings and suffer MOF leaching due to the weak interactions between the MOF and the polymer. In this work, we report the continuous extrusion of MOF–polymer composites containing up to 60 wt % of commercially available MOFs and the successful extrusion of small amounts of composites containing 70 wt % MOF, with the composite viscosity being an important factor in the success of the extrusion. The MOF is well-distributed through the composite and remains crystalline despite the high temperatures and mechanical forces involved in the extrusion process. While the composites are more brittle than the base polymer and have negligible BET surface area, the suspected presence of inaccessible internal pores coupled with the increased thermal stability of the composites compared to the base polymer indicates the potential for the composites to be used as fire-resistant materials.
{"title":"Extrusion of MOF–Polymer Nanocomposites with High MOF Loadings","authors":"Joshua A. Powell, Jazmine Aiya D. Marquez, Giles A. Johnson, Ray O. K. Ozdemir, Qingsheng Wang","doi":"10.1021/acs.iecr.4c02380","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c02380","url":null,"abstract":"While metal–organic frameworks (MOFs) hold great promise for a wide range of industrial applications, the challenges of handling fine crystalline powders have limited their adoption. MOF–polymer composites are one solution to this challenge, as composites or membranes are substantially easier to handle; however, most existing MOF–polymer composites have low MOF loadings and suffer MOF leaching due to the weak interactions between the MOF and the polymer. In this work, we report the continuous extrusion of MOF–polymer composites containing up to 60 wt % of commercially available MOFs and the successful extrusion of small amounts of composites containing 70 wt % MOF, with the composite viscosity being an important factor in the success of the extrusion. The MOF is well-distributed through the composite and remains crystalline despite the high temperatures and mechanical forces involved in the extrusion process. While the composites are more brittle than the base polymer and have negligible BET surface area, the suspected presence of inaccessible internal pores coupled with the increased thermal stability of the composites compared to the base polymer indicates the potential for the composites to be used as fire-resistant materials.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"257 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713292","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}
Pub Date : 2024-11-26DOI: 10.1021/acs.iecr.4c03042
Ziqing Zhao, Amanda Baumann, Emily M. Ryan
The design of novel reactors and chemical processes requires an understanding of the fundamental chemical-physical processes at small spatial and temporal scales and a systematic scale-up of these studies to investigate how the process will perform at industrial scales. The financial and temporal costs of these studies can be significant. The use of statistical machine-learning-based methods can significantly reduce these costs. The use of the design of experimental methods can help design an experimental plan that efficiently explores the design space using the fewest experiments possible. Computational methods such as computational fluid dynamics (CFD) are effective tools for detailed studies of small-scale physics and are critical aids to facilitate and understand physical experiments. However, CFD methods can also be time-consuming, often requiring hours or days of time on supercomputers. In this research, we investigate the combination of machine learning with reducing 3D CFD simulation to 2D by exploiting axial symmetry to facilitate the design of experiments. Focusing on a 3D carbon dioxide (CO2) capture reactor as an example, we demonstrate how machine learning and CFD can help facilitate modeling and design optimization. A 2D CFD is used to simulate the chemical–physical processes in the reactor and is then coupled with machine learning to develop a less computationally expensive model to accurately predict CO2 adsorption. The learned model can be used to optimize the design of the reactor. This paper demonstrates the decrease in temporal and financial costs of designing industrial-scale chemical processes by combining reducing the CFD dimension and machine learning. Equally importantly, this research demonstrates the significance of selecting a proper machine-learning algorithm for different tasks by comparing the performances of different machine-learning algorithms.
{"title":"Using Machine-Learning-Aided Computational Fluid Dynamics to Facilitate Design of Experiments","authors":"Ziqing Zhao, Amanda Baumann, Emily M. Ryan","doi":"10.1021/acs.iecr.4c03042","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c03042","url":null,"abstract":"The design of novel reactors and chemical processes requires an understanding of the fundamental chemical-physical processes at small spatial and temporal scales and a systematic scale-up of these studies to investigate how the process will perform at industrial scales. The financial and temporal costs of these studies can be significant. The use of statistical machine-learning-based methods can significantly reduce these costs. The use of the design of experimental methods can help design an experimental plan that efficiently explores the design space using the fewest experiments possible. Computational methods such as computational fluid dynamics (CFD) are effective tools for detailed studies of small-scale physics and are critical aids to facilitate and understand physical experiments. However, CFD methods can also be time-consuming, often requiring hours or days of time on supercomputers. In this research, we investigate the combination of machine learning with reducing 3D CFD simulation to 2D by exploiting axial symmetry to facilitate the design of experiments. Focusing on a 3D carbon dioxide (CO<sub>2</sub>) capture reactor as an example, we demonstrate how machine learning and CFD can help facilitate modeling and design optimization. A 2D CFD is used to simulate the chemical–physical processes in the reactor and is then coupled with machine learning to develop a less computationally expensive model to accurately predict CO<sub>2</sub> adsorption. The learned model can be used to optimize the design of the reactor. This paper demonstrates the decrease in temporal and financial costs of designing industrial-scale chemical processes by combining reducing the CFD dimension and machine learning. Equally importantly, this research demonstrates the significance of selecting a proper machine-learning algorithm for different tasks by comparing the performances of different machine-learning algorithms.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"20 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713336","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}
Pub Date : 2024-11-26DOI: 10.1021/acs.iecr.4c03880
Prakhar Srivastava, Aayush Gupta, Nitin Kaistha
This study presents the synthesis and design of a two-column compact distillation (CD) process for separating a dilute ethyl acetate (EtAc)–methanol (MeOH)–water mixture, which has two minimum boiling azeotropes, into its constituent (nearly) pure components. The synthesized flowsheet leverages the pressure sensitivity of the azeotropes as well as the liquid–liquid phase split for efficient separation. To improve the energy efficiency, the basic flowsheet, consisting of a decanter, a high-pressure simple column, and a low-pressure divided-wall column, is heat-integrated (HI) using external heat exchangers to obtain the HI-CD process. The most energy-efficient hybrid-CD process is obtained by incorporating vapor recompression-driven reboil in the two columns along with external process-to-process heat exchange. A quantitative comparison with the recently reported best design, namely, the hybrid heterogeneous triple-column distillation (HTCD) process, reveals substantial economic and sustainability advantages of the proposed hybrid-CD process design. Specifically, the total annualized cost of the hybrid-CD process is lower by 15.4% compared with the hybrid-HTCD process. Energy consumption and CO2 emission are also significantly lower by 34.3 and 31.4%, respectively.
{"title":"Synthesis and Integrated Design of a Compact Azeotropic Process for EtAc–MeOH–Water Separation","authors":"Prakhar Srivastava, Aayush Gupta, Nitin Kaistha","doi":"10.1021/acs.iecr.4c03880","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c03880","url":null,"abstract":"This study presents the synthesis and design of a two-column compact distillation (CD) process for separating a dilute ethyl acetate (EtAc)–methanol (MeOH)–water mixture, which has two minimum boiling azeotropes, into its constituent (nearly) pure components. The synthesized flowsheet leverages the pressure sensitivity of the azeotropes as well as the liquid–liquid phase split for efficient separation. To improve the energy efficiency, the basic flowsheet, consisting of a decanter, a high-pressure simple column, and a low-pressure divided-wall column, is heat-integrated (HI) using external heat exchangers to obtain the HI-CD process. The most energy-efficient hybrid-CD process is obtained by incorporating vapor recompression-driven reboil in the two columns along with external process-to-process heat exchange. A quantitative comparison with the recently reported best design, namely, the hybrid heterogeneous triple-column distillation (HTCD) process, reveals substantial economic and sustainability advantages of the proposed hybrid-CD process design. Specifically, the total annualized cost of the hybrid-CD process is lower by 15.4% compared with the hybrid-HTCD process. Energy consumption and <i>CO</i><sub>2</sub> emission are also significantly lower by 34.3 and 31.4%, respectively.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"25 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142718525","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}
Pub Date : 2024-11-26DOI: 10.1021/acs.iecr.4c02620
Xiaodong Hong, Xuan Dong, Zuwei Liao, Jingdai Wang, Yongrong Yang
The simultaneous optimization problem of the heat exchanger network and organic Rankine cycle (HEN-ORC) poses significant challenges due to its highly nonconvex and nonlinear equations. We develop an adaptive partition linearization global optimization algorithm which is suitable for a wide range of mixed integer nonlinear programming (MINLP) problems and specially customized for HEN-ORC. The algorithm identifies convex equations of the logarithmic mean temperature function and the power function within the HEN-ORC model, which are relaxed by the first Taylor expansion and piecewise linearization. A multilevel McCormick relaxation is applied for the bilinear/multilinear functions derived from the HEN-ORC energy balance equations. The algorithm achieves global optimality by solving mixed integer linear programming and NLP submodels iteratively, enhancing the lower bound adaptively. Tested on seven heat exchanger networks and waste heat power generation cases, it outperforms two mainstream MINLP global optimization solvers (Baron and Couenne). The current best solutions are obtained for both a HEN and a HEN-ORC case, respectively.
{"title":"Adaptive Partition Linearization Global Optimization Algorithm and Its Application on the Simultaneous Heat Exchanger Network and Organic Rankine Cycle Optimization","authors":"Xiaodong Hong, Xuan Dong, Zuwei Liao, Jingdai Wang, Yongrong Yang","doi":"10.1021/acs.iecr.4c02620","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c02620","url":null,"abstract":"The simultaneous optimization problem of the heat exchanger network and organic Rankine cycle (HEN-ORC) poses significant challenges due to its highly nonconvex and nonlinear equations. We develop an adaptive partition linearization global optimization algorithm which is suitable for a wide range of mixed integer nonlinear programming (MINLP) problems and specially customized for HEN-ORC. The algorithm identifies convex equations of the logarithmic mean temperature function and the power function within the HEN-ORC model, which are relaxed by the first Taylor expansion and piecewise linearization. A multilevel McCormick relaxation is applied for the bilinear/multilinear functions derived from the HEN-ORC energy balance equations. The algorithm achieves global optimality by solving mixed integer linear programming and NLP submodels iteratively, enhancing the lower bound adaptively. Tested on seven heat exchanger networks and waste heat power generation cases, it outperforms two mainstream MINLP global optimization solvers (Baron and Couenne). The current best solutions are obtained for both a HEN and a HEN-ORC case, respectively.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"63 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142718521","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}
Pub Date : 2024-11-26DOI: 10.1021/acs.iecr.4c03386
Shiqiang Wang, Dan Guo, Meng Han, Yitong Yao, Pengfei Zhang, Xuening Zhang, Jing Lv, Yong Wang, Shengping Wang, Xinbin Ma
Syngas, an extremely meaningful chemical feedstock consisting of hydrogen and carbon monoxide, can be produced through methane dry reforming with carbon dioxide. The extensively utilized Ni-based catalysts usually suffer from coke-induced instability. Herein, we design Ni-CeOx bifunctional catalysts with different proximity and explore the influence of proximity level on anticoking performance. Ni-CeOx bimetallic nanoparticles with intimate contact are precisely regulated through the anchoring strategy of coordination unsaturated Al3+penta, which undergoes the topotactic exsolution of a Ni–Ce–O quasi-solid solution into Ni-CeOx bimetallic nanoparticles. A trend toward easier elimination and even the absence of graphitic carbon is observed with a decreasing spatial distance between Ni and CeOx, which is attributed to the proximity between the dissociation and gasification sites of CHx* intermediates. CHx* species generated at Ni nanoparticles migrated to adjacent CeOx oxygen carriers for Ni-CeOx/Al2O3 catalyst gasification with Ni-CeOx bimetallic nanoparticle interfaces, which undergo the Mars–van Krevelen (MvK) mechanism. The exploration of the Ni-CeOx proximity provides guidance for developing efficient and durable Ni-based DRM catalysts.
{"title":"Stabilizing Ni-CeOx Bifunctional Nanoparticles on Activated Alumina to Enhance Carbon Resistance for Dry Reforming of Methane","authors":"Shiqiang Wang, Dan Guo, Meng Han, Yitong Yao, Pengfei Zhang, Xuening Zhang, Jing Lv, Yong Wang, Shengping Wang, Xinbin Ma","doi":"10.1021/acs.iecr.4c03386","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c03386","url":null,"abstract":"Syngas, an extremely meaningful chemical feedstock consisting of hydrogen and carbon monoxide, can be produced through methane dry reforming with carbon dioxide. The extensively utilized Ni-based catalysts usually suffer from coke-induced instability. Herein, we design Ni-CeO<sub><i>x</i></sub> bifunctional catalysts with different proximity and explore the influence of proximity level on anticoking performance. Ni-CeO<sub><i>x</i></sub> bimetallic nanoparticles with intimate contact are precisely regulated through the anchoring strategy of coordination unsaturated Al<sup>3+</sup><sub>penta</sub>, which undergoes the topotactic exsolution of a Ni–Ce–O quasi-solid solution into Ni-CeO<sub><i>x</i></sub> bimetallic nanoparticles. A trend toward easier elimination and even the absence of graphitic carbon is observed with a decreasing spatial distance between Ni and CeO<sub><i>x</i></sub>, which is attributed to the proximity between the dissociation and gasification sites of CH<sub><i>x</i></sub>* intermediates. CH<sub><i>x</i></sub>* species generated at Ni nanoparticles migrated to adjacent CeO<sub><i>x</i></sub> oxygen carriers for Ni-CeO<sub><i>x</i></sub>/Al<sub>2</sub>O<sub>3</sub> catalyst gasification with Ni-CeO<sub><i>x</i></sub> bimetallic nanoparticle interfaces, which undergo the Mars–van Krevelen (MvK) mechanism. The exploration of the Ni-CeO<sub><i>x</i></sub> proximity provides guidance for developing efficient and durable Ni-based DRM catalysts.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"17 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713291","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}
Despite the wide application of chemical protective clothing (CPC), the poor breathability, low gas-absorption capacity, and poor flexibility of conventional CPC still deteriorate the safety and wear comfort. To eliminate the use of binders during the coating of activated carbon on textiles and improve the service stability in various harsh environments, an activated carbon (AC)-loaded porous poly(m-phenyleneisophthalamide) (PMIA) fiber was fabricated by a blending wet-spinning process for creating breathable and flexible textiles with high gas-absorption capacity. Herein, for maximizing the exposure-immobilization effects of AC on the porous PMIA fiber surface and preserving the mechanical performance of porous composite fibers, the pore parameters derived from the nonsolvent-induced phase-separation process were further optimized by adding polyethylene glycol (PEG) as a porogen. By adjusting the molecular weight and the content of PEG, not only various pores with different morphological parameters were prepared but also the effects of different pore parameters on the gas-absorption capacity, mechanical performance, and AC loading stability of the resultant porous composite fibers were clarified. When the molecular weight and addition amount of PEG were selected as 2000 g/mol and 5 wt %, the combination of micropores with a specific surface area of 17.7 cm2/g and mesopores with a specific surface area of 145.2 cm2/g can offer better synergistic effects to maximize exposure and carry out the stable immobilization of AC on the fiber surface, as well as the preservation of composite’s mechanical properties. The gas-adsorption capacity and tensile strength of corresponding AC-loaded porous fibers reached 132.29 mg/g and 0.6 cN/dtex, respectively. Meanwhile, after the mechanical friction experiment, the load stability of the AC without any detachment from the fiber surface was further confirmed. Finally, compared to the commercial CPC (FFF02), better air permeability and higher gas adsorption capacity can be offered by gas-absorption textiles directly fabricated from these AC-loaded PMIA porous fibers.
尽管化学防护服（CPC）得到了广泛应用，但传统 CPC 透气性差、气体吸收能力低、柔韧性差等问题仍会降低其安全性和穿着舒适性。为了避免在纺织品上涂覆活性炭时使用粘合剂，并提高其在各种恶劣环境中的使用稳定性，研究人员采用混纺湿法纺丝工艺制作了一种活性炭（AC）负载多孔聚（间苯二胺）（PMIA）纤维，用于制造具有高气体吸收能力的透气柔性纺织品。为了最大限度地提高 AC 在多孔 PMIA 纤维表面的暴露-固定效果并保持多孔复合纤维的机械性能，本文通过添加聚乙二醇（PEG）作为成孔剂，进一步优化了非溶剂诱导相分离过程中得到的孔隙参数。通过调整 PEG 的分子量和含量，不仅制备出了形态参数不同的各种孔隙，还明确了不同孔隙参数对所得多孔复合纤维的气体吸收能力、力学性能和 AC 负载稳定性的影响。当 PEG 的分子量和添加量分别选择为 2000 g/mol 和 5 wt % 时，比表面积为 17.7 cm2/g 的微孔和比表面积为 145.2 cm2/g 的中孔的组合能产生更好的协同效应，最大限度地增加 AC 在纤维表面的暴露和稳定固定，并保持复合材料的机械性能。相应的 AC 负载多孔纤维的气体吸附容量和拉伸强度分别达到了 132.29 mg/g 和 0.6 cN/dtex。同时，经过机械摩擦实验，AC 的负载稳定性得到了进一步证实，AC 不会从纤维表面脱离。最后，与商用 CPC（FFF02）相比，由这些负载 AC 的 PMIA 多孔纤维直接制成的吸气纺织品具有更好的透气性和更高的气体吸附能力。
{"title":"Exposure-Immobilization of Activated Carbon on Porous PMIA Fibers with High Gas-Absorption Capacity by Manipulating Their Pore Parameters Based on PEG as a Porogen for Designing Breathable and Flexible Chemical Protective Clothing","authors":"Lingcheng Meng, Bo Li, Qibin Xu, Xiaosong Li, Deyang Wu, Pengqing Liu, Shengchang Zhang","doi":"10.1021/acs.iecr.4c03080","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c03080","url":null,"abstract":"Despite the wide application of chemical protective clothing (CPC), the poor breathability, low gas-absorption capacity, and poor flexibility of conventional CPC still deteriorate the safety and wear comfort. To eliminate the use of binders during the coating of activated carbon on textiles and improve the service stability in various harsh environments, an activated carbon (AC)-loaded porous poly(<i>m</i>-phenyleneisophthalamide) (PMIA) fiber was fabricated by a blending wet-spinning process for creating breathable and flexible textiles with high gas-absorption capacity. Herein, for maximizing the exposure-immobilization effects of AC on the porous PMIA fiber surface and preserving the mechanical performance of porous composite fibers, the pore parameters derived from the nonsolvent-induced phase-separation process were further optimized by adding polyethylene glycol (PEG) as a porogen. By adjusting the molecular weight and the content of PEG, not only various pores with different morphological parameters were prepared but also the effects of different pore parameters on the gas-absorption capacity, mechanical performance, and AC loading stability of the resultant porous composite fibers were clarified. When the molecular weight and addition amount of PEG were selected as 2000 g/mol and 5 wt %, the combination of micropores with a specific surface area of 17.7 cm<sup>2</sup>/g and mesopores with a specific surface area of 145.2 cm<sup>2</sup>/g can offer better synergistic effects to maximize exposure and carry out the stable immobilization of AC on the fiber surface, as well as the preservation of composite’s mechanical properties. The gas-adsorption capacity and tensile strength of corresponding AC-loaded porous fibers reached 132.29 mg/g and 0.6 cN/dtex, respectively. Meanwhile, after the mechanical friction experiment, the load stability of the AC without any detachment from the fiber surface was further confirmed. Finally, compared to the commercial CPC (FFF02), better air permeability and higher gas adsorption capacity can be offered by gas-absorption textiles directly fabricated from these AC-loaded PMIA porous fibers.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"34 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142696709","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}
Pub Date : 2024-11-25DOI: 10.1021/acs.iecr.4c03173
Nihal Rao, Ashwin W Patwardhan
The LOHC dehydrogenation furnace and reactor are simulated in the present work to produce 10 N m3/h of hydrogen. Two reactor configurations are considered for the LOHC dehydrogenation system–helical and U-tube coil configuration. The furnace model is validated by comparing model predictions with the steam-cracking furnace simulation from Habibi et al. (Impact of Radiation Models in CFD Simulations of Steam Cracking Furnaces. Comput Chem Eng2007, 31 (11), 1389–1406. https://doi.org/10.1016/j.compchemeng.2006.11.009.). The flue gas temperature distribution, velocity, heat flux, and wall temperature within the furnace are determined by solving the mass, momentum, and energy equations through simulations conducted in Ansys Fluent software. The wall temperature obtained from the CFD simulation is used as an input for the 1D model of the dehydrogenation reactor to obtain the process side temperature and perhydro dibenzyltoluene (PDBT) conversion along the reactor length for both configurations. The reactor is designed to achieve more than 99% conversion of perhydro dibenzyl toluene. The wall temperature along the reactor length varies linearly from 660 to 807 K for the helical coil configuration, whereas the wall temperature for the U-tube configuration varies sinusoidally along the reactor length between 670 and 817 K. Additionally, the high wall temperature reduces the length required for the helical and U-tube coil configurations to achieve 99% conversion, compared to the constant wall temperature conditions reported in previous literature (Rao et al., Optimization of Liquid Organic Hydrogen Carrier (LOHC) Dehydrogenation System. Int J Hydrogen Energy2022, 47 (66), 28530–28547. https://doi.org/10.1016/j.ijhydene.2022.06.197). The helical coil configuration also demonstrates slightly higher thermal efficiency across various conversions compared to the U-tube configuration, offering valuable insights for designing efficient LOHC dehydrogenation systems.
本研究模拟了低浓氢化炉和反应器，以生产 10 N 立方米/小时的氢气。LOHC 脱氢系统考虑了两种反应器配置--螺旋形和 U 型管盘管配置。通过将模型预测结果与 Habibi 等人的蒸汽裂解炉模拟结果（《蒸汽裂解炉 CFD 模拟中辐射模型的影响》（Impact of Radiation Models in CFD Simulations of Steam Cracking Furnaces.Comput Chem Eng 2007, 31 (11), 1389-1406. https://doi.org/10.1016/j.compchemeng.2006.11.009.）。通过在 Ansys Fluent 软件中进行模拟，求解质量、动量和能量方程，确定炉内的烟气温度分布、速度、热通量和炉壁温度。从 CFD 模拟中获得的炉壁温度被用作脱氢反应器一维模型的输入，以获得两种配置下反应器长度方向的工艺侧温度和过氢二苄甲苯（PDBT）转化率。该反应器的设计目标是使全氢二苄基甲苯的转化率达到 99% 以上。此外，与之前文献（Rao 等人，《液体有机氢载体（LOHC）脱氢系统的优化》，Int J Hydrogen Energy 2022）报道的恒定壁温条件相比，高壁温缩短了螺旋线圈和 U 型管线圈配置实现 99% 转化率所需的长度。Int J Hydrogen Energy 2022, 47 (66), 28530-28547. https://doi.org/10.1016/j.ijhydene.2022.06.197）。与 U 型管配置相比，螺旋线圈配置在各种转换中的热效率也略高，为设计高效的 LOHC 脱氢系统提供了宝贵的见解。
{"title":"CFD Simulation and Analysis of LOHC Dehydrogenation Furnace and Reactor Configurations","authors":"Nihal Rao, Ashwin W Patwardhan","doi":"10.1021/acs.iecr.4c03173","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c03173","url":null,"abstract":"The LOHC dehydrogenation furnace and reactor are simulated in the present work to produce 10 N m<sup>3</sup>/h of hydrogen. Two reactor configurations are considered for the LOHC dehydrogenation system–helical and U-tube coil configuration. The furnace model is validated by comparing model predictions with the steam-cracking furnace simulation from Habibi et al. (Impact of Radiation Models in CFD Simulations of Steam Cracking Furnaces. <i>Comput Chem Eng</i> <b>2007</b>, <i>31</i> (11), 1389–1406. https://doi.org/10.1016/j.compchemeng.2006.11.009.). The flue gas temperature distribution, velocity, heat flux, and wall temperature within the furnace are determined by solving the mass, momentum, and energy equations through simulations conducted in Ansys Fluent software. The wall temperature obtained from the CFD simulation is used as an input for the 1D model of the dehydrogenation reactor to obtain the process side temperature and perhydro dibenzyltoluene (PDBT) conversion along the reactor length for both configurations. The reactor is designed to achieve more than 99% conversion of perhydro dibenzyl toluene. The wall temperature along the reactor length varies linearly from 660 to 807 K for the helical coil configuration, whereas the wall temperature for the U-tube configuration varies sinusoidally along the reactor length between 670 and 817 K. Additionally, the high wall temperature reduces the length required for the helical and U-tube coil configurations to achieve 99% conversion, compared to the constant wall temperature conditions reported in previous literature (Rao et al., Optimization of Liquid Organic Hydrogen Carrier (LOHC) Dehydrogenation System. <i>Int J Hydrogen Energy</i> <b>2022</b>, <i>47</i> (66), 28530–28547. https://doi.org/10.1016/j.ijhydene.2022.06.197). The helical coil configuration also demonstrates slightly higher thermal efficiency across various conversions compared to the U-tube configuration, offering valuable insights for designing efficient LOHC dehydrogenation systems.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"25 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713040","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}
Pub Date : 2024-11-25DOI: 10.1021/acs.iecr.4c02774
Liza R. White, Jordan N. Miner, Luke D. McKinney, Lindsay E. Pierce, Anna Folley, Ariel Larrabee, Lea Scrapchansky, Wyatt Fessler, Manisha Choudhary, Manoj Kamalanathan, Ramin Pouria, Saman Zare, Emma Perry, Sheila Edalatpour, Onur G. Apul, Caitlin Howell
The timely detection of aqueous analytes is critical to decision-makers in agriculture, industry, and municipalities. However, nearly all aqueous sensor systems rely on single-point measurements, often taken at an instantaneous point in time and in one location, which can limit their ability to detect analytes passing through the aqueous solution at other locations or times. In this work, we present the concept of employing a mass-manufactured nanotextured diffraction surface as a variable-area sensor system capable of providing spectrophotometric information about aqueous analytes across multiple locations over time. We show that by placing the nanotextured surface of the sensor system under or behind a water sample, the water can be scanned by simply changing the location or angle of the light source and detector. We demonstrate the detection and quantification of a variety of aqueous analytes, including visible and ultraviolet (UV)-absorbing dyes, dust particles, and microalgae species, at accuracies similar to those of commercial equipment. A machine-learning algorithm was used to lower the limit of detection of dye from 5 to 3 μg/mL as well as automate the classification of distinct analyte types. These results demonstrate that using a mass-manufactured, textured surface can offer benefits as aqueous sensors, facilitating widely deployable aqueous analyte monitoring in a variety of applications.
{"title":"Variable-Area Sensor Permits Near-Continuous Multipoint Measurements of Aqueous Biological and Chemical Analytes","authors":"Liza R. White, Jordan N. Miner, Luke D. McKinney, Lindsay E. Pierce, Anna Folley, Ariel Larrabee, Lea Scrapchansky, Wyatt Fessler, Manisha Choudhary, Manoj Kamalanathan, Ramin Pouria, Saman Zare, Emma Perry, Sheila Edalatpour, Onur G. Apul, Caitlin Howell","doi":"10.1021/acs.iecr.4c02774","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c02774","url":null,"abstract":"The timely detection of aqueous analytes is critical to decision-makers in agriculture, industry, and municipalities. However, nearly all aqueous sensor systems rely on single-point measurements, often taken at an instantaneous point in time and in one location, which can limit their ability to detect analytes passing through the aqueous solution at other locations or times. In this work, we present the concept of employing a mass-manufactured nanotextured diffraction surface as a variable-area sensor system capable of providing spectrophotometric information about aqueous analytes across multiple locations over time. We show that by placing the nanotextured surface of the sensor system under or behind a water sample, the water can be scanned by simply changing the location or angle of the light source and detector. We demonstrate the detection and quantification of a variety of aqueous analytes, including visible and ultraviolet (UV)-absorbing dyes, dust particles, and microalgae species, at accuracies similar to those of commercial equipment. A machine-learning algorithm was used to lower the limit of detection of dye from 5 to 3 μg/mL as well as automate the classification of distinct analyte types. These results demonstrate that using a mass-manufactured, textured surface can offer benefits as aqueous sensors, facilitating widely deployable aqueous analyte monitoring in a variety of applications.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"25 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713293","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}
Pub Date : 2024-11-25DOI: 10.1021/acs.iecr.4c03270
Sisanth Krishnageham Sidharthan, Jibin Keloth Paduvilan, Prajitha Velayudhan, Sabu Thomas
This study investigates silicone rubber–conductive carbon black (CCB) composites for antistatic applications aimed at protecting electronic devices from electrostatic discharge (ESD). The effects of the CCB concentration on the electrical and mechanical properties of the composites were analyzed. As the CCB concentration increased, the mechanical properties gradually decreased, while direct current (DC) conductivity increased. Composites containing 15 parts per hundred rubber (phr) of CCB exhibited effective antistatic properties with a resistivity of 9.37 × 104 Ω cm. Morphological analysis revealed that CCB was uniformly dispersed at lower concentrations but agglomerated at higher loadings. Power law fitting indicated a percolation threshold around 10 phr of CCB, suggesting the formation of a conductive network. Solvent transport and dissolution studies showed that the CCB network hindered diffusion, with diffusion behavior transitioning from Fickian to non-Fickian behavior, best described by the Peppas–Sahlin model. Additionally, molecular mass and crosslink density measurements confirmed the development of a network structure, which is critical for enhancing antistatic performance. These findings highlight the potential of CCB-based silicone rubber composites for effective ESD protection in electronic applications.
{"title":"Mechanical, Electrical, Morphological, and Solvent Transport Properties of Silicone Rubber–Conductive Carbon Black Composites for Antistatic Applications","authors":"Sisanth Krishnageham Sidharthan, Jibin Keloth Paduvilan, Prajitha Velayudhan, Sabu Thomas","doi":"10.1021/acs.iecr.4c03270","DOIUrl":"https://doi.org/10.1021/acs.iecr.4c03270","url":null,"abstract":"This study investigates silicone rubber–conductive carbon black (CCB) composites for antistatic applications aimed at protecting electronic devices from electrostatic discharge (ESD). The effects of the CCB concentration on the electrical and mechanical properties of the composites were analyzed. As the CCB concentration increased, the mechanical properties gradually decreased, while direct current (DC) conductivity increased. Composites containing 15 parts per hundred rubber (phr) of CCB exhibited effective antistatic properties with a resistivity of 9.37 × 10<sup>4</sup> Ω cm. Morphological analysis revealed that CCB was uniformly dispersed at lower concentrations but agglomerated at higher loadings. Power law fitting indicated a percolation threshold around 10 phr of CCB, suggesting the formation of a conductive network. Solvent transport and dissolution studies showed that the CCB network hindered diffusion, with diffusion behavior transitioning from Fickian to non-Fickian behavior, best described by the Peppas–Sahlin model. Additionally, molecular mass and crosslink density measurements confirmed the development of a network structure, which is critical for enhancing antistatic performance. These findings highlight the potential of CCB-based silicone rubber composites for effective ESD protection in electronic applications.","PeriodicalId":39,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":"38 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713041","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}
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