AIChE Journal最新文献

英文中文

Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling 通过物理信息机器学习库普曼建模实现非线性系统的自调整移动地平线估计

IF 3.7 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-22 DOI: 10.1002/aic.18649

Mingxue Yan, Minghao Han, Adrian Wing-Keung Law, Xunyuan Yin

In this article, we propose a physics-informed learning-based Koopman modeling approach and present a Koopman-based self-tuning moving horizon estimation design for a class of nonlinear systems. Specifically, we train Koopman operators and two neural networks—the state lifting network and the noise characterization network—using both data and available physical information. The first network accounts for the nonlinear lifting functions for the Koopman model, while the second network characterizes the system noise distributions. Accordingly, a stochastic linear Koopman model is established in the lifted space to forecast the dynamic behaviors of the nonlinear system. Based on the Koopman model, a self-tuning linear moving horizon estimation (MHE) scheme is developed. The weighting matrices of the MHE design are updated using the pretrained noise characterization network at each sampling instant. The proposed estimation scheme is computationally efficient, as only convex optimization needs to be solved during online implementation, and updating the weighting matrices of the MHE scheme does not require re-training the neural networks. We verify the effectiveness and evaluate the performance of the proposed method via the application to a simulated chemical process.

在本文中，我们提出了一种基于物理信息学习的 Koopman 建模方法，并针对一类非线性系统提出了一种基于 Koopman 的自调整移动地平线估计设计。具体来说，我们利用数据和可用物理信息训练库普曼算子和两个神经网络--状态提升网络和噪声表征网络。第一个网络用于计算库普曼模型的非线性提升函数，第二个网络用于描述系统噪声分布。因此，在提升空间中建立了随机线性库普曼模型，以预测非线性系统的动态行为。在 Koopman 模型的基础上，开发了一种自调整线性移动地平线估计（MHE）方案。MHE 设计的加权矩阵在每个采样时刻都会使用预训练的噪声特征网络进行更新。所提出的估计方案计算效率很高，因为在在线实施过程中只需要解决凸优化问题，而且更新 MHE 方案的加权矩阵不需要重新训练神经网络。我们通过对模拟化学过程的应用验证了所提方法的有效性，并对其性能进行了评估。

{"title":"Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling","authors":"Mingxue Yan, Minghao Han, Adrian Wing-Keung Law, Xunyuan Yin","doi":"10.1002/aic.18649","DOIUrl":"https://doi.org/10.1002/aic.18649","url":null,"abstract":"In this article, we propose a physics-informed learning-based Koopman modeling approach and present a Koopman-based self-tuning moving horizon estimation design for a class of nonlinear systems. Specifically, we train Koopman operators and two neural networks—the state lifting network and the noise characterization network—using both data and available physical information. The first network accounts for the nonlinear lifting functions for the Koopman model, while the second network characterizes the system noise distributions. Accordingly, a stochastic linear Koopman model is established in the lifted space to forecast the dynamic behaviors of the nonlinear system. Based on the Koopman model, a self-tuning linear moving horizon estimation (MHE) scheme is developed. The weighting matrices of the MHE design are updated using the pretrained noise characterization network at each sampling instant. The proposed estimation scheme is computationally efficient, as only convex optimization needs to be solved during online implementation, and updating the weighting matrices of the MHE scheme does not require re-training the neural networks. We verify the effectiveness and evaluate the performance of the proposed method via the application to a simulated chemical process.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"20 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142684955","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}

引用次数: 0

Optimal design of hydrogen-blended natural gas pipeline network considering separation systems 考虑分离系统的氢混天然气管网优化设计

IF 3.7 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-22 DOI: 10.1002/aic.18648

Shiya Gu, Yunhai Bai, Yachao Dong, Jian Du

Blending hydrogen into existing natural gas pipelines is considered the most feasible choice for long-distance, large-scale hydrogen transportation in the early stage of hydrogen economy development. To integrate the optimization of hydrogen-blended natural gas pipeline network and subsequent hydrogen/natural gas separation process, this article presents a mixed-integer nonlinear programming model, aiming to minimize the total annual project net cost. To tackle the computational complexity resulting from the large-scale and nonlinear nature of practical design problems, a decomposition algorithm is tailored to the proposed model. Two case studies demonstrate that compared to stepwise model, the proposed pipeline-separation integrated model offers economic benefits and practical value, incorporating separation processes and satisfying constraints of hydrogen demand, pressure and blending ratio requirements, which achieves an economically optimal design for both pipeline transportation and separation systems, and provides a viable solution for the broader application of hydrogen-blended natural gas networks.

在氢经济发展初期，将氢气掺入现有天然气管道被认为是长距离、大规模氢气运输的最可行选择。为了将氢气混合天然气管网和后续氢气/天然气分离过程的优化结合起来，本文提出了一个混合整数非线性编程模型，旨在使项目年总净成本最小化。为解决实际设计问题的大规模和非线性性质所带来的计算复杂性，本文针对所提模型提出了一种分解算法。两个案例研究表明，与分步模型相比，所提出的管道分离综合模型具有经济效益和实用价值，既包含了分离过程，又满足了氢气需求、压力和混合比要求等约束条件，实现了管道运输和分离系统的经济优化设计，为混合氢气天然气网络的广泛应用提供了可行的解决方案。

引用次数: 0

An experimental study of pressure drop characteristics under single-phase flow through packed bed microreactors 填料床微反应器中单相流压降特性的实验研究

IF 3.7 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-20 DOI: 10.1002/aic.18640

Lu Zhang, Arne Hommes, Remon Schuring, Jun Yue

Packed bed microreactors offer a promising platform for intensifying heterogeneously catalyzed reactions. To understand hydrodynamics therein, N₂ or water flow was investigated experimentally through microreactors packed with glass beads in this work, corresponding to a microreactor to particle diameter ratio (D/d) of 1.29–25.12. The porosity of a single pellet string microreactor (D/d < 1.866) agrees with the literature's theoretical equation. For microreactors with larger D/d ratios, an empirical porosity correlation is proposed to address the dense packing nature of the bed. The existing correlations are inadequate to describe the pressure drop data in microreactors within the entire D/d ratios and modified Reynolds numbers (Re_m < 291). At D/d ≥ 3, the measured pressure drop is described by the modified Ergun equation using properties of the bulk bed zone to exclude the wall effect. At D/d < 3, it can be predicted by introducing a correction term for the wall effect into the Ergun equation.

填料床微反应器为强化异构催化反应提供了一个前景广阔的平台。为了了解其中的流体力学，本研究通过实验研究了氮气或水在微反应器中的流动情况，微反应器与颗粒的直径比（D/d）为 1.29-25.12。单颗粒串微反应器的孔隙率（D/d <1.866）与文献中的理论方程一致。对于 D/d 比值较大的微反应器，建议采用经验孔隙率相关性来解决床层的致密堆积特性。在整个 D/d 比和修正雷诺数（Rem < 291）范围内，现有的相关性不足以描述微反应器中的压降数据。当 D/d ≥ 3 时，测得的压降由修正的厄尔贡方程描述，该方程使用了大量床层区域的特性来排除壁面效应。在 D/d < 3 时，可以通过在厄尔贡方程中引入壁面效应修正项来预测压降。

{"title":"An experimental study of pressure drop characteristics under single-phase flow through packed bed microreactors","authors":"Lu Zhang, Arne Hommes, Remon Schuring, Jun Yue","doi":"10.1002/aic.18640","DOIUrl":"https://doi.org/10.1002/aic.18640","url":null,"abstract":"Packed bed microreactors offer a promising platform for intensifying heterogeneously catalyzed reactions. To understand hydrodynamics therein, N2 or water flow was investigated experimentally through microreactors packed with glass beads in this work, corresponding to a microreactor to particle diameter ratio (D/d) of 1.29–25.12. The porosity of a single pellet string microreactor (D/d < 1.866) agrees with the literature's theoretical equation. For microreactors with larger D/d ratios, an empirical porosity correlation is proposed to address the dense packing nature of the bed. The existing correlations are inadequate to describe the pressure drop data in microreactors within the entire D/d ratios and modified Reynolds numbers (Rem < 291). At D/d ≥ 3, the measured pressure drop is described by the modified Ergun equation using properties of the bulk bed zone to exclude the wall effect. At D/d < 3, it can be predicted by introducing a correction term for the wall effect into the Ergun equation.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"237 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673126","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}

引用次数: 0

Anatase-reinforced PtZn@Silicalite-1 structured catalysts boosting propane dehydrogenation 无铬酸盐增强型 PtZn@Silicalite-1 结构催化剂促进丙烷脱氢

IF 3.7 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-16 DOI: 10.1002/aic.18650

Liming Xia, Bofeng Zhang, Gang Hou, Shuo Zhang, Li Wang, Guozhu Liu

Structured catalysts exhibit the advantages of high diffusion efficiency and low heat transfer resistance, which have attracted increasing attention to non-adiabatic gas–solid process. However, the metal-supported coating catalysts face the problems of weaker bond strength and severe sintering, especially under the conditions of large flow rate and high temperature. Herein, metal@Silicalite-1 structured catalysts with high adhesion and thermal stability were successfully prepared by hydroxylating the substrate with anatase. Rich surface Ti-OH significantly strengthened the adhesion stability of the zeolite coating. In propane dehydrogenation reaction, the optimized PtZn@S-1-15Ti showed a high specific activity of 49.6 mol_C3H6·mol_Pt⁻¹·s⁻¹ with propylene selectivity above 99% at 600°C. The introduction of anatase accelerated the aggregation of silicon sources and induced nucleation with growth content of zeolite increased by 3.6 times. It breaks the inherent contradiction between high loading amount and strong binding ability of coated catalysts, which broadens the avenues for industrial applications.

结构催化剂具有扩散效率高、传热阻力小等优点，在非绝热气固工艺中受到越来越多的关注。然而，金属支撑涂层催化剂面临着结合强度较弱、烧结严重等问题，尤其是在大流量和高温条件下。在此，通过对锐钛矿基底进行羟基化处理，成功制备了具有高粘附性和热稳定性的金属@硅灰石-1结构催化剂。丰富的表面 Ti-OH 显著增强了沸石涂层的粘附稳定性。在丙烷脱氢反应中，优化后的 PtZn@S-1-15Ti 在 600°C 时的比活度高达 49.6 molC3H6-molPt-1-s-1，丙烯选择性超过 99%。锐钛矿的引入加速了硅源的聚集并诱导成核，沸石的生长含量增加了 3.6 倍。它打破了涂层催化剂高负载量与强结合能力之间的固有矛盾，拓宽了工业应用的途径。

{"title":"Anatase-reinforced PtZn@Silicalite-1 structured catalysts boosting propane dehydrogenation","authors":"Liming Xia, Bofeng Zhang, Gang Hou, Shuo Zhang, Li Wang, Guozhu Liu","doi":"10.1002/aic.18650","DOIUrl":"https://doi.org/10.1002/aic.18650","url":null,"abstract":"Structured catalysts exhibit the advantages of high diffusion efficiency and low heat transfer resistance, which have attracted increasing attention to non-adiabatic gas–solid process. However, the metal-supported coating catalysts face the problems of weaker bond strength and severe sintering, especially under the conditions of large flow rate and high temperature. Herein, metal@Silicalite-1 structured catalysts with high adhesion and thermal stability were successfully prepared by hydroxylating the substrate with anatase. Rich surface Ti-OH significantly strengthened the adhesion stability of the zeolite coating. In propane dehydrogenation reaction, the optimized PtZn@S-1-15Ti showed a high specific activity of 49.6 molC3H6·molPt−1·s−1 with propylene selectivity above 99% at 600°C. The introduction of anatase accelerated the aggregation of silicon sources and induced nucleation with growth content of zeolite increased by 3.6 times. It breaks the inherent contradiction between high loading amount and strong binding ability of coated catalysts, which broadens the avenues for industrial applications.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"99 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142670928","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}

引用次数: 0

Lignin‐carbon buffered Cu sites for clean H2 evolution coupled to lignin upgrading to jet fuel precursor 木质素-碳缓冲 Cu 位点用于清洁 H2 演化，并将木质素升级为喷气燃料前体

IF 3.7 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-15 DOI: 10.1002/aic.18651

Xiaofei Wang, Jinbin Liao, Xueqing Qiu, Yaxin Deng, Xuliang Lin, Yanlin Qin

Solar‐driven photocatalysis is a promising strategy for clean hydrogen (H2) generation cooperated with selective organic synthesis. Lignin, rich in aromatic units and functional groups, serves as an ideal hole sacrificial agent and substrate, facilitating H2 evolution and yielding high‐value chemicals/fuels. To boost overall photocatalytic redox efficiency, thermal catalysis was further combined to enhance the transfer and activity of photo‐generated carriers. And a highly controllable Cu‐based catalyst was developed using technical lignin‐carbon as an electron buffer. The active‐pyrolyzed lignin‐carbon layer precisely regulated the crystal dispersion of Cu species on Cu/SiO2, simultaneously dynamically constructing active electron‐rich Cu0 and electron‐deficient Cuσ+ (1 < σ ≤ 2) sites. Excellent thermo‐photo redox performances were achieved, with an H2 evolution rate up to 1313.2 μmol·gcat−1·h−1 and a yield of 45.2% for C13–C16 aromatic dimers from lignin monomers. This study reveals the highly utilization of lignin in functional catalysts, as well as the efficient production of H2 and jet fuel precursors.

太阳能驱动的光催化技术是一种前景广阔的清洁制氢（H2）策略，可与选择性有机合成相结合。木质素富含芳香单元和官能团，可作为理想的空穴牺牲剂和底物，促进 H2 演化并产生高价值的化学品/燃料。为了提高整体光催化氧化还原效率，还进一步结合了热催化技术，以增强光生载流子的转移和活性。利用工业木质素碳作为电子缓冲器，开发出了一种高度可控的铜基催化剂。活性热解木质素碳层可精确调节 Cu/SiO2 上 Cu 物种的晶体分散，同时动态构建富电子的 Cu0 和缺电子的 Cuσ+ (1 < σ ≤ 2) 活性位点。该化合物具有优异的热光氧化还原性能，其 H2 进化速率高达 1313.2 μmol-gcat-1-h-1，木质素单体 C13-C16 芳香族二聚体的产率为 45.2%。这项研究揭示了木质素在功能催化剂中的高度利用率，以及高效生产 H2 和喷气燃料前体的可能性。

{"title":"Lignin‐carbon buffered Cu sites for clean H2 evolution coupled to lignin upgrading to jet fuel precursor","authors":"Xiaofei Wang, Jinbin Liao, Xueqing Qiu, Yaxin Deng, Xuliang Lin, Yanlin Qin","doi":"10.1002/aic.18651","DOIUrl":"https://doi.org/10.1002/aic.18651","url":null,"abstract":"Solar‐driven photocatalysis is a promising strategy for clean hydrogen (H2) generation cooperated with selective organic synthesis. Lignin, rich in aromatic units and functional groups, serves as an ideal hole sacrificial agent and substrate, facilitating H2 evolution and yielding high‐value chemicals/fuels. To boost overall photocatalytic redox efficiency, thermal catalysis was further combined to enhance the transfer and activity of photo‐generated carriers. And a highly controllable Cu‐based catalyst was developed using technical lignin‐carbon as an electron buffer. The active‐pyrolyzed lignin‐carbon layer precisely regulated the crystal dispersion of Cu species on Cu/SiO2, simultaneously dynamically constructing active electron‐rich Cu0 and electron‐deficient Cuσ+ (1 < σ ≤ 2) sites. Excellent thermo‐photo redox performances were achieved, with an H2 evolution rate up to 1313.2 μmol·gcat−1·h−1 and a yield of 45.2% for C13–C16 aromatic dimers from lignin monomers. This study reveals the highly utilization of lignin in functional catalysts, as well as the efficient production of H2 and jet fuel precursors.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"160 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637127","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}

引用次数: 0

Optimizing supramolecular interactions within metal–organic frameworks for ultra‐high purity propylene purification 优化金属有机框架内的超分子相互作用，实现超高纯度丙烯纯化

IF 3.7 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-15 DOI: 10.1002/aic.18646

Tong Li, Lu Zhang, Yong Wang, Xiaoxia Jia, Hui Chen, Yongjian Li, Qi Shi, Lin‐Bing Sun, Jinping Li, Banglin Chen, Libo Li

Purifying ultra‐high purity propylene (>99.995%) with an energy‐efficient adsorptive separation method is a promising yet challenging technology that remains unfulfilled. Instead of solely considering the effect of adsorbents on guest molecules, we propose a synergistic adsorption mechanism for the deep removal of propane and propyne, utilizing supramolecular interactions in both “host‐guest” and “guest‐guest” systems. Through modulation of the pore environment, Ni‐DMOF‐DM exhibits exceptionally high adsorption capacities for propane and propyne (171 and 197 cm3/g at ambient temperature and pressure, respectively), and unprecedented propane/propylene separation selectivity (2.74). Theoretical calculations confirm the geometric interactions of C‐H···π bonds and C‐H···O hydrogen bonds resulting from host‐guest interactions, alongside C‐H···H guest‐guest interactions within the confined pore space. Breakthrough experiments demonstrated that ultra‐high purity propylene (propane < 0.005% and propyne < 1.0 ppm) can be directly collected from ternary mixtures on Ni‐DMOF‐DM, achieving a productivity of up to 152.14 L/kg.

利用高能效吸附分离方法提纯超高纯度丙烯（99.995%）是一项前景广阔但极具挑战性的技术，目前仍未实现。我们没有单纯考虑吸附剂对客体分子的影响，而是提出了一种协同吸附机制，利用 "主-客体 "和 "客-客体 "系统中的超分子相互作用，深度去除丙烷和丙炔。通过调节孔隙环境，Ni-DMOF-DM 对丙烷和丙炔的吸附容量极高（常温常压下分别为 171 和 197 cm3/g），丙烷/丙烯分离选择性也达到了前所未有的水平（2.74）。理论计算证实，C-H--π键和C-H--O氢键的几何相互作用是由主客体相互作用以及密闭孔隙内的C-H--H主客体相互作用产生的。突破性实验证明，在 Ni-DMOF-DM 上可直接从三元混合物中收集超高纯度丙烯（丙烷含量为 0.005%，丙炔含量为 1.0 ppm），生产率高达 152.14 升/千克。

{"title":"Optimizing supramolecular interactions within metal–organic frameworks for ultra‐high purity propylene purification","authors":"Tong Li, Lu Zhang, Yong Wang, Xiaoxia Jia, Hui Chen, Yongjian Li, Qi Shi, Lin‐Bing Sun, Jinping Li, Banglin Chen, Libo Li","doi":"10.1002/aic.18646","DOIUrl":"https://doi.org/10.1002/aic.18646","url":null,"abstract":"Purifying ultra‐high purity propylene (>99.995%) with an energy‐efficient adsorptive separation method is a promising yet challenging technology that remains unfulfilled. Instead of solely considering the effect of adsorbents on guest molecules, we propose a synergistic adsorption mechanism for the deep removal of propane and propyne, utilizing supramolecular interactions in both “host‐guest” and “guest‐guest” systems. Through modulation of the pore environment, Ni‐DMOF‐DM exhibits exceptionally high adsorption capacities for propane and propyne (171 and 197 cm3/g at ambient temperature and pressure, respectively), and unprecedented propane/propylene separation selectivity (2.74). Theoretical calculations confirm the geometric interactions of C‐H···π bonds and C‐H···O hydrogen bonds resulting from host‐guest interactions, alongside C‐H···H guest‐guest interactions within the confined pore space. Breakthrough experiments demonstrated that ultra‐high purity propylene (propane < 0.005% and propyne < 1.0 ppm) can be directly collected from ternary mixtures on Ni‐DMOF‐DM, achieving a productivity of up to 152.14 L/kg.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"197 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637128","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}

引用次数: 0

Liquid holdup of gas–liquid two-phase flow in micro-packed beds reactors 微型堆积床反应器中气液两相流的液体截留量

IF 3.7 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-13 DOI: 10.1002/aic.18636

Keyi Chen, Yangcheng Lu

Liquid holdup is a crucial factor in the study of hydrodynamic behaviors in the micro-packed bed reactor (μPBR). In this work, the values of liquid holdup are studied with the weighing method with good accuracy. The packed bed is a tube made of stainless steel with a length of 20 cm and an inner diameter of 4 mm, packed with 177–250 μm or 350–500 μm microbeads. The gas and liquid flow rates vary from 5 to 20 mL/min and 0.25 to 2 mL/min, respectively. A new hypothesis of the flow regions is proposed based on the experimental results. Furthermore, a new set of empirical correlation is built with great agreement, particularly for viscous liquids, whose viscosity ranges from 0.99 to 5.98 mPa·s, showing an atypical tendency.

液体滞留是研究微填料床反应器（μPBR）流体力学行为的一个关键因素。本研究采用称重法对液体滞留值进行了精确研究。填料床是一个长 20 厘米、内径 4 毫米的不锈钢管，内填 177-250 微米或 350-500 微米的微珠。气体和液体流速分别为 5 至 20 mL/min 和 0.25 至 2 mL/min。根据实验结果，对流动区域提出了新的假设。此外，还建立了一套新的经验相关性，尤其是对于粘度介于 0.99 至 5.98 mPa-s 之间的粘性液体，其相关性非常一致，显示出一种非典型趋势。

引用次数: 0

Reverse design of molecule-process-process networks: A case study from HEN-ORC system 分子-过程-过程网络的逆向设计：HEN-ORC 系统案例研究

IF 3.7 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-12 DOI: 10.1002/aic.18643

Xiaodong Hong, Xuan Dong, Zuwei Liao, Jingyuan Sun, Jingdai Wang, Yongrong Yang

The integrated design of the heat exchanger network (HEN) and organic Rankine cycle (ORC) system with new working fluids is a complex optimization problem. It involves navigating a vast design space across working fluid molecules, ORC processes, and networks. In this article, a new two-stage reverse strategy is developed. The optimal HEN-ORC configurations and operating conditions, and the thermodynamic properties of the hypothetical working fluid are identified by an equation of state (EOS) free HEN-ORC model in the first stage. With two developed group contribution-artificial neural network thermodynamic property prediction models, working fluid molecules are screened out in the second stage from a database containing more than 430,000 hydrofluoroolefins (HFOs). The presented method is employed in two cases, where new working fluids are found. The total annual cost of Case 1 is 12%–22% lower than the literature, and the power output of Case 2 is 5%–8% higher than the literature.

热交换器网络（HEN）和采用新型工作流体的有机郎肯循环（ORC）系统的集成设计是一个复杂的优化问题。它涉及到在工作流体分子、有机郎肯循环过程和网络的巨大设计空间中进行导航。本文开发了一种新的两阶段逆向策略。在第一阶段，通过无状态方程（EOS）HEN-ORC 模型确定最佳 HEN-ORC 配置和工作条件，以及假设工作流体的热力学特性。在第二阶段，利用所开发的两个小组贡献人工神经网络热力学性质预测模型，从包含 43 万多种氢氟烯烃（HFOs）的数据库中筛选出工作流体分子。所介绍的方法在两个案例中得到了应用，在这两个案例中都发现了新的工作流体。案例 1 的年总成本比文献低 12%-22%，案例 2 的功率输出比文献高 5%-8%。

引用次数: 0

Vapor–liquid phase equilibrium prediction for mixtures of binary systems using graph neural networks 利用图神经网络预测二元系统混合物的气液相平衡

IF 3.7 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-05 DOI: 10.1002/aic.18637

Jinke Sun, Jianfei Xue, Guangyu Yang, Jingde Li, Wei Zhang

Vapor–liquid phase equilibrium (VLE) plays a crucial role in chemical process design, process equipment control, and experimental process simulation. However, experimental acquisition of VLE data is a challenging and complex task. As an alternative to experimentation, VLE data prediction offers great convenience and utility. In this article, an artificial intelligence network is proposed to predict the temperature and the vapor phase composition of binary mixtures. We constructed a graph neural network (GNN) and designed an uncertainty-aware learning and inference mechanism (UALF) in the prediction process. The model was tested on both a self-constructed dataset and a publicly available dataset. The results demonstrate that the proposed method effectively reveals the phase equilibrium properties of the target data. This work presents a novel approach for predicting vapor–liquid phase equilibrium in binary systems and proposes innovative ideas for investigating phase equilibrium mechanisms and principles.

气液相平衡（VLE）在化学工艺设计、工艺设备控制和实验工艺模拟中起着至关重要的作用。然而，通过实验获取 VLE 数据是一项具有挑战性的复杂任务。作为实验的替代方法，VLE 数据预测提供了极大的便利和实用性。本文提出了一种人工智能网络来预测二元混合物的温度和气相成分。我们构建了一个图神经网络（GNN），并在预测过程中设计了不确定性感知学习和推理机制（UALF）。该模型在自建数据集和公开数据集上进行了测试。结果表明，所提出的方法能有效揭示目标数据的相平衡特性。这项研究提出了一种预测二元体系汽液相平衡的新方法，并为研究相平衡机制和原理提出了创新思路。

引用次数: 0

Development and validation of a controlled heating apparatus for long-term MRI of 3D microfluidic tumor models 开发并验证用于三维微流控肿瘤模型长期磁共振成像的受控加热装置

IF 3.5 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal

Pub Date : 2024-11-05 DOI: 10.1002/aic.18638

Hassan Alkhadrawi, Kokeb Dese, Dhruvi M. Panchal, Alexander R. Pueschel, Kasey A. Freshwater, Amanda Stewart, Haleigh Henderson, Michael Elkins, Raj T. Dave, Hunter Wilson, John W. Bennewitz, Margaret F. Bennewitz

Conventional testing of novel contrast agents for magnetic resonance imaging (MRI) involves cell and animal studies. However, 2D cultures lack dynamic flow and in vivo MRI is limited by regulatory approval of long-term anesthesia use. Microfluidic tumor models (MTMs) offer a cost-effective, reproducible, and high throughput platform for bridging cell and animal models. Yet, MRI of microfluidic devices is challenging, due to small fluid volumes generating low sensitivity. For the first time, an MRI of MTMs was performed at low field strength (1 T) using conventional imaging equipment without microcoils. To enable longitudinal MRI, we developed (1) CHAMP-3 (controlled heating apparatus for microfluidics and portability) which heats MTMs during MRI scans and (2) an MRI-compatible temperature monitoring system. CHAMP-3 maintained chip surface temperature at ~37°C and the media inside at ~35.5°C. Enhanced T₁-weighted MRI contrast was achieved in 3D MTMs with free manganese (Mn²⁺) solutions and Mn²⁺ labeled tumor cells.

用于磁共振成像（MRI）的新型造影剂的传统测试包括细胞和动物研究。然而，二维培养缺乏动态流动性，而且体内磁共振成像受限于长期麻醉的监管审批。微流控肿瘤模型（MTMs）为细胞和动物模型提供了一个具有成本效益、可重复性和高通量的平台。然而，由于流体体积小、灵敏度低，微流控设备的磁共振成像具有挑战性。这是首次使用传统成像设备，在低场强（1 T）下对 MTMs 进行磁共振成像，而不使用微线圈。为实现纵向磁共振成像，我们开发了（1）CHAMP-3（用于微流体和便携性的受控加热设备），它能在磁共振成像扫描期间加热 MTM；（2）与磁共振成像兼容的温度监控系统。CHAMP-3 将芯片表面温度保持在约 37°C，内部介质温度保持在约 35.5°C。用游离锰（Mn2+）溶液和 Mn2+ 标记的肿瘤细胞在三维 MTM 中实现了增强的 T1 加权 MRI 对比度。

{"title":"Development and validation of a controlled heating apparatus for long-term MRI of 3D microfluidic tumor models","authors":"Hassan Alkhadrawi, Kokeb Dese, Dhruvi M. Panchal, Alexander R. Pueschel, Kasey A. Freshwater, Amanda Stewart, Haleigh Henderson, Michael Elkins, Raj T. Dave, Hunter Wilson, John W. Bennewitz, Margaret F. Bennewitz","doi":"10.1002/aic.18638","DOIUrl":"10.1002/aic.18638","url":null,"abstract":"Conventional testing of novel contrast agents for magnetic resonance imaging (MRI) involves cell and animal studies. However, 2D cultures lack dynamic flow and in vivo MRI is limited by regulatory approval of long-term anesthesia use. Microfluidic tumor models (MTMs) offer a cost-effective, reproducible, and high throughput platform for bridging cell and animal models. Yet, MRI of microfluidic devices is challenging, due to small fluid volumes generating low sensitivity. For the first time, an MRI of MTMs was performed at low field strength (1 T) using conventional imaging equipment without microcoils. To enable longitudinal MRI, we developed (1) CHAMP-3 (controlled heating apparatus for microfluidics and portability) which heats MTMs during MRI scans and (2) an MRI-compatible temperature monitoring system. CHAMP-3 maintained chip surface temperature at ~37°C and the media inside at ~35.5°C. Enhanced T1-weighted MRI contrast was achieved in 3D MTMs with free manganese (Mn2+) solutions and Mn2+ labeled tumor cells.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"70 12","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142580722","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}

引用次数: 0

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

AIChE Journal

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀