Nature Chemical Engineering最新文献_第4页

A chemical reservoir computer 化学储存库计算机

Nature Chemical Engineering Pub Date : 2024-08-14 DOI: 10.1038/s44286-024-00109-2

Alessio Lavino

引用次数: 0

Oscillating chemical reaction networks stopped cold 摆动的化学反应网络停止了冷启动

Nature Chemical Engineering Pub Date : 2024-08-07 DOI: 10.1038/s44286-024-00092-8

Wilhelm T. S. Huck

引用次数: 0

Neural coding of temperature with a DNA-based spiking chemical neuron 利用基于 DNA 的尖峰化学神经元对温度进行神经编码

Nature Chemical Engineering Pub Date : 2024-08-07 DOI: 10.1038/s44286-024-00087-5

N. Lobato-Dauzier, A. Baccouche, G. Gines, T. Levi, Y. Rondelez, T. Fujii, S. H. Kim, N. Aubert-Kato, A. J. Genot

{"title":"Neural coding of temperature with a DNA-based spiking chemical neuron","authors":"N. Lobato-Dauzier, A. Baccouche, G. Gines, T. Levi, Y. Rondelez, T. Fujii, S. H. Kim, N. Aubert-Kato, A. J. Genot","doi":"10.1038/s44286-024-00087-5","DOIUrl":"10.1038/s44286-024-00087-5","url":null,"abstract":"Complex organisms perceive their surroundings with sensory neurons that encode physical stimuli into spikes of electrical activities. The past decades have seen a throve of computing approaches taking inspiration from neurons, including reports of DNA-based chemical neurons that mimic artificial neural networks with chemical reactions. Yet, they lack the physical sensing and temporal coding of sensory biological neurons. Here we report a thermosensory chemical neuron based on DNA and enzymes that spikes with chemical activity when exposed to cold. Surprisingly, this chemical neuron shares deep mathematical similarities with a toy model of a cold nociceptive neuron: they follow a similar bifurcation route between rest and oscillations and avoid artefacts associated with canonical bifurcations (such as irreversibility, damping or untimely spiking). We experimentally demonstrate this robustness by encoding—digitally and analogically—thermal messages into chemical waveforms. This chemical neuron could pave the way for implementing the third generation of neural network models (spiking networks) in DNA and opens the door for associative learning. Complex organisms perceive their surroundings with sensory neurons that encode physical stimuli into spikes of electrical activities. Here a thermosensory chemical neuron based on DNA and enzymes has been reported, which spikes with chemical activity when exposed to cold.","PeriodicalId":501699,"journal":{"name":"Nature Chemical Engineering","volume":"1 8","pages":"510-521"},"PeriodicalIF":0.0,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44286-024-00087-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Engineering and direct imaging of nanocube self-assembly pathways 纳米立方体自组装路径的工程设计和直接成像

Nature Chemical Engineering Pub Date : 2024-08-06 DOI: 10.1038/s44286-024-00102-9

Yaxu Zhong, Timothy C. Moore, Tobias Dwyer, Alex Butrum-Griffith, Vincent R. Allen, Jun Chen, Yi Wang, Fanrui Cheng, Sharon C. Glotzer, Xingchen Ye

{"title":"Engineering and direct imaging of nanocube self-assembly pathways","authors":"Yaxu Zhong, Timothy C. Moore, Tobias Dwyer, Alex Butrum-Griffith, Vincent R. Allen, Jun Chen, Yi Wang, Fanrui Cheng, Sharon C. Glotzer, Xingchen Ye","doi":"10.1038/s44286-024-00102-9","DOIUrl":"10.1038/s44286-024-00102-9","url":null,"abstract":"Nanoparticle self-assembly offers a scalable and versatile means to fabricate next-generation materials. The prevalence of metastable and nonequilibrium states during the assembly process makes the final structure and function directly dependent upon formation pathways. However, it remains challenging to steer the assembly pathway of a nanoparticle system toward multiple superstructures while visualizing in situ. Here we use liquid-cell transmission electron microscopy to image complete self-assembly processes of gold nanocubes, a model shape-anisotropic nanocolloidal system, into distinct superlattices. Theoretical analysis and molecular dynamics simulations indicate that the electrostatic screening of the medium dictates self-assembly pathways by its effects on the interactions between nanocubes. We leverage this understanding to demonstrate on-the-fly control of assembly behavior through rapid solvent exchange. Our joint experiment–simulation–theory investigation paves the way for elucidating the relationships among building block attributes, assembly pathways and superstructures in nanoscale assembly and opens new avenues for the bottom-up design of reconfigurable and adaptive metamaterials. Guiding the assembly pathway of a nanoparticle system toward multiple superstructures while visualizing in situ remains challenging. Here the authors combine liquid-cell transmission electron microscopy, scaling theory and molecular dynamics simulations to image and quantify self-assembly processes of gold nanocubes into distinct superlattices.","PeriodicalId":501699,"journal":{"name":"Nature Chemical Engineering","volume":"1 8","pages":"532-541"},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Turning defects in metal–organic frameworks into benefits for membrane separation 将金属有机框架的缺陷转化为膜分离的优势

Nature Chemical Engineering Pub Date : 2024-08-05 DOI: 10.1038/s44286-024-00107-4

引用次数: 0

Large-scale current collectors for regulating heat transfer and enhancing battery safety 用于调节传热和提高电池安全性的大规模电流收集器

Nature Chemical Engineering Pub Date : 2024-08-05 DOI: 10.1038/s44286-024-00103-8

Lun Li, Jinlong Yang, Rui Tan, Wei Shu, CheeTong John Low, Zixin Zhang, Yu Zhao, Cheng Li, Yajun Zhang, Xingchuan Li, Huazhang Zhang, Xin Zhao, Zongkui Kou, Yong Xiao, Francis Verpoort, Hewu Wang, Liqiang Mai, Daping He

{"title":"Large-scale current collectors for regulating heat transfer and enhancing battery safety","authors":"Lun Li, Jinlong Yang, Rui Tan, Wei Shu, CheeTong John Low, Zixin Zhang, Yu Zhao, Cheng Li, Yajun Zhang, Xingchuan Li, Huazhang Zhang, Xin Zhao, Zongkui Kou, Yong Xiao, Francis Verpoort, Hewu Wang, Liqiang Mai, Daping He","doi":"10.1038/s44286-024-00103-8","DOIUrl":"10.1038/s44286-024-00103-8","url":null,"abstract":"Thermal runaway, a major battery safety issue, is triggered when the local temperature exceeds a threshold value resulting from slower heat dissipation relative to heat generation inside the cell. However, improving internal heat transfer is challenged by the low thermal conductivity of metal current collectors (CCs) and challenges in manufacturing nonmetal CC foils at large scales. Here we report a rapid temperature-responsive nonmetallic CC that can substitute benchmark Al and Cu foils to enhance battery safety. The nonmetallic CC was fabricated through a continuous thermal pressing process to afford a highly oriented Gr foil on a hundred-meter scale. This Gr foil demonstrates a high thermal conductivity of 1,400.8 W m−1 K−1, about one order of magnitude higher than those of Al and Cu foils. Importantly, LiNi0.8Co0.1Mn0.1O2||graphite cells integrated with these temperature-responsive foils show faster heat dissipation, eliminating the local heat concentration and circumventing the fast exothermic aluminothermic and hydrogen-evolution reactions, which are critical factors causing the thermal failure propagation of lithium-ion battery packs. Understanding and preventing thermal runaway is critical to ensuring the safe and reliable operation of batteries. Here the authors demonstrate the large-scale production of a highly conductive graphene-based foil current collector to mitigate thermal runaway in high-capacity batteries.","PeriodicalId":501699,"journal":{"name":"Nature Chemical Engineering","volume":"1 8","pages":"542-551"},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning-assisted discovery of flow reactor designs 机器学习辅助发现流动反应器设计

Nature Chemical Engineering Pub Date : 2024-08-05 DOI: 10.1038/s44286-024-00099-1

Tom Savage, Nausheen Basha, Jonathan McDonough, James Krassowski, Omar Matar, Ehecatl Antonio del Rio Chanona

{"title":"Machine learning-assisted discovery of flow reactor designs","authors":"Tom Savage, Nausheen Basha, Jonathan McDonough, James Krassowski, Omar Matar, Ehecatl Antonio del Rio Chanona","doi":"10.1038/s44286-024-00099-1","DOIUrl":"10.1038/s44286-024-00099-1","url":null,"abstract":"Additive manufacturing has enabled the fabrication of advanced reactor geometries, permitting larger, more complex design spaces. Identifying promising configurations within such spaces presents a significant challenge for current approaches. Furthermore, existing parameterizations of reactor geometries are low dimensional with expensive optimization, limiting more complex solutions. To address this challenge, we have established a machine learning-assisted approach for the design of new chemical reactors, combining the application of high-dimensional parameterizations, computational fluid dynamics and multi-fidelity Bayesian optimization. We associate the development of mixing-enhancing vortical flow structures in coiled reactors with performance and used our approach to identify the key characteristics of optimal designs. By appealing to the principles of fluid dynamics, we rationalized the selection of design features that lead to experimental plug flow performance improvements of ~60% compared with conventional designs. Our results demonstrate that coupling advanced manufacturing techniques with ‘augmented intelligence’ approaches can give rise to reactor designs with enhanced performance. Identifying the optimal geometry of continuous flow reactors is a major challenge due to the large available parameter design space. Here the authors combine a machine learning-assisted methodology with computational fluid dynamics and additive manufacturing for the design of more efficient, complex coiled-tube reactors.","PeriodicalId":501699,"journal":{"name":"Nature Chemical Engineering","volume":"1 8","pages":"522-531"},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44286-024-00099-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine-learning optimization of 3D-printed flow-reactor geometry 机器学习优化 3D 打印流动反应器的几何形状

Nature Chemical Engineering Pub Date : 2024-08-05 DOI: 10.1038/s44286-024-00095-5

Jeffrey A. Bennett, Milad Abolhasani

引用次数: 0

Selective liquid-phase molecular sieving via thin metal–organic framework membranes with topological defects 通过具有拓扑缺陷的金属有机框架薄膜实现选择性液相分子筛分

Nature Chemical Engineering Pub Date : 2024-07-25 DOI: 10.1038/s44286-024-00096-4

Xiansong Shi, He Li, Ting Chen, Yidan Duan, Dongchen Shi, Chengjun Kang, Zhaoqiang Zhang, Dan Zhao

{"title":"Selective liquid-phase molecular sieving via thin metal–organic framework membranes with topological defects","authors":"Xiansong Shi, He Li, Ting Chen, Yidan Duan, Dongchen Shi, Chengjun Kang, Zhaoqiang Zhang, Dan Zhao","doi":"10.1038/s44286-024-00096-4","DOIUrl":"10.1038/s44286-024-00096-4","url":null,"abstract":"Separating fine and similarly sized targets in liquids is a crucial but challenging task. Although current membranes have the potential to be sustainable and energy-efficient options, their molecular selectivity and durability remain limited. Here we report robust and accurate molecular-sieving membranes created through the topological design of a Zr-based metal–organic framework, namely UiO-66, for use in durable liquid-phase separations. Our findings reveal that crystallizing UiO-66 using a bimetallic method yields distinctive reo-topology frameworks with periodic missing-cluster defects. We crystallize reo-UiO-66 into thin polycrystalline membranes that exhibit improved and robust performance, lasting for over 1,500 h. The modified Ferry transport model provides a quantitative description of solute rejection from the polycrystalline membrane. Multiple molecular-sieving experiments recognize excellent membrane selectivity to accurately discriminate fine complex mixtures with molecular weights below 350 g mol−1. In addition, our membrane demonstrates promise in purifying and recovering high-value pharmaceuticals and catalysts. This work paves the way for developing polycrystalline membrane technology for the sustainable separation of chemical mixtures in liquids. Efficiently separating high-value targets with small structural differences in liquids is important to the chemical industry. Here the authors develop a metal–organic framework-based membrane with engineered topologic defects for accurate and prolonged sieving of species with molecular weights below 350 g mol−1.","PeriodicalId":501699,"journal":{"name":"Nature Chemical Engineering","volume":"1 7","pages":"483-493"},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141805742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How green is the grass on the other side? 另一边的草地有多绿？

Nature Chemical Engineering Pub Date : 2024-07-25 DOI: 10.1038/s44286-024-00106-5

引用次数: 0