Drugs for the Musculo-Skeletal System (M)

Kutscher, Bernhard

doi:10.1002/14356007.a03_033.pub2

Cited by 3 publications

(4 citation statements)

References 78 publications

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“…Xylene isomers, including para -xylene ( p -xylene), meta -xylene ( m -xylene), and ortho -xylene ( o -xylene), are important chemical feedstock in the petrochemical and pharmaceutical industries. − Although the shape-selective catalysis with zeolite is recognized as an efficient way to obtain the desired xylene, − the product is usually of low purity. Therefore, the separation of these isomers, a prerequisite for most industrial applications, is recognized as an important but challenging task.…”

Section: Introductionmentioning

confidence: 99%

Exceptionally Fast Separation of Xylene Isomers with Zeolitic Nanotube Array Membranes

Shen,

Xue,

Qiu

et al. 2024

J. Am. Chem. Soc.

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The separation of xylene isomers is of vital importance in chemical industry but remains challenging due to their similar structure and overlapping physiochemical properties. Membrane-based separations using the zeolite MFI, graphene oxide, and metal−organic frameworks have been intensively studied for this application, but the performance is limited by the well-known rule that the filtrate permeance scales inversely with the membrane thickness. We propose a novel membrane design that is capable of breaking this rule, based on an array of recently discovered zeolite nanotubes. Each zeolite nanotube possesses a 3.6-nm-wide central channel, connecting to dense, uniform 0.8-nm-wide holes on its wall that act as selective pores. Comprehensive molecular dynamics simulations show that this membrane exhibits permeance exceeding current state-of-the-art membranes by at least an order of magnitude while simultaneously maintaining an acceptable selectivity. In particular, a thicker membrane featuring longer zeolite nanotubes exhibits a higher permeance due to the presence of more selective pores. The proposed membrane design is expected to be broadly applied to other gas separations and even desalination as long as zeolitic nanotubes with customized pores are available.

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Section: Introductionmentioning

confidence: 99%

Exceptionally Fast Separation of Xylene Isomers with Zeolitic Nanotube Array Membranes

Shen,

Xue,

Qiu

et al. 2024

J. Am. Chem. Soc.

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“…Specifically, the nucleation behavior of cyclohexanolan organic sublimation agentduring cooling and solidification on bare Si and patterned Si substrates is analyzed; the bare Si substrate was a Si substrate with a flat surface, whereas the patterned Si substrate had nanostructures on its surface. Cyclohexanol has a crystal form known as glass crystal and is an organic compound with a melting point of 23 °C and vapor pressure of 0.13 kPa (at 20 °C) in the solid phase. , The freezing point of cyclohexanol is close to room temperature, making it an easier sublimation agent to handle than ice in semiconductor processes.…”

Section: Introductionmentioning

confidence: 99%

“…Cyclohexanol has a crystal form known as glass crystal 28 and is an organic compound with a melting point of 23 °C and vapor pressure of 0.13 kPa (at 20 °C) in the solid phase. 29 , 30 The freezing point of cyclohexanol is close to room temperature, making it an easier sublimation agent to handle than ice in semiconductor processes.…”

Section: Introductionmentioning

confidence: 99%

New Formulas for Evaluation of Cyclohexanol Solidification on Substrates with Surface Nanostructures

Hanawa,

Zhang,

Sasmito

et al. 2024

ACS Omega

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In semiconductor manufacturing, the sublimation drying process is crucial but poorly understood�particularly regarding the solidification of agents such as cyclohexanol on Si substrates. This knowledge gap results in inconsistent film properties and risks such as structural collapse. To address this critical gap in knowledge, the present study focused on an in-depth examination of the nucleation behavior exhibited by cyclohexanol during its cooling and solidification on Si substrates. Using a digital camera (GoPro10), the solidification process in experiments was recorded for a range of cooling rates and using substrates with distinct surface patterns. To evaluate temporal changes in crystal nucleation, video images were visually checked, and the temporal changes in the number of nuclei were examined. For a more quantitative analysis, the least-squares method was successfully employed to correlate mathematical equations to time-dependent nucleation data. Interestingly, the outcomes revealed significant correlations between the nucleation rate, cooling rate, and substrate pattern. In summary, this research offers a robust experimental framework for understanding the complex solidification behavior of cyclohexanol on Si substrates. The study contributes both qualitative and quantitative analyses, enriching our understanding of the variables that govern the solidification process, which has significant implications for enhancing the overall reliability and efficiency of semiconductor manufacturing.

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“…However, this method is no longer competitive, and EO production relies primarily on direct oxidation. This process involves the catalytic oxidation of ethylene with oxygen using a silver-based catalyst to form EO. , …”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Energy Mapping of Chlorine Effects in an Epoxidation Reaction Catalyzed by a Silver–Copper Oxide Nanocatalyst

Urbiztondo Castro,

Rodrigo,

Hamad

2023

J. Phys. Chem. C

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Deep learning is poised to revolutionize the field of heterogeneous catalysis. In this study, we harness its potential to predict energy values across a catalyst surface, a task traditionally relegated to computationally intensive density functional theory (DFT). We propose a novel deep learning approach to construct an exhaustive energy map, pinpointing the optimal locations for adsorbed chlorine in the ethylene epoxidation reaction. Leveraging the power of trained neural networks, we achieved a staggering reduction in computational time, cutting down the duration of energy calculations by over 50 million times compared with traditional methods. This groundbreaking integration of artificial intelligence not only accelerates this process but also effectively surpasses the limitations of conventional methods. By highlighting the transformative potential of deep learning in catalysis, this research paves the way for future studies and stands to revolutionize efficiency in the chemical industry, fostering an urgent need to delve deeper into the implications and applications of this technology.

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Drugs for the Musculo-Skeletal System (M)

Cited by 3 publications

References 78 publications

Exceptionally Fast Separation of Xylene Isomers with Zeolitic Nanotube Array Membranes

Exceptionally Fast Separation of Xylene Isomers with Zeolitic Nanotube Array Membranes

New Formulas for Evaluation of Cyclohexanol Solidification on Substrates with Surface Nanostructures

Deep Learning-Based Energy Mapping of Chlorine Effects in an Epoxidation Reaction Catalyzed by a Silver–Copper Oxide Nanocatalyst

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