Propylene is an important building block for enormous petrochemicals including polypropylene, propylene oxide, acrylonitrile and so forth. Propane dehydrogenation (PDH) is an industrial technology for direct propylene production which has received extensive attention in recent years. With the development of dehydrogenation technologies, the efficient adsorption/activation of propane and subsequential desorption of propylene on the surfaces of heterogeneous catalysts remain scientifically challenging. This review describes recent advances in the fundamental understandings of the PDH process in terms of emerging technologies, catalyst development and new chemistry in regulating the catalyst structures and inhibiting the catalyst deactivation. The active sites, reaction pathways and deactivation mechanisms of PDH over metals and metal oxides as well as their dependent factors are also analysed and discussed, which is expected to enable efficient catalyst design for minimizing the reaction barriers and controlling the selectivity towards propylene. The challenges and perspectives of PDH over heterogeneous catalysts are also proposed for further development.

Propane dehydrogenation: catalyst development, new chemistry, and emerging technologies

On-site production of hydrogen peroxide (H2O2) using electrochemical methods could be more efficient than the current industrial process. However, due to the existence of scaling relations for the ...

Simultaneously Achieving High Activity and Selectivity toward Two-Electron O2 Electroreduction: The Power of Single-Atom Catalysts

Hexagonal boron nitride (h-BN) has emerged as a strong candidate for two-dimensional (2D) material owing to its exciting optoelectrical properties combined with mechanical robustness, thermal stability, and chemical inertness. Super-thin h-BN layers have gained significant attention from the scientific community for many applications, including nanoelectronics, photonics, biomedical, anti-corrosion, and catalysis, among others. This review provides a systematic elaboration of the structural, electrical, mechanical, optical, and thermal properties of h-BN followed by a comprehensive account of state-of-the-art synthesis strategies for 2D h-BN, including chemical exfoliation, chemical, and physical vapor deposition, and other methods that have been successfully developed in recent years. It further elaborates a wide variety of processing routes developed for doping, substitution, functionalization, and combination with other materials to form heterostructures. Based on the extraordinary properties and thermal-mechanical-chemical stability of 2D h-BN, various potential applications of these structures are described.

Structure, Properties and Applications of Two-Dimensional Hexagonal Boron Nitride.

MXenes, a bourgeoning class of 2D transition metal carbides, are of considerable interest in catalysis due to their rich surface chemistry, tunable electronic structures, and thermal stability. Here, recent conceptual advances in applying MXenes and their nanocomposites in (photo)electrocatalysis and conventional heterogeneous catalysis are highlighted. In addition, the nature of active sites in the MXene-based catalysts are discussed and the significance and challenges in the future development of catalysts using MXenes as the platforms are summarized.

2D Early Transition Metal Carbides (MXenes) for Catalysis.

Propane dehydrogenation (PDH) has great potential to meet the increasing global demand for propylene, but the widely used Pt-based catalysts usually suffer from short-term stability and unsatisfactory propylene selectivity. Herein, we develop a ligand-protected direct hydrogen reduction method for encapsulating subnanometer bimetallic Pt-Zn clusters inside silicalite-1 (S-1) zeolite. The introduction of Zn species significantly improved the stability of the Pt clusters and gave a superhigh propylene selectivity of 99.3 % with a weight hourly space velocity (WHSV) of 3.6-54 h-1 and specific activity of propylene formation of 65.5 mol C 3 H 6 gPt -1 h-1 (WHSV=108 h-1 ) at 550 °C. Moreover, no obvious deactivation was observed over PtZn4@S-1-H catalyst even after 13000 min on stream (WHSV=3.6 h-1 ), affording an extremely low deactivation constant of 0.001 h-1 , which is 200 times lower than that of the PtZn4/Al2 O3 counterpart under the same conditions. We also show that the introduction of Cs+ ions into the zeolite can improve the regeneration stability of catalysts, and the catalytic activity kept unchanged after four continuous cycles.

Subnanometer Bimetallic Platinum-Zinc Clusters in Zeolites for Propane Dehydrogenation

The exothermic oxidative dehydrogenation of propane reaction to generate propene has the potential to be a game-changing technology in the chemical industry. However, even after decades of research, selectivity to propene remains too low to be commercially attractive because of overoxidation of propene to thermodynamically favored CO 2 . Here, we report that hexagonal boron nitride and boron nitride nanotubes exhibit unique and hitherto unanticipated catalytic properties, resulting in great selectivity to olefins. As an example, at 14% propane conversion, we obtain selectivity of 79% propene and 12% ethene, another desired alkene. Based on catalytic experiments, spectroscopic insights, and ab initio modeling, we put forward a mechanistic hypothesis in which oxygen-terminated armchair boron nitride edges are proposed to be the catalytic active sites.

https://science.sciencemag.org/content/sci/early/2016/11/30/science.aaf7885.full.pdf

Selective oxidative dehydrogenation of propane to propene using boron nitride catalysts

Brønsted‐Evans‐Polanyi (BEP) relationships, i. e., a linear scaling between reaction and activation energies, lie at the core of computational design of heterogeneous catalysts. However, BEPs are not general and often require reparameterization for each class of reactions. Here we construct generalized BEPs (gBEPs), which can predict activation energies for a diverse dataset of reactions of C, O, N and H containing molecules on metal surfaces. In a first step we develop a set of descriptors based on scaling relationships that can capture the change in chemical identity of reactants during the reaction. Subsequently, we use the reaction energy, these descriptors and a single descriptor for the surface structure to parameterize machine learning based regression approaches for the prediction of activation energies. The best approach we developed shows a Mean Absolute Error (MAE) of 0.11 eV for the training set (80 % of the data set) and 0.23 eV for the test set (20 % of the data set). The methodology presented here allows to calculate activation energies within fractions of seconds on a typical personal computer and due to its generality, accuracy and simplicity in application it might prove to be useful in transition metal catalyst design.

Generalized Brønsted‐Evans‐Polanyi Relationships for Reactions on Metal Surfaces from Machine Learning

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

F. Goeltl

Author Tools

Chat about Author

Papers

Selective oxidative dehydrogenation of propane to propene using boron nitride catalysts

Generalized Brønsted‐Evans‐Polanyi Relationships for Reactions on Metal Surfaces from Machine Learning