WeChat Mini Program
Old Version Features

Under-Coordinated Selenide Enriched Amorphous Cobalt Selenide Prepared under Ambient Conditions for Highly Efficient Immobilization of Gaseous Elemental Mercury

CHEMICAL ENGINEERING JOURNAL(2023)

Cent South Univ

Cited 11|Views16
Abstract
The limited adsorption capacity of commercialized sorbents towards elemental mercury (Hg-0) remains a major challenge facing their extensive applications under the regulation of the Minamata Convention. Metal selenides were recently found to be promising alternatives to commercialized sorbents for capturing Hg-0 from industrial flue gas due to the high affinity between Hg-0 and selenide. In metal selenides, under-coordinated selenide sites play critical roles in oxidation and subsequent immobilization of Hg-0, while there is still no simple way to increase the abundance of under-coordinated selenide in metal selenides under ambient conditions. In this work, an effective and facile precipitation pathway was proposed to prepare amorphous cobalt selenide (a-CoSe2) with under-coordinated selenide enriched surface under ambient conditions. The a-CoSe2 as synthesized achieved outstanding Hg-0 uptake capacity and adsorption rate (534.2 mg g(-1) and 483.1 mu g g(-1) min(-1)), far surpassing those of crystalline cobalt selenide (c-CoSe2) by magnitudes. The characteristic results demonstrated that the under-coordinated selenide enriched nature of a-CoSe2 is the principal reason causing the significant performance improvement, which is fully in line with our hypothesis and purpose. This work not only proposes a potential sorbent for efficient Hg-0 sequestration from industrial flue gas but also inspires the further development of synthesis strategies for amorphous materials.
More
Translated text
Key words
Elemental mercury,Cobalt selenide,Amorphization,Under-coordinated sites,Flue gas
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined