WeChat Mini Program
Old Version Features
Activate VIP¥0.73/day
Master AI Research

[Inactivation of Cd and As by an Enterobacter Isolated from Cd and As Contaminated Farmland Soil].

Environmental Science(2023)

College of Resources and Environment

Cited 0|Views10
Abstract
A strain of Enterobacter was screened from cadmium and arsenic contaminated farmland soil and its passivation mechanism of cadmium and arsenic were explored through removing performance and characterization experiments. The results showed that the screened strain M5 was identified as Enterobacter sp. with a sulfate-reduction function, and its maximum resistance concentration was approximately 1 mmol·L-1 to cadmium and arsenic. In the simulation system, the maximum removal efficiencies of cadmium and arsenic were 94.13% and 27.26% by strain M5, respectively. The results of SEM-EDS and XRD confirmed that Cd and As were fixed to CdS and As2S3, and XPS results showed that carboxyl groups, hydroxyl groups, and amide groups on the surface of the bacteria were mainly involved in biological adsorption. These results can provide new ideas and a theoretical basis for microbial applications to soil remediations for heavy metal pollution.
More
Translated text
Key words
Soil Remediation
上传PDF
Bibtex
收藏
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

要点】:研究筛选出一种来自镉和砷污染农田土壤的肠杆菌M5,探究其对镉和砷的钝化机制,发现其通过生物吸附作用有效固定镉和砷,为重金属污染土壤的生物修复提供了新思路和理论依据。

方法】:通过去除性能和表征实验探索肠杆菌M5对镉和砷的钝化机制。

实验】:实验在模拟系统中进行,使用Enterobacter sp. M5处理镉和砷,最大去除效率分别为94.13%和27.26%,通过SEM-EDS和XRD确认镉和砷被固定为CdS和As2S3,XPS结果显示细菌表面的羧基、羟基和酰胺基主要参与生物吸附。