Adsorption and Desorption of Cu / Zn Ions with Triethylenetetramine-Functionalized Adsorbents: Kinetics Study

2012 ◽  
Vol 209-211 ◽  
pp. 1999-2004
Author(s):  
Chang Kun Liu ◽  
Xu Xin Zhao ◽  
Hong Zhu ◽  
Xiao Fang Yue
Keyword(s):  
Adsorption Kinetics ◽  
Metal Ion ◽  
Single Species ◽  
Desorption Kinetics ◽  
Adsorption And Desorption ◽  
Diffusion Controlled ◽  
Initial Stage ◽  
And Performance ◽  
Two Stages ◽  
Zn Ions

Adsorption and desorption kinetics is critical in the efficiency and performance evaluation of the adsorbents. In this study, the adsorption and desorption kinetics of copper and/or zinc ions was investigated with the polyamine-functionalized adsorbents (P-TETA). The adsorption kinetics was studied in both single species system (when only one metal ion was present) and binary species system (when both metal ions were present). The adsorption kinetics in single species system was well fitted with two models at two stages for both Cu and Zn ions, indicating that the adsorption was diffusion-controlled at the initial stage and attachment-controlled at later stage. The adsorption kinetics in binary species system revealed the stronger coordination affinity of Cu ion with P-TETA than Zn ion. The desorption kinetics was well fitted with Elovich model for Cu ion desorption only, in both single and binary species system, with a higher desorption rate in single species system.

Preparation of Triethylenetetramine-Functionalized Adsorbents for Selective Adsorption of Copper and Zinc Ions

2012 ◽  
Vol 557-559 ◽  
pp. 1078-1084
Author(s):  
Chang Kun Liu ◽  
Xu Xin Zhao ◽  
Lin Fang ◽  
Xiao Fang Yue
Keyword(s):  
Metal Ion ◽  
Selective Adsorption ◽  
Ph Effect ◽  
Single Species ◽  
Industrial Applications ◽  
Zinc Ions ◽  
Adsorption Selectivity ◽  
Copper And Zinc ◽  
Zn Ions ◽  
Cu And Zn

Selective adsorption of a target adsorbate is critical in adsorbent performance evaluation, and is of great importance in industrial applications. In this study, the selective adsorption of copper and zinc ions was investigated with the polyamine-functionalized polymeric adsorbents. The adsorbent was prepared by amination of crosslinked poly (glycidyl methacrylate) (PGMA) with triethylenetetramine (TETA). The influencing factors including reaction time and TETA content during adsorbent synthesis were investigated. The prepared adsorbents (P-TETA) was used to study the adsorption selectivity toward copper and zinc ions in single species system (when only one metal ion is present) and binary species system (when both metal ions are present). Both the pH effect and the adsorption isotherm were examined in single and binary species system. It was found that both Cu and Zn ions would be adsorbed onto P-TETA in significant amount in single species system at higher pH values. However, in binary species system with high initial concentrations for both Cu and Zn ions, Cu ions would be selectively adsorbed onto P-TETA, with insignificant amount of Zn ion adsorbed. The higher coordination constant (in Log K form) of Cu-TETA coordination than Zn-TETA coordination was identified as the major mechanism for the selective adsorption of Cu over Zn ions with P-TETA adsorbents.

Breast Cancer Detection and Classification using Traditional Computer Vision Techniques: A Comprehensive Review

2020 ◽  
Vol 16 ◽  
Author(s):  
Saliha Zahoor ◽  
Ikram Ullah Lali ◽  
Muhammad Attique Khan ◽  
Kashif Javed ◽  
Waqar Mehmood
Keyword(s):  
Breast Cancer ◽  
Computer Aided Diagnosis ◽  
Diagnose Breast Cancer ◽  
Initial Stage ◽  
Computer Aided ◽  
Diagnosis And Classification ◽  
And Performance ◽  
Tools And Techniques ◽  
Aided Diagnosis

: Breast Cancer is a common dangerous disease for women. In the world, many women died due to Breast cancer. However, in the initial stage, the diagnosis of breast cancer can save women's life. To diagnose cancer in the breast tissues there are several techniques and methods. The image processing, machine learning and deep learning methods and techniques are presented in this paper to diagnose the breast cancer. This work will be helpful to adopt better choices and reliable methods to diagnose breast cancer in an initial stage to survive the women's life. To detect the breast masses, microcalcifications, malignant cells the different techniques are used in the Computer-Aided Diagnosis (CAD) systems phases like preprocessing, segmentation, feature extraction, and classification. We have been reported a detailed analysis of different techniques or methods with their usage and performance measurement. From the reported results, it is concluded that for the survival of women’s life it is essential to improve the methods or techniques to diagnose breast cancer at an initial stage by improving the results of the Computer-Aided Diagnosis systems. Furthermore, segmentation and classification phases are challenging for researchers for the diagnosis of breast cancer accurately. Therefore, more advanced tools and techniques are still essential for the accurate diagnosis and classification of breast cancer.

Water Adsorption and Desorption Kinetics on Silica Insulation

1996 ◽  
Vol 180 (1) ◽  
pp. 276-284 ◽  
Author(s):  
A. Feng ◽  
B.J. McCoy ◽  
Z.A. Munir ◽  
D.E. Cagliostro
Keyword(s):  
Water Adsorption ◽  
Desorption Kinetics ◽  
Adsorption And Desorption

Intellectual capital and performance of listed companies: empirical evidence from Italy

2014 ◽  
Vol 18 (1) ◽  
pp. 22-35 ◽  
Author(s):  
Domenico Celenza ◽  
Fabrizio Rossi
Keyword(s):  
Explanatory Power ◽  
Value Added ◽  
Listed Companies ◽  
Cross Sectional ◽  
Content Type ◽  
Accounting Performance ◽  
And Performance ◽  
The One ◽  
Two Stages ◽  
The Relationship

Purpose – The aim of this paper is to investigate the relationship between corporate performance and Value Added Intellectual Coefficient (VAICTM) on the one hand, and the relationship between the variations in market value and the variations in VAIC on the other hand. Design/methodology/approach – Starting from the VAIC model, 23 Italian listed companies were examined with the aim of investigating the relationship between VAIC and the performance of the firms in the sample. The analysis was divided into two stages. In the first stage, eight models of linear regression were estimated to verify the presence of a positive and statistically significant relationship between M/BV and VAIC and between accounting performance indicators (ROE, ROI, ROS) and the VAIC. In the second stage, six other models were tested, considering as an independent variable the variations in VAIC and the variations in profitability indicators. Findings – The outcomes of the application stress the importance of VAIC in the explanation of the variations in MV and its role as “additional coefficient” in the analysis of equity performance. Originality/value – This methodology highlights some very interesting aspects. In particular, whereas the relationship between M/BV and VAIC and between profitability indicators (ROI, ROE, ROS) and VAIC is statistically insignificant, the subsequent analysis highlights the importance of VAIC as a variable capable of increasing the explanatory power of the regression in a cross-sectional perspective.

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