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Improved pseudo-capacitive performance of nano-porous manganese oxide on an electrochemically derived nickel framework, Article Analytical Letters ; Volume 46, Issue 15 , October , 2013 , Pages 2372-2387 ; 00032719 (ISSN) ; Jafarzadeh, S ; Sharif University of Technology
The pseudocapacitance and morphology of electrodeposited transition metal oxides depend significantly on the morphology of the substrate. The nanoporous nickel substrate, derived from selective electro-dissolution of antimony from an electro-deposited Ni-Sb alloy, effectively promotes the electrochemical utilization of manganese oxide deposited on this structure. The large electronic and ionic conduction within the nanostructured deposit improve the energy storage performance of Mn oxide as compared to that on flat Ni substrate. In this work, the MnO2 specific capacitances of around 612 F g-1 were obtained, which was five times higher than Mn oxide deposited on a flat Ni-ribbon. A highly...
A comparative study of sequentially layer-deposited and co-deposited Co-Mn oxides as potential redox capacitors, Article Journal of Solid State Electrochemistry ; Volume 16, Issue 4 , April , 2012 , Pages 1561-1569 ; 14328488 (ISSN) ; Jafarzadeh, S ; Sharif University of Technology
Layers of cobalt and manganese oxides were co-deposited or deposited on top of each other or next to each other by potentiostatic method onto stainless steel substrate. Deposition potentials of 1 and -1 V for the anodic and cathodic depositions were employed. Specific capacitance values in the range of 38.5-78 F g -1 were found with cobalt oxide on top of manganese oxide having the lowest and manganese oxide on top of cobalt oxide having the highest capacitances. The usefulness of the electrodes was characterized by cyclic voltammetry, charge-discharge cycling, and electrochemical impedance spectroscopy in 2 M NaOH electrolyte for redox supercapacitor applications. The latter presented the...
Article PLOS ONE ; Volume 13, Issue 5 , 23 May , 2018 ; 19326203 (ISSN) ; Jafarzadeh, S ; Rabiee, H. R ; Sharif University of Technology
Public Library of Science 2018
Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-temporal behavior of users in social networks is of great importance for predicting the future behavior of users, controlling the users’ movements, and finding the latent influence network. It is observed that users have periodic patterns in their movements. Also, they are influenced by the locations that their close friends recently visited. Leveraging these two observations, we propose a probabilistic model based on a doubly stochastic point process with a periodic-decaying kernel for the time of check-ins and a...