Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


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Academia.edu
(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Education 5.0: Using the Design Thinking Process – An Interdisciplinary View
Birgit Oberer, Alptekin Erkollar
(pages: 1-17)

Impact of Artificial Intelligence on Smart Cities
Mohammad Ilyas
(pages: 18-39)

A Multi-Disciplinary Cybernetic Approach to Pedagogic Excellence
Russell Jay Hendel
(pages: 40-63)

Data Management Sharing Plan: Fostering Effective Trans-Disciplinary Communication in Collaborative Research
Cristo Ernesto Yáñez León, James Lipuma
(pages: 64-79)

From Disunity to Synergy: Transdisciplinarity in HR Trends
Olga Bernikova, Daria Frolova
(pages: 80-92)

The Impact of Artificial Intelligence on the Future Business World
Hebah Y. AlQato
(pages: 93-104)

Wi-Fi and the Wisdom Exchange: The Role of Lived Experience in the Age of AI
Teresa H. Langness
(pages: 105-113)

Older Adult Online Learning during COVID-19 in Taiwan: Based on Teachers' Perspective
Ya-Hui Lee, Yi-Fen Wang, Hsien-Ta Cha
(pages: 114-129)

Data Visualization of Budgeting Assumptions: An Illustrative Case of Trans-disciplinary Applied Knowledge
Carol E. Cuthbert, Noel J. Pears, Karen Bradshaw
(pages: 130-149)

The Importance of Defining Cybersecurity from a Transdisciplinary Approach
Bilquis Ferdousi
(pages: 150-164)

ChatGPT, Metaverses and the Future of Transdisciplinary Communication
Jasmin (Bey) Cowin
(pages: 165-178)

Trans-Disciplinary Communication for Policy Making: A Reflective Activity Study
Cristo Leon
(pages: 179-192)

Trans-Disciplinary Communication in Collaborative Co-Design for Knowledge Sharing
James Lipuma, Cristo Leon
(pages: 193-210)

Digital Games in Education: An Interdisciplinary View
Birgit Oberer, Alptekin Erkollar
(pages: 211-230)

Disciplinary Inbreeding or Disciplinary Integration?
Nagib Callaos
(pages: 231-281)


 

Abstracts

 


ABSTRACT


Spin Transfer Torque Evaluation Based on Coupled Spin and Charge Transport: A Finite Element Method Approach

Simone Fiorentini, Johannes Ender, Siegfried Selberherr, Wolfgang Goes, Viktor Sverdlov


Emerging spin transfer torque magnetoresistive random access memories (STT MRAM) are nonvolatile and offer high speed and endurance. MRAM cells include a fixed reference magnetic layer and a free-to-switch ferromagnetic layer (FL), separated by a tunnel barrier. The FL usually consists of several sub-layers separated by nonmagnetic buffer layers. The magnetization dynamics is governed by the Landau-Lifshitz-Gilbert (LLG) equation supplemented with the corresponding torques. To accurately design MRAM cells it is necessary to evaluate the torques in composite magnetic layers, which depend on nonequilibrium spin accumulation generated by an electric current. Spin accumulation and current also depend on the magnetization. Therefore, the LLG and the spin-charge transport equations must be solved simultaneously. We apply the finite element method (FEM) to numerically solve this coupled system of partial differential equations. We follow a modular approach and use well-developed C++ FEM libraries. For the computation of the torques acting in a magnetic tunnel junction (MTJ), a magnetization-dependent resistivity of the tunnel barrier is introduced. A fully three-dimensional solution of the equations is performed to accurately model the torques acting on the magnetization. The use of a unique set of equations for the whole memory cell is an ultimate advantage of our approach.

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