scholarly journals G-mode magnetic force microscopy: Separating magnetic and electrostatic interactions using big data analytics

2016 ◽  
Vol 108 (19) ◽  
pp. 193103 ◽  
Author(s):  
Liam Collins ◽  
Alex Belianinov ◽  
Roger Proksch ◽  
Tingting Zuo ◽  
Yong Zhang ◽  
...  
2011 ◽  
Vol 2 ◽  
pp. 552-560 ◽  
Author(s):  
Miriam Jaafar ◽  
Oscar Iglesias-Freire ◽  
Luis Serrano-Ramón ◽  
Manuel Ricardo Ibarra ◽  
Jose Maria de Teresa ◽  
...  

The most outstanding feature of scanning force microscopy (SFM) is its capability to detect various different short and long range interactions. In particular, magnetic force microscopy (MFM) is used to characterize the domain configuration in ferromagnetic materials such as thin films grown by physical techniques or ferromagnetic nanostructures. It is a usual procedure to separate the topography and the magnetic signal by scanning at a lift distance of 25–50 nm such that the long range tip–sample interactions dominate. Nowadays, MFM is becoming a valuable technique to detect weak magnetic fields arising from low dimensional complex systems such as organic nanomagnets, superparamagnetic nanoparticles, carbon-based materials, etc. In all these cases, the magnetic nanocomponents and the substrate supporting them present quite different electronic behavior, i.e., they exhibit large surface potential differences causing heterogeneous electrostatic interaction between the tip and the sample that could be interpreted as a magnetic interaction. To distinguish clearly the origin of the tip–sample forces we propose to use a combination of Kelvin probe force microscopy (KPFM) and MFM. The KPFM technique allows us to compensate in real time the electrostatic forces between the tip and the sample by minimizing the electrostatic contribution to the frequency shift signal. This is a great challenge in samples with low magnetic moment. In this work we studied an array of Co nanostructures that exhibit high electrostatic interaction with the MFM tip. Thanks to the use of the KPFM/MFM system we were able to separate the electric and magnetic interactions between the tip and the sample.


2019 ◽  
Vol 54 (5) ◽  
pp. 20
Author(s):  
Dheeraj Kumar Pradhan

2020 ◽  
Vol 49 (5) ◽  
pp. 11-17
Author(s):  
Thomas Wrona ◽  
Pauline Reinecke

Big Data & Analytics (BDA) ist zu einer kaum hinterfragten Institution für Effizienz und Wettbewerbsvorteil von Unternehmen geworden. Zu viele prominente Beispiele, wie der Erfolg von Google oder Amazon, scheinen die Bedeutung zu bestätigen, die Daten und Algorithmen zur Erlangung von langfristigen Wettbewerbsvorteilen zukommt. Sowohl die Praxis als auch die Wissenschaft scheinen geradezu euphorisch auf den „Datenzug“ aufzuspringen. Wenn Risiken thematisiert werden, dann handelt es sich meist um ethische Fragen. Dabei wird häufig übersehen, dass die diskutierten Vorteile sich primär aus einer operativen Effizienzperspektive ergeben. Strategische Wirkungen werden allenfalls in Bezug auf Geschäftsmodellinnovationen diskutiert, deren tatsächlicher Innovationsgrad noch zu beurteilen ist. Im Folgenden soll gezeigt werden, dass durch BDA zwar Wettbewerbsvorteile erzeugt werden können, dass aber hiermit auch große strategische Risiken verbunden sind, die derzeit kaum beachtet werden.


2019 ◽  
Vol 7 (2) ◽  
pp. 273-277
Author(s):  
Ajay Kumar Bharti ◽  
Neha Verma ◽  
Deepak Kumar Verma

2017 ◽  
Vol 49 (004) ◽  
pp. 825--830
Author(s):  
A. AHMED ◽  
R.U. AMIN ◽  
M. R. ANJUM ◽  
I. ULLAH ◽  
I. S. BAJWA

Author(s):  
Way-Jam Chen ◽  
Lily Shiau ◽  
Ming-Ching Huang ◽  
Chia-Hsing Chao

Abstract In this study we have investigated the magnetic field associated with a current flowing in a circuit using Magnetic Force Microscopy (MFM). The technique is able to identify the magnetic field associated with a current flow and has potential for failure analysis.


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