Many solid materials "remember" their past. A piece of metal may respond differently after being stretched, heated, or cooled, and memory materials rely precisely on this kind of history-dependent ...

Rain comes down steadily, painting the skies a dull grey and sending a chill breeze wafting through the windows of high-rise buildings. On the street below, water creeps out of cracks and pores. Next ...

Antiferroelectrics attract attention due to their unusual physical characteristics, chief among which is the double hysteresis loop that separates their antipolar ground state from the voltage-induced ...

Hysteresis, a phenomenon in which the state of a system depends not only on current conditions but also on its history, was first introduced in 1882 by J. A. Ewing to describe the behavior of magnetic ...

Magnetic couplings transmit high torque with no physical contact, and they disengage smoothly when load gets too high. Generally speaking, the couplings use magnetic power in three different ways; ...

For most websites, the homepage represents your brand’s first interaction with your audience on your website. As the catch-all landing page where people will be sent by default, your homepage needs to ...

Abstract: In this brief, a decomposition-learning-based output tracking approach is proposed to compensate for both hysteresis and dynamics effects on output tracking of hysteresis systems such as ...

Hysteresis is a unique behavior of ferromagnetic materials in the process of magnetization and demagnetization. This phenomenon is very important in electrical engineering, physics research and ...

An electronic comparator is a circuit that compares an analog voltage signal to a reference voltage. Its main function is to compare the magnitude of two or more input signals and output the result as ...

Today’s dc-dc converters use an enable pin to control the design conditions at which the power supply turns on and off. However, your dc-dc converter may not have this “enable hysteresis” control, or ...

Soil respiration in dryland ecosystems is challenging to model due to its complex interactions with environmental drivers. Knowledge-guided deep learning provides a much more effective means of ...

Thanks for the detailed tutorials provided here, it offers a good starting point for beginners like me to start simulation. Followed the tutorial, I've conducted several free energy perturbation tasks ...