New Organic Spintronic Memristor Mimics Human Brain Synapses for Advanced Computing

A team of international researchers has developed a new type of organic spintronic memristor that mimics the behaviour of human brain synapses. The breakthrough, published in Nature Communications in early 2026, involved scientists from the University of Leeds, the University of Münster, and the National University of Singapore. This advancement could pave the way for more efficient computing technologies and brain-inspired systems.

The memristor is built using a layered structure: a base of La₀.₆₇Sr₀.₃₃MnO₃, a middle layer of poly(vinylidene fluoride), and a top cobalt coating. Its resistance changes as fluorine atoms move within the polymer layer, driven by electrical polarisation. When positive polarisation is applied, these atoms shift towards the La₀.₆₇Sr₀.₃₃MnO₃ side, increasing resistance. Conversely, negative polarisation pulls them toward the cobalt layer, lowering resistance.

The device also exhibits a tunneling magnetoresistance (TMR) effect, which can be adjusted by the movement of fluorine atoms. This effect can even be switched between positive and negative values simply by altering electrical polarisation. Additionally, an external magnetic field can fine-tune the memristor's resistance, offering a non-electrical method of control.

Simulations further demonstrate that integrating magnetic control into artificial neural networks enhances their accuracy and stability. The research, led by Tongxin Chen, Yinyu Nie, Yafei Hao, and their colleagues, highlights the potential of this technology in future computing applications.

This new organic spintronic memristor represents a step forward in developing energy-efficient, brain-like computing systems. By combining electrical and magnetic control, the device offers precise resistance modulation, which could improve the performance of artificial neural networks. The findings open doors for further exploration in spintronics and neuromorphic engineering.