- Hu, Yong;
- Broderick, Scott;
- Guo, Zipeng;
- N’Diaye, Alpha T;
- Bola, Jaspal S;
- Malissa, Hans;
- Li, Cheng;
- Zhang, Qiang;
- Huang, Yulong;
- Jia, Quanxi;
- Boehme, Christoph;
- Vardeny, Z Valy;
- Zhou, Chi;
- Ren, Shenqiang
The convergence of proton conduction and multiferroics is generating a compelling opportunity to achieve strong magnetoelectric coupling and magneto-ionics, offering a versatile platform to realize molecular magnetoelectrics. Here we describe machine learning coupled with additive manufacturing to accelerate the design strategy for hydrogen-bonded multiferroic macromolecules accompanied by strong proton dependence of magnetic properties. The proton switching magnetoelectricity occurs in three-dimensional molecular heterogeneous solids. It consists of a molecular magnet network as proton reservoir to modulate ferroelectric polarization, while molecular ferroelectrics charging proton transfer to reversibly manipulate magnetism. The magnetoelectric coupling induces a reversible 29% magnetization control at ferroelectric phase transition with a broad thermal hysteresis width of 160 K (192 K to 352 K), while a room-temperature reversible magnetic modulation is realized at a low electric field stimulus of 1 kV cm-1. The findings of electrostatic proton transfer provide a pathway of proton mediated magnetization control in hierarchical molecular multiferroics.