Machine learning assisted screening of metal binary alloys for anode materials

In the dynamic and rapidly advancing battery field, alloy anode materials are a focal point due to their superior electrochemical performance. Traditional screening methods are inefficient and time-consuming. Our research introduces a machine learning-assisted strategy to expedite the discovery and optimization of these materials. We compiled a vast dataset from the MP and AFLOW databases, encompassing tens of thousands of alloy compositions and properties. Utilizing a CGCNN, we accurately predicted the potential and specific capacity of alloy anodes, validated against experimental data. This approach identified approximately 120 low potential and high specific capacity alloy anodes suitable for various battery systems including Li, Na, K, Zn, Mg, Ca, and Al-based. Our method not only streamlines the screening of battery anode materials but also propels the advancement of battery material research and innovation in energy storage technology.41 pages include SI, 5 figures in mai

Harness of room-temperature polar skyrmion bag in oxide superlattice.

Skyrmion bag is a higher-order skyrmion-based topological structure that can be used to reduce the risk of data loss in memory devices. It consists of an outer skyrmion wall and several inner skyrmions with opposite polarities. While skyrmion bags have been observed in ferromagnetic materials and liquid crystals, creating a polar skyrmion bag has proven challenging. Herein, we report the creation, evolution, and destruction of a polar skyrmion bag in a ferroelectric/dielectric oxide superlattice. The creation of a polar skyrmion bag is facilitated by applying an electric field pulse through a charged tip, which could be eliminated by changing the field direction. We also discover that the topological charge inside a polar skyrmion bag can be manipulated in situ by adjusting the magnitude of the applied potential. Through combined experimental observations and theoretical calculations, we have gained new insights into multipolar boundaries and identified promising prospects for future high-density, scalable, robust memory and low-loss nanoelectronics devices

Order-disorder transitions in a polar vortex lattice

Order-disorder transitions are widely explored in various vortex structures in condensed matter physics, that is, in the type-II superconductors and Bose-Einstein condensates. In this study, the ordering of the polar vortex phase in [Pb(Zr0.4Ti0.6)O3]n/(SrTiO3)n (PZT/STO) superlattices is investigated through phase-field simulations. With a large tensile substrate strain, an antiorder vortex state (where the rotation direction of the vortex arrays in the neighboring ferroelectric layers are flipped) is discovered for short-period PZT/STO superlattice. The driving force is the induced in-plane polarization in the STO layers due to the large tensile epitaxial strain. Increasing the periodicity leads to antiorder to disorder transition, resulting from the high energy of the head-to-head/tail-to-tail domain structure in the STO layer. On the other hand, when the periodicity is kept constant in short-period superlattices, the order-disorder-antiorder transition can be engineered by mediating the substrate strain, due to the competition between the induction of out-of-plane (due to interfacial depolarization effect) and in-plane (due to strain) polarization in the STO layer. The 3D ordering of such polar vortices is still a topic of significant current interest and it is envisioned that this study will spur further interest toward the understanding of order?disorder transitions in ferroelectric topological structuresThis work was supported by the Joint Funds of the National Natural Science Foundation of China under grant U21A2067 (Y.W.), and the Fundamental Research Funds for the Central Universities (No. 2021FZZX003-02-03, Z.H.). Z.H. also gratefully acknowledge a start-up grant from Zhejiang University. The financial support from Grant PGC2018-096955-B-C41 funded by MCIN/AEI/10.13039/501100011033 is acknowledged (J.J., P.G.-F., F.G.-O.). F.G.-O. acknowledge financial support from Grant No. FPU18/04661 funded by Spanish Ministry of Universities. The phase-field simulation was performed on the MoFang III cluster on Shanghai Supercomputing Center (SSC). S. D. is currently at Materials Research Centre, Indian Institute of Science, Bangalore, India