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<jats:p>Traditional materials discovery is in ‘trial-and-error’ mode, leading to the issues of low-efficiency, high-cost, and unsustainability in materials design. Meanwhile, numerous experimental and computational trials accumulate enormous quantities of data with multi-dimensionality and complexity, which might bury critical ‘structure–properties’ rules yet unfortunately not well explored. Machine learning (ML), as a burgeoning approach in materials science, may dig out the hidden structure–properties relationship from materials bigdata, therefore, has recently garnered much attention in materials science. In this review, we try to shortly summarize recent research progress in this field, following the ML paradigm: (i) data acquisition → (ii) feature engineering → (iii) algorithm → (iv) ML model → (v) model evaluation → (vi) application. In section of application, we summarize recent work by following the ‘material science tetrahedron’: (i) structure and composition → (ii) property → (iii) synthesis → (iv) characterization, in order to reveal the quantitative structure–property relationship and provide inverse design countermeasures. In addition, the concurrent challenges encompassing data quality and quantity, model interpretability and generalizability, have also been discussed. This review intends to provide a preliminary overview of ML from basic algorithms to applications.</jats:p>

<jats:p>The sintering–alloying processes of nickel (Ni), iron (Fe), and magnesium (Mg) with aluminum (Al) nanoparticles were studied by molecular dynamics simulation with the analytic embedded-atom model (AEAM) potential. Potential energy, mean heterogeneous coordination number <jats:inline-formula> <jats:tex-math> <?CDATA ${N}_{{\rm{A}}}^{{\rm{B}}}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msubsup> <mml:mi>N</mml:mi> <mml:mi mathvariant="normal">A</mml:mi> <mml:mi mathvariant="normal">B</mml:mi> </mml:msubsup> </mml:mrow> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="cpb_29_11_116601_ieqn1.gif" xlink:type="simple" /> </jats:inline-formula>, and surface atomic number <jats:italic>N</jats:italic> <jats:sub>surf–A</jats:sub> were used to monitor the sintering–reaction processes. The effects of surface segregation, heat of formation, and melting point on the sintering–alloying processes were discussed. Results revealed that sintering proceeded in two stages. First, atoms with low surface energy diffused onto the surface of atoms with high surface energy; second, metal atoms diffused with one another with increased system temperature to a threshold value. Under the same initial conditions, the sintering reaction rate of the three systems increased in the order MgAl &lt; FeAl &lt; NiAl. Depending on the initial reaction temperature, the final core–shell (FeAl and MgAl) and alloyed (NiAl and FeAl) nanoconfigurations can be observed.</jats:p>

<jats:p>We investigate the ground-state phases and spin textures of spin–orbit-coupled dipolar pseudo-spin-1/2 Bose–Einstein condensates in a rotating two-dimensional toroidal potential. The combined effects of dipole–dipole interaction (DDI), spin–orbit coupling (SOC), rotation, and interatomic interactions on the ground-state structures and topological defects of the system are analyzed systematically. For fixed SOC strength and rotation frequency, we provide a set of phase diagrams as a function of the DDI strength and the ratio between inter- and intra-species interactions. The system can show rich quantum phases including a half-quantum vortex, symmetrical (asymmetrical) phase with quantum droplets (QDs), asymmetrical segregated phase with hidden vortices (ASH phase), annular condensates with giant vortices, triangular (square) vortex lattice with QDs, and criss-cross vortex string lattice, depending on the competition between DDI and contact interaction. For given DDI strength and rotation frequency, the increase of the SOC strength leads to a structural phase transition from an ASH phase to a tetragonal vortex lattice then to a pentagonal vortex lattice and finally to a vortex necklace, which is also demonstrated by the momentum distributions. Without rotation, the interplay of DDI and SOC may result in the formation of a unique trumpet-shaped Bloch domain wall. In addition, the rotation effect is discussed. Furthermore, the system supports exotic topological excitations, such as a half-skyrmion (meron) string, triangular skyrmion lattice, skyrmion–half-skyrmion lattice, skyrmion–meron cluster, skyrmion–meron layered necklace, skyrmion–giant-skyrmion necklace lattice, and half-skyrmion–half-antiskyrmion necklace.</jats:p>

<jats:p>Na<jats:sub>0.5</jats:sub>Bi<jats:sub>0.5</jats:sub>TiO<jats:sub>3</jats:sub>–BiMnO<jats:sub>3</jats:sub> (NBT–BM) limited solid solution films were fabricated to investigate the lattice modification on the energy storage performances. The introduction of the BM solute lattice induces the NBT solvent lattices undergoing the transition from the pure phase, solid solution, solubility limit to precipitation. Correspondingly, the polarization states transfer from the macroscopic ferroelectric domains to nanodomains then to compound ferroelectric domains. The introduction of BiMnO<jats:sub>3</jats:sub> generates great lattice changes including the local lattice fluctuation and the large lattice stretching, which enhance the energy storage performances, with the energy storage efficiency being enhanced from 39.2% to 53.2% and 51.7% and the energy density being enhanced from 33.1 J/cm<jats:sup>3</jats:sup> to 76.5 J/cm<jats:sup>3</jats:sup> and 83.8 J/cm<jats:sup>3</jats:sup> for the BM components of 2% and 4%, respectively. The lattice modifications play a key role in the energy storage performances for limited solid solution films, which provides an alternative strategy for energy storage material.</jats:p>

<jats:p>In the past decades there have been many breakthroughs in low-dimensional materials, especially in two-dimensional (2D) atomically thin crystals like graphene. As structural analogues of graphene but with a sizeable band gap, monolayers of atomically thin transition metal dichalcogenides (with formula of <jats:italic>MX</jats:italic> <jats:sub>2</jats:sub>, <jats:italic>M</jats:italic> = Mo, W; <jats:italic>X</jats:italic> = S, Se, Te, etc.) have emerged as the ideal 2D prototypes for exploring fundamentals in physics such as valleytronics due to the quantum confinement effects, and for engineering a wide range of nanoelectronic, optoelectronic, and photocatalytic applications. Transition metal trioxides as promising materials with low evaporation temperature, high work function, and inertness to air have been widely used in the fabrication and modification of <jats:italic>MX</jats:italic> <jats:sub>2</jats:sub>. In this review, we reported the fabrications of one-dimensional MoS<jats:sub>2</jats:sub> wrapped MoO<jats:sub>2</jats:sub> single crystals with varied crystal direction via atmospheric pressure chemical vapor deposition method and of 2D MoO<jats:sub> <jats:italic>x</jats:italic> </jats:sub> covered Mo<jats:italic>X</jats:italic> <jats:sub>2</jats:sub> by means of exposing Mo<jats:italic>X</jats:italic> <jats:sub>2</jats:sub> to ultraviolet ozone. The prototype devices show good performances. The approaches are common to other transition metal dichalcogenides and transition metal oxides.</jats:p>

<jats:p>We train a neural network to identify impurities in the experimental images obtained by the scanning tunneling microscope (STM) measurements. The neural network is first trained with a large number of simulated data and then the trained neural network is applied to identify a set of experimental images taken at different voltages. We use the convolutional neural network to extract features from the images and also implement the attention mechanism to capture the correlations between images taken at different voltages. We note that the simulated data can capture the universal Friedel oscillation but cannot properly describe the non-universal physics short-range physics nearby an impurity, as well as noises in the experimental data. And we emphasize that the key of this approach is to properly deal with these differences between simulated data and experimental data. Here we show that even by including uncorrelated white noises in the simulated data, the performance of the neural network on experimental data can be significantly improved. To prevent the neural network from learning unphysical short-range physics, we also develop another method to evaluate the confidence of the neural network prediction on experimental data and to add this confidence measure into the loss function. We show that adding such an extra loss function can also improve the performance on experimental data. Our research can inspire future similar applications of machine learning on experimental data analysis.</jats:p>

<jats:p>Spin Hall nano oscillator (SHNO), a new type spintronic nano-device, can electrically excite and control spin waves in both nanoscale magnetic metals and insulators with low damping by the spin current due to spin Hall effect and interfacial Rashba effect. Several spin-wave modes have been excited successfully and investigated substantially in SHNOs based on dozens of different ferromagnetic/nonmagnetic (FM/NM) bilayer systems (e.g., FM = Py, [Co/Ni], Fe, CoFeB, Y<jats:sub>3</jats:sub>Fe<jats:sub>5</jats:sub>O<jats:sub>12</jats:sub>; NM = Pt, Ta, W). Here, we will review recent progress about spin-wave excitation and experimental parameters dependent dynamics in SHNOs. The nanogap SHNOs with in-plane magnetization exhibit a nonlinear self-localized bullet soliton localized at the center of the gap between the electrodes and a secondary high-frequency mode which coexists with the primary bullet mode at higher currents. While in the nanogap SHNOs with out of plane magnetization, besides both nonlinear bullet soliton and propagating spin-wave mode are achieved and controlled by varying the external magnetic field and current, the magnetic bubble skyrmion mode also can be excited at a low in-plane magnetic field. These spin-wave modes show thermal-induced mode hopping behavior at high temperature due to the coupling between the modes mediated by thermal magnon mediated scattering. Moreover, thanks to the perpendicular magnetic anisotropy induced effective field, the single coherent mode also can be achieved without applying an external magnetic field. The strong nonlinear effect of spin waves makes SHNOs easy to achieve synchronization with external microwave signals or mutual synchronization between multiple oscillators which improve the coherence and power of oscillation modes significantly. Spin waves in SHNOs with an external free magnetic layer have a wide range of applications from as a nanoscale signal source of low power consumption magnonic devices to spin-based neuromorphic computing systems in the field of artificial intelligence.</jats:p>

<jats:p>We calculate the spin and density susceptibility of Weyl fermions with repulsive S-wave interaction in ultracold gases. Weyl fermions have a linear dispersion, which is qualitatively different from the parabolic dispersion of conventional materials. We find that there are different collective modes for the different strengths of repulsive interaction by solving the poles equations of the susceptibility in the random-phase approximation. In the long-wavelength limit, the sound velocity and the energy gaps vary with the different strengths of the interaction in the zero sound mode and the gapped modes, respectively. The particle–hole continuum is obtained as well, where the imaginary part of the susceptibility is nonzero.</jats:p>

<jats:p>We investigate the modulation of magnetic anisotropy of thulium iron garnet (TmIG) films by interfaced Bi<jats:sub>2</jats:sub>Se<jats:sub>3</jats:sub> thin films. High quality epitaxial growth of Bi<jats:sub>2</jats:sub>Se<jats:sub>3</jats:sub> films has been achieved by molecular beam epitaxy on TmIG films. By the method of ferromagnetic resonance, we find that the perpendicular magnetic anisotropy (PMA) of TmIG can be greatly strengthened by the adjacent Bi<jats:sub>2</jats:sub>Se<jats:sub>3</jats:sub> layer. Moreover, the competition between topological surface states and thickness dependent bulk states of Bi<jats:sub>2</jats:sub>Se<jats:sub>3</jats:sub> gives rise to the modulation of PMA of the Bi<jats:sub>2</jats:sub>Se<jats:sub>3</jats:sub>/TmIG heterostructures. The interfacial interaction can be attributed to the enhanced exchange coupling between Fe<jats:sup>3+</jats:sup> ions of TmIG mediated by topological surface electrons of Bi<jats:sub>2</jats:sub>Se<jats:sub>3</jats:sub>.</jats:p>

<jats:p>The electronic and thermoelectric properties of alkali metal-based fluorides CsYbF<jats:sub>3</jats:sub> and RbYbF<jats:sub>3</jats:sub> are studied by using Wien2k and BoltzTraP codes. The structural and thermodynamic stability of these materials are confirmed by tolerance factor (0.94 and 0.99 for RbYbF<jats:sub>3</jats:sub> and CsYbF<jats:sub>3</jats:sub>) and negative formation energy. The optimized lattice constants and bulk moduli are consistent with the results reported in the literature. The reported band gap for RbYbF<jats:sub>3</jats:sub> is 0.86 eV which decreases to 0.83 eV by the replacement of Cs with Rb. The electrical and thermal conductivities along with Seebeck coefficients decrease with temperature rising from 0 K to 800 K. The large values of thermoelectric parameters for positive chemical potentials show that the character is dominated by electrons. The studied materials have figures of merit 0.82 and 0.81 at room temperature respectively, for RbYbF<jats:sub>3</jats:sub> and CsYbF<jats:sub>3</jats:sub> and increase with temperature rising. Therefore, the materials under study may have potential application values in thermoelectric generators and refrigerators.</jats:p>