arXiv subjects

Baoan Sun

Publications and source records attributed to Baoan Sun.

4 recordsLinked to original sources

arXiv2025

Combinatorial Development of Amorphous/nanocrystalline Biphase Soft Magnetic Alloys with Silicon-steel like Saturated Magnetic Induction

Maximization saturation magnetic induction (Bs) of soft magnetic alloys is essential for the high power-density electromagnetic devices. However, identifying the alloy compositions with high Bs often replies on the lab-intensive melt casting method and a high-throughput characterization on magnetic properties remains challenging. Here, we develop a new combinatorial method for fast screening alloys with optimal soft magnetic properties based on the high-throughput MOKE screening method. Based on the combinatorial method, we found that the alloys with a combination of high Bs and low coercivity (Hc) tend to have a feature of amorphous-nanocrystalline biphase microstructure. We also identified an amorphous/nanocrystalline alloy film with the composition the Fe68.09Co17.02B10.9Si4, exhibiting an ultra-high Bs up to 2.02 T that surpasses all amorphous/nanocrystalline alloys reported so far and is comparable to that of silicon steels, together with a high resistivity of 882 {\mu}{\Omega} {\dot} cm, about 17 times of silicon steels. Our high-throughput magnetic screening method provides a paradigm for understanding the relationship between microstructure and magnetic properties and the development of the next-generation soft magnetic materials.

cond-mat.mtrl-sci↗

arXiv2025

Discovering High-Strength Alloys via Physics-Transfer Learning

Predicting the strength of materials requires considering various length and time scales, striking a balance between accuracy and efficiency. Peierls stress measures material strength by evaluating dislocation resistance to plastic flow, reliant on elastic lattice responses and crystal slip energy landscape. Computational challenges due to the non-local and non-equilibrium nature of dislocations prohibit Peierls stress evaluation from state-of-the-art material databases. We propose a data-driven framework that leverages neural networks trained on force field simulations to understand crystal plasticity physics, predicting Peierls stress from material parameters derived via density functional theory computations, which are otherwise computationally intensive for direct dislocation modeling. This physics transfer approach successfully screen the strength of metallic alloys from a limited number of single-point calculations with chemical accuracy. Guided by these predictions, we fabricate high-strength binary alloys previously unexplored, utilizing high-throughput ion beam deposition techniques. The framework extends to problems facing the accuracy-performance dilemma in general by harnessing the hierarchy of physics of multiscale models in materials sciences.

cond-mat.mtrl-sci↗

arXiv2022

Atomic-scale Deformation Process of Glasses Unveiled by Stress-induced Structural Anisotropy

Experimentally resolving atomic-scale structural changes of a deformed glass remains challenging owing to the disordered nature of glass structure. Here, we show that the structural anisotropy emerges as a general hallmark for different types of glasses (metallic glasses, oxide glass, amorphous selenium, and polymer glass) after thermo-mechanical deformation, and it is highly correlates with local nonaffine atomic displacements detected by the high-energy X-ray diffraction technique. By analyzing the anisotropic pair density function, we unveil the atomic-level mechanism responsible for the plastic flow, which notably differs between metallic glasses and covalent glasses. The structural rearrangements in metallic glasses are mediated through cutting and formation of atomic bonds, which occurs in some localized inelastic regions embedded in elastic matrix, whereas that of covalent glasses is mediated through the rotation of atomic bonds or chains without bond length change, which occurs in a less localized manner.

cond-mat.mtrl-sci↗

arXiv2020

"Butterfly Effect" in Shear-Banding Mediated Plasticity of Metallic Glasses

Metallic glasses response to the mechanical stress in a complex and inhomogeneous manner with plastic strain highly localized into nanoscale shear bands. Contrary to the well-defined deformation mechanism in crystalline solids, understanding the mechanical response mechanism and its intrinsic correlation with the macroscopical plasticity in metallic glasses remains long-standing issues. Through a combination of experimental and theoretical analysis, we showed that the shear banding process in metallic glasses exhibits complex chaotic dynamics, which manifests as the existence of a torus destroyed phase diagram, a positive Lyapunov exponent and a fractional Lyapunov dimension. We also demonstrated that the experimentally observed large plasticity fluctuation of metallic glasses tested at the same conditions can be interpreted from the chaotic shear-band dynamics, which could leads to an uncertainty on the appearance of the critical condition for runaway shear banding. Physically, the chaotic shear-band dynamics arises from the interplay between structural disordering and temperature rise within the shear band. By tuning the deformation parameters, the chaotic dynamics can be transformed to a periodic orbit state corresponding to a smaller plasticity fluctuation in metallic glasses. Our results suggest that the plastic flow of metallic glasses is a complex dynamic process, which is highly sensitive to initial conditions and reminiscent of the "butterfly effect" as observed in many complex dynamic systems.

cond-mat.mtrl-sci↗