相关论文: Small-Data Machine Learning Uncovers Decoupled Con…
Structure optimization, which yields the relaxed structure (minimum-energy state), is essential for reliable materials property calculations, yet traditional ab initio approaches such as density-functional theory (DFT) are computationally…
Nonlinear optical generation from a crystalline material can reveal the symmetries of both its lattice structure and underlying ordered electronic phases and can therefore be exploited as a complementary technique to diffraction based…
Atomically thin oxides are increasingly recognized as an emerging class of 2D materials, yet their multifunctional properties have been far less investigated compared to other layered materials. Among these, gallium oxide is distinguished…
Solvent-based techniques usually involve preparing dilute blends of electron-donor and electron-acceptor materials dissolved in a volatile solvent. After some form of coating onto a substrate, the solvent evaporates. An initially…
We perform full 3D topology optimization (in which "every voxel" of the unit cell is a degree of freedom) of photonic-crystal structures in order to find optimal omnidirectional band gaps for various symmetry groups, including fcc…
We develop a method combining machine learning (ML) and density functional theory (DFT) to predict low-energy polymorphs by introducing physics-guided descriptors based on structural distortion modes. We systematically generate crystal…
Optical metasurfaces have enabled high-speed, low-power image processing within a compact footprint. However, reconfigurable imaging in such flat devices remains a critical challenge for fully harnessing their potential in practical…
Despite the rapid rise in perovskite solar cell efficiency, poor reproducibility remains a major barrier to commercialization. Film crystallization and device performance are highly sensitive to environmental factors during fabrication, yet…
The epitaxial growth of crystalline oxides on semiconductors provides a pathway to introduce new functionalities to semiconductor devices. Key to electrically coupling crystalline oxides with semiconductors to realize functional behavior is…
Modeling metasurfaces with high accuracy and efficiency is challenging because they have features smaller than the wavelength but sizes much larger than the wavelength. Full wave simulation is accurate but very slow. Popular design…
Surface oxides are associated with two-level systems (TLSs) that degrade the performance of niobium-based superconducting quantum computing devices. To address this, we introduce a predictive framework for selecting metal capping layers…
Laser powder bed fusion (L-PBF) of semi-crystalline polymers such as polyamide-12 (PA12) has found increasing use in various industrial applications. However, achieving high dimensional accuracy remains a significant challenge. Despite the…
Strongly correlated transition-metal perovskite oxides pose a fundamental challenge for electronic-structure theory and for large-scale, data-driven materials discovery. While DFT+DMFT provides a quantitatively accurate description of such…
Crystal structure optimization is fundamental to materials modeling but remains computationally expensive when performed with density-functional theory (DFT). Machine-learning (ML) approaches offer substantial acceleration, yet existing…
Electromagnetic metasurface design based on far-field constraints without the complete knowledge of the fields on both sides of the metasurface is typically a time consuming and iterative process, which relies heavily on heuristics and ad…
A Gaussian Approximation Potential (GAP) was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO2 facets through simulated annealing. Ab initio thermodynamics identifies (101) and…
The advancement in thin-film exfoliation for synthesizing oxide membranes has opened up new possibilities for creating artificially-assembled heterostructures with structurally and chemically incompatible materials. The sacrificial layer…
Optical metasurfaces empower us to manipulate the electromagnetic space and control light propagation at the nanoscale, offering a powerful tool to achieve modulation of light for information processing and storage. In this work, we propose…
Auxiliary nanostructures introduce additional flexibility into optomechanical manipulation schemes. Metamaterials and metasurfaces capable to control electromagnetic interactions at the near-field regions are especially beneficial for…
Crystal structure prediction has traditionally relied on prototype-based seeding, approaches that often bias sampling toward known low-energy basins and overlook metastable polymorphs with unconventional symmetries. Here, we introduce…