Results 101 to 110 of about 20,650,460 (241)
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu +3 more
wiley +1 more source
Diverse Landscape of Tunable Magnetic, Topological, and Ferroelectric States in 2D Ti3Se3Te2
Ti3Se3Te2 emerges as a multifunctional 2D van der Waals platform. The monolayer is a dynamically stable ferromagnetic quantum anomalous Hall insulator. In bilayers, two stacking configurations yield distinct phases: AA‐stacking hosts an altermagnetic quantum spin Hall insulator, while AA′‐stacking exhibits three‐state in‐plane ferroelectricity ...
Jiangtao Yu +5 more
wiley +1 more source
The paper uses Monte Carlo algorithms applications to solve large-scale and sparse linear systems that have a significant spectrum of application in the modern field of computation science.
Adedeji Daniel GBADEBO
doaj
Q-LEAP: Millisecond Hyperdimensional Optimization for Full-Spectrum Optical Metamaterials. [PDF]
Q‐LEAP integrates physics‐informed residual machine learning with factorization‐machine‐encoded quantum annealing to design full‐spectrum optical metamaterials. It explores a 2108 design space and, in a single 2.56 ms annealing step, reaches 85.83% of the theoretical FoM limit, enabling selective 5‐8 µm emission with 3–5 and 8–14 µm suppression and ∼40×
Guo Z, Wu Y, Guo Y, Ju S.
europepmc +2 more sources
Superatom Distortion Induces Triferroicity and Spin Splitting in Two‐Dimensional Antiferromagnets
The incorporation of superatoms into a 2D square lattice induces symmetry breaking, thereby enabling concurrent coupling among magnetism, ferroelectricity, and ferroelasticity. This strategy achieves triferroic behavior—characterized by spin‐split antiferromagnetic ground states—and offers a viable pathway toward energy‐efficient spintronic devices ...
Zhen Gao +6 more
wiley +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
This work visualizes local variations in luminescence and relates them to nanoscale chemical inhomogeneities in single InxGa1−xN quantum wells. We demonstrate that the elemental segregation is only inherent to quantum wells with high indium content. Density functional theory shows this to be the result of strain‐induced phase stabilization, explaining ...
Jing‐Yang Chung +12 more
wiley +1 more source
Recently, we introduced random complex and phase screen methods as powerful tools for numerically investigating the evolution of partially coherent pulses (PCPs) in nonlinear dispersive media.
Pujuan Ma +4 more
doaj +1 more source
A novel multiscale MD/DFT framework to elucidate microenzyme adsorption and electron transfer is reported. This method reveals distinct configurations for microperoxidase‐11 on graphene and those best suited for electron transfer. Rate constants align with the limited experimental data, establishing this framework as a tool for optimizing microenzyme ...
Milan Mijajlovic +6 more
wiley +1 more source
A methodological framework for Monte Carlo probabilistic inference for diffusion processes [PDF]
The methodological framework developed and reviewed in this article concerns the unbiased Monte Carlo estimation of the transition density of a diffusion process, and the exact simulation of diffusion processes.
Papaspiliopoulos, Omiros
core

