Results 101 to 110 of about 11,939,645 (246)
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Generation of Probabilistic Bits by Exploiting Orthogonal Spin Currents in Magnetic Trilayers
Fe/Ti/CoFeB trilayers generate orthogonal spin currents that drive stochastic spin–orbit‐torque switching for probabilistic‐bit operation. The switching probability is continuously controlled by the in‐plane magnetic field and drive current, enabling tunable random bit generation.
Donghyeon Han +17 more
wiley +1 more source
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
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
Speculative moves : multithreading Markov Chain Monte Carlo programs [PDF]
The increasing availability of multi-core and multi-processor architectures provides new opportunities for improving the performance of many computer simulations.
Bhalerao, Abhir +2 more
core +1 more source
Computing mean first exit times for stochastic processes using multi-level Monte Carlo [PDF]
The multi-level approach developed by Giles (2008) can be used to estimate mean first exit times for stochastic differential equations, which are of interest in finance, physics and chemical kinetics.
Roj, Mikolaj, Higham, Desmond
core +1 more source
Determination of the detection efficiency of in thiroid using Monte Carlo method
Monte Carlo Method was the base to estimate the detection efficiency of of the identiFINDER ultra detector in “thyroid” geometry. The suitability of the calibration methodology is discussed using a comparison of the results of the Direct Monte Carlo ...
Dayana Ramos Machado +3 more
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