72 research outputs found
Structural and Chemical Orders in Ni64.5Zr35.5 Metallic Glass by Molecular Dynamics Simulation
The atomic structure of Ni64.5Zr35.5 metallic glass has been investigated by
molecular dynamics (MD) simulations. The calculated structure factors from the
MD glassy sample at room temperature agree well with the X-ray diffraction
(XRD) and neutron diffraction (ND) experimental data. Using the pairwise
cluster alignment and clique analysis methods, we show that there are three
types dominant short-range order (SRO) motifs around Ni atoms in the glass
sample of Ni64.5Zr35.5, i.e., Mixed-Icosahedron(ICO)-Cube, Twined-Cube and
icosahedron-like clusters. Furthermore, chemical order and medium-range order
(MRO) analysis show that the Mixed-ICO-Cube and Twined-Cube clusters exhibit
the characteristics of the crystalline B2 phase. Our simulation results suggest
that the weak glass-forming ability (GFA) of Ni64.5Zr35.5 can be attributed to
the competition between the glass forming ICO SRO and the crystalline
Mixed-ICO-Cube and Twined-Cube motifs
Blind2Sound: Self-Supervised Image Denoising without Residual Noise
Self-supervised blind denoising for Poisson-Gaussian noise remains a
challenging task. Pseudo-supervised pairs constructed from single noisy images
re-corrupt the signal and degrade the performance. The visible blindspots solve
the information loss in masked inputs. However, without explicitly noise
sensing, mean square error as an objective function cannot adjust denoising
intensities for dynamic noise levels, leading to noticeable residual noise. In
this paper, we propose Blind2Sound, a simple yet effective approach to overcome
residual noise in denoised images. The proposed adaptive re-visible loss senses
noise levels and performs personalized denoising without noise residues while
retaining the signal lossless. The theoretical analysis of intermediate medium
gradients guarantees stable training, while the Cramer Gaussian loss acts as a
regularization to facilitate the accurate perception of noise levels and
improve the performance of the denoiser. Experiments on synthetic and
real-world datasets show the superior performance of our method, especially for
single-channel images
- …