180 research outputs found
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Effect of pressure quenching on the structures and properties of borosilicate glasses: Insights from molecular dynamics simulations
Article describes how processes including hot compression, cold compression and subsequent annealing on the structures and properties are investigated and compared. They found that applying pressure up to 10 GPa at the glass transition temperature led to permanent densifications and a dramatic increase of elastic moduli by 90%, while thermal annealing reversed the increase and applying pressure at ambient temperature did not increase the modulus
Unabridged phase diagram for single-phased FeSexTe1-x thin films
A complete phase diagram and its corresponding physical properties are
essential prerequisites to understand the underlying mechanism of iron based
superconductivity. For the structurally simplest 11 (FeSeTe) system, earlier
attempts using bulk samples have not been able to do so due to the fabrication
difficulties. Here, thin FeSexTe1-x films with the Se content covering the full
range were fabricated by using pulsed laser deposition method. Crystal
structure analysis shows that all films retain the tetragonal structure in room
temperature. Significantly, the highest superconducting transition temperature
(TC = 20 K) occurs in the newly discovered domain, 0.6 - 0.8. The single-phased
superconducting dome for the full Se doping range is the first of its kind in
iron chalcogenide superconductors. Our results present a new avenue to explore
novel physics as well as to optimize superconductors
Robust Mid-Pass Filtering Graph Convolutional Networks
Graph convolutional networks (GCNs) are currently the most promising paradigm
for dealing with graph-structure data, while recent studies have also shown
that GCNs are vulnerable to adversarial attacks. Thus developing GCN models
that are robust to such attacks become a hot research topic. However, the
structural purification learning-based or robustness constraints-based defense
GCN methods are usually designed for specific data or attacks, and introduce
additional objective that is not for classification. Extra training overhead is
also required in their design. To address these challenges, we conduct in-depth
explorations on mid-frequency signals on graphs and propose a simple yet
effective Mid-pass filter GCN (Mid-GCN). Theoretical analyses guarantee the
robustness of signals through the mid-pass filter, and we also shed light on
the properties of different frequency signals under adversarial attacks.
Extensive experiments on six benchmark graph data further verify the
effectiveness of our designed Mid-GCN in node classification accuracy compared
to state-of-the-art GCNs under various adversarial attack strategies.Comment: Accepted by WWW'2
Investigation of Electron-Phonon Coupling in Epitaxial Silicene by In-situ Raman Spectroscopy
In this letter, we report that the special coupling between Dirac fermion and
lattice vibrations, in other words, electron-phonon coupling (EPC), in silicene
layers on Ag(111) surface was probed by an in-situ Raman spectroscopy. We find
the EPC is significantly modulated due to tensile strain, which results from
the lattice mismatch between silicene and the substrate, and the charge doping
from the substrate. The special phonon modes corresponding to two-dimensional
electron gas scattering at edge sites in the silicene were identified.
Detecting relationship between EPC and Dirac fermion through the Raman
scattering will provide a direct route to investigate the exotic property in
buckled two-dimensional honeycomb materials.Comment: 15 pages, 4 figure
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