Dynamic covalent polymer networks: a molecular platform for designing functions beyond chemical recycling and self-healing
Dynamic covalent polymer networks (DCPN) have historically attracted attention for their
unique roles in chemical recycling and self-healing, which are both relevant for sustainable …
unique roles in chemical recycling and self-healing, which are both relevant for sustainable …
Recent progress in shape memory polymer: New behavior, enabling materials, and mechanistic understanding
Q Zhao, HJ Qi, T Xie - Progress in Polymer Science, 2015 - Elsevier
Shape memory polymers (SMPs), as a class of programmable stimuli-responsive shape
changing polymers, are attracting increasing attention from the standpoint of both fundamental …
changing polymers, are attracting increasing attention from the standpoint of both fundamental …
High efficiency perovskite quantum dot solar cells with charge separating heterostructure
Metal halide perovskite semiconductors possess outstanding characteristics for
optoelectronic applications including but not limited to photovoltaics. Low-dimensional and …
optoelectronic applications including but not limited to photovoltaics. Low-dimensional and …
[HTML][HTML] Mie resonance-based dielectric metamaterials
Q Zhao, J Zhou, F Zhang, D Lippens - Materials today, 2009 - Elsevier
Increasing attention on metamaterials has been paid due to their exciting physical behaviors
and potential applications. While most of such artificial material structures developed so far …
and potential applications. While most of such artificial material structures developed so far …
Dynamic covalent polymer networks: from old chemistry to modern day innovations
W Zou, J Dong, Y Luo, Q Zhao, T Xie - Advanced Materials, 2017 - Wiley Online Library
Dynamic covalent polymer networks have long been recognized. With the initial focus on
the unintended impact of dynamic covalent linkages on the viscoelasticity of commercial …
the unintended impact of dynamic covalent linkages on the viscoelasticity of commercial …
A model-driven deep neural network for single image rain removal
Deep learning (DL) methods have achieved state-of-the-art performance in the task of single
image rain removal. Most of current DL architectures, however, are still lack of sufficient …
image rain removal. Most of current DL architectures, however, are still lack of sufficient …
Kronecker-basis-representation based tensor sparsity and its applications to tensor recovery
As a promising way for analyzing data, sparse modeling has achieved great success
throughout science and engineering. It is well known that the sparsity/low-rank of a vector/matrix …
throughout science and engineering. It is well known that the sparsity/low-rank of a vector/matrix …
Identification of a novel coronavirus causing severe pneumonia in human: a descriptive study
…, JP Zhao, Y Hu, ZS Cheng, LL Liu, ZH Qian… - Chinese medical …, 2020 - mednexus.org
Background: Human infections with zoonotic coronaviruses (CoVs), including severe acute
respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV, have …
respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV, have …
MHF-Net: An interpretable deep network for multispectral and hyperspectral image fusion
Multispectral and hyperspectral image fusion (MS/HS fusion) aims to fuse a high-resolution
multispectral (HrMS) and a low-resolution hyperspectral (LrHS) images to generate a high-…
multispectral (HrMS) and a low-resolution hyperspectral (LrHS) images to generate a high-…
Status and prospects of MXene‐based lithium–sulfur batteries
Lithium–sulfur (Li–S) batteries with a theoretical energy density of 2567 Wh kg −1 are very
promising next‐generation energy storage systems, but suffer from the insulativity of sulfur …
promising next‐generation energy storage systems, but suffer from the insulativity of sulfur …