Youfa Liu
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View article: Tailoring Crystalline States of Alloy Coating for High Current Density and Large Areal Capacity of Zn
Tailoring Crystalline States of Alloy Coating for High Current Density and Large Areal Capacity of Zn Open
Due to issues of hydrogen evolution, corrosion, and uncontrolled deposition behaviors at the Zn anode, the practical implementation of Zn‐ion batteries has faced significant obstacles. Very limited attention is directed toward various allo…
View article: Recurrently gellable and thermochromic inorganic hydrogel thermogalvanic cells
Recurrently gellable and thermochromic inorganic hydrogel thermogalvanic cells Open
Thermogalvanic cells (TGCs) draw great attention in the field of heat to electricity conversion, but TGCs were only in the form of liquid or organic gel. Here, we report an all-inorganic hydrogel TGC via simply mixing and stirring two inor…
View article: Non‐Epitaxial Electrodeposition of Overall 99 % (002) Plane Achieves Extreme and Direct Utilization of 95 % Zn Anode and By‐Product as Cathode
Non‐Epitaxial Electrodeposition of Overall 99 % (002) Plane Achieves Extreme and Direct Utilization of 95 % Zn Anode and By‐Product as Cathode Open
Zn anode protection in Zn‐ion batteries (ZIBs) face great challenges of high Zn utilization rate (i.e., depth of discharge, DOD) and high current density due to the large difficulty in obtaining an extreme overall RTC (relative texture coe…
View article: Exploration and Practice of P2G Teaching Mode of Big Data Architecture and Mode Experiment Based on Clustering Algorithm
Exploration and Practice of P2G Teaching Mode of Big Data Architecture and Mode Experiment Based on Clustering Algorithm Open
According to the characteristics and teaching objectives of the Experimental Course of Big Data Architecture and Mode, a P2G mode teaching mode is proposed and practiced after analyzing and summarizing the problem in the teaching process.P…
View article: Rebalanced Zero-shot Learning
Rebalanced Zero-shot Learning Open
Zero-shot learning (ZSL) aims to identify unseen classes with zero samples during training. Broadly speaking, present ZSL methods usually adopt class-level semantic labels and compare them with instance-level semantic predictions to infer …
View article: Real Quadratic-Form-Based Graph Pooling for Graph Neural Networks
Real Quadratic-Form-Based Graph Pooling for Graph Neural Networks Open
Graph neural networks (GNNs) have developed rapidly in recent years because they can work over non-Euclidean data and possess promising prediction power in many real-word applications. The graph classification problem is one of the central…
View article: Schatten Graph Neural Networks
Schatten Graph Neural Networks Open
Graph Neural Networks (GNNs) have been intensively studied in recent years because of their promising performance over graph-structural data and have provided assistance in many fields. Recalling recent works on graph neural networks, we f…
View article: Energy Levels Based Graph Neural Networks for Heterophily
Energy Levels Based Graph Neural Networks for Heterophily Open
The representation power of graph neural networks (GNNs) under heterophily has drawn much attention recently, in which some connected nodes do not have common labels or similar features. Previous approaches typically incorporate high-order…
View article: Green synthesis of air-stable tellurium nanowires <i>via</i> biomolecule-assisted hydrothermal for thermoelectrics
Green synthesis of air-stable tellurium nanowires <i>via</i> biomolecule-assisted hydrothermal for thermoelectrics Open
Air-stable Te NWs with good electrical conductivity and the Seebeck effect have been obtained by a green method.