A5034333750- Advanced Memory and Neural Computing
- Silicon and Solar Cell Technologies
- Neural dynamics and brain function
- Ferroelectric and Negative Capacitance Devices
- High-Temperature Coating Behaviors
- Additive Manufacturing Materials and Processes
- Fuel Cells and Related Materials
- Advancements in Solid Oxide Fuel Cells
- Biodiesel Production and Applications
- Induction Heating and Inverter Technology
- Additive Manufacturing and 3D Printing Technologies
- 2D Materials and Applications
- Welding Techniques and Residual Stresses
- MXene and MAX Phase Materials
- Catalytic C–H Functionalization Methods
- Neural Networks and Reservoir Computing
- Electrocatalysts for Energy Conversion
- Hydrogen embrittlement and corrosion behaviors in metals
- Sulfur-Based Synthesis Techniques
- Perovskite Materials and Applications
- Silicon Carbide Semiconductor Technologies
- Copper-based nanomaterials and applications
- Metal and Thin Film Mechanics
- Metallurgical Processes and Thermodynamics
- Algal biology and biofuel production
State Key Laboratory of Polymer Physics and Chemistry
2024-2025
Huawei Technologies (China)
2025
University of Science and Technology of China
2024-2025
Changchun Institute of Applied Chemistry
2024-2025
Chinese Academy of Sciences
2024-2025
Jilin Normal University
2021-2024
Wenzhou Medical University
2023-2024
Zhejiang University of Science and Technology
2022-2024
Tianjin University of Technology
2021-2023
Zhejiang University
2022
Self-assembled monolayers (SAMs) as the hole-selective contact have achieved remarkable success in iodine-based perovskite solar cells (PSCs), while their impact on bromine-based PSCs is limited due to poor crystallization behavior and mismatched energy level alignment. Here, a highly efficient SAM of (2-(3,6-diiodo-9H-carbazol-9-yl)ethyl)phosphonic acid (I-2PACz) employed address these challenges FAPbBr
Spiking neural networks (SNNs) operating with asynchronous discrete events show higher energy efficiency sparse computation. A popular approach for implementing deep SNNs is artificial network (ANN)-SNN conversion combining both efficient training of ANNs and inference SNNs. However, the accuracy loss usually nonnegligible, especially under few time steps, which restricts applications SNN on latency-sensitive edge devices greatly. In this article, we first identify that such performance...
Spiking neural networks (SNNs) have increasingly drawn massive research attention due to biological interpretability and efficient computation. Recent achievements are devoted utilizing the surrogate gradient (SG) method avoid dilemma of non-differentiability spiking activity directly train SNNs by backpropagation. However, fixed width SG leads vanishing mismatch problems, thus limiting performance trained SNNs. In this work, we propose a novel perspective unlock limitation SG, called...
Spiking neural networks (SNNs) are increasingly applied to deep architectures. Recent works developed apply spatio-temporal backpropagation directly train SNNs. But the binary and non-differentiable properties of spike activities force trained SNNs suffer from serious gradient vanishing. In this paper, we first analyze cause vanishing problem identify that gradients mostly backpropagate along synaptic currents. Based on that, modify current equation leaky-integrate-fire neuron model propose...
The performance of inverted perovskite solar cells (PSCs) is hindered by non-radiative recombination within the and charge at cathode interface. To address these issues, we propose a technique involving oriented crystallization control interface energetic modification using conjugated thienyl-fused BODIPY homopolymer named IP1. IP1 demonstrated effectiveness in both defect passivation energy level adjustment. Simultaneously, acts as "protective shield" anchored on grain boundaries surfaces...
Surface-enhanced Raman scattering (SERS) is widely used in many fields, such as biosensors, medical diagnostics, materials science, and food security. Here, we report a low-cost, high-throughput laser-induced fractional reaction method for optical fiber SERS probes. Under laser irradiation, the local thermal effect electromagnetic interaction between nanoparticles effectively contribute to formation growth of silver on facet. Sodium dodecyl sulfate (SDS) solution with concentration 2 mM...
Spiking neural networks (SNNs) operating with asynchronous discrete events show higher energy efficiency sparse computation. A popular approach for implementing deep SNNs is ANN-SNN conversion combining both efficient training of ANNs and inference SNNs. However, the accuracy loss usually non-negligible, especially under a few time steps, which restricts applications SNN on latency-sensitive edge devices greatly. In this paper, we first identify that such performance degradation stems from...
The development of solid-state polymer electrolytes is an effective way to overcome the notorious shuttle effect polysulfides in traditional liquid lithium sulfur batteries. In this paper, cationic cyclopropenium based cross-linked was firstly prepared with one pot method, and then counter ion replaced by TFSI− anion using simple replacement. Cationic hyper-crosslinked (HP) introduced into a polyethylene oxide (PEO) matrix solution casting method prepare composite electrolyte membrane. By...
Abstract Recent work on spiking neural networks (SNNs) has focused achieving deep architectures. They commonly use backpropagation (BP) to train SNNs directly, which allows go deeper and achieve higher performance. However, the BP training procedure is computing intensive complicated by many trainable parameters. Inspired global pooling in convolutional (CNNs), we present spike probabilistic (SPGP) method based a probability function for SNNs. It aims remove difficulty of too parameters...
Semiconductor photocatalysis with the Z‐scheme mechanism is regarded as a promising approach in enhancing photocatalytic performance. A novel I‐BiOBr/C 3 N 4 heterostructure successfully synthesized via hydrothermal method. The as‐prepared catalyst exhibits superior degradation performance of various organic pollutants (tetracycline, rhodamine, and norfloxacin). Meanwhile, optimized shows an enhanced hydrogen evolution rate contrast to pristine BiOBr, I‐BiOBr, g‐C . ascribed widened visible...
In this work, strain and interfacial defect tailored electronic structures of h-BN/WSe 2 heterostructure are investigated systematically. The results show that the WSe /h-BN is a direct bandgap semiconductor (1.211[Formula: see text]eV) with type-I band alignment compared isolated h-BN monolayers. Applying in-plane can well adjust structure heterostructure, resulting in transition from indirect to at −2% for heterostructures. monotonically increases compressive strains −6% −2%, whereas...
The refining of MG-silicon (MG-Si) is closely related to the cost and purity solar-grade silicon (SoG-Si) as well semiconductor-grade (SeG-Si). Plasma arc one alternative effective route remove impurities in silicon. In this study, a 60KW transfer-arc plasma melting furnace operated in105Pa was used purify MG-Si by different kinds working gas, which composed 100%Ar, 95%Ar+5%O2, 95%Ar+5%H2, 70%Ar+30%H2 respectively. During processing, an optical spectrometer monitor changes compositions....