A5102312697- Advanced Memory and Neural Computing
- Solar Thermal and Photovoltaic Systems
- Ferroelectric and Negative Capacitance Devices
- Neural dynamics and brain function
- Heat Transfer Mechanisms
- 2D Materials and Applications
- Transition Metal Oxide Nanomaterials
- Radical Photochemical Reactions
- Sulfur-Based Synthesis Techniques
- Thermal Radiation and Cooling Technologies
- Photovoltaic System Optimization Techniques
- Conducting polymers and applications
- Solar Radiation and Photovoltaics
- Building Energy and Comfort Optimization
- Neuroscience and Neural Engineering
- Perovskite Materials and Applications
- Advanced Photocatalysis Techniques
- Topic Modeling
- Natural Language Processing Techniques
- Photoreceptor and optogenetics research
- Nanomaterials for catalytic reactions
- Urban Heat Island Mitigation
- Molecular Junctions and Nanostructures
- Magnetic Properties and Applications
- Advanced Text Analysis Techniques
Ningbo University
2023-2025
Guangdong Polytechnic of Science and Technology
2023-2025
Materials Science & Engineering
2025
Southwest University
2024
Beijing University of Posts and Telecommunications
2024
Jimei University
2024
Tsinghua University
2021-2023
Centre National de la Recherche Scientifique
2023
Chimie ParisTech
2023
Université Paris Sciences et Lettres
2023
Hydroarylation of alkenes has been demonstrated to be an atom-economic approach access functionalized arenes from easily accessible raw materials. Herein, we report a visible light-induced photocatalytic system that enables intramolecular hydroarylation N-arylacrylamides with high 5-exo-trig selectivity through robust proton-coupled electron transfer (PCET). This mild protocol provides straightforward entry structurally valuable oxindoles and complements previously established 6-endo-trig...
Highlights Below are the highlights of this review: This paper explores embedded RRAM development, parameters, and integration tech compatible with CMOS, highlighting advantages in systems its potential impact on chip process nodes. introduces recent industry developments RRAM, featuring research from companies like Intel TSMC, showcasing significant commercial application potential. discusses RRAM’s progress beyond storage, exploring applications FPGA, MCU, CIM, Neuromorphic Computing,...
Abstract 2D material based memristors have exhibited superior performance as artificial synapses for neuromorphic computing. However, neurons note been exploited an indispensable computational element owing to the rich dynamics of neurons, which impede construction a network. A methodology is developed by introducing ionic migration and electrochemical reaction into monolayer MoS 2 single crystal neuron realized. The sophisticated electrophysiology process leaky integrate‐and‐fire (LIF)...
Physically transient electronics have attracted increasing attention recently due to their potential as the basis for building "green" and biomedical devices. In development of devices applications, however, dilemma between strictly required biodegradability device performance has brought great difficulties material selection. this paper, we introduced silk fibroin dielectric layer fabricate biodegradable resistive memory Comprising a W/silk fibroin/Mg sandwich structure, stable bipolar...
A mild transition-metal- and photosensitizer-free photoredox system based on the combination of NaI PPh3 was found to enable highly selective reduction nitroarenes. This protocol tolerates a broad range reducible functional groups such as halogen (Cl, Br, even I), aldehyde, ketone, carboxyl, cyano. Moreover, catalysis with stoichiometric provides also an alternative entry Cadogan-type reductive amination when o-nitrobiarenes were used.
Memristive devices based on two-dimensional (2D) semiconducting materials have emerged as highly promising neuromorphic due to their intrinsic atomic body and unique properties. However, the migration redistribution of anions induces built-in electric field at 2D materials/electrode interface. It inevitably leads nonlinearity saturation conductance change, which are key challenges synaptic achieve high accuracy applications. In this work, we report a vertical heterostructure formed by...
The C–S bond formation from aryl halides and thiols has been well established under various catalytic systems. In this work, user-friendly sulfinates have exploited as an efficient sulfenylating reagent in the couplings through visible-light-induced photo/nickel dual catalysis base- external reductant-free conditions. A large number of sulfide products were accessed with high selectivity tolerance functionalities.
The frequencies for load-independent output voltage in two-coil and three-coil wireless power transfer (WPT) systems have been studied. However, analysis of multiple-receiver WPT is still lacking previous studies. This letter investigates the characteristics a system against load variations determines operating frequency to achieve constant voltage. First, modeled, analytical expression root mean square derived. By substituting loaded quality factor coupling coefficient between each receiver...
Memristive devices, having a huge potential as artificial synapses for low‐power neural networks, have received tremendous attention recently. Despite great achievements in demonstration of plasticity and learning functions, little progress has been made the repeatable analog resistance states memristive which is, however, crucial achieving controllable synaptic behavior. The behavior synapse is highly desired building networks it helps reduce training epochs diminish error probability....
Metal- and additive-free photoredox cyclization of N-arylacrylamides is herein reported that provides a concise access to the formation dihydroquinolinones. In this protocol, sustainable visible light was used as energy source, organic light-emitting molecule 4CzIPN served efficient photocatalyst. This reaction system features exclusive 6-endo-trig selectivity with generally good yield range functionalized dihydroquinolinones dihydrobenzoquinolinones. Mechanistical studies reveal feasibility...
The recently unfolded ferroionic phenomena in 2D van der Waals (vdW) copper-indium-thiophosphate (CuInP2 S6 or CIPS) have received widespread interest as they allow for dynamic control of conductive switching properties, which are appealing the paradigm-shift computing. intricate couplings between ferroelectric polarization and ionic conduction vdW CIPS facilitate manipulation behaviors. However, complex interplays underlying mechanisms not yet fully explored understood. Here, by...
A nanostructural catalyst with long-term durability under harsh conditions is very important for an outstanding catalytic performance. Herein, a new ultrastable PtCo/Co3O4–SiO2 nanocatalyst was explored to improve the performance of carbon monoxide (CO) oxidation by virtue surface active lattice oxygen derived from strong metal–support interactions. Such structure can overcome issues Co3O4–SiO2 inactivation water vapor and Pt inferior activity at low temperature. Further, nanosheets endow...
Micrometer-sized water droplets have emerged as a promising platform to perform spontaneous redox reactions. Nevertheless, explorations concerning the utilization of microdroplet chemistry for material fabrication are rather limited. In current study, classic breath figure process was utilized conduct microdroplet-induced reduction and oxidation reaction achieve functionalization porous film. The conversions AgNO3 Ag, resazurin resorufin, 4-chloro-2-hydroxybenzaldehyde 4-chlorocatechol were...
The rapid evolution of multimedia technology has revolutionized human perception, paving the way for multi-view learning. However, traditional learning approaches are tailored scenarios with fixed data views, falling short emulating intricate cognitive procedures brain processing signals sequentially. Our cerebral architecture seamlessly integrates sequential through feed-forward and feedback mechanisms. In stark contrast, methods struggle to generalize effectively when confronted spanning...
Considering the importance of capturing both global conversational topics and local speaker dependencies for multimodal emotion recognition in conversations, current approaches first utilize sequence models like Transformer to extract context information, then apply Graph Neural Networks model information extraction, coupled with Contrastive Learning (GCL) enhance node representation learning. However, this sequential design introduces potential biases: extracted inevitably influences...
Developing an energy‐efficient artificial sensory system is of great significance for neuroprosthesis, neurorobotics, and intelligent human–machine interfaces. Inspired by the biological perception, achieving this goal through spatiotemporal processing viable. But some challenges, such as continuous signal coding resulting in high‐energy consumption, are yet to be solved, hindering realization human perception emulation. Herein, a perceptual simulation enabled spike‐based demonstrated, which...
Selector elements with high nonlinearity are an indispensable part in constructing density, large-scale, 3D stackable emerging nonvolatile memory and neuromorphic network. Although significant efforts have been devoted to developing novel thin-film selectors, it remains a great challenge achieving good switching performance the selectors satisfy stringent electrical criteria of diverse elements. In this work, we utilized high-defect-density chalcogenide glass (Ge2Sb2Te5) conjunction mobility...