A5100717543- Covalent Organic Framework Applications
- Conducting polymers and applications
- Supercapacitor Materials and Fabrication
- Metal and Thin Film Mechanics
- Crystallization and Solubility Studies
- Ionic liquids properties and applications
- Carbon dioxide utilization in catalysis
- X-ray Diffraction in Crystallography
- Carbon Dioxide Capture Technologies
- Advancements in Battery Materials
- Phase Equilibria and Thermodynamics
- Advanced Polymer Synthesis and Characterization
- Diamond and Carbon-based Materials Research
- Advanced Sensor and Energy Harvesting Materials
- Liquid Crystal Research Advancements
- Analytical Chemistry and Chromatography
- Advanced Photocatalysis Techniques
- Carbon Nanotubes in Composites
- Chemical Synthesis and Reactions
- Enhanced Oil Recovery Techniques
- Nanocluster Synthesis and Applications
- Cardiac Health and Mental Health
- Nanofabrication and Lithography Techniques
- Optical Coatings and Gratings
- Vascular Procedures and Complications
Nanjing University of Aeronautics and Astronautics
2022-2025
Xi'an University of Science and Technology
2021-2024
Shandong University
2024
Northeast Electric Power University
2022-2024
Xi'an Jiaotong University
2024
China University of Petroleum, East China
2023-2024
China University of Mining and Technology
2022-2023
Xinjiang University
2022
Tongji University
2022
Electric Power University
2022
MXene-reinforced composite coatings have recently shown promise for metal anticorrosion due to their large aspect ratio and antipermeability; however, the challenges of poor dispersion, oxidation, sedimentation MXene nanofillers in a resin matrix that are often encountered existing curing methods greatly limited practical applications. Herein, we reported an efficient, ambient, solvent-free electron beam (EB) technology fabricate PDMS@MXene filled acrylate-polyurethane (APU) 2024 Al alloy,...
Nowadays, coal gasification fine slag (CGFS) generated during the process has become difficult to treat bulk solid waste. CGFS contains high levels of residual carbon, which is recycle due tight binding minerals with residual. In our study, carbon source active (P-AC) was obtained by molten-caustic leaching (MCL) method, in alkaline solution can be further used as a ceramic precursor. Subsequently, KOH activation method prepare activated (AC) electrode materials. The deashing conditions and...
Highly porous multi-responsive shape memory foams have unique advantages in designing 3D materials with lightweight for varied applications. Herein, a facile and efficient approach to fabricating thermo-, electro-, photo-responsive composite foam is demonstrated. A specific multi-step carbonization protocol adopted transforming commercial melamine sponge (MS) highly carbon (CF) robust elastic resilience, electrothermal/photothermal conversions, super-amphiphilicity. It novel proposal CF take...
The rapid success of Large Language Models (LLMs) has unlocked vast potential for AI applications in privacy-sensitive domains. However, the traditional centralized training LLMs poses significant challenges due to privacy concerns regarding collecting sensitive data from diverse sources. This paper offers a promising and privacy-enhancing solution LLMs: collaboratively via Federated Learning (FL) across multiple clients, eliminating need raw transmission. To this end, we present F4LLM, new...
The rapid advancement of generative artificial intelligence (AI) has transformed the information environment, creating both opportunities and challenges. This paper explores how AI influences economic rent-seeking behavior its broader impact on social welfare. We develop a dynamic model involving multiple agents who may engage in activities regulator aiming to mitigate welfare losses. Our analysis reveals dual effect AI: while it reduces traditional rents by increasing transparency, also...
Information asymmetry often leads to adverse selection and moral hazard in economic markets, causing inefficiencies welfare losses. Traditional methods address these issues, such as signaling screening, are frequently insufficient. This research investigates how Generative Artificial Intelligence (AI) can create detailed informational signals that help principals better understand agents' types monitor their actions. By incorporating AI-generated into a principal-agent model, the study aims...