A5006740627- Advanced Photocatalysis Techniques
- Advanced materials and composites
- X-ray Diffraction in Crystallography
- Microstructure and mechanical properties
- Catalytic Processes in Materials Science
- Aluminum Alloys Composites Properties
- Crystallization and Solubility Studies
- Covalent Organic Framework Applications
- CO2 Reduction Techniques and Catalysts
- Crystallography and molecular interactions
- Aluminum Alloy Microstructure Properties
- Metal-Organic Frameworks: Synthesis and Applications
- Structural Health Monitoring Techniques
- Metal Alloys Wear and Properties
- Intermetallics and Advanced Alloy Properties
- High-Temperature Coating Behaviors
- MXene and MAX Phase Materials
- Structural Load-Bearing Analysis
- Electronic and Structural Properties of Oxides
- 2D Materials and Applications
- Innovative concrete reinforcement materials
- Hydrological Forecasting Using AI
- Energy Load and Power Forecasting
- Metal and Thin Film Mechanics
- Powder Metallurgy Techniques and Materials
Yan'an University
2025
Jiangsu University
2020-2024
Collaborative Innovation Center of Advanced Microstructures
2017-2024
Nanjing University
2016-2024
Zhengzhou Institute of Machinery
2024
China Academy Of Machinery Science & Technology (China)
2024
National Laboratory of Solid State Microstructures
2018-2024
Jiangxi Academy of Sciences
2006-2023
Vietnam National University of Agriculture
2019-2022
Huaiyin Institute of Technology
2018-2019
This study aims to analyze the sensitivity and robustness of two Artificial Intelligence (AI) techniques, namely Gaussian Process Regression (GPR) with five different kernels (Matern32, Matern52, Exponential, Squared Rational Quadratic) an Neural Network (ANN) using a Monte Carlo simulation for prediction High-Performance Concrete (HPC) compressive strength. To this purpose, 1030 samples were collected, including eight input parameters (contents cement, blast furnace slag, fly ash, water,...
Abstract Converting water into hydrogen fuel and oxidizing benzyl alcohol to benzaldehyde simultaneously under visible light illumination is of great significance, but the fast recombination photogenerated carriers in photocatalysts seriously decreases conversion efficiency. Herein, a novel dual-functional 0D Cd 0.5 Zn S/2D Ti 3 C 2 hybrid was fabricated by solvothermally in-situ generated assembling method. The S nano-spheres with fluffy surface completely uniformly covered ultrathin...
Gaseous oxides generated during industrial processes, such as carbon (COx) and nitrogen (NOx), have important effects on the Earth's atmosphere. It is highly desired to develop a low-cost efficient route convert them harmless products. Here, direct splitting of gaseous was proposed basis photocatalysis by an amorphous oxide semiconductor. As example, CO2 into oxygen achieved over zinc germanate (α-Zn-Ge-O) semiconductor photocatalyst under 300 W Xe lamp irradiation. Electron paramagnetic...
Abstract Light‐driven CO 2 reduction into high value‐added product is a potential route to convert and store solar energy. Here, using the hydroxyls on an oxyhydroxide photocatalyst, CoGeO (OH) , as solid‐state proton source reduce CH 4 proposed. It found that under irradiation, lattice surface of are oxidized by photogenerated holes, resulting in generation oxygen vacancies (O Vs ) protons. The photoinduced O (Lewis acid) its proximal base) more likely form frustrated Lewis acid–base pairs,...
Activating CO 2 molecule and promoting proton release from kinetically sluggish water oxidation are two important half‐reaction processes for achieving efficient solar‐driven conversion of to fuels. Here, an effective route is proposed that uses a solid base modify photocatalyst with defects, aiming simultaneously accelerate the reaction processes. To verify this hypothesis, La O 3 decorated on surface LaTiO N oxygen vacancies, twofold increase in CH 4 yield rate reduction. The prominent...
Use of manufactured sand to replace natural is increasing in the last several decades. This study devoted assessment using Principal Component Analysis (PCA) together with Teaching-Learning-Based Optimization (TLBO) for enhancing prediction accuracy individual Adaptive Neuro Fuzzy Inference System (ANFIS) predicting compressive strength concrete (MSC). The PCA technique was applied reducing noise input space, whereas, TLBO employed increase performance single ANFIS model searching optimal...
This study aims to investigate the prediction of critical buckling load steel columns using two hybrid Artificial Intelligence (AI) models such as Adaptive Neuro-Fuzzy Inference System optimized by Genetic Algorithm (ANFIS-GA) and Particle Swarm Optimization (ANFIS-PSO). For this purpose, a total number 57 experimental tests novel high strength Y-section were collected from available literature generate dataset for training validating proposed AI models. Quality assessment criteria...
Gas multisensor devices offer an effective approach to monitor air pollution, which has become a pandemic in many cities, especially because of transport emissions. To be reliable, properly trained models need developed that combine output from sensors with weather data; however, factors can affect the accuracy models. The main objective this study was explore impact several input variables training different quality indexes using fuzzy logic combined two metaheuristic optimizations:...
Understanding shear behavior is crucial for the design of reinforced concrete beams and sustainability in construction civil engineering. Although numerous studies have been proposed, predicting such still needs further improvement. This study proposes a soft-computing tool to predict ultimate capacities (USCs) with steel fiber, one most important factors structural design. Two hybrid machine learning (ML) algorithms were created that combine neural networks (NNs) two distinct optimization...
The main aim of this study is to develop different hybrid artificial intelligence (AI) approaches, such as an adaptive neuro-fuzzy inference system (ANFIS) and two ANFISs optimized by metaheuristic techniques, namely simulated annealing (SA) biogeography-based optimization (BBO) for predicting the critical buckling load structural members under compression, taking into account influence initial geometric imperfections. With aim, existing results compression tests on steel columns were...
The principal purpose of this work is to develop three hybrid machine learning (ML) algorithms, namely ANFIS-RCSA, ANFIS-CA, and ANFIS-SFLA which are a combination adaptive neuro-fuzzy inference system (ANFIS) with metaheuristic optimization techniques such as real-coded simulated annealing (RCSA), cultural algorithm (CA) shuffled frog leaping (SFLA), respectively, predict the critical buckling load I-shaped cellular steel beams circular openings. For purpose, existing database tests on were...