Review of thermal rectification experiments and theoretical calculations in 2D materials
S Zhao, Y Zhou, H Wang - International Journal of Heat and Mass Transfer, 2022 - Elsevier
Thermal rectification is a phenomenon similar to electrical rectification, which can actively
regulate the heat flow. It exhibits high thermal conductivity in one direction, thereby …
regulate the heat flow. It exhibits high thermal conductivity in one direction, thereby …
Physics-informed neural networks (PINNs) for 4D hemodynamics prediction: an investigation of optimal framework based on vascular morphology
X Zhang, B Mao, Y Che, J Kang, M Luo, A Qiao… - Computers in Biology …, 2023 - Elsevier
Hemodynamic parameters are of great significance in the clinical diagnosis and treatment of
cardiovascular diseases. However, noninvasive, real-time and accurate acquisition of …
cardiovascular diseases. However, noninvasive, real-time and accurate acquisition of …
Prediction of water transport properties on an anisotropic wetting surface via deep learning
Understanding the water flow behavior on an anisotropic wetting surface is of practical
significance in nanofluidic devices for their performance improvement. However, current …
significance in nanofluidic devices for their performance improvement. However, current …
Liquid-vapor two-phase flow in centrifugal pump: Cavitation, mass transfer, and impeller structure optimization
Computational fluid dynamics (CFD) has been widely used to model the internal flow field of
centrifugal pumps to analyze cavitation phenomena. However, accurate determination of …
centrifugal pumps to analyze cavitation phenomena. However, accurate determination of …
Deep learning to reveal the distribution and diffusion of water molecules in fuel cell catalyst layers
Water management in the catalyst layers (CLs) of proton-exchange membrane fuel cells is
crucial for its commercialization and popularization. However, the high experimental or …
crucial for its commercialization and popularization. However, the high experimental or …
Machine learning for harnessing thermal energy: From materials discovery to system optimization
Recent advances in machine learning (ML) have impacted research communities based on
statistical perspectives and uncovered invisibles from conventional standpoints. Though the …
statistical perspectives and uncovered invisibles from conventional standpoints. Though the …
Interfacial heat and mass transfer at silica/binary molten salt interface from deep potential molecular dynamics
F Liang, J Ding, X Wei, G Pan, S Liu - … Journal of Heat and Mass Transfer, 2023 - Elsevier
Interfacial heat and mass transfer properties at molten salt/solid interfaces are crucial for the
study of heat storage/transfer properties of molten salt nanocomposite materials as well as …
study of heat storage/transfer properties of molten salt nanocomposite materials as well as …
Deep learning, numerical, and experimental methods to reveal hydrodynamics performance and cavitation development in centrifugal pump
The hydrodynamic performance and cavitation development in centrifugal pump have a
decisive impact on its energy conversion and performance. However, there are still …
decisive impact on its energy conversion and performance. However, there are still …
Morphology evolution and adsorption behavior of ionomers from solution to Pt/C substrates
Coarse-grained molecular dynamics simulations were performed to understand the
morphological evolution and adsorption mechanism of Nafion ionomers from the aqueous …
morphological evolution and adsorption mechanism of Nafion ionomers from the aqueous …
Dual-directional small-sampling deep-learning modelling on co-flowing microfluidic droplet generation
JX Wang, J Qian, H Wang, M Sun, L Wu… - Chemical Engineering …, 2024 - Elsevier
User-specified droplets generated by microfluidics are critical but requires intensive
expertise and much time. Stimulated by data boosts from microfluidic experiments, deep …
expertise and much time. Stimulated by data boosts from microfluidic experiments, deep …