A5090993350- Lattice Boltzmann Simulation Studies
- Block Copolymer Self-Assembly
- Fluid Dynamics and Heat Transfer
- Blood properties and coagulation
- Surface Modification and Superhydrophobicity
- Fluid Dynamics Simulations and Interactions
- Nanopore and Nanochannel Transport Studies
- Rheology and Fluid Dynamics Studies
- Microfluidic and Bio-sensing Technologies
- Fluid Dynamics and Mixing
- Enhanced Oil Recovery Techniques
- Platelet Disorders and Treatments
- Meteorological Phenomena and Simulations
- Metallurgical Processes and Thermodynamics
- Fluid Dynamics and Thin Films
- Machine Learning in Materials Science
- Fluid Dynamics and Turbulent Flows
- Cellular Automata and Applications
- Advanced Chemical Sensor Technologies
- Olfactory and Sensory Function Studies
- Granular flow and fluidized beds
- Non-Destructive Testing Techniques
- Adhesion, Friction, and Surface Interactions
- Chemical and Physical Properties of Materials
- Icing and De-icing Technologies
Fudan University
2022-2025
Beijing Academy of Artificial Intelligence
2025
Pudong Medical Center
2023
Tongji University
2018-2022
Brown University
2021
Columbia University
2020
Simulating and predicting multiscale problems that couple multiple physics dynamics across many orders of spatiotemporal scales is a great challenge has not been investigated systematically by deep neural networks (DNNs). Herein, we develop framework based on operator regression, the so-called network (DeepONet), with long term objective to simplify modeling avoiding fragile time-consuming "hand-shaking" interface algorithms for stitching together heterogeneous descriptions phenomena. To...
Normal haemostasis is an important physiological mechanism that prevents excessive bleeding during trauma, whereas the pathological thrombosis especially in diabetics leads to increased incidence of heart attacks and strokes as well peripheral vascular events. In this work, we propose a new multiscale framework integrates seamlessly four key components blood clotting, namely transport coagulation factors, kinetics, cell mechanics platelet adhesive dynamics, model development thrombi under...
Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand scientific challenge. Recently, machine learning-based weather forecasting models outperform the most successful numerical predictions generated by European Centre Medium-Range Weather Forecasts (ECMWF), have not yet surpassed conventional at timescales. This paper introduces FuXi Subseasonal-to-Seasonal (FuXi-S2S), learning model that provides global daily mean up to 42 days, encompassing five...
Modelling multiscale systems from nanoscale to macroscale requires the use of atomistic and continuum methods and, correspondingly, different computer codes. Here, we develop a seamless method based on DeepONet, which is composite deep neural network (a branch trunk network) for regressing operators. In particular, consider bubble growth dynamics, model tiny bubbles initial size 100 nm 10 in regime. After an offline training data both regimes, DeepONet can make accurate predictions...
Controlling the motion of liquid drops on solid surface has broad technological implications. In this study, many-body dissipative particle dynamics (MDPD) was employed to study drop behaviors chemical chessboard-patterned surfaces formed by square or triangular tiles. The scaling relationship model established based tension, viscosity, and density a real fluid, an improved contact angle measurement technique introduced MDPD system. For horizontal plane with different tile sizes, equilibrium...
We investigate the dynamics of droplet impacts on a ring-decorated solid surface, which is reported to reduce integral contact area over time by up 80%. By using many-body dissipative particle (MDPD), particle-based simulation method, we measure temporal evolution shape and impact force two specific types phenomena, overrun ejection. The numerical model first validated with experimental data plain surface from literature. Then, it used extract impacting ring substrate separately, showing...
Intracranial aneurysm (IA) is a common cerebrovascular disease that usually asymptomatic but may cause severe subarachnoid hemorrhage (SAH) if ruptured. Although clinical practice based on individual factors and morphological features of the aneurysm, its pathophysiology hemodynamic mechanisms remain controversial. To address limitations current research, this study constructed comprehensive dataset intracranial aneurysms. The 466 real models, 10,000 synthetic models were generated by...
The vibration of solids is ubiquitous in nature and industrial applications gives rise to alternative droplet dynamics during impact. Using many-body dissipative particle dynamics, we investigate the impact droplets on superhydrophobic solid surfaces vibrating vertical direction at a period similar contact time. Specifically, study influence phase frequency. We evaluate from aspects maximum spreading diameter, solid–liquid time area, momentum variation To quantitatively contact, introduce...
Background Asymmetry in motor dysfunction and associated dopaminergic deficit is a common characteristic of Parkinson's disease (PD), yet potential explanations remain mysterious. Hereby, we assessed whether asymmetry the nasal cavity related to PD patients. Methods This cross-sectional, multi-center observational study included 761 patients from three cohorts. First, analyzed data Huashan Parkinsonian PET Imaging Database (March 2011 February 2020), which served as primary cohort (n=333)....
Minimizing the contact between impacting droplets and solid substate is useful in many applications, for example, anti-icing. This study shows that a simple crater-like decoration on can reduce area time simultaneously cut overall up to 75%. The novel simulation model used this has been validated with experiments great advantage accurately measuring dynamic wetting liquid substrate, which only be inferred much difficulty experiments.
The thermocapillary motion of a drop on solid substrate is common phenomenon in daily life and many industrial fields. can be significantly affected by the temperature gradient properties liquid, such as surface tension, viscosity, thermal coefficient, density, diffusivity. In this study, numerical model based modified many-body dissipative particle dynamics was developed to capture correctly dependence fluid. momentum, diffusivity, tension liquid water at various temperatures ranging from...
Anti-icing is a crucial concern for solid surfaces in numerous industrial domains and has garnered significant attention recent years. Traditional anti-icing methods often require substantial input of energy. In this study, we provide brief overview the potential applications advancements field. Then, present novel method, design superhydrophobic based on droplet dynamics. Additionally, delve into several related topics that could benefit future research area, such as with various...
We apply Lagrangian particle tracking to the two-dimensional single-mode Rayleigh–Taylor (RT) instability study dynamical evolution of fluid interface. At onset nonlinear RT stage, we select three ensembles tracer particles located at bubble tip, spike and inside spiral mushroom structure, which cover most interfacial region as develops. Conditional statistics performed on sets over different stages, such trajectory curvature, velocity, acceleration, reveals temporal spatial flow patterns...
Dissipative particle dynamics (DPD) is a thriving particle-based simulation method of modeling mesoscale fluids. After two decades evolution, DPD has shown unique advantages in researches about polymer, red blood cell, droplets wetting, etc. However, limited to relatively simple geometries due the lack satisfactory boundary method. In this paper, we propose an adaptive for complex geometry, which fulfills three basic requirements method: no penetration into solid, no-slip near boundary,...
Molecular combing facilitates the investigation of single DNA molecules with a moving water–air interface to immobilize on solid surface. In this study, we use dissipative particle dynamics model three-phase system complex fluids. We visually demonstrated deposition process and quantitatively described degree linearization. Then, study effect substrate property results. Finally, propose chemical heterogeneous stripe-patterned that can improve linearization deposited chains.
Graphene has received a lot of attention for its excellent physical and chemical properties, the unique wettability graphene is still under investigation. Most previous studies focused on or carbon nanotubes, less them comparison between other materials to reveal characteristic graphene. In present study, monolayer graphene, copper silica are studied by using molecular dynamics simulation, in which contact angle water molecule arrangement (i.e. density distribution molecules) substrates...
In this paper, the graphic processing unit (GPU) parallel computing of dissipative particle dynamics (DPD) based on compute unified device architecture is carried out. Some issues involved, such as thread mapping, cell-list array updating, generating pseudo-random number GPU, memory access optimization and loading balancing are discussed in detail. Furthermore, Poiseuille flow suddenly contracting expanding simulated to verify correctness GPU computing. The results DPD show that speedup...