Machine learning methods for small data challenges in molecular science
B Dou, Z Zhu, E Merkurjev, L Ke, L Chen… - Chemical …, 2023 - ACS Publications
Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
Proportional–integral-type estimator design for delayed recurrent neural networks under encoding–decoding mechanism
In this paper, the proportional–integral-type estimator design problem is studied for recurrent
neural networks under the encoding–decoding communication mechanism. In the process …
neural networks under the encoding–decoding communication mechanism. In the process …
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 …
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 …
Prediction of nanoscale thermal transport and adsorption of liquid containing surfactant at solid–liquid interface via deep learning
Hypothesis Recent advances in deep learning (DL) have enabled high level of real-time
prediction of thermophysical properties of materials. On the other hand, molecular dynamics …
prediction of thermophysical properties of materials. On the other hand, molecular dynamics …
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 …
Analyzing ionic liquid systems using real-time electron microscopy and a computational framework combining deep learning and classic computer vision techniques
DA Boiko, AS Kashin, VR Sorokin, YV Agaev… - Journal of Molecular …, 2023 - Elsevier
Electron microscopy (EM) is one of the most important methods for characterizing various
systems, and it is traditionally applied to static solid structures. Remarkable recent …
systems, and it is traditionally applied to static solid structures. Remarkable recent …
Applying machine learning to reveal the microscopic heat transfer mechanism of nanofluids as coolants
Nanofluids are considered as excellent coolants to optimize thermal management of
electronic devices, where the nanoparticle morphology and the addition of surfactants can …
electronic devices, where the nanoparticle morphology and the addition of surfactants can …