Data‐Driven Materials Innovation and Applications
Owing to the rapid developments to improve the accuracy and efficiency of both
experimental and computational investigative methodologies, the massive amounts of data …
experimental and computational investigative methodologies, the massive amounts of data …
Research progress for plastic waste management and manufacture of value-added products
Nowadays, plastic products are closely related to human life. While it brings convenience to
human beings, there are also great health and environmental threats. Most of the plastic …
human beings, there are also great health and environmental threats. Most of the plastic …
Applications of machine learning in perovskite materials
Z Wang, M Yang, X Xie, C Yu, Q Jiang… - … Composites and Hybrid …, 2022 - Springer
Abstract Machine learning (ML) offers the opportunities to discover certain unique properties
for typical material. Taking perovskite materials as an example, this review summarizes the …
for typical material. Taking perovskite materials as an example, this review summarizes the …
Optimization of elliptical pin-fin microchannel heat sink based on artificial neural network
C Yu, X Zhu, Z Li, Y Ma, M Yang, H Zhang - International Journal of Heat …, 2023 - Elsevier
Conjugate fluid-solid heat transfer in a pin-fin microchannel heat sink is an effective way to
dissipate heat from the heating surface with high heat flux. The introduction of fins increases …
dissipate heat from the heating surface with high heat flux. The introduction of fins increases …
Estimation of tetracycline antibiotic photodegradation from wastewater by heterogeneous metal-organic frameworks photocatalysts
In this work, the potential ability of various modern and powerful machine learning methods
such as Categorical Boosting (CatBoost), Light Gradient Boosting Machine (LightGBM) …
such as Categorical Boosting (CatBoost), Light Gradient Boosting Machine (LightGBM) …
Bonding‐Enhanced Interfacial Thermal Transport: Mechanisms, Materials, and Applications
Rapid advancements in nanotechnologies for energy conversion and transport applications
urgently require a further understanding of interfacial thermal transport and enhancement of …
urgently require a further understanding of interfacial thermal transport and enhancement of …
A mini review on thermally conductive polymers and polymer-based composites
The continuous trend of miniaturization leads to unprecedented power densities within
electronic devices, which also becomes the bottleneck of the device performance. Effective …
electronic devices, which also becomes the bottleneck of the device performance. Effective …
Machine learning approaches for predicting arsenic adsorption from water using porous metal–organic frameworks
Arsenic in drinking water is a serious threat for human health due to its toxic nature and
therefore, its eliminating is highly necessary. In this study, the ability of different novel and …
therefore, its eliminating is highly necessary. In this study, the ability of different novel and …
[HTML][HTML] Perspective: Predicting and optimizing thermal transport properties with machine learning methods
In recent years,(big) data science has emerged as the “fourth paradigm” in physical science
research. Data-driven techniques, eg machine learning, are advantageous in dealing with …
research. Data-driven techniques, eg machine learning, are advantageous in dealing with …
Machine learning approach for the prediction and optimization of thermal transport properties
Y Ouyang, C Yu, G Yan, J Chen - Frontiers of Physics, 2021 - Springer
Traditional simulation methods have made prominent progress in aiding experiments for
understanding thermal transport properties of materials, and in predicting thermal …
understanding thermal transport properties of materials, and in predicting thermal …