From prediction to design: recent advances in machine learning for the study of 2D materials
H He, Y Wang, Y Qi, Z Xu, Y Li, Y Wang - Nano Energy, 2023 - Elsevier
Although data-driven approaches have made significant strides in various scientific fields,
there has been a lack of systematic summaries and discussions on their application in 2D …
there has been a lack of systematic summaries and discussions on their application in 2D …
Unlocking the Full Potential of Heteroatom-Doped Graphene-Based Supercapacitors through Stacking Models and SHAP-Guided Optimization
K Deshsorn, K Payakkachon… - Journal of Chemical …, 2023 - ACS Publications
Graphene-based supercapacitors have emerged as a promising candidate for energy
storage due to their superior capacitive properties. Heteroatom-doping is a method of …
storage due to their superior capacitive properties. Heteroatom-doping is a method of …
The structure analysis and chemical properties probing during recycling processes of transition metal dichalcogenides exfoliation
Transition metal dichalcogenides (TMDs) have attracted much attention in electrochemistry
due to their outstanding properties; however, there is a limit to the production of TMDs …
due to their outstanding properties; however, there is a limit to the production of TMDs …
Ultrahigh stable laminar graphene membranes for effective ionic and molecular nanofiltration with a machine learning-assisted study
P Paechotrattanakul, K Jitapunkul, P Iamprasertkun… - Nanoscale, 2023 - pubs.rsc.org
Graphene oxide (GO) membranes have gained great attention for water purification due to
the formation of stacked nanosheets giving nanocapillary channels. Unlike graphene, the …
the formation of stacked nanosheets giving nanocapillary channels. Unlike graphene, the …
Study and prediction of photocurrent density with external validation using machine learning models
Aiming to develop a generalized machine learning (ML) model for evaluating the
performance of photoelectrode in PEC system by predicting the photocurrent density (J), we …
performance of photoelectrode in PEC system by predicting the photocurrent density (J), we …
[HTML][HTML] “Crypton 1.0”: Accurate cyclic voltammetry forecasting of activated carbon electrode with machine learning
A Jarubenjaluk, P Kullattanapratep… - Chemical Engineering …, 2023 - Elsevier
Cyclic voltammetry (CV) is a technique for determining the electrochemical properties of the
electrode, and electrolyte in electrochemical systems. However, it is sensitive to various …
electrode, and electrolyte in electrochemical systems. However, it is sensitive to various …