首页|Recent Research from Dalian University of Technology Highlight Findings in Machi ne Learning (New Insights Into the Role of Nitrogen Doping In Microporous Carbon On the Capacitive Charge Storage Mechanism: From Ab Initio To Machine Learning ...)
Recent Research from Dalian University of Technology Highlight Findings in Machi ne Learning (New Insights Into the Role of Nitrogen Doping In Microporous Carbon On the Capacitive Charge Storage Mechanism: From Ab Initio To Machine Learning ...)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Fresh data on Machine Learning are presented in a new report. According to news reporting originating in Dalian, People's Republi c of China, by NewsRx journalists, research stated, "Fundamental understandings of the relationship between ion-electrode interaction and structural feature in porous carbon electrodes at a molecular level provides guidelines for the design of high-performance electric double layer supercapacitors. It is certified by e xperiments that porous carbon structures doped with nitrogen show enhanced capac itive performance." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news reporters obtained a quote from the research from the Dalian University of Technology, "However, in the theoretical simulations, the fundamental charge storage mechanism is still elusive. In particular, the recent experimental resu lt shows that the generally ignored nitrolic nitrogen (N5) in porous carbon exhi bits a positive effect on capacitance, while graphitic nitrogen (N3) does the op posite, which is against with the simulation results based the 2D-modeled porous graphene structure. Here, we perform ab initio molecular dynamics simulations o n the N3 and N5-doped carbon/electrolyte interfaces, including both 2D planar an d 3D microporous carbon electrodes. Our calculation indicates that N3 in the 3D pore hinders the electrolyte transport, while N5-doped micropore still serves as an electrolyte transport channel through the formation of H-bond. The charge st orage mechanism is further elucidated by the analysis of the well equilibrated i nterfaces obtained from the machine learning force field accelerated molecular d ynamics. Our work provides a new insight into the effect of nitrogen doping in 3 D porous carbon, which is exactly opposite to the 2D planar graphene."
DalianPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningMolecular DynamicsNitrogenPhysicsDalian University of Technology
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