首页|Wuhan University Reports Findings in Strain Engineering (Interfacial Optimizatio n for AlN/Diamond Heterostructures via Machine Learning Potential Molecular Dyna mics Investigation of the Mechanical Properties)

Wuhan University Reports Findings in Strain Engineering (Interfacial Optimizatio n for AlN/Diamond Heterostructures via Machine Learning Potential Molecular Dyna mics Investigation of the Mechanical Properties)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Engineering - Strain Engineering is the subject of a report. According to news reporting originating from Wuhan, People’s Republic of China, by NewsRx correspondents, research stated, “AlN/diam ond heterostructures hold tremendous promise for the development of next-generat ion highpower electronic devices due to their ultrawide band gaps and other exc eptional properties. However, the poor adhesion at the AlN/diamond interface is a significant challenge that will lead to film delamination and device performan ce degradation.” Our news editors obtained a quote from the research from Wuhan University, “In t his study, the uniaxial tensile failure of the AlN/diamond heterogeneous interfa ces was investigated by molecular dynamics simulations based on a neuroevolution ary machine learning potential (NEP) model. The interatomic interactions can be successfully described by trained NEP, the reliability of which has been demonst rated by the prediction of the cleavage planes of AlN and diamond. It can be rev ealed that the annealing treatment can reduce the total potential energy by enha ncing the binding of the C and N atoms at interfaces. The strain engineering of AlN also has an important impact on the mechanical properties of the interface. Furthermore, the influence of the surface roughness and interfacial nanostructur es on the AlN/diamond heterostructures has been considered.”

WuhanPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesEngineeringMachine LearningMolecular Dynami csPhysicsStrain Engineering

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jun.5)