scholarly journals Visualization of Optical Vortex Forces Acting on Au Nanoparticles Transported in Nanofluidic Channels

ACS Omega ◽  
2022 ◽  
Author(s):  
Kichitaro Nakajima ◽  
Tempei Tsujimura ◽  
Kentaro Doi ◽  
Satoyuki Kawano
Keyword(s):  
Au Nanoparticles ◽  
Optical Vortex ◽  
Nanofluidic Channels

Electrical Sensing of Au Nanoparticles Manipulated by an Optical Vortex

2021 ◽  
Author(s):  
Ryoji Nakatsuka ◽  
Syuhei Yanai ◽  
Kichitaro Nakajima ◽  
Kentaro Doi ◽  
Satoyuki Kawano
Keyword(s):  
Au Nanoparticles ◽  
Optical Vortex ◽  
Electrical Sensing

Machine Learning Accelerated Genetic Algorithms for Computational Materials Search

2018 ◽  
Author(s):  
Steen Lysgaard ◽  
Paul C. Jennings ◽  
Jens Strabo Hummelshøj ◽  
Thomas Bligaard ◽  
Tejs Vegge
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Au Nanoparticles ◽  
Learning Model ◽  
Energy Calculations ◽  
Atomic Distribution ◽  
Machine Learning Model ◽  
Fold Reduction ◽  
Computational Materials

A machine learning model is used as a surrogate fitness evaluator in a genetic algorithm (GA) optimization of the atomic distribution of Pt-Au nanoparticles. The machine learning accelerated genetic algorithm (MLaGA) yields a 50-fold reduction of required energy calculations compared to a traditional GA.

Synergistic effects of SnO2 and Au nanoparticles decorated on WS2 nanosheets for flexible, room-temperature CO gas sensing

2021 ◽  
Vol 332 ◽  
pp. 129493
Author(s):  
Jae-Hun Kim ◽  
Jin-Young Kim ◽  
Ali Mirzaei ◽  
Hyoun Woo Kim ◽  
Sang Sub Kim
Keyword(s):  
Room Temperature ◽  
Au Nanoparticles ◽  
Gas Sensing ◽  
Synergistic Effects ◽  
Ws2 Nanosheets ◽  
Co Gas

scholarly journals Designing the Hotspots Distribution by Anisotropic Growth

Molecules ◽  
2021 ◽  
Vol 26 (1) ◽  
pp. 187
Author(s):  
Tianshun Li ◽  
Renxian Gao ◽  
Xiaolong Zhang ◽  
Yongjun Zhang
Keyword(s):  
Au Nanoparticles ◽  
Fdtd Method ◽  
Polarization Dependence ◽  
Noble Metal Nanoparticles ◽  
Oblique Angle Deposition ◽  
Matlab Simulation ◽  
Different Shapes ◽  
Plasma Enhancement ◽  
Difference Time ◽  
Good Agreement

Changing the morphology of noble metal nanoparticles and polarization dependence of nanoparticles with different morphologies is an important part of further research on surface plasma enhancement. Therefore, we used the method based on Matlab simulation to provide a simple and effective method for preparing the morphologies of Au nanoparticles with different morphologies, and prepared the structure of Au nanoparticles with good uniformity and different morphologies by oblique angle deposition (OAD) technology. The change of the surface morphology of nanoparticles from spherical to square to diamond can be effectively controlled by changing the deposition angle. The finite difference time domain (FDTD) method was used to simulate the electromagnetic fields of Au nanoparticles with different morphologies to explore the polarization dependence of nanoparticles with different shapes, which was in good agreement with Raman spectrum.

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