Revolutionizing clean energy labs: Robotic imitation learning for efficient fabrication AI-powered electrical units assembly platform
The energy industry, now in an era of digitization driven by computational design, is gradually moving towards automating the entire process from computational prediction to device assembly, aiming to minimize the reliance on time-consuming, manual trial-and-error validation. In this study, guided b...
Saved in:
| Main Authors: | Xi Xu, Yijun Gu, Tianyi Zhang, Jiwen Yu, Stephen Skinner |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | Energy and AI |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546825000497 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Estudio DFT+U de las propiedades estructurales y electrónicas del La₀.₁₂Sr₀.₈₈TiO₃: implicaciones para las celdas de combustible de óxido solido
by: Victor Ernesto Tagarelli Gaete, et al.
Published: (2025-08-01) -
Advancements in electrocatalytic technologies for metal-supported solid oxide fuel cells: enhancing efficiency and durability for biofuel-powered mobility applications
by: Ganesan Subbiah, et al.
Published: (2025-08-01) -
Modeling nuclear fuel assemblies through porous zones in a Small Modular Reactor: fluid dinamic considerations
by: Rebeca Cabral Gonçalves, et al.
Published: (2025-07-01) -
Debris filtering efficiency assessment of the fuel assembly bottom nozzle
by: Zheng Mei-yin, et al.
Published: (2025-03-01) -
A simple and universal quasi-modular cloning system using NEBuilder® HiFi DNA assembly kit
by: M. Rey Toleco, et al.
Published: (2025-07-01)