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AI-enabled Automation of Atomic Manipulation and Characterization in the STEM

Conference Paper

August, 2023

Discovering the Electron Beam Induced Transition Rates for Silicon Dopants in Graphene with Deep Neural Networks in the STEM

Conference Paper

August, 2023

Discovering invariant spatial features in electron energy loss spectroscopy images on the mesoscopic and atomic levels...

Journal

March, 2024

Experimental evidence for nonspherical magnetic form factor in Ru3+

Journal

March, 2024

Ghost states and surface structures of the charge density wave kagome metal ScV 6 Sn 6

Journal

May, 2024

In this artist’s conception of the process, an automated deposition system places a new material onto a base material (purple beam, right) as the last sample that was made is analyzed and sent to the AI (green beams, brain, left). The AI tells the pulsed laser deposition machine what to do next (data cable, bottom).

Researchers harness AI for autonomous discovery and optimization of materials

June 11, 2024

Today, scientific discovery is accelerated by automated experiments, artificial intelligence and high-performance computing.

Amantadine interactions with phase separated lipid membranes...

Journal

May, 2024

Resonant Raman in armchair graphene nanoribbons from first-principles

Journal

May, 2024

Bright and durable scintillation from colloidal quantum shells

Journal

May, 2024

Deep learning with plasma plume image sequences for anomaly detection and prediction of growth kinetics during pulsed laser deposition

Journal

May, 2024

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