Thursday, 7 July 2022
Towards autonomous prediction and synthesis of novel magnetic materials
In materials science, candidates for novel functional materials are usually explored in a trial-and-error fashion through calculations, synthetic methods, and material analysis. However, the approach is time-consuming and requires expertise. Now, researchers have used a data-driven approach to automate the process of predicting new magnetic materials. By combining first-principles calculations, Bayesian optimization, and monoatomic alternating deposition, the proposed method can enable a faster development of next-generation electronic devices.
Subscribe to:
Post Comments (Atom)
How 'clean' does a quantum computing test facility need to be?
How to keep stray radiation from 'shorting' superconducting qubits; a pair of studies shows where ionizing radiation is lurking and ...
-
In this project, we will learn about the MCP2515 CAN Controller Module, how to interface the MCP2515 CAN Bus Controller with Arduino and fin...
-
I was first introduced to logic gates when I was around 14 years old. I had heard that computers consisted of ones and zeroes. But I didn’t...
-
Do you need a MOSFET gate resistor? What value should it be? And should it go before or after the pulldown resistor? If you’re a bit impati...
No comments:
Post a Comment