2000 character limit reached
Probabilistic design of a molybdenum-base alloy using a neural network
Published 2 Mar 2018 in cond-mat.mtrl-sci, cs.LG, and physics.comp-ph | (1803.00879v1)
Abstract: An artificial intelligence tool is exploited to discover and characterize a new molybdenum-base alloy that is the most likely to simultaneously satisfy targets of cost, phase stability, precipitate content, yield stress, and hardness. Experimental testing demonstrates that the proposed alloy fulfils the computational predictions, and furthermore the physical properties exceed those of other commercially available Mo-base alloys for forging-die applications.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.