English

Probabilistic design of a molybdenum-base alloy using a neural network

Materials Science 2018-03-05 v1 Machine Learning Computational Physics

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.

Keywords

Cite

@article{arxiv.1803.00879,
  title  = {Probabilistic design of a molybdenum-base alloy using a neural network},
  author = {B. D. Conduit and N. G. Jones and H. J. Stone and G. J. Conduit},
  journal= {arXiv preprint arXiv:1803.00879},
  year   = {2018}
}