  Through learning from past literature, artificial intelligence models have
been able to predict the future applications of various stoichiometric
inorganic materials in a variety of subfields of materials science. This
capacity offers exciting opportunities for boosting the research and
development (R&D) of new functional materials. Unfortunately, the previous
models can only provide the prediction for existing materials in past
literature, but cannot predict the applications of new materials. Here, we
construct a model that can predict the applications of any stoichiometric
inorganic material (regardless of whether it is a new material). Historical
validation confirms the high reliability of our model. Key to our model is that
it allows the generation of the word embedding of any stoichiometric inorganic
material, which cannot be achieved by the previous models. This work constructs
a powerful model, which can predict the future applications of any
stoichiometric inorganic material using only a laptop, potentially
revolutionizing the R&D paradigm for new functional materials
