The new development comes from Dr. Elijah Thimsen, who is an engineer specializing in energy, environmental and chemical mechanics, and who works at the School of Engineering and Applied Science at Washington University in St. Louis. The researcher has constructed a model that is designed to explore =theories about how electrons move through nanomaterials. It is hoped that the model will lay the foundation for using nanomaterials in a machine learning device. The reason why this is important is because it will increase the sophistication of intelligent machines by allowing for faster and more varied computations; this arises due to the way electrons move through nanomaterials (which is based on the peculiarities of the electron transport mechanism). The nanomaterials used in the research have a crystalline form. A nanocrystal is a material particle having at least one dimension smaller than 100 nanometres (a nanoparticle) and composed of atoms in either a single- or poly-crystalline arrangement.
The basis of the model is that each nanoparticle in a network is a node, and each node is connected to every other node, not only its immediate neighbors. It also stands that the the current flowing through the nodes does not necessarily occupy the spaces between the nodes; to be effective the current needs only to pass through the nodes themselves. This behavior produces observable current hotspots at the nanoscale. These are the triggers for more sophisticated machine learning.
From this the researchers have also modeled a neural network that is based on the human brain and nervous system. The aim here is to use such mapping to design a new generation of computer chips. These chips should advance functions like pattern-recognition tasks, allowing artificial intelligence systems to better interpret subtle variations in human faces or objects.
The research is published in the journal The Journal of Physical Chemistry C, in a research paper headed “Visualizing Current Flow at the Mesoscale in Disordered Assemblies of Touching Semiconductor Nanocrystals.”
