In what could be a small step for science potentially leading to a breakthrough, an engineer at Washington University in St. Louis has taken steps toward using nanocrystal networks for artificial intelligence applications.
Elijah Thimsen, assistant professor of energy, environmental & chemical engineering in the School of Engineering & Applied Science, and his collaborators have developed a model in which to test existing theories about how electrons move through nanomaterials. This model may lay the foundation for using nanomaterials in a machine learning device.
"When one builds devices out of nanomaterials, they don't always behave like they would for a bulk material," Thimsen said. "One of the things that changes dramatically is the way in which these electrons move through material, called the electron transport mechanism, but it's not well understood how that happens."
Thimsen and his team based the model on an unusual theory that every nanoparticle in a network is a node that is connected to every other node, not only its immediate neighbors. Equally unusual is that the current flowing through the nodes doesn't necessarily occupy the spaces between the nodes -- it needs only to pass through the nodes themselves. This behavior, which is predicted by the model, produces experimentally observable current hotspots at the nanoscale, the researcher said.
In addition, the team looked at another model called a neural network, based on the human brain and nervous system. Scientists have been working to build new computer chips to emulate these networks, but these chips are far short of the human brain, which contains up to 100 billion nodes and 10,000 connections per node.
"If we have a huge number of nodes -- much larger than anything that exists -- and a huge number of connections, how do we train it?" Thimsen asks. "We want to get this large network to perform something useful, such as a pattern-recognition task."
Based on those network theories, Thimsen has proposed an initial project to design a simple chip, give it particular inputs and study the outputs.
"If we treat it as a neural network, we want to see if the output from the device will depend on the input," Thimsen said. "Once we can prove that, we'll take the next step and propose a new device that allows us to train this system to perform a simple pattern-recognition task."
The results of their work were published in advanced online publication of The Journal of Physical Chemistry C.
Chen Q, Guest J, Thimsen E. "Visualizing Current Flow at the Mesoscale in Disordered Assemblies of Touching Semiconductor Nanocrystals." The Journal of Physical Chemistry C. Advanced online publication. DOI: 10.1021/acs.jpcc.7b04949
Erika Ebsworth-Goold | EurekAlert!
Controlling robots with brainwaves and hand gestures
20.06.2018 | Massachusetts Institute of Technology, CSAIL
Innovative autonomous system for identifying schools of fish
20.06.2018 | IMDEA Networks Institute
In a recent publication in the renowned journal Optica, scientists of Leibniz-Institute of Photonic Technology (Leibniz IPHT) in Jena showed that they can accurately control the optical properties of liquid-core fiber lasers and therefore their spectral band width by temperature and pressure tuning.
Already last year, the researchers provided experimental proof of a new dynamic of hybrid solitons– temporally and spectrally stationary light waves resulting...
Scientists from the University of Freiburg and the University of Basel identified a master regulator for bone regeneration. Prasad Shastri, Professor of...
Moving into its fourth decade, AchemAsia is setting out for new horizons: The International Expo and Innovation Forum for Sustainable Chemical Production will take place from 21-23 May 2019 in Shanghai, China. With an updated event profile, the eleventh edition focusses on topics that are especially relevant for the Chinese process industry, putting a strong emphasis on sustainability and innovation.
Founded in 1989 as a spin-off of ACHEMA to cater to the needs of China’s then developing industry, AchemAsia has since grown into a platform where the latest...
The BMBF-funded OWICELLS project was successfully completed with a final presentation at the BMW plant in Munich. The presentation demonstrated a Li-Fi communication with a mobile robot, while the robot carried out usual production processes (welding, moving and testing parts) in a 5x5m² production cell. The robust, optical wireless transmission is based on spatial diversity; in other words, data is sent and received simultaneously by several LEDs and several photodiodes. The system can transmit data at more than 100 Mbit/s and five milliseconds latency.
Modern production technologies in the automobile industry must become more flexible in order to fulfil individual customer requirements.
An international team of scientists has discovered a new way to transfer image information through multimodal fibers with almost no distortion - even if the fiber is bent. The results of the study, to which scientist from the Leibniz-Institute of Photonic Technology Jena (Leibniz IPHT) contributed, were published on 6thJune in the highly-cited journal Physical Review Letters.
Endoscopes allow doctors to see into a patient’s body like through a keyhole. Typically, the images are transmitted via a bundle of several hundreds of optical...
13.06.2018 | Event News
08.06.2018 | Event News
05.06.2018 | Event News
22.06.2018 | Materials Sciences
22.06.2018 | Earth Sciences
22.06.2018 | Life Sciences