Computers, data centers and other electronics use a lot of energy. The Netherlands is focusing, among other things, on wind farms to meet this high energy demand. However, a new type of molecular switches may also contribute to this. The switches can learn from past behavior and activate ‘brain-like computers’. In this way, they can contribute to making the electronics more efficient.
The switches were developed by an international group of researchers led by Prof. Dr. Christian Nijhuis from the University of Twente. Instead of focusing only on the realization of sustainable energy sources, Nijhuis also wants to focus on making electronics more efficient. “Our brains are the most efficient computers we know of. They use ten thousand times less energy than the most efficient computers,” reports the professor.
The high energy efficiency of human brains is possible because brains process data in a completely different way. Computers process binary streams of information consisting of zeros and ones. However, brains work analogously using time-dependent impulses.
“Our brains process information from millions of nerve cells from all our senses without any problems. Unlike traditional electronics, they only use the brain cells and synapses through which the pulses pass,” reports Nijhuis. As a result, in practice our brain only uses energy during one pulse. This enables the brain to efficiently process a large amount of data simultaneously.
Nijhuis and his team developed molecules that can perform all the Boolean logic gates required for deep learning. “Deep learning is a form of machine learning based on artificial neural networks and is widely used for automatic recognition of images and speech, but also in the search for new medicine and more recently in making art. All things that are much more difficult for a computer than for our brain,” explains Nijhuis.
For some time now, there have been all sorts of developments in artificial intelligence software. With the molecules, the research team will now also bring hardware for artificial intelligence closer.
Change behavior based on previously received stimuli
To mimic the dynamic behavior of synapses at the molecular level, the researchers combined fast electron transfer with slow proton coupling limited by diffusion. This is similar to the fast pulses and slow uptake of neurotransmitters by the neurons in the human brain.
The molecules are able to adjust the strength and duration of the pulses. In doing so, they exhibit a form of classical conditioning, the researchers report. The molecules adapt their behavior to the stimuli they have previously received, which is a form of learning. In the future, such molecules should also be able to respond to other stimuli, such as light, according to the researchers.
The researchers foresee a wide range of applications. According to the researchers, the discovery paves the way for the development of various adaptive and reconfigurable systems. These in turn can lead to new multifunctional adaptive systems that greatly simplify artificial neural networks. Nijhuis explains: “This drastically reduces the energy consumption of our electronics.” Multifunctional molecules that are also light-sensitive or can detect other molecules can lead to new types of neural networks or sensors.
More information is available in the publication ‘Dynamic molecular switches with hysteretic negative differential conductance emulating synaptic behavior’ in the scientific journal Nature Materials.
Author: Wouter Hoeffnagel
Photo: Gordon Johnson via Pixabay