Chair: Wilfred van der Wiel
One of the greatest successes of the 20th century has been the development of digital computers. Conventional computation is based on Turing’s abstract model of a machine, now referred to as the Turing machine. Based on the ideas of Turing, Von Neumann proposed a computer architecture, which forms the foundation for all digital computing. In this computational paradigm, physical components are constructed into logic gates, from which the Von Neumann architecture is built. During the last decades computers have become more and more powerful by integrating increasingly many and smaller components on chips. It is becoming very hard and extremely expensive to continue this miniaturisation. Current transistors consist of only a handful of atoms. It is a major challenge to produce chips in which the millions of transistors have the same characteristics, and thus to make the chips operate properly. Another drawback is that their energy consumption is reaching unacceptable levels. It is obvious that we have to look for alternative, unconventional directions.
In this session, we will address questions as Have we reached the end of the Digital Age? Can we use molecular self-assembly for future electronics? and Can we exploit the computational power of nanoscale materials to realize revolutionary new computer architectures? The audience is invited to participate in a lively discussion following the four short presentations.
Introduction by Wilfred van der Wiel
Jurriaan Schmitz (SC)
The future of digital logic
Celestine Preetham Lawrence (NE)
Natural computing in Nanomaterio
Liang Ye (MNF)
Molecular layer doping of semiconductors
Anirban Ghosh (IMS)
Ferroelectrics for synaptic memory
The future of digital logic – Jurriaan Schmitz (Semiconductor Components)
Moore's Law is coming to an end. Are chips still improving, or have we reached the end of the Digital Age? Starting from the question, what kind of improvements we are still dreaming of, an overview is presented of new ideas and recent developments in the domain of integrated circuits.
Natural computing in Nanomaterio – Celestine Preetham Lawrence (NanoElectronics)
Natural computers like the human brain are more efficient than man-made computers for solving high IQ problems. This is because humans designed circuits out of well-defined units, while nature evolves emergent functionality out of networks of locally active components. We thus seek to implement Natural computing in Nanomaterio, like say nanoparticles, because they can be self-assembled to form scalable networks and exhibit highly nonlinear nearest neighbor interactions.
Boosting the doping level in monolayer doping by carboranes – Liang Ye (Molecular NanoFabrication)
Monolayer doping (MLD) presents an alternative method to achieve silicon doping without causing crystal damage, and it has the capability of ultra-shallow doping and doping of non-planar surfaces. MLD utilizes a dopant-containing alkene molecule that form a monolayer on the silicon surface using the well-established hydrosilylation process. Here, we demonstrate that MLD can be extended to high doping levels by designing alkenes with a high content of dopant atoms. Concretely, carborane derivatives, which have 10 B atoms per molecule, were functionalized with an alkene group. MLD using a monolayer of such a derivative yielded up to ten times higher doping levels, compared to alkenes with a single B atom. Thermal budget analyses indicate that the doping level can be further optimized by changing the annealing conditions.
Ferroelectrics for synaptic memory
Tuning the polarization switching dynamics through polarization coupling in a
PbZrxTi(1-x)O3/ZnO heterostructure towards neuron like synaptic memory – Anirban Ghosh (Inorganic Materials Science)
Computers today are very inefficient in performing even very simple brain like tasks e.g image recognition etc. Present day computation uses logic gates (0 and 1) as their primary computational element which is achieved by using a thermodynamically bistable system which can be switched back and forth. The main challenge lies how to achieve multiple switchable states necessary for brain like computation.
In the present work, we demonstrate a method to tune the polarization switching dynamics in ferroelectric PbZrxTi(1-x)O3, based on the coupling between the non-switchable polarization of ZnO and the switchable polarization of PbZrxTi(1-x)O3. The highly sensitive exponential relationship between the thickness of ZnO and the activation energy enables us to utilize the random disorder at the PbZrxTi(1-x)O3 – ZnO interface and roughness of ZnO to have different switching voltages at different regions of the film. The polarization versus write time curve could be changed from typical Heaviside like step function to a linear one, which in principle can lead to synaptic memory devices.