Jani Kivioja

Science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems

We present the science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems, targeting an evolution in technology, that might lead to impacts and benefits reaching into most areas of society. This roadmap was developed within the framework of the European Graphene Flagship and outlines the main targets and research areas as best understood at the start of this ambitious project. We provide an overview of the key aspects of graphene and related materials (GRMs), ranging from fundamental research challenges to a variety of applications in a large number of sectors, highlighting the steps necessary to take GRMs from a state of raw potential to a point where they might revolutionize multiple industries. We also define an extensive list of acronyms in an effort to standardize the nomenclature in this emerging field.

Stretch-induced plasmonic anisotropy of self-assembled gold nanoparticle mats

Close-packed monolayers of 20 nm Au nanoparticles are self-assembled at hexane/water interfaces and transferred to elastic substrates. Stretching the resulting nanoparticle mats provides active and reversible tuning of their plasmonic properties, with a clear polarization dependance. Both uniaxial and biaxial strains induce strong blue shifts in the plasmonic resonances. This matches theoretical simulations and indicates that plasmonic coupling at nanometer scale distances is responsible for the observed spectral tuning. Such stretch-tunable metal nanoparticle mats can be exploited for the development of optical devices, such as flexible colour filters and molecular sensors.

Top-Gated Silicon Nanowire Transistors in a Single Fabrication Step

Top-gated silicon nanowire transistors are fabricated by preparing all terminals (source, drain, and gate) on top of the nanowire in a single step via dose-modulated e-beam lithography. This outperforms other time-consuming approaches requiring alignment of multiple patterns, where alignment tolerances impose a limit on device scaling. We use as gate dielectric the 10-15 nm SiO(2) shell naturally formed during vapor-transport growth of Si nanowires, so the wires can be implemented into devices after synthesis without additional processing. This natural oxide shell has negligible leakage over the operating range. Our single-step patterning is a most practical route for realization of short-channel nanowire transistors and can be applied to a number of nanodevice geometries requiring nonequivalent electrodes.

Transport Conductivity of Graphene at RF and Microwave Frequencies

We measure graphene coplanar waveguides from direct current (DC) to 13.5GHz and show that the apparent resistance (in the presence of parasitic impedances) has an quadratic frequency dependence, but the intrinsic conductivity (without the influence of parasitic impedances) is frequency-independent. Consequently, in our devices the real part of the complex alternating current conductivity is the same as the DC value and the imaginary part~0. The graphene channel is modelled as a parallel resistive-capacitive network with a frequency dependence identical to that of the Drude conductivity with momentum relaxation time~2.1ps, highlighting the influence of alternating current (AC) electron transport on the electromagnetic properties of graphene. This can lead to optimized design of high-speed analogue field-effect transistors, mixers, frequency doublers, low-noise amplifiers and radiation detectors.

Silicon nanowire arrays as learning chemical vapour classifiers

Nanowire field-effect transistors are a promising class of devices for various sensing applications. Apart from detecting individual chemical or biological analytes, it is especially interesting to use multiple selective sensors to look at their collective response in order to perform classification into predetermined categories. We show that non-functionalised silicon nanowire arrays can be used to robustly classify different chemical vapours using simple statistical machine learning methods. We were able to distinguish between acetone, ethanol and water with 100% accuracy while methanol, ethanol and 2-propanol were classified with 96% accuracy in ambient conditions.

Graphene-driven revolutions in ICT and beyond

This session described the FET Flagship Pilot on graphene and related two-dimensional materials. The flagship targets a revolution in information and communication technology, with impacts reaching into other areas of the society. The session featured four talks on the scientific and technological potential and open research challenges within the scope of the proposed flagship, industrial view on possibilities and challenges posed by graphene and related materials, and presentation on the implementation and structure of the flagship pilot.

Input/output pulse operation of ZnO nanowire threshold integrators

Integrating more functionality into individual nano-components is a key step to exploit alternative architectures for energy-efficient computation, such as, for instance, neuromorphic computing. Here, we show how to configure ZnO nanowire field-effect transistors as light pulse integrators with programmable threshold. We demonstrate that these single-component devices can be operated as both synchronous and asynchronous neuron-like structures, where the firing threshold and the form of the output signal, either step-like or spiked, can be controlled by using several operational parameters, including the environment in which the device operates. A detailed study showing how environmental variables, such as relative humidity, ambient light and temperature, affect device operation is presented.