ERC FUNDED PROJECTS

We propose to develop truly two-dimensional continuous materials and two-dimensional monolayer films composed of individual nanocrystals by the comparatively fast, inexpensive, and scalable colloidal synthesis method. The materials’ properties will be studied in detail, especially regarding their (photo-) electrical transport. This will allow developing new types of device structures, such as Coulomb blockade and field enhancement based transistors. Recently, we demonstrated the possibility to synthesize in a controlled manner truly two-dimensional colloidal nanostructures. We will investigate their formation mechanism, synthesize further materials as “nanosheets”, develop methodologies to tune their geometrical properties, and study their (photo-) electrical properties. Furthermore, we will use the Langmuir-Blodgett method to deposit highly ordered monolayers of monodisperse nanoparticles. Such structures show interesting transport properties governed by Coulomb blockade effects known from individual nanoparticles. This leads to semiconductor-like behavior in metal nanoparticle films. The understanding of the electric transport in such “multi-tunnel devices” is still very limited. Thus, we will investigate this concept in detail and take it to its limits. Beside improvement of quality and exchange of material we will tune the nanoparticles’ size and shape in order to gain a deeper understanding of the electrical properties of supercrystallographic assemblies. Furthermore, we will develop device concepts for diode and transistor structures which take into account the novel properties of the low-dimensional assemblies. Nanosheets and monolayers of nanoparticles truly follow the principle of building devices by the bottom-up approach and allow electric transport measurements in a 2D regime. Highly ordered nanomaterial systems possess easy and reliably to manipulate electronic properties what make them interesting for future (inexpensive) electronic devices.

1 497 200 €

Start date: 2013-02-01, End date: 2019-01-31

"Understanding structure-property relationships across lengthscales is key to the design of functional and structural materials and devices. Moreover, the complexity of modern devices extends to three dimensions and as such 3D characterization is required across those lengthscales to provide a complete understanding and enable improvement in the material’s physical and chemical behaviour. 3D imaging and analysis from the atomic scale through to granular microstructure is proposed through the development of electron tomography using (S)TEM, and ‘dual beam’ SEM-FIB, techniques offering complementary approaches to 3D imaging across lengthscales stretching over 5 orders of magnitude. We propose to extend tomography to include novel methods to determine atom positions in 3D with approaches incorporating new reconstruction algorithms, image processing and complementary nano-diffraction techniques. At the nanoscale, true 3D nano-metrology of morphology and composition is a key objective of the project, minimizing reconstruction and visualization artefacts. Mapping strain and optical properties in 3D are ambitious and exciting challenges that will yield new information at the nanoscale. Using the SEM-FIB, 3D ‘mesoscale’ structures will be revealed: morphology, crystallography and composition can be mapped simultaneously, with ~5nm resolution and over volumes too large to tackle by (S)TEM and too small for most x-ray techniques. In parallel, we will apply 3D imaging to a wide variety of key materials including heterogeneous catalysts, aerospace alloys, biomaterials, photovoltaic materials, and novel semiconductors. We will collaborate with many departments in Cambridge and institutes worldwide. The personnel on the proposal will cover all aspects of the tomography proposed using high-end TEMs, including an aberration-corrected Titan, and a Helios dual beam. Importantly, a postdoc is dedicated to developing new algorithms for reconstruction, image and spectral processing."

2 337 330 €

Start date: 2012-01-01, End date: 2017-12-31

The goal of crystal engineering is the design of functional crystalline materials in which the arrangement of basic structural building blocks imparts desired properties. The engineering of organic molecular crystals has, to date, relied largely on empirical rules governing the intermolecular association of functional groups in the solid state. However, many materials properties depend intricately on the complete crystal structure, i.e. the unit cell, space group and atomic positions, which cannot be predicted solely using such rules. Therefore, the development of computational methods for crystal structure prediction (CSP) from first principles has been a goal of computational chemistry that could significantly accelerate the design of new materials. It is only recently that the necessary advances in the modelling of intermolecular interactions and developments in algorithms for identifying all relevant crystal structures have come together to provide predictive methods that are becoming reliable and affordable on a timescale that could usefully complement an experimental research programme. The principle aim of the proposed work is to establish the use of state-of-the-art crystal structure prediction methods as a means of guiding the discovery and design of novel molecular materials. This research proposal both continues the development of the computational methods for CSP and, by developing a computational framework for screening of potential molecules, develops the application of these methods for materials design. The areas on which we will focus are organic molecular semiconductors with high charge carrier mobilities and, building on our recently published results in Nature [1], the development of porous organic molecular materials. The project will both deliver novel materials, as well as improvements in the reliability of computational methods that will find widespread applications in materials chemistry. [1] Nature 2011, 474, 367-371.

1 499 906 €

Start date: 2012-10-01, End date: 2017-09-30

"The objective of this proposal is to tackle two of the greatest challenges in quantum chemistry: (i) extending the applicability of highly accurate wave function methods to large molecular systems, and (ii) developing accurate and robust multi-reference methods that can be used for studying important but very difficult problems in transition metal chemistry, catalysis, and photochemistry. Solutions to these problems have now come within reach due to three advances we recently reported: first, the steep scaling of the computational cost with molecular size can be reduced to linear by exploiting the short-range character of electron correlation (local correlation methods). Second, the accuracy, efficiency, and robustness of these local correlation methods can be strongly improved by new tensor decomposition approaches and the inclusion of terms depending explicitly on the inter-electronic distances (F12 methods). Third, the development of highly complex electronic structure theories can be greatly facilitated and accelerated by new automated tensor network evaluation techniques. We are certain that by combining and generalizing these advances the long-standing problems (i) and (ii) can be solved. We will focus especially on highly scalable algorithms in order to use massively parallel computer systems efficiently. For linear-scaling methods this means that the size of the molecules that can be treated in a fixed time will grow linearly with the number of available processors. We will furthermore explore new multi-reference ansätze and implement analytical energy gradients and response properties for local methods. Hybrid and embedding methods to account for solvent and environment effects will also be investigated. It is our priority to make our new methods as easy to use, robust, and widely applicable as possible. We believe that they will open entirely new horizons for innumerable applications in chemistry, physics, biology, and materials science."

2 454 000 €

Start date: 2013-02-01, End date: 2018-01-31