The goal of Laser Inertial Confinement Fusion (ICF) is to create and ignite a minute star. The energy liberated through thermonuclear fusion can be harnessed, providing mankind with an essentially limitless source of safe, sustainable, secure, carbon-free, electricity. If realised, laser-fusion would not only provide a solution to global warming, but enable the UK to become a net energy exporter, and also create a new market in ultra-high-tech technology exports in areas where the UK is currently world-leading, such as laser and targetry manufacture. The multi-billion dollar National Ignition Facility (NIF) is currently the only laser which, in principal, has sufficient energy to achieve ignition (where the 'star' burns), although to-date NIF has not achieved ignition. The base-line 'indirect-drive' NIF design uses an array of laser beams to create x-rays in a metallic cylinder (hohlraum), these x-rays in turn ablate the spherical ICF target, driving a convergent implosion. This causes the target to be compressed, creating density and temperature conditions similar to those within the centre of the Sun, thereby igniting the 'star'. While there are some advantages to the indirect-drive approach to ICF, it is extremely inefficient, and it is currently unclear whether it will be possible to achieve indirect drive ignition with the laser energy available on NIF. Alternative ICF schemes exist including 'direct drive' and 'shock ignition'. Here, the lasers directly illuminate the target improving efficiency by a factor of ~5, meaning it should be possible to achieve ignition with NIF's energy. Shock ignition is a recently invented variant of direct drive. Here the implosion velocity can be lower than the minimum required for ignition, instead ignition is initiated by a strong shock launched towards the end of the implosion. Shock ignition has many potential advantages over other ICF schemes; the laser energy requirements for ignition are well within those possible on NIF, as the implosion velocity can be lower, the susceptibility to deleterious fluid instabilities (Rayleigh-Taylor) is also reduced. Importantly, the energy gain (fusion energy out/electrical energy in) should be sufficient for power generation. Laser-plasma interaction instabilities (LPI) such as Stimulated Raman Scatter, Two Plasmon Decay and Stimulated Brillouin Scatter occur in all ICF schemes. These LPIs alter the temporospatial characteristics of laser absorption and can create significant populations of energetic (or hot) electrons. Determining the characteristics of the LPIs and the associated hot electrons is of critical importance for ICF as they dictate whether the fusion fuel will be heated prior to the fuel being compressed (pre-heat) - potentially precluding ignition - or whether the hot electrons' energy can be harnessed, enhancing shock generation in the shock ignition scheme, potentially leading to fusion energy gains sufficient for energy applications on today's lasers. This crucial area of ICF physics is the focus of this proposal. New experiments on the Omega laser facility will measure the LPI and hot electron characteristics in the parameter spaces of ignition-scale direct drive and shock ignition. A key outcome will be the encapsulation of the experimental data in innovative new laser-plasma interaction and hot electron simulation models, which will run in-line with the UK's radiation-hydrodynamics code framework: Odin. These will significantly improve our predictive simulation capabilities, providing benchmarked, high-fidelity simulation tools which will be made openly available to the UK academic laser-plasma physics community. This work, with direct involvement and leadership of ICF experiments on large scale facilities, provides a clear route by which the UK community can attain the skills, expertise, and tools to develop next-generation ICF designs for, and execute experiments on, the world's largest largest lasers into the 2020s.

The basic theme of this research is to use random walks and interacting particle systems to improve network exploration and structure. Our aim is to study algorithmic problems in Computer Science modeled by particles (agents, messages, robots) moving more or less randomly on a large network. We suppose such particles may be single or numerous, of various types, and that they may able to interact with each other and with the network. We assume the particles have a purpose either in relation to the network, such as searching the network or modifying its structure; or in relation to other particles, such as passing messages to each other. Many large networks can be found in modern society, and obtaining information from these networks is an important problem. Examples of such networks include the World Wide Web, and social networks such as Twitter and FaceBook. These networks are very large, change over time and are essentially unknowable or do not need to be known in detail. They are highly interlinked (e.g. URL's embedded in Twitter and FaceBook) and can be viewed as part of a larger whole. New social networks appear frequently, and the influence of these networks on social, economic and political aspects of everyday life is substantial. Searching, sampling and indexing the content of such networks is a major application area a substantial user of computer time, and likely to become more so in the future. The evolving use of these networks is changing social and economic behavior. Improving the ability to search such networks is of value to us all. Random walks are a simple method of network exploration, and as such, are particularly suitable for searching massive networks. A random walk traverses a network by moving from its current position to a neighboring vertex chosen at random. Decisions about where to go next can be taken locally, and only limited resources are needed for the search. The exploration is carried out in a fully distributed manner, and can adapt easily to dynamic networks. The long run behavior of the walk acts as a distributed voting mechanism, in which the number of visits to a vertex is proportional to its popularity or accessability. Suppose we could alter the behavior of the random walk to reduce the search time. How can this be done, and at what cost? Speeding up random walks, to reduce search time, is a fundamental question in the theory of computing. The price of this speed up, is normally some extra work which is performed locally by the walk, or undertaken by the vertices of the graph. Possible ways of speeding up random walks we have identified include biassed transitions, use of previous history and local exploration around current position. One way to reduce search time is to use several random walks which search simultaneously. In the simplest model the walks are oblivious of each other and do not interact in any way. Search time should be reduced, but at the expense of using additional walks. Suppose we could also allow the random walks to interact with each other, or with the underlying network? How should this interaction be designed, in order to speed up search, and what other applications might it have? Historically, interacting particle systems have only been analyzed on infinite networks, and even then not with computer science applications in mind. Recently, we began to make progress in this direction, and found that many related problems such as distributed voting, to elect a leader for example, could be understood in the framework we developed. Potential applications of interacting particle systems are many and include: Gossiping and broadcasting among agents moving on a network, Models of epidemics spreading between particles and the graph, Distributed search with intelligent robots, Software agents moving in an intranet. Models of voting and social consensus. Good agents chasing bad agents on a network.

Light is energy. Sunlight can be harnessed by solar cells, for instance, turning light into electricity, which can, in turn, be used to power big and small devices. This is, however, a rather inefficient process and light can be used differently for various applications. One way to efficiently use light is through a photothermal material, which converts light into heat. Heat is an important user of fossil fuels: industrial processes for instance consume vast quantities of fossil fuels. It has been reported that 4.2% of worldwide delivered energy is consumed manufacturing basic inorganic, organic, and agricultural chemicals. Of this 17 quadrillion Btu, 78% comes from liquid fuels, natural gas, and coal, leading to greenhouse gas emissions. [1] A substantial fraction of these fuels are used to heat up chemical reactions, while free, green, and abundant sunshine could instead provide the required energy via a photothermal material. Heat also heals: photothermal materials injected near cancer cells can be excited by an otherwise non-interacting infrared light, leading to local temperature rise (of the order of 10s of degrees) sufficient to kill cancer cells without any surgery or chemotherapy. This proposal targets the development of a new class of biocompatible photothermal material based on the 8th most abundant element in earth's crust, magnesium. We have shown previously that small particles of magnesium are stable in air and interact strongly with light. Magnesium, like gold and silver, is extraordinarily good at absorbing light because its interaction is different than that of simple "black" materials. Indeed, these nanoparticles act like antenna for light and consequently absorb more light than their physical footprint. This phenomenon is truly nanoscale; it involves the light-driven oscillation of electrons in small metallic particles and is called localized surface plasmon resonance. In the two years of this project, we first aim to develop ways to make large quantities of magnesium nanostructures, suitable for industrial-scale production. We will then demonstrate their ability to efficiently produce heat from light, and will study how to best match the particle size to the specific application, for both sunlight-matched and medical applications. At the end of the project, we will be in a position to approach industrial partners to discuss further development and commercialization of these new green technologies. [1] Energy Information Administration, Government Publications Office, International Energy Outlook: 2016 with Projections to 2040. U.S. Government Printing Office: 2016.

Atmospheric composition and climate are closely linked because compounds such as carbon dioxide and methane are greenhouse gases: increases in their concentration are expected to warm the atmosphere. Such increases have occurred in the last two centuries, and are expected to accelerate in the next few decades. However, exactly how these concentrations and climate will evolve together depends on processes that link them within the so-called Earth System. Our understanding of these processes is expressed in models that represent and connect parts of the system such as the growth of vegetation, ocean circulation, atmospheric circulation and chemistry, etc. However, the best way we have of validating whether these models are correctly representing the Earth is by looking at the past. Various palaeoclimate records provide us with a view of how climate has behaved in the past. The ice core record is particularly valuable because it shows how both climate and atmospheric composition have evolved over the last 800,000 years. During this time, the Earth has passed into and out of glacial states many times, and it turns out that the principal greenhouse gases and climate have varied together during this period. Carbon dioxide and methane have high concentrations during warm interglacials and low concentrations in cold glacials. They thus offer numerous examples of how climate reacts to changes in atmospheric composition, and strong clues about how the sources and sinks of carbon dioxide and methane react to climate change. Our current understanding is that methane increases when climate warms because of a combination of expanded wetland sources and diminished atmospheric sinks. However, we lack many details about these sources and sinks, and have no clear evidence to differentiate their respective roles. For carbon dioxide, the changes are believed to stem mainly from processes in the Southern Ocean, but within this view there are a number of competing hypotheses. This proposal will combine the strongest elements of the relevant observational and modelling communities in the UK and France. Firstly, we will examine both the ice core and other datasets to provide as many constraints as possible on the causes of change in concentration of carbon dioxide and methane. This will involve particularly new measurements of isotopes of carbon that are diagnostic of sources, and new measurements of marine sediments in the Southern Ocean that can constrain mechanisms for changes in the carbon cycle. Particular aspects of the emission and processing of methane and carbon dioxide will be considered in order to make necessary improvements in models. We will then use a variety of models of different levels of complexity to explore the major changes seen in the ice record: between cold glacials and warm interglacials, between different interglacials, and at other particular times in the last 800,000 years that may allow us to differentiate the operation of certain mechanisms. Detailed models, including the new QUEST Earth System Model, will be used to assess the production and loss of methane at particular times in the record. Models of lower complexity will be run over longer time periods to determine the expected signal in different palaeoclimate archives of various mechanisms for changes in carbon dioxide, with a view to narrowing the uncertainties on the importance of each mechanism. Models will also be used to test whether we can understand the different climates seen in past interglacials knowing the energy input from the Sun and the concentrations of greenhouse gases seen in ice cores. The end result of this project will be an improved ability to simulate the past, a better understanding of the processes that control atmospheric composition, climate and the carbon cycle and, as an end result, an improved representation of all relevant processes in models used to predict the future evolution of the Earth System.

Deoxyribonucleic acid, or DNA, is a long polymer made up of repeating units called nucleotides. Each nucleotide consists of three components: sugar, phosphate and base. There are four possible bases that can be attached to the sugar-phosphate backbone, thymine (T), adenine (A), guanine (G) and cytosine (C). A specific base sequence along the chain enables DNA to encode a set of unique instructions for the synthesis of various biological components of the cell, for example a particular protein. DNA can adopt different conformations and structures in solution but the most common one is called B-DNA, where two polymer strands combine (hybridise) through base-pairing to form a right-handed double helix (or duplex).Due to its crucial role in initiating cell division (i.e. growth of an organism), DNA has long been a target for drugs, in particular anti-cancer compounds. However more recently, chemists have become interested in ways of chemically modifying DNA by attaching other groups (or tags) to the polymer chain. Part of this interest has stemmed from a need to sense DNA, in particular specific base sequences that could signify a genetic disease. We have shown that by attaching fluorescent groups to a DNA probe strand, a selective sensor can be designed that enables two target strands, 15 bases long, that differ only in the identity of one of their bases (G instead of A), to be told apart. This is a result of the two duplexes (each formed from the target strand binding to the probe strand) giving different different emission profiles (colour intensities) upon hybridisation. In this fellowship, we wish to explore and rationalise these findings in more detail and work with end users so that the viability of this new approach to detecting these so-called single nucleotide polymorphisms (or SNPs, pronounced 'snips') in DNA can be assessed.We also wish to extend the chemical modification of DNA further by introducing groups that give DNA even more functionality. One particular aspect concerns so-called photochromic groups that undergo a reversible structural change upon their exposure to light. If these groups are attached to DNA, then the structure of DNA should also change upon photo-irradation, which in turn should control its biological function.Using a similar approach, we will also attach groups to DNA that respond to an oxidising potential rather than light. These so-called redox-active groups can be oxidised which, if attached to DNA, allow DNA to be sensed electrochemically through the flow of current. We wish to use redox-active groups that are not only tagged to DNA but also interact with the structure itself through a process called intercalation, where a group inserts itself between the base pairs of duplex DNA. Through this approach, we expect that electrochemical DNA sensing can be made more effective and sensitive. Finally, we wish to incorporate the redox-active group ferrocene into the actual backbone of DNA through its replacement of a sugar-phosphate-sugar motif to create synthetic mimics of DNA. If such a process is successful, then oxidation of the ferrocene groups could change the stability of the DNA duplex in an unprecedented manner, allowing redox processes to control various DNA functions.