Breakthroughs in battery technologies are critically needed to enable the widespread adoption of electric vehicles and the grid-scale storage of renewable energy. Solid-state batteries using a lithium (Li) metal anode are rapidly emerging and promise greater range and charging speeds, as well as improved safety. However, dendrite formation almost universally compromises such cells, and they quickly fail under realistic operating conditions. Only inorganic glassy solid electrolyes (SEs) have shown the exceptional ability to "template" stable Li plating/stripping at relevant rates. However, these SEs remain underexplored as they require high-cost, low-throughput vacuum deposition techniques that are incompatible with large-scale battery production. The aim of this research proposal is to engineer a new family of scalable "templating layers" to enable high-rate solid-state batteries. Taking inspiration from vacuum-deposited SEs -- namely the homogeneous, non-crystalline (glass) structure, electrically insulating nature and very flat morphology of the SE used -- we will use low temperature, solution-based techniques that can realise these key attributes and be easily scaled-up to industrially relevant levels. A major challenge in engineering glassy materials stems from their inherent disorder, meaning the critical relationships between atomic structure, electrochemical properties and processing usually remain elusive. A suite of advanced characterisation methods, including X-ray scattering, thermal desorption spectroscopy and operando imaging, will uncover new design rules that span materials to devices. The outputs of this study will be invaluable for the study of disordered functional coatings and have wide impact in energy storage, especially to related battery chemistries, microelectronics and sensing applications.

The development of innovative autonomous vehicles (AV) with increased efficiency and low carbon emissions is of interest to many different organisations across the world, at both political, commercial and research levels. Economically benefits are estimated to be worth £1.5 trillion by 2025. Recognising the potential, transportation authorities are already investing heavily in studies to exploit these innovative technologies through the development of 'platooning' methods, whereby a series of vehicles run in close formation, exploiting potential energy savings created through a reduction in drag, further enabling greater mobility. In the immediate future, it is likely the freight haulage industry will be the first users to introduce autonomous technologies on a network-wide scale. The UK road network provides the ideal test bed for developing these innovative technologies, due to the complexities of adopting such systems within a highly congested network, with traffic moving at variable speeds. Ensuring AVs and platooning methods are appropriate for challenging transport systems, such as that in the UK, will enable these systems to be adopted on an international scale more easily. To date, most AV research has focused on ensuring the technical possibilities for vehicles travelling in close formation through the implementation of autonomous guidance systems. These factors are however only one area of consideration when introducing new operational methods that involve complex vehicle interactions into an already a complex transport mode. Fundamental research undertaken at the University of Birmingham (UoB) (EP/N004213/1) has shown that aerodynamic forces will, in many cases, be the governing design parameter. There is a need to understand and correctly account for the highly turbulent aerodynamic flow created around platoons and unsteady forces leading to vehicle instabilities and dangerous conditions for other road users. This proposal is concerned with the technical area of vehicle aerodynamics associated with close running vehicles and the aerodynamic interactions with other vehicles and road users. In particular the following aspects will be investigated: -Overall stability of close formation vehicles (Heavy Goods Vehicles (HGVs)), particularly the interaction of unsteady aerodynamic flows between platooning vehicles and other road users. -The aerodynamic implications in terms of stability and overall drag for vehicles moving out of alignment with other vehicles in a platoon and the interaction of overtaking vehicles. -The aerodynamic interaction of a passing platoon of HGVs with other road users leading to potential stability and safety issues. The fundamental research questions will be addressed by novel approaches: -A fundamental physical modelling programme at the UoB moving model TRAIN rig facility. Detailed measurement of vehicle surface pressure (such that aerodynamic forces can be calculated) will determine the nature of the flow field and the aerodynamic interaction of vehicles. Multi-hole pressure probe measurements will investigate the unsteady flow to determine potential stability and safety implications as a platoon passes. -Development of an analytical framework, providing a method to help industry assess the magnitude of aerodynamic loads on roadside workers and other road users. The current study is seen as a necessary precursor to the introduction of AV technologies. In depth understanding of these practical issues underpins the safe, timely and cost effective implementation of these new technologies. This project will, for the first time, address these issues, developing an understanding of aerodynamic effects, not only for platooning vehicles but also other road users interacting with the platoon on public transport systems. The national importance of AVs forms an integral part of the Government strategic vision for transport and is of considerable importance to a variety of stakeholders.

Hydrogen will play a central role in the clean economy and in meeting ambitious climate targets. However, to realise its full potential, we must enable low cost, widespread production of zero-carbon H2 by water electrolysis, powered using renewable energy. Underlying this challenge is improved understanding of these complex systems from atoms to cells under real world operating conditions. AMPERE brings together experts from academia, national laboratories and industry to diagnose and understand degradation and performance-limiting processes in electrolysers. Crucially, this project will address the effects of system dynamics, a key but often overlooked aspect of operation when using intermittent energy sources such as solar and wind. We will leverage a unique toolbox of state-of-the-art measurement techniques, spanning length scales from ionic motion in the polymer membrane, to local electrochemical activity across electrode assemblies, water management and bubble formation. This will produce the definitive picture of multi-scale electrolyser dynamics and our focus on realistic production rates and in-situ/operando methods will ensure these insights will have practical relevance. Thus, the outputs of AMPERE will help usher in zero-carbon H2 at scale, as a chemical feedstock and energy vector for clean power generation, heating and transportation.

Trusted Execution Environments (TEEs) shield computations using security-sensitive data (e.g. personal data, banking information, or encryption keys) inside a secure "enclave" from the rest of the untrusted operating system. A TEE protects its data and code even if an attacker has gained full root access to the untrusted parts of the system. Today, TEEs like ARM Trustzone and Intel SGX are therefore widely used in general-purposes devices, including most laptops and smartphones. But with increasingly wide-spread use, TEEs have proven vulnerable to a number of hardware and software-based attacks, often leading to the complete compromise of the protected data. In this project, we will use capability architectures (as e.g. developed by the CHERI project) to protect TEEs against such state-of-the-art attacks. We address a wide range of threats from software vulnerabilities such as buffer overflows to sophisticated hardware attacks like fault injection. CAP-TEE will provide a strong, open-source basis for the future generation of more secure TEEs. When developing such disruptive technologies, it is key to minimise the efforts for porting existing codebases to the new system to facilitate adoption in practice. In CAP-TEE, we therefore focus on techniques to ease the transition to our capability-enabled TEE. In industrial cases studies for the automotive and rail sector, we will demonstrate how complex code written in a memory-unsafe language like C(++) can be seamlessly moved to our platform to benefit from increased security without a full redesign.

Autonomous systems, such as medical systems, autonomous aerial and road vehicles, and manufacturing and agricultural robots, promise to extend and expand human capacities. But their benefits will only be harnessed if people have trust in the human processes around their design, development, and deployment. Enabling designers, engineers, developers, regulators, operators, and users to trace and allocate responsibility for the decisions, actions, failures, and outcomes of autonomous systems will be essential to this ecosystem of trust. If a self-driving car takes an action that affects you, you will want to know who is responsible for it and what are the channels for redress. If you are a doctor using an autonomous system in a clinical setting, you will want to understand the distribution of accountability between you, the healthcare organisation, and the developers of the system. Designers and engineers need clarity about what responsibilities fall on them, and when these transfer to other agents in the decision-making network. Manufacturers need to understand what they would be legally liable for. Mechanisms to achieve this transparency will not only provide all stakeholders with reassurance, they will also increase clarity, confidence, and competence amongst decision-makers. The research project is an interdisciplinary programme of work - drawing on the disciplines of engineering, law, and philosophy - that culminates in a methodology to achieve precisely that tracing and allocation of responsibility. By 'tracing responsibility' we mean the process of tracking the autonomous system's decisions or outcomes back to the decisions of designers, engineers, or operators, and understanding what led to the outcome. By 'allocating responsibility' we mean both allocating role responsibilities to different agents across the life-cycle and working out in advance who would be legally liable and morally responsible for different system decisions and outcomes once they have occurred. This methodology will facilitate responsibility-by-design and responsibility-through-lifecycle. In practice, the tracing and allocation of responsibility for the decisions and outcomes of AS is very complex. The complexity of the systems and the constant movement and unpredictability of their operational environments makes individual causal contributions difficult to distinguish. When this is combined with the fact that we delegate tasks to systems that require ethical judgement and lawful behaviour in human beings, it also gives rise to potential moral and legal responsibility gaps. The more complex and autonomous the system is, the more significant the role that assurance will play in tracing and allocating responsibility, especially in contexts that are technically and organisationally complex. The research project tackles these challenges head on. First, we clarify the fundamental concepts of responsibility, the different kinds of responsibility in play, the different agents involved, and where 'responsibility gaps' arise and how they can be addressed. Second, we build on techniques used in the technical assurance of high-risk systems to reason about responsibility in the context of uncertainty and dynamism, and therefore unpredictable socio-technical environments. Together, these strands of work provide the basis for a methodology for responsibility-by-design and responsibility-through-lifecycle that can be used in practice by a wide range of stakeholders. Assurance of responsibility will be achieved that not only identifies which agents are responsible for which outcomes and in what way throughout the lifecycle, and explains how this identification is achieved, but also establishes why this tracing and allocation of responsibility is well-justified and complete.