The internet transmits data with a rate of hundreds of Terabits per second (Tbit/s), consumes 9% of the worldwide produced electrical energy and is growing at a rate of 20 - 30 % per year. One single carrier produced by a laser diode, can provide the data transmission of 26 Tbit/s. By combining optical carriers with TeraHertz (THz) waves as well, data rates of several Tbit/s can be transmitted over a wireless link, which will enable hybrid optical/THz wireless links. The next/sixth generation (6G) communication network is expected to be commercialised from 2030. 6G will generate greater diffusion and provide technical platforms to solve social, economic and humanity issues with higher data rates, wider bandwidth and lower latency. The urgency and challenges require the development of revolutionary technologies to meet the projected performance levels. These developments are captured in the recent beyond-5G roadmaps from research forums such as WWRF, NetWorld2020, H2020 5G-PPP, 6G-Summit, USA NSF, industry organizations including 3GPP, IEEE, ETSI, ITU-R, ITU-T, and spectrum regulatory forums e.g., FCC, ECC, OFCOM, WRC'19 [https://doi.org/10.3390/electronics9020351]. At the University of Glasgow (UofG), more than 10 research groups in James Watt School of Engineering are working on enabling technologies in the area of wireless communications, optical networking and a mix of fibre optics, millimetre wave and ultrafast THz wireless links. Such concepts require novel semiconductor devices and circuits that must be characterised at an early stage of development, i.e. at chip level, once they are manufactured at our James Watt Nanofabrication Centre (JWNC). To support this research, this project aims to establish an on-chip device and integrated circuit test cluster together with a carrier independent, ultra-high data transmission rate and processing system to measure key performance indicators in both the user and control planes. The proposed Test Cluster is the first of this kind in the world that allows complex signal and waveforms directly deployed to devices under test on chip. This will trigger new device concepts as well as enable development of transceiver architectures. This work will potentially create industry game changers. The Cluster consists of three key modules: waveform generation, signal analysis, and device characterisation. The three modules can operate individually or collectively and are built around a semi-automated probe station and an optical bench to allow on-chip probing, quasi-optics coupling and over-the-air characterisation setups. The waveform generation module can generate CW and wideband high-speed complex waveforms (>40 GHz) to meet the requirements of future communications for frequencies up to 1.1 THz. The signal analysis module can perform spectrum analysis of signal sources as well as real-time signal analysis on ultra-wideband, high data rate, complex signals in time domain for frequencies up to 1.1 THz. The device characterisation module permits continuous/pulsed current-voltage, network analysis and active load-pull measurements up to 1.1 THz. We are targeting measurements in hybrid transmission systems of several hundred Gigabits per second (Gbit/s). To allow other external groups and industry to use this unique measurement system for their research and development, a key aspect of the new measurement system is the possibility for remote control of all parameters via the Internet, which will enable use of the measurement system without the need to move the measurement system around and allow remote access to real-time data.

The electronics industry "ElecTech" sector is central to the UK's future economy, environment, and society. With over 1 million employees in sectors enabled by electronics, the contribution of electronic technologies is indispensable. At the heart of electronics are nanoelectronic semiconductor "chips", and it has a leading position in semiconductor intellectual property vendors and emerging areas such as quantum technologies, sustainable electronics manufacturing, and compound semiconductors. The UK's potential lies, and where its future role in the global semiconductor value chain lies, as evidenced in the BEIS committee inquiry. We will establish an Automated Nano AnaLysing, characterisatiOn and additive packaGing sUitE (ANALOGUE) suite. ANALOGUE will be an exemplary facility that provides a fully automated platform for semiconductor processing, from devices to applications, with centralised workflow design, data collection/capture and real-time analytics. ANALOGUE will enable wafer-scale fully automated electrical characterisation of devices including reliability and temperature cycling capabilities. A fully automated back-end processing platform is integrated enabling die- and wire-bonding, 3D printed electronics and additive heterogenous packaging, co-located with high-resolution printed circuit laser patterning. Co-located with the £35M James Watt Nanofabrication Centre (JWNC), and the Centre for Advanced Electronics (CAE), the facility will enable devices-to-systems across the ICT spectrum, towards a user-centric and responsible design approach for electronics manufacturing. With a team representing two application-oriented user groups, medical and industrial nanoelectronics, we will create an ecosystem whereby manufacturing, users, and circular economy experts are brought together as users of ANALOGUE. ANALOGUE will support research on implantables, wearables, and diagnostics, through ultrasonic devices. Embedding sustainable manufacturing and onshoring the research into the backend processes of electronics is crucial to meeting the requirements of future electronics design flows. Original Equipment Manufacturers (OEM) buyers like Apple are already demanding commitments from suppliers to decarbonise their products, with distributors expected to assess each product's environmental impact throughout its lifecycle - from design and manufacture to end-of-life. As such, ANALOGUE allows UK researchers to explore the "black-box" of the semiconductor supply chain using automated characterisation and heterogenous packaging, encompassed by an automation and data collection framework for evaluating the efficacy of our experimental workflows. ANALOGUE will be accessible to the UK's research community across HealthTech, Beyond-Moore Computing, and Circular and Sustainable Electronics. Owing to its automated and streamlined nature, ANALOGUE will allow users from different institutions to utilise the suite remotely, facilitated by expert technical support, enabling rapid innovation across the nanoelectronics spectrum, insulating the UK's electronics research eco-system from global supply chain interruptions, e.g. chip shortages, and underpinning new research into otherwise offshore aspects of the electronics manufacturing. ANALOGUE builds on the UK's internationally acknowledged strengths in low-power IC Design, electronic materials, and applications in sustainable manufacturing. The Glasgow collaboration as an essential link in the supply chain linking materials producers (e.g., IQE), designers (Arm) manufacturers (PragmatIC Semiconductors, Printed Electronics, MTC), with academic users. The ANALOGUE team will regularly engage with these stakeholders through joint projects, meetings, workshops, and targeted events. The alignment of the proposal with the strategic sustainable systems focus of UofG will also help the envisaged research's long-term planning and strategy building.

The current AI paradigm at best reveals correlations between model input and output variables. This falls short of addressing health and healthcare challenges where knowing the causal relationship between interventions and outcomes is necessary and desirable. In addition, biases and vulnerability in AI systems arise, as models may pick up unwanted, spurious correlations from historic data, resulting in the widening of already existing health inequalities. Causal AI is the key to unlock robust, responsible and trustworthy AI and transform challenging tasks such as early prediction, diagnosis and prevention of disease. The Causality in Healthcare AI with Real Data (CHAI) Hub will bring together academia, industry, healthcare, and policy stakeholders to co-create the next-generation of world-leading artificial intelligence solutions that can predict outcomes of interventions and help choose personalised treatments, thus transforming health and healthcare. The CHAI Hub will develop novel methods to identify and account for causal relationships in complex data. The Hub will be built by the community for the community, amassing experts and stakeholders from across the UK to 1) push the boundaries of AI innovation; 2) develop cutting-edge solutions that drive desperately needed efficiency in resource-constrained healthcare systems; and 3) cement the UK's standing as a next-gen AI superpower. The data complexity in heterogeneous and distributed environments such as healthcare exacerbates the risks of bias and vulnerability and introduces additional challenges that must be addressed. Modern clinical investigations need to mix structured and unstructured data sources (e.g. patient health records, and medical imaging exams) which current AI cannot integrate effectively. These gaps in current AI technology must be addressed in order to develop algorithms that can help to better understand disease mechanisms, predict outcomes and estimate the effects of treatments. This is important if we want to ensure the safe and responsible use of AI in personalised decision making. Causal AI has the potential to unearth novel insights from observational data, formalise treatment effects, assess outcome likelihood, and estimate 'what-if' scenarios. Incorporating causal principles is critical for delivering on the National AI Strategy to ensure that AI is technically and clinically safe, transparent, fair and explainable. The CHAI Hub will be formed by a founding consortium of powerhouses in AI, healthcare, and data science throughout the UK in a hub-spoke model with geographic reach and diversity. The hub will be based in Edinburgh's Bayes Centre (leveraging world-class expertise in AI, data-driven innovation in health applications, a robust health data ecosystem, entrepreneurship, and translation). Regional spokes will be in Manchester (expertise in both methods and translation of AI through the Institute for Data Science and AI, and Pankhurst Institute), London (hosted at KCL, representing also UCL and Imperial, leveraging London's rapidly growing AI ecosystem) and Exeter (leveraging strengths in philosophy of causal inference and ethics of AI). The hub will develop a UK-wide multidisciplinary network for causal AI. Through extended collaborations with industry, policymakers and other stakeholders, we will expand the hub to deliver next-gen causal AI where it is needed most. We will work together to co-create, moving beyond co-ideation and co-design, to co-implementation, and co-evaluation where appropriate to ensure fit-for-purpose solutions Our programme will be flexible, will embed trusted, responsible innovation and environmental sustainability considerations, will ensure that equality diversity and inclusion principles are reflected through all activities, and will ensure that knowledge generated through CHAI will continue to have real-world impact beyond the initial 60 months.