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Quantum information processing with spatially structured light
No full textQudits have proven to be a powerful resource for quantum information processing, offering enhanced channel capacities, improved robustness to noise, and highly efficient implementations of quantum algorithms. The encoding of photonic qudits in transverse-spatial degrees of freedom has emerged as a versatile tool for quantum information processing, allowing access to a vast information capacity within a single photon. We examine recent advances in quantum optical circuits with spatially structured light, focusing particularly on top-down approaches that employ complex mode-mixing transformations in free space and fibers. We highlight circuits based on platforms such as multi-plane light conversion, complex scattering media, multi-mode, and multi-core fibers. We discuss their applications for the manipulation and measurement of multi-dimensional and multi-mode quantum states. Furthermore, we discuss how these circuits have been employed to perform multi-party operations and multi-outcome measurements, thereby opening new avenues for scalable photonic quantum information processing
An analytical framework of quantifying carbon emission impacts of construction and demolition waste circularity and trading: A case study of the UK
No full textDeveloping a circular economy (CE) for construction and demolition waste (CDW) presents a promising pathway to decarbonize the construction industry by reducing reliance on carbon-intensive primary material production. However, most existing studies rely on life cycle assessment (LCA) approaches and treat CDW flows as isolated processes, overlooking the broader economy-wide emission consequences and distributional effects arising from complex inter-sectoral and inter-regional material and energy flows. This limitation risks underestimating the full carbon mitigation potential of CDW circularity, thereby hindering progress toward the Net-Zero targets pledged by most global economies. This study introduces a novel analytical framework integrating LCA with environmentally extended input-output (EEIO) analysis to quantify the environmental impacts of CDW circularity, explicitly accounting for sectoral and regional trading linkages. Applying the framework to the United Kingdom (UK), this study estimates carbon emissions and potential savings under multiple CDW circularity scenarios for the year 2018. The results indicate that material use for domestic final demand and exports generates approximately 159 and 170 million tonnes of CO₂, respectively, while CDW circularity achieves only modest emission savings of 2–3 million tonnes (<1%). Reuse scenarios deliver greater reductions than recycling, with the most significant benefits observed in secondary and tertiary industries, particularly from the circular use of metallic and wood materials. Despite the UK's high CDW recovery rate, inefficient treatment pathways and weak alignment between recovered-material supply and industrial demand constrain the net-zero potential of CDW circularity. Enhancing recovery efficiency, advancing cleaner technologies, and improving material productivity are therefore critical for supporting the UK's net-zero transition. This study is novel in pioneering one of the first LCA–EEIO analytical frameworks for evaluating the economy-wide environmental impacts of CDW circularity, providing a scalable methodological foundation and system-level evidence for global economies seeking to accelerate their pathways toward Net-Zero targets
From dilemmas to paradoxes:A complex systems view of sustainability management in UK universities
No full textRecently, universities have transformed from passive contributors to active participants in the global sustainability movement. However, the absence of robust theoretical frameworks and larger-scale samples has limited the progress that universities can make towards becoming sustainable. By applying complex adaptive systems and taking stock for the first time of a whole national sector's progress towards sustainability (n = 137), combined with semi-structured interviews from a representative sample of institutions (n = 25), this paper contributes a much-needed theoretical conceptualisation. It highlights the relationship between organisational control and change in universities, identifying structural and relational conditions that shape institutional approaches to sustainability. Our typology of sustainability approaches reveals a paradox of control: as universities yield control over the operationalisation of sustainability, they create more favourable conditions for effective organisational change. We identify four archetypes of sustainability approaches across the UK university sector, each characterised by different configurations of coupling between value-adding activities (such as teaching and research) and non-value-adding activities (such as campus operations). These archetypes demonstrate varying orientations towards system adaptation. In some cases, institutions direct resources to activities aligned with their disciplinary expertise and sources of financial value, while in others, efforts are directed towards controlling features of the operating environment that remain inherently uncertain. The findings illustrate how universities interpret and respond to conditions of complexity and uncertainty, producing organisational logics that shape the scope and potential resilience of their sustainability strategies. The practice-relevant findings provide valuable insights for change agents in universities, empowering them to advocate for actions and assist university managers in making informed decisions about implementation.</p
AI-Driven Enzyme Engineering: Emerging Models and Next-Generation Biotechnological Applications
No full textEnzyme engineering drives innovation in biotechnology, medicine, and industry, yet conventional approaches remain limited by labour-intensive workflows, high costs, and narrow sequence diversity. Artificial intelligence (AI) is revolutionising this field by enabling rapid, precise, and data-driven enzyme design. Machine learning and deep learning models such as AlphaFold2, RoseTTAFold, ProGen, and ESM-2 accurately predict enzyme structure, stability, and catalytic function, facilitating rational mutagenesis and optimisation. Generative models, including ProteinGAN and variational autoencoders, enable de novo sequence creation with customised activity, while reinforcement learning enhances mutation selection and functional prediction. Hybrid AI–experimental workflows combine predictive modelling with high-throughput screening, accelerating discovery and reducing experimental demand. These strategies have led to the development of synthetic “synzymes” capable of catalysing non-natural reactions, broadening applications in pharmaceuticals, biofuels, and environmental remediation. The integration of AI-based retrosynthesis and pathway modelling further advances metabolic and process optimisation. Together, these innovations signify a shift from empirical, trial-and-error methods to predictive, computationally guided design. The novelty of this work lies in presenting a unified synthesis of emerging AI methodologies that collectively define the next generation of enzyme engineering, enabling the creation of sustainable, efficient, and functionally versatile biocatalysts
Life cycle environmental and economic assessments of industry-level hydrogen production technologies
No full textHydrogen energy is pivotal for global decarbonization due to its high energy density and potential to achieve carbon neutrality. This study employs life cycle assessment (LCA) and life cycle cost (LCC) to evaluate the environmental and economic performance of five hydrogen production technologies in China: methanol steam reforming (MSR), steam methane reforming (SMR), coke oven gas reforming (COG), coal gasification (CGH), and renewable energy water electrolysis (REWE). Based on comprehensive industry data, the LCA results show that REWE emits only 465 kg CO2 eq per ton of hydrogen but underperforms in terms of photochemical ozone formation potential and resource consumption. LCC and net present value (NPV) analyses indicate COG has the lowest cost (USD 1220/ton), while CGH break evens within 1–2 years. Scenario analyses aligned with China's “dual carbon” goals project that hydrogen demand will reach 100 million tons by 2060, with renewable hydrogen accounting for 70–80 % of the supply. This pathway could reduce the global warming potential to 23.9 % of the 2020 levels and lower green hydrogen costs by 71.5 %, despite a 392 % increase in energy consumption. This study provides an industry-level benchmarking framework to support technology selection and sustainable hydrogen planning.</p
Driving systems transition through learning:a case study for net zero school transport in rural Scotland
No full textThe school run is a persistent local transport issue in most urban areas. Private automobiles remain the dominant transport mode for school journeys, supported by infrastructure and vehicles designed for traffic flow, safety, comfort and convenience. While the car journey offers perceived benefits to carers, it also generates well-documented externalities, including traffic congestion, air pollution, reduced physical activity and increased risks for pedestrians and cyclists. The School Strike for Climate added the ground-up pressure from students to take action. This study explores a transdisciplinary systems approach to tackling the wicked problem of the car drop-off at primary schools. The transition engineering methodology was carried out to design a novel education programme that empowers students to understand global warming and the role of petrol car trips, communicate their needs to carers and contribute to achieving net-zero transport goals through equitable and inclusive changes. The programme was implemented in a participatory action research process involving over 300 students, educators and local stakeholders. Participants reflected that the programme catalysed a cultural shift within the school community, fostering ownership of sustainable school transport and aligning with broader community-level transport strategies. This article presents the design methodology, implementation of outcomes, prototyping experiences and stakeholder feedback. The article contributes a novel programme for sustainable school transport that supports the development of competencies among students to become change makers.</p
Five Ways Scotland is Using Tech to Drive Sustainability
No full textDr Luciana Blaha, Assistant Professor with the Heriot-Watt University Edinburgh, takes a tour of some innovative AI projects in Scotland that address sustainability and AI
Textile-based piezoelectric nanogenerators (PENGs) for structural health monitoring (SHM)
No full textThis chapter explores the potential uses of textile-based piezoelectric nanogenerators (PENGs) in the field of structural health monitoring (SHM). PENGs harness the piezoelectric effect to convert mechanical stress into electrical charges, allowing for the integration of sensing capabilities by textile-based structures. This chapter looks into the fundamental principles underlying PENGs, highlighting the various piezoelectric materials that can be employed in textile applications, and their suitability for SHM purposes. Furthermore, this chapter discusses the challenges associated with the optimization of PENG design and material selection to enhance sensing performance and durability. Key topics covered include impedance sensing based on PENG sensors, the utilization of guide wave ultrasonic techniques, and the potential of PENGs in real-time monitoring of structural deformations and damages. By addressing these aspects, this chapter offers a comprehensive overview of the potential applications of PENGs in SHM and outlines the challenges that must be overcome for their successful implementation
Deep ultraviolet ultrashort laser pulses for precise ablation of soft biological tissue
No full textLaser ablation offers the potential for precisely removing pathological tissue without damaging surrounding healthy structures. Among the existing laser types, deep ultraviolet ultrashort pulsed lasers offer the highest axial precision and reduced collateral damage, yet their application for ablating soft tissues apart from the cornea remains underexplored. Here, ablation of ex vivo lamb liver using laser pulses at 206 nm wavelength and 250 fs pulse duration is investigated. Laser parameters that enable clean, controlled tissue removal are identified by systematically varying the laser pulse energy, spot size, and pulse repetition rate, and the ablated tissues are analysed using histological analysis and surface profilometry. With optimised settings, tissue removal with axial precision down to 10 microns is demonstrated. Ablation threshold fluence of 38.7 ± 2.1 mJ·cm−2 is determined for lamb liver tissue, and fluence windows yielding precise ablation with no observable collateral damage are defined for different laser spot sizes. The ablation responses of tissues with different physical properties are also investigated. These results advance understanding of laser-tissue interaction in the deep ultraviolet ultrashort pulse regime and demonstrate the potential of the proposed tissue removal method for high-precision surgical applications
Hydrogen storage technologies for future energy systems
No full textHydrogen is a shining clean energy vector in the journey toward net-zero, possessing a gravimetric energy density of 120 MJ/kg and potential to decarbonize transport, industry, and power sectors. Its rollout necessitates, however, the development of efficient and scaled-up storage technology. This chapter provides an in-depth technical description of hydrogen storage technologies including compressed gas (350–700 bar), liquid hydrogen (−253 °C), metal hydrides (1.5–2.0 wt% H2 capacity), chemical carriers, and advanced solid-state porous materials such as MOFs (>3000 m2/g surface area). Each system is examined in terms of its energy density, cycling stability, thermodynamic behavior, and integration feasibility. Thermal and mass transfer modeling proves that inefficient heat dissipation lowers hydrogen uptake by 30–40% for hydride systems. Round-trip efficiencies of compressed and liquefied storage systems range from 30% to 45%, and energy losses are 5–15 kWh/kg H2. Blending hydrogen with renewable power sources such as solar pressure vessel and wind decreases curtailment by over 25% and enhances energy autonomy in hybrid microgrids to 90% or higher. Levelized cost of storage (LCOS) varies greatly, from <1/kg H2 for salt caverns to >1,500/kg H2 for metal hydrides. Lifecycle assessments (LCA) indicate that green hydrogen storage systems have the potential to emit <2 kg CO2e/kg H2, assuming supply by renewables, compared to 10–14 kg CO2e/kg H2 for conventional systems. This chapter provides a comparative synthesis of technical, economic, and environmental performance, setting the foundation for future investigations and deployment of hydrogen storage into sustainable energy systems
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