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The world increasingly depends on batteries to store renewable energy and use that same energy in our vehicles and portable communication devices. This puts exceeding pressure on global resources. We need batteries that charge faster and live longer, such that we can use less resources. Faster charge and longer life are currently limited by the negative electrode, typically graphite, because fast charging would push the potential into the regime of hazardous and cycle-life degrading lithium plating. The ideal potential for fast charge would be low, but just above the around 1 V reduction potential of the electrolyte. Niobium-based metal oxides have the optimal electronegativity to strike this balance, with a nominal potential around 1.6 V, charging rates >5C and a cycle-life projected over 10,000 cycles. Chapter 1 shows that the exact potential can be tuned further by changing the average oxidation state through substitution of Nb5+ with for example W6+ or Ti4+. The range of average oxidation states then directly spans a material phase space classed by anion-to-cation ratios of 2.33 ≤ *y* < 2.82. These "off-stoichiometric" ratios typically force the unit cell to rearrange into an ordered balance of *y*=3 ReO3-type blocks of corner-sharing octahedra that have ample window sites to rapidly intercalate many lithium-ions, interspaced with *y*=2.5 crystallographic shear planes of edge-sharing octahedra that add stability and electronic conductivity to the structure, and anchored at their corner by *y*=2 regions of tetrahedra or edge-sharing octahedra. The influence of this structure on cell performance is relatively unknown. Numerous publications exist on individual members of this Wadsley-Roth (WR) material family, but gaps in theory and varying experimental conditions make it impossible to compare. The aim of this thesis is to provide a fair and fundamental comparison across this material class, relating compositional and structural properties to cell thermodynamics and kinetics that can then be used to optimise the material selection and model any full-scale cell geometry. In total 16 different compounds were synthesised with comparable geometrical parameters. Subsequently, they were fully parameterised with various electrochemical tests. Current theory is still too firmly based on traditional metal plate electrodes. Because the WR materials allow extreme conditions of high currents and could be tuned over an extensive structural and compositional range, their study forms an excellent opportunity to modernise the fundamental understanding of the thermodynamics and kinetics of intercalation lithium-ion batteries, in general, and in relation to structural and compositional parameters. Chapter 2, on thermodynamics and energy density, introduces fundamental principles of configurational entropy to explain the steep bends at the cell potential ends and the detailed peaks in the cyclovoltammogram. Density function theory (DFT) exposed a site filling order and structural straightening. Via molecular orbital theory this was then related to enthalpic effects of relatively steeper potential regions due to progressively poorer charge-compensation and relatively poor shielding, but also relatively flatter potential regions related to metal-to-metal repulsion and pseudo Jahn-Teller effects at the block edge. Owing to their increased edge-sharing, low *y* materials could thus reach lower potentials without reaching the voltage cut-off earlier. Low *y* materials thus exhibit high energy density, particularly considering that they also consist of more lightweight elements. The structural straightening upon reduction was identified as the crucial mechanism that provides a competitive energy density to the WR material. The first cycle data and DFT also revealed the mechanism that tetrahedral linkages are irreversibly trapping lithium and that they can be left out of the structure to achieve nearly 100% first cycle efficiencies. On the other hand, the study in Chapter 3 of their intercalation kinetics through temperature-dependent GITT and PEIS with novel application of the compensation effect shows that lower *y* is at the cost of lower entropy of the diffusion pathways, such that their intercalation diffusion coefficients are lower. In general, the compensation effect and the effect of entropy can not be underestimated, while the effect of activation enthalpy could be misleading. Various PEIS, cyclovoltammetry, PITT and GITT techniques had to be critically reviewed and stripped from metal-plate concepts, to identify the formation of film layers and the trends in diffusion. The charge transfer reaction rate and lithium intercalation diffusion were identified as the main contributors to loss, limiting the charge/discharge rate. However, this study observed that the chemical lithium intercalation diffusion coefficient increases with rate. This surprising effect is no longer adequately described by the conventional mass-transfer theory and suggests effects of non-equilibrium driving forces, excited lithium hopping, lattice vibrations and energy barrier softening. Such a mechanism is essential to explain the high rate performance of WR materials and intercalation materials in general and provides an important direction for future theory and experimental research. All in all, this study showed a tradeoff between energy and rate, with TiNb2O7, Zn2Nb34O87 and PNb9O25 as winners. Independent of the tradeoff, performance could be further improved in the future with the substitution of lightweight cations, and by increasing the crystallographic entropy with multiple cations. In general, this work identified several new applications of theory to the modern battery cell, which will hopefully become more widely applied and further underpinned by in-situ direct observation methods on the particle level. All the theory and full parameterisation methods above were combined into a full cell continuum model in Chapter 4, that not only validates these approaches but also allows the design, verification and prediction of any commercial format multilayer cell geometry. This paves the way for this new class of ultra fast-charge long-life batteries that can power more of the world, with fewer batteries.

Boreal forests hold 32% of the world’s terrestrial organic matter and are continually disturbed by biotic and abiotic events. These disturbances are especially important since they facilitate the redistribution of nutrients within and between ecosystems, which can alter resource use and productivity. Yet how various types of disturbances, both individually and in combination, impact the overall resource balance of northern forests remains poorly understood. This thesis aims to advance our understanding of forest disturbances as drivers of forest resource balances, primarily through shifts in carbon, to better facilitate management of forests under climate change. Chapter 1 reviews current knowledge on forest disturbances and cross- ecosystem linkages. It also provides a summary of current gaps in our understanding of disturbances as drivers of forest function and possible downstream effects. Chapter 2 explores how disturbance history influences long-term carbon balance in boreal forests. Theory predicts that disturbances will increase with climate change but how the order and timing of multiple disturbance events will impact ecosystem function remains unresolved. Chapter 3 extends our understanding of forest carbon balance by asking how different disturbance types change the phenology and surface reflectance of boreal forests. Understanding how single disturbance events change growing season length and radiative forcing of forests can help predict potential feedbacks of forest health on climate warming. Chapter 4 tests how outbreaks of defoliating insects alter biogeochemical cycling from land to receiving waters through the consumption of foliage and subsequent release of nutrient-rich waste. Forests typically provide a pulse of nutrients to nearby waters in autumn when leaves are shed but insects disrupt this pattern by changing the timing, quantity, and quality of resource transfers. Chapter 5 traces terrestrial nutrients within lakes and asks if they can promote productivity in zooplankton communities. Finally, Chapter 6 discusses the main findings of the thesis and ends with possible directions for future research.

Since the first commercialization of Li-ion batteries (LIBs) in 1991, they have continued to power the society for decades. However, the ever-growing demands pose challenges to their sustainability in terms of restricted energy density, inadequate cycle life, and limited key resources. In the first part of this thesis (chapter 2), efforts made within Li batteries, with respect to sustainability in energy density, cycle life and resources are reported in three sub-chapters discussed below. Use of pure metallic Li is an important strategy for full utilization of the inherently high energy density of Li. In chapter 2.1, novel research is devoted towards quantifying major Li loss pathways for the first time. Based on the fundamental understanding gained from the quantified correlation between major Li loss forms, a rational interphase design principle for achieving highly reversible lean Li and lean electrolyte Li metal batteries (LMBs) from a holistic perspective is proposed. An inorganic-rich insoluble inner solid-electrolyte interphase (SEI) layer with high electron passivity is established, as well as the suppression of organic SEI dissolution. This work has demonstrated an ultra-low Li loss rate (mainly from Li corrosion and SEI dissolution) of 0.13 μAh cm-2 h-1 and an ultra-low SEI growth rate (mainly from Li corrosion) of 3.20 mΩ cm-2 h-1, leading to over 5000 h Li metal cycling stability at a Li utilization rate of 50%, which is very high in lean Li||Li symmetric cells. Based upon this novel molecular-level interphase design, full LIB cells have been fabricated and validated with promising results. A Li||LiFePO4 (LFP) full cell with lean Li (negative to positive, i.e., N/P ratio of 2) subject to a deep cycling rate of 0.2 C over 700 cycles running over 280 days demonstrates 90% capacity retention at an average Coulombic efficiency (CE) of 99.99%, and impressively a 480 Wh kg-1 Ah-level Li||LiNi0.8Mn0.1Co0.1O2 (NMC811) pouch cell with a lean N/P ratio of 1.02 and a lean electrolyte to capacity (E/C) ratio of 3 g Ah-1 achieves over 90% capacity retention over 160 cycles. In chapter 2.2, novel research with LIBs on using the high energy density of Si, second only to Li, is proposed for mitigating mechanical fracture and loss of electrical contact prevalent with a Si-based anode. A SiOx-based anode, which is capable of alleviating volumetric expansion while strengthening the electrical connectivity in the electrodes with an average CE over 99.9% in a high-loading full cell, is developed based upon a robust Si-O-C covalent bonding by molecular-level interphase wiring. Foundational-level innovative research on recovering the valuable cathodic elements from a spent LIB is devised based upon interphase designs in chapter 2.3. This novel chemically active but mechanically passive photothermal powered device consists of a solar thermal collector interphase with a porous alumina reservoir for Li, which in turn is in interphase with a thin layer of ion-sieving metal organic framework (MOF) separator fed from a solution containing Li+ and Co2+ ions from spent cathodes. A preliminary Life Cycle Assessment (LCA) is reported to validate the potential benefits from such a photothermal recycling strategy in terms of cost, energy consumption, and environmental issues. In the second part of this thesis (chapter 3), research is carried out with respect to Na-ion batteries (NIBs), as a complementary alternative to LIBs deriving benefits with respect to resource sustainability. Na is an attractive lower cost and a more widely available option than Li, and does not depend on the expensive and geographically constrained Co in the cathode. The bill of materials for a NIB is further decreased based upon the replacement of the anodic current collector from Cu to a much cheaper and lighter Al. However, SEI dissolution is much more severe in NIBs than in LIBs, leading to low Na reversibility and poor utilization of Na. The first part in chapter 3 builds a direct correlation between SEI solubility and SEI components, and for the first time quantifies that an organic SEI has 3.26 times the solubility of an inorganic SEI. A novel strategy of preforming an insoluble inorganic-rich SEI has been developed, which contributes to a high-loading hard carbon (HC)||NaMn0.33Fe0.33Ni0.33O2 full cell with 80.0% capacity retention and a record-high 99.95% average CE at 0.33 C over 900 cycles with a commercial electrolyte. In another sustainability validation with NIBs, a novel dual-salt/dual-solvent based electrolyte has been developed that is able to achieve a homogeneous and insoluble SEI. Such molecular-level interphase design contributes to 80.5% capacity retention and a record-high 99.95% average CE at 0.33 C over 1500 cycles in a HC||NaMn0.33Fe0.33Ni0.33O2 full cell. It further leads to an 87.5% state of charge (SOC) capacity in a highly challenging scenario of 4 C fast charging and 0.33 C slow discharging for a high-loading full cell, which demonstrates practical applications for challenging fast charging slow discharging scenarios such as electric vehicles (EVs). In the final part of research with NIBs, an electrolyte design principle based on a low dissolution coefficient, and a new protocol to quantify SEI dissolution have been proposed and developed for the first time. These principles have been validated in a high-loading full cell, achieving a near-unity average CE of 99.98% at 0.33 C over 1000 cycles in a HC||NaMn0.33Fe0.33Ni0.33O2 full cell. This near-unity average CE of 99.98% is not only a record value reported so far for a practical Na-ion full cell, but also satisfies the End-of-Life (EoL) model for the first time in the Na battery field, to the best of my knowledge, providing guidelines for designing stable SEIs with high Na ion reversibility. In summary, this thesis has developed and validated molecular-level interphase design principles that can help pave new ways for enhancing battery sustainability in terms of prolonged cycle life with high energy density and endurable resources.

This research provides new techno-economic insights into integrating flexible combined-cycle gas turbines with post-combustion carbon capture and storage (CCGT-CCS) for low-carbon power systems. This study developed a versatile unit-commitment optimisation model of CCGT-CCS. This research highlights the model’s adaptability, accommodating diverse techno-economic configurations, feed gases (e.g., biomethane or fossil natural gas), carbon capture rates, and policy instruments. This generalisation empowers seamless application in various policy and market contexts, making the model a potent tool for researchers and policymakers. While the case study focuses on the UK, the findings are relevant for most low-carbon power systems with variable renewable supplies. Analysing the UK’s net-zero scenarios from 2030 to 2050, the economic viability of flexible CCGT-CCS was highlighted. Intertemporal flexibility proves highly valuable with greater electricity price volatility, with a total ROI range of 81–246 %, surpassing the CCGT-CCS plant’s ROI (7–64 %). A flexible solvent storage solution should be seen in the context of the overall system ‘flexibility’ requirements of a low-carbon power system. On a cost basis, solvent storage represents just a fraction of the capital costs of more “mainstream” energy storage technologies, such as lithium-ion batteries or hydro-pumped storage, while CCGT-CCS offers firm power. Overall, while seen as a rather technical solution, if abated fossil fuel generation is to be part of a future low-carbon power system, having this flexibility adds economic benefits not just to operators but also improves overall system security and complements high shares of variable renewables on the grid.

Metal-halide perovskites are materials at the forefront of the next generation of optoelectronic materials. Of particular interest is their remarkable power conversion efficiencies when incorporated into thin film solar cells. The properties of next-generation semiconductors such as perovskites are dominated by microscopic variations in their structure, composition and photophysics. Perovskites show extraordinary levels of disorder and this has considerable implications for their function. Gaining a microscopic understanding into how the optoelectronic quality of perovskite thin films and their interfaces with contact layers affects their performance is crucial to enabling solar cells with sufficient performance and stability to commercialise. In this thesis, I detail the development of a multi-modal microscopy toolkit to probe the optoelectronic quality of perovskite thin films and devices and spatially correlate these measurements with microscopic chemistry and structural information. In the first experimental chapter, I detail the capabilities of a hyperspectral, wide-field optical microscope, capable of measuring spatially resolved photoluminescence, reflectance and transmittance spectra with diffraction resolution. With a variety of perovskite thin film samples, I show that thin-film morphology and surface passivation play a huge role in photoluminescence intensity, spectrum and stability. The second experimental chapter applies calibration tools to the hyperspectral microscope, enabling the extraction of device relevant metrics such as the quasi-Fermi level splitting and Urbach Energy microscopically. We spatially correlate these measurements with nanoprobe X-ray diffraction and fluorescence to probe structure and chemistry. Applying this multimodal toolkit to state-of-the-art alloyed perovskites, we find that nanoscale variations in chemical composition dominate the optoelectronic properties of these perovskite films and form energetic funnels that carriers fall down and away from trap states. This study helps to explain the remarkable defect tolerance of these materials. The final experimental chapter augments the optical microscopy setup to measure voltage dependent photoluminescence maps. Voltage dependent photoluminescence allows the extraction of pseudo current-voltage curves of the devices, enabling the recombination and charge transport losses of perovskite solar cells to be mapped microscopically. I show that microscopic performance heterogeneity has a large impact on both macroscopic performance and stability. By mapping the same areas before devices before and after ageing, the microscopic effects of degradation on charge extraction can be imaged. Taken together, the results here show the important microscopic influences on performance from thin films to complete devices and the powerful multi-modal methodologies developed are widely applicable to a wide array of disordered semiconductors.

We use extreme regional pollution emergencies to provide new evidence regarding the motivations for corporate social responsibility (CSR). We document that local firms strategically improve CSR to build trust following pollution emergencies, and this is specifically true for highly polluting firms. Firms face different intensities of external pressure from their stakeholders. In particular, following pollution emergencies, political dependency, institutional investors and public monitoring are the main sources of stakeholder pressure and drivers of the increased CSR. We further find that firms that gain trust through CSR activities after pollution emergencies are rewarded. CSR serves as a buffer against financial constraints, financing distress and the negative profitability effect following emergencies. This study contributes to the CSR literature on trust-building-motivated CSR strategies.

Dye-sensitized solar cells (DSCs) are a photovoltaic technology based around light-harvesting dye molecules bound to thin semiconductor films of high surface area. Many of the highest-performing DSCs to date incorporate multiple dyes that harvest light from different regions of the solar spectrum in a complementary manner – these are known as cosensitized DSCs. However, finding dyes that are well-suited for cosensitization is a long and costly experimental process when carried out through trial and error in a laboratory. To help direct experimentalists towards promising candidates, the main project of this thesis harnesses ideas from data-driven materials discovery to develop an entirely computational pipeline that predicts boosts in performance of dye pairs when cosensitized. It does this by identifying partner dyes that show the most complementary absorption characteristics to sets of well-known or high-performing starting dyes, systematically sifting candidates from a large database of optically active compounds. It then uses density functional theory (DFT) simulations to compute key structural, electronic and optical properties of the selected pairs of dyes, which are used as inputs to models that predict short-circuit current density (JSC) and open-circuit voltage (VOC), two key device performance parameters. The predictive models for JSC and VOC of singly-sensitized devices are developed further from existing models used in previous works, and are also expanded to the cosensitized case for the first time. 11 starting dyes were passed through the pipeline (six organic and five organometallic), leading to 22 dyes in total being modelled at the DFT level as 11 pairs. The accuracy of predicted JSC and VOC for single sensitizers was tested against existing experimental references. Notably, half of the JSC predictions were within 20% error or less of experimental values whilst others had greater discrepancies, the sources of which are discussed in detail. These results are significant given the choice of structurally dissimilar dyes here – this accuracy is on par with previous computational studies that focussed only on sets of structurally analogous dyes. From the predictions of cosensitized devices containing the complementary dye pairs, two standout cells were those containing **SQ2**+**LD2** dyes and **YD2**+**VKXB** dyes, which gave +13% and +12% boosts to JSC relative to their singly-sensitized counterparts, respectively. A secondary computational project was also carried out in collaboration with previous experiments of DSC dye monolayer growth over time. Whilst complete dye monolayers have been studied extensively, their behaviour as they grow is less well understood, despite its importance for DSC fabrication. X-ray reflectometry (XRR) had been used by a collaborator to investigate monolayer thicknesses and densities as they grow under different conditions in the DSC fabrication process. This author trained a neural network to perform rapid, deterministic fitting of 360 experimental reflectivity curves in high-throughput fashion. The DSC dye layer parameters predicted by this machine-learning model were compared to those from a human-assisted fit with standard software (such fitting being orders of magnitude slower to carry out). The neural network predictions had high accuracy for instances where monolayers adhered to the assumptions of the Parratt model used to fit reflectivity curves, but poorer accuracy during periods of faster change in thickness, suggesting dynamic behaviour of dye ensembles that warrants further investigation. Thus, the neural network acted as a supporting tool to identify where to focus further experimental DSC investigation, which is the overarching theme connecting the two projects of this thesis. Chapter 1 provides a literature review of DSC function, the structure-property relationships of their component materials, and pre-existing computational methods that predict DSC performance. Chapter 2 provides a technical background to the density-functional theory (DFT) methods used throughout much of this work. Chapter 3 presents the design-to-device pipeline methodology developed in this work. Chapter 4 displays and discusses the results of this pipeline as applied to six well-known or high-performing organic dyes and their six complementary partner dyes identified. Chapter 5 similarly presents results for five ruthenium-based dyes and their cognate organic partner dyes that were identified by the pipeline. Chapter 6 provides a background to XRR and neural networks, before presenting the training of neural network and evaluating its performance in reproducing fitted layer parameters from the experimental XRR data described above. Chapter 7 discusses the conclusions of this work and how further research may be enabled.

The construction industry in Europe is in transition. In the last decade, challenges related to inefficiencies in the sector, the shortage of skilled labour, and environmental concerns initiated a shift towards off-site manufacturing. In Hungary, the first examples of prefabricated residential buildings have just appeared after a 30-year-long break. At the same time, in post-socialist countries, the general attitude towards modern methods of construction is rather complex. While the Western examples of modular constructions are admired, local examples of prefabricated and standardised homes from the socialist era are neglected or criticised for their uniformity and inability to change. This thesis examines the social limits of standardisation in the Hungarian context, specifically focusing on how we can ensure that in the future, mass-manufactured buildings will be sustainable and retain their social respectability, technical qualities and economic value for a long time. It is found that standardisation does not necessarily limit creativity and can be socially sustainable, provided that it does not result in uniform constructions. Findings rely on an extensive review of the literature and real-life architectural examples, statistical results from two online surveys on preconceptions about mass-manufactured buildings, and space syntactical investigations of preferred home layouts. The findings of the project include showing that young Hungarian adults associate mass produced buildings with the loss of diversity, but they find these buildings environmentally friendly, fast to produce, progressive and fashionable. In addition, it is shown that it is possible to use small graph matching and density-based clustering to find the most suitable layouts for socially-conscious mass manufacturing. The practical outcomes of this project include an exemplar dwelling that showcases good design, a framework for discussing standardised buildings, and a Plug-in that can evaluate any new apartments created in Autodesk Revit based on the developed guidelines.

Supercapacitors are high-power energy storage devices that will play an important role in the transition to a low-carbon society. In recent years, layered electrically conductive metal-organic frameworks (MOFs) have emerged as one of the most promising electrode materials for next-generation supercapacitors. Their crystalline and tuneable structures facilitate structure-performance studies, which are challenging to conduct with traditional porous carbon electrodes. In this work, the electrochemical performances of layered conductive MOFs in supercapacitors are investigated to both improve our understanding of these materials and to develop structure-performance relationships. Having demonstrated that the layered conductive MOF Cu3(HHTP)2 (HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene) exhibits good performance in supercapacitors, measurements on samples with different particle morphologies reveal that ‘flake’ particles, with small length-to-width aspect ratios, are optimal for these devices. This is due to improved ion accessibility and dynamics through the short pores of the ‘flake’ particles, resulting in a higher power performance compared to particle morphologies with longer pores. Electrochemical quartz crystal microbalance (EQCM) and three-electrode experiments are then performed with Cu3(HHTP)2 and a series of electrolytes with different cation sizes to investigate both the charging mechanism of this MOF and how electrolyte ion size impacts electrochemical performance. It is shown that cations are the dominant charge carriers in Cu3(HHTP)2, with co-ion desorption occurring upon positive charging and counterion adsorption during negative charging. Large ions lead to porosity saturation in MOF electrodes, reducing charge storage and forcing solvent molecules to participate in the charge storage mechanism. The impact of modifying MOF-electrolyte interactions on the electrochemical capacity of layered MOF supercapacitors is then investigated by altering both the electrolyte cation and the MOF electrode functionality. These experiments allow for the systematic probing of the influence of different functional groups on supercapacitor performance, and reveal that MOFs with hydroxy ligating groups, together with Li⁺ electrolytes, constitute the best electrode-electrolyte combination for maximising capacitive performance. Finally, an interlaboratory study is conducted to assess the variability in the reporting of performance metrics across different laboratories. Overall, this work provides unique insights into the performances of layered conductive MOFs for supercapacitor applications, and will guide the design of improved electrode materials for next-generation supercapacitors.