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Conference paperDave RJ, Min X, Lou Z, et al., 2024,
Investigating construction and integration techniques of dry silver-based textile electrodes on electromyography of biceps Brachii muscle
, 5th International Conference on the Challenges, Opportunities, Innovations and Applications in Electronic Textiles, Publisher: MDPI, ISSN: 2673-4591This research paper recommends an electrode construction and integration technique for dry silver-based textile electrodes capturing electromyographic (EMG) signals. Three integration methods with two different conductive textiles were compared using two analysis methods; analysis was also conducted before and after six washing cycles. Six wearable arm bands with each of the design parameter combinations were worn on the biceps brachii muscle to capture EMG signals from three users under a controlled task both before any washing of the bands occurred and after four washing cycles were completed. Additionally, impedance measurements over six frequency bands were recorded after each washing cycle. Textile electrodes made of Shieldex Techniktex P180B using an extended electrode integration method were found to perform best.
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Conference paperZhang M, Stewart R, Bryan-Kinns N, 2024,
Empowering textile and fashion designers with e-textiles for creative expression
, 5th International Conference on the Challenges, Opportunities, Innovations and Applications in Electronic Textiles, Publisher: MDPI, ISSN: 2673-4591In the field of textile and fashion design, there is a growing desire to integrate interactive technologies into creative work. Traditional design education typically lacks support for material-oriented designers to develop electronic skills alongside their expertise in materials. There is a need to develop proper support for these designers to enter the world of electronic textiles (e-textiles). Our previous work introduced a material-centred e-textile learning approach through the development of a toolkit. This paper offers a glimpse into a design project made by our students, where digital functionality intertwines with physical design. It serves as a testament to the effectiveness of our approach in merging interactive technology concepts with material expertise, thereby aiding these designers in their creative endeavours.
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Journal articleLi H, Gong Y, Zhou H, et al., 2024,
Author Correction: Ampere-hour-scale soft-package potassium-ion hybrid capacitors enabling 6-minute fast-charging.
, Nat Commun, Vol: 15 -
Journal articleNaylor Marlow M, Chen J, Wu B, 2024,
Degradation in parallel-connected lithium-ion battery packs under thermal gradients
, Communications Engineering, Vol: 3, ISSN: 2731-3395Practical lithium-ion battery systems require parallelisation of tens to hundreds of cells, however understanding of how pack-level thermal gradients influence lifetime performance remains a research gap. Here we present an experimental study of surface cooled parallel string battery packs (temperature range 20–45 °C), and identify two main operational modes; convergent degradation with homogeneous temperatures, and (the more detrimental) divergent degradation driven by thermal gradients. We attribute the divergent case to the, often overlooked, cathode impedance growth. This was negatively correlated with temperature and can cause positive feedback where the impedance of cells in parallel diverge over time; increasing heterogeneous current and state-of-charge distributions. These conclusions are supported by current distribution measurements, decoupled impedance measurements and degradation mode analysis. From this, mechanistic explanations are proposed, alongside a publicly available aging dataset, which highlights the critical role of capturing cathode degradation in parallel-connected batteries; a key insight for battery pack developers
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Journal articlePinkse J, Demirel P, Marino A, 2024,
Unlocking innovation for net zero: constraints, enablers, and firm-level transition strategies
, Industry and Innovation: dynamics, strategies, policies, Vol: 31, Pages: 16-41, ISSN: 1366-2716Transition pathways for net zero encompass seemingly insurmountable innovation challenges for the scaling of less mature technological solutions such as hydrogen, materials substitution, and electrification as well as societal challenges to increase the market acceptability of these solutions. In this article, we present a conceptual framework which provides a firm-level perspective on net-zero innovation which has four unique characteristics, i.e. it is complex, systemic, urgent, and directional. The framework shows that the input, process, and output constraints that incumbent firms face in the net-zero transition can be tackled through four firm-level innovation levers – i.e. recombinative, collaborative, integrative, and socio-cognitive capabilities – which, in concert, act as enablers for firms to address these net-zero constraints. We conclude the article by outlining the framework’s main insights for firms’ innovation strategies for net zero and the policy implications. We also propose avenues for future research on net-zero innovation.
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Journal articleQian Q, Wang Y, Boyle D, 2024,
On solving close enough orienteering problems with overlapped neighborhoods
, European Journal of Operational Research, ISSN: 0377-2217The Close Enough Traveling Salesman Problem (CETSP) is a well-known variant of the classic Traveling Salesman Problem whereby the agent may complete its mission at any point within a target neighborhood. Heuristics based on overlapped neighborhoods, known as Steiner Zones (SZ), have gained attention in addressing CETSPs. While SZs offer effective approximations to the original graph, their inherent overlap imposes constraints on the search space, potentially conflicting with global optimization objectives. Here we show how such limitations can be converted into advantages in the Close Enough Orienteering Problem (CEOP) by aggregating prizes across overlapped neighborhoods. We further extend the classic CEOP with Non-uniform Neighborhoods (CEOP-N) by introducing non-uniform cost considerations for prize collection. To tackle CEOP (and CEOP-N), we develop a new approach featuring a Randomized Steiner Zone Discretization (RSZD) scheme coupled with a hybrid algorithm based on Particle Swarm Optimization (PSO) and Ant Colony System (ACS) — CRaSZe-AntS. The RSZD scheme identifies sub-regions for PSO exploration, and ACS determines the discrete visiting sequence. We evaluate the RSZD's discretization performance on CEOP instances derived from established CETSP instances and compare CRaSZe-AntS against the most relevant state-of-the-art heuristic focused on single-neighborhood optimization for CEOP instances. We also compare the performance of the interior search within SZs and the boundary search on individual neighborhoods in the context of CEOP-N. Our experimental results show that CRaSZe-AntS can yield comparable solution quality with significantly reduced computation time compared to the single neighborhood strategy, where we observe an averaged 140.44% increase in prize collection and 55.18% reduction of algorithm execution time. CRaSZe-AntS is thus highly effective in solving emerging CEOP-N, examples of which include truck-and-drone delivery scenarios.
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Journal articleXie R, Pinson P, Xu Y, et al., 2024,
Robust Generation Dispatch With Purchase of Renewable Power and Load Predictions
, IEEE Transactions on Sustainable Energy, ISSN: 1949-3029The increasing use of renewable energy sources (RESs) and responsive loads has made power systems more uncertain. Meanwhile, thanks to the development of advanced metering and forecasting technologies, predictions by RES and load owners are now attainable. Many recent studies have revealed that pooling the predictions from RESs and loads can help the operators predict more accurately and make better dispatch decisions. However, how the prediction purchase decisions are made during the dispatch processes needs further investigation. This paper fills the research gap by proposing a novel robust generation dispatch model considering the purchase and use of predictions from RESs and loads. The prediction purchase decisions are made in the first stage, which influence the accuracy of predictions from RESs and loads, and further the uncertainty set and the worst-case second-stage dispatch performance. This two-stage procedure is essentially a robust optimization problem with decision-dependent uncertainty (DDU). A mapping-based column-and-constraint generation (C&CG) algorithm is developed to overcome the potential failures of traditional solution methods in detecting feasibility, guaranteeing convergence, and reaching optimal strategies under DDU. Case studies demonstrate the effectiveness, necessity, and scalability of the proposed model and algorithm.
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Journal articlevan der Meer D, Pinson P, Camal S, et al., 2024,
CRPS-based online learning for nonlinear probabilistic forecast combination
, International Journal of Forecasting, ISSN: 0169-2070Forecast combination improves upon the component forecasts. Most often, combination approaches are restricted to the linear setting only. However, theory shows that if the component forecasts are neutrally dispersed—a requirement for probabilistic calibration—linear forecast combination will only increase dispersion and thus lead to miscalibration. Furthermore, the accuracy of the component forecasts may vary over time and the combination weights should vary accordingly, necessitating updates as time progresses. In this paper, we develop an online version of the beta-transformed linear pool, which theoretically can transform the probabilistic forecasts such that they are neutrally dispersed. We show that, in the case of stationary synthetic time series, the performance of the developed method converges to that of the optimal combination in hindsight. Moreover, in the case of nonstationary real-world time series from a wind farm in mid-west France, the developed model outperforms the optimal combination in hindsight.
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Journal articlePierrot A, Pinson P, 2024,
On Tracking Varying Bounds When Forecasting Bounded Time Series
, Technometrics, ISSN: 0040-1706We consider a new framework where a continuous, though bounded, random variable has unobserved bounds that vary over time. In the context of univariate time series, we look at the bounds as parameters of the distribution of the bounded random variable. We introduce an extended log-likelihood estimation and design algorithms to track the bound through online maximum likelihood estimation. Since the resulting optimization problem is not convex, we make use of recent theoretical results on stochastic quasiconvex optimization, to eventually derive an Online Normalized Gradient Descent algorithm. We illustrate and discuss the workings of our approach based on both simulation studies and a real-world wind power forecasting problem.
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Journal articleGonzález-Toledo D, Cuevas-Rodríguez M, Vicente T, et al., 2024,
Spatial release from masking in the median plane with non-native speakers using individual and mannequin head related transfer functions.
, J Acoust Soc Am, Vol: 155, Pages: 284-293Spatial release from masking (SRM) in speech-on-speech tasks has been widely studied in the horizontal plane, where interaural cues play a fundamental role. Several studies have also observed SRM for sources located in the median plane, where (monaural) spectral cues are more important. However, a relatively unexplored research question concerns the impact of head-related transfer function (HRTF) personalisation on SRM, for example, whether using individually-measured HRTFs results in better performance if compared with the use of mannequin HRTFs. This study compares SRM in the median plane in a speech-on-speech virtual task rendered using both individual and mannequin HRTFs. SRM is obtained using English sentences with non-native English speakers. Our participants show lower SRM performances compared to those found by others using native English participants. Furthermore, SRM is significantly larger when the source is spatialised using the individual HRTF, and this effect is more marked for those with lower English proficiency. Further analyses using a spectral distortion metric and the estimation of the better-ear effect, show that the observed SRM can only partially be explained by HRTF-specific factors and that the effect of the familiarity with individual spatial cues is likely to be the most significant element driving these results.
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Journal articleRaja AA, Pinson P, Kazempour J, et al., 2024,
A market for trading forecasts: a wagering mechanism
, International Journal of Forecasting, Vol: 40, Pages: 142-159, ISSN: 0169-2070In many areas of industry and society, including energy, healthcare, and logistics, agents collect vast amounts of data that are deemed proprietary. These data owners extract predictive information of varying quality and relevance from data depending on quantity, inherent information content, and their own technical expertise. Aggregating these data and heterogeneous predictive skills, which are distributed in terms of ownership, can result in a higher collective value for a prediction task. In this paper, a platform for improving predictions via the implicit pooling of private information in return for possible remuneration is envisioned. Specifically, a wagering-based forecast elicitation market platform has been designed, in which a buyer intending to improve their forecasts posts a prediction task, and sellers respond to it with their forecast reports and wagers. This market delivers an aggregated forecast to the buyer (pre-event) and allocates a payoff to the sellers (post-event) for their contribution. A payoff mechanism is proposed and it is proven that it satisfies several desirable economic properties, including those specific to electronic platforms. Furthermore, the properties of the forecast aggregation operator and scoring rules are discussed in order to emphasize their effect on the sellers’ payoff. Finally, numerical examples are provided in order to illustrate the structure and properties of the proposed market platform.
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Conference paperCedeno MR, Porat T, Baxter W, 2024,
“This is MY PhD project… or is it?” Understanding perceived doctoral project ownership through psychological ownership mapping
, Pages: 2815-2824This paper investigates PhD student’s perceived feeling of project ownership and how it influences their project management. Drawing on psychological ownership (PO) theory and the PO mapping method, this study identifies distinct project ownership paths among students, revealing how project engagement can be improved. The findings demonstrate the importance of carefully considered and timely student-supervisor expectation discussions to help influence project ownership. To this end, the paper offers several routes of ownership that can influence project ownership among PhD students.
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Journal articleWen H, Pinson P, Gu J, et al., 2024,
Wind energy forecasting with missing values within a fully conditional specification framework
, International Journal of Forecasting, Vol: 40, Pages: 77-95, ISSN: 0169-2070Wind power forecasting is essential to power system operation and electricity markets. As abundant data became available thanks to the deployment of measurement infrastructures and the democratization of meteorological modeling, extensive data-driven approaches have been developed within both point and probabilistic forecasting frameworks. These models usually assume that the dataset at hand is complete and overlook missing value issues that often occur in practice. In contrast to that common approach, we here rigorously consider the wind power forecasting problem in the presence of missing values, by jointly accommodating imputation and forecasting tasks. Our approach can infer the joint distribution of input features and target variables at the model estimation stage based on incomplete observations only. We place emphasis on a fully conditional specification method, owing to its desirable properties, e.g., being assumption-free when it comes to these joint distributions. Then, at the operational forecasting stage, with available features at hand, one can issue forecasts by implicitly imputing all missing entries. The approach is applicable to both point and probabilistic forecasting, while yielding competitive forecast quality in both simulated and real-world case studies. The results confirm that by using a powerful universal imputation method based on a fully conditional specification, the proposed universal imputation approach is superior to the common impute-then-predict approach, especially in the context of probabilistic forecasting.
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Journal articleAlmukhtar A, Batcup C, Bowman M, et al., 2024,
Barriers and facilitators to sustainable operating theatres: a systematic review using the Theoretical Domains Framework
, International Journal of Surgery, Vol: 110, Pages: 554-568, ISSN: 1743-9159Background:The health sector contributes significantly to the climate crisis. Operating theatres in particular are a major contributor of greenhouse gas emissions and waste, and while there are several evidence-based guidelines to reduce this impact, these are often not followed. We systematically reviewed the literature to identify barriers and facilitators of sustainable behaviour in operating theatres, categorising these using the TheoreticalDomains Framework (TDF).Method:Medline, Embase, PsychInfo, and Global Health databases were searched for articles published between January 2000- June 2023, using the concepts: barriers and facilitators, sustainability, and surgery. Two reviewers screened abstracts from identified studies, evaluated quality, and extracted data. Identified determinants weremapped to TDF domains and further themes as required.Findings:Twenty-one studies were selected for analysis and assessment (seventeen surveys and four interview studies) comprising 8286 participants, including surgeons, nurses and anaesthetists. Eighteen themes across ten TDF domains were identified. The mostcommon barriers to adoption of green behaviours in operating theatres were in domains of: ‘knowledge’ (N=18) e.g. knowledge of sustainable practices;‘environmental context and resources’ (N=16) e.g.‘personnel shortage and workload and inadequate recycling facilities; ‘social influences’ (N=9) e.g. lack ofleadership/organisational mandate or support; ‘beliefs about consequences’ (N=9) e.g. concerns regarding safety. Intention was the most common facilitator, with eleven studies citing it.Discussion:Despite intentions to adopt sustainable practices in operating theatres, this review identifies several barriers to doing so. Interventions should focus on mitigating these, especially by improving staff's knowledge of sustainability practices and working within the environmental context and time pressures. Furthermore, inst
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Journal articleSadek M, Calvo RA, Mougenot C, 2024,
Closing the Socio–Technical Gap in AI: The Need for Measuring Practitioners’ Attitudes and Perceptions
, IEEE Technology and Society Magazine, ISSN: 0278-0097This article discusses the need for artificial intelligence (AI) practitioners to shift their focus from a purely technical mindset toward a more human-centered approach. Technical experts are trained to consider the technical aspects of their work, which can cause them to overlook important socio–technical considerations and implications, resulting in a socio–technical gap in AI-based systems [4]. Unhelpful practitioner cultures can lead to them “rejecting practices or downplaying the importance of values or the possible threats of ignoring them” [1]. While efforts are being made to create ethical and more human-centered AI systems, there is a need for corresponding changes in the attitudes and perceptions of AI practitioners. Practitioners need to move away from a sole focus on compliance with responsible AI guidelines and regulations toward active reflection and empathy based on a true understanding of the profound effects their decisions can have on different stakeholders. However, one problematic barrier to beginning work on interventions that target practitioners’ mindsets and attitudes is the lack of a standardized method for evaluating or measuring the effectiveness of design interventions on their attitudes and perceptions. This article suggests the need for clearer metrics within the human–computer interaction (HCI) community for looking at practitioners’ attitudes toward socio–technical factors in AI design.
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Journal articleFrölke L, Prat E, Pinson P, et al., 2024,
On the efficiency of energy markets with non-merchant storage
, Energy Systems, ISSN: 1868-3967Energy market designs with non-merchant storage have been proposed in recent years, with the aim of achieving optimal market integration of storage. In order to handle the time-linking constraints that are introduced in such markets, existing works commonly make simplifying assumptions about the end-of-horizon storage level, e.g., by imposing an exogenous level for the amount of energy to be left for the next time horizon. This work analyzes market properties under such assumptions, as well as in their absence. We find that, although they ensure cost recovery for all market participants, these assumptions generally lead to market inefficiencies. Therefore we consider the design of markets with non-merchant storage without such simplifying assumptions. Using illustrative examples, as well as detailed proofs, we provide conditions under which market prices in subsequent market horizons fail to reflect the value of stored energy. We show that this problem is essential to address in order to preserve market efficiency and cost recovery. Finally, we propose a method for restoring these market properties in a perfect-foresight setting.
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Journal articleDeady M, Collins DAJ, Glozier N, et al., 2024,
Naturalistic Evaluation of HeadGear: A Smartphone App to Reduce Depressive Symptoms in Workers
, Behavior Therapy, ISSN: 0005-7894 -
Journal articleWang Z, Acha S, Bird M, et al., 2024,
A total cost of ownership analysis of zero emission powertrain solutions for the heavy goods vehicle sector
, Journal of Cleaner Production, Vol: 434, ISSN: 0959-6526Transport-related activities represented 34% of the total carbon emissions in the UK in 2022 and heavy-duty vehicles (HGVs) accounted for one-fifth of the road transport greenhouse gas (GHG) emissions. Currently, battery electric vehicles (BEVs) and hydrogen fuel cell electric vehicles (FCEVs) are considered as suitable replacements for diesel fleets. However, these technologies continue to face techno-economic barriers, creating uncertainty for fleet operators wanting to transition away from diesel-powered internal combustion engine vehicles (ICEVs). This paper assesses the performance and cost competitiveness of BEV and FCEV powertrain solutions in the hard-to-abate HGV sector. The study evaluates the impact of battery degradation and a carbon tax on the cost of owning the vehicles. An integrated total cost of ownership (TCO) model, which includes these factors for the first time, is developed to study a large retailer's HGV fleet operating in the UK. The modelling framework compares the capital expenditures (CAPEX) and operating expenses (OPEX) of alternative technologies against ICEVs. The TCO of BEVs and FCEVs are 11% to 33% and 37% to 78% higher than ICEVs; respectively. Despite these differences, by adopting a longer lifetime for the vehicle it can effectively narrow the cost gap. Alternatively, cost parity with ICEVs could be achieved if BEV battery cost reduces by 56% or if FCEV fuel cell cost reduces by 60%. Besides, the pivot point for hydrogen price is determined at £2.5 per kg. The findings suggest that BEV is closer to market as its TCO value is becoming competitive, whereas FCEV provides a more viable solution than BEV for long-haul applications due to shorter refuelling time and lower load capacity penalties. Furthermore, degradation of performance in lithium-ion batteries is found to have a minor impact on TCO if battery replacement is not required. However, critical component replacement and warranty can influence commercial viability. Given
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Journal articleCacciarelli D, Kulahci M, 2024,
Active learning for data streams: a survey
, Machine Learning, Vol: 113, Pages: 185-239, ISSN: 0885-6125<jats:title>Abstract</jats:title><jats:p>Online active learning is a paradigm in machine learning that aims to select the most informative data points to label from a data stream. The problem of minimizing the cost associated with collecting labeled observations has gained a lot of attention in recent years, particularly in real-world applications where data is only available in an unlabeled form. Annotating each observation can be time-consuming and costly, making it difficult to obtain large amounts of labeled data. To overcome this issue, many active learning strategies have been proposed in the last decades, aiming to select the most informative observations for labeling in order to improve the performance of machine learning models. These approaches can be broadly divided into two categories: static pool-based and stream-based active learning. Pool-based active learning involves selecting a subset of observations from a closed pool of unlabeled data, and it has been the focus of many surveys and literature reviews. However, the growing availability of data streams has led to an increase in the number of approaches that focus on online active learning, which involves continuously selecting and labeling observations as they arrive in a stream. This work aims to provide an overview of the most recently proposed approaches for selecting the most informative observations from data streams in real time. We review the various techniques that have been proposed and discuss their strengths and limitations, as well as the challenges and opportunities that exist in this area of research.</jats:p>
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Journal articleHogg A, Jenkins M, Liu H, et al., 2024,
HRTF upsampling with a generative adversarial network using a gnomonic equiangular projection
, IEEE Transactions on Audio, Speech and Language Processing, Vol: 32, Pages: 2085-2099, ISSN: 1558-7916An individualised (HRTF) is very important for creating realistic (VR) and (AR) environments. However, acoustically measuring high-quality HRTFs requires expensive equipment and an acoustic lab setting. To overcome these limitations and to make this measurement more efficient HRTF upsampling has been exploited in the past where a high-resolution HRTF is created from a low-resolution one. This paper demonstrates how (GAN) can be applied to HRTF upsampling. We propose a novel approach that transforms the HRTF data for direct use with a convolutional (SRGAN). This new approach is benchmarked against three baselines: barycentric upsampling, (SH) upsampling and an HRTF selection approach. Experimental results show that the proposed method outperforms all three baselines in terms of (LSD) and localisation performance using perceptual models when the input HRTF is sparse (less than 20 measured positions).
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Journal articleSadan MK, Lian GJ, Smith RM, et al., 2023,
Co, Ni-free ultrathick free-standing dry electrodes for sustainable lithium-ion batteries
, ACS Applied Energy Materials, Vol: 6, Pages: 12166-12171, ISSN: 2574-0962The conventional method of manufacturing lithium-ion battery electrodes employs a complex slurry casting process with solvents that are not environmentally friendly and process parameters that are often difficult to control. This study explores a solvent-free dry electrode fabrication process of Co- and Ni-free LiMn2O4 (LMO) cathodes using a fibrillated polymer, polytetrafluoroethylene (PTFE). A thick, dry electrode (265–368 μm, 30–64 mg cm–2) of LMO cathode was prepared successfully for the first time. Altering the conductive additives in the LMO dry electrode revealed multiwalled carbon nanotubes (CNTs) as the best conducting agent for dry electrode formulation in terms of conductivity and rate performance. Additionally, an all-dry electrode full cell consisting of both a dry electrode cathode (LMO) and an anode (LTO) delivered a stable cycling performance with a capacity retention of 82.8% after 200 cycles, demonstrating the scope for all-dry electrode full cells for future applications.
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Journal articlePan Y, Ruan H, Regmi YN, et al., 2023,
A Machine Learning Accelerated Hierarchical 3D+1D Model for Proton Exchange Membrane Fuel Cells
, ECS Meeting Abstracts, Vol: MA2023-02, Pages: 1706-1706<jats:p> Physics-based continuum models for proton exchange membrane fuel cells (PEMFCs) are an essential tool for fuel cell design and management. To date, many continuum models, ranging from 1D to 3D, have been developed for PEMFCs. Although computationally efficient, 1D models do not account for heterogeneity in flow fields, which negatively impact their accuracy. In contrast, 2D and 3D models are usually more representative of actual operating conditions but computationally intensive due to the coupled partial differential equations and large number of mesh elements involved. To overcome these issues, a hierarchical approach that combines a 2D/3D description of flow fields, gas diffusion layers (GDLs) and a simplified microporous layer (MPL)/catalyst layer (CL)/membrane sub-model has been proposed in the literature. However, studies based on this method often use a simplified or 0D MPL/CL/membrane sub-model, whose results may deviate from a full 1D description due to the neglected nonlinearity, especially at higher loads.</jats:p> <jats:p>In this study, we present a computationally efficient 3D+1D hierarchical model for PEMFCs accelerated by machine learning. The 3D model, which captures the two-phase flow in the gas channels and GDLs, is coupled with a full 1D description of the MPLs, membrane, CLs, and CL agglomerates by exchanging boundary values and fluxes, as shown in the figure. To avoid the high computing cost increase associated with the full 1D description, we develop a physics-informed neural network to replace the 1D sub-model for coupling with the 3D model, while maintaining the full description of fuel cell internal states. Large synthetic datasets are generated using the 1D model for training the neural network, ensuring the accuracy of the model. The proposed 3D+1D model is validated against experimentally obtained polarization curves and high frequency resistances under different relative humidities. The proposed
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Journal articleGovey-Scotland J, Johnstone L, Myant C, et al., 2023,
Towards a skin-on-a-chip for screening the dermal absorption of cosmetics
, Lab on a Chip: miniaturisation for chemistry, physics, biology, materials science and bioengineering, Vol: 23, Pages: 5068-5080, ISSN: 1473-0189Over the past few decades, there have been increasing global efforts to limit or ban the use of animals for testing cosmetic products. This ambition has been at the heart of international endeavours to develop new in vitro and animal-free approaches for assessing the safety of cosmetics. While several of these new approach methodologies (NAMs) have been approved for assessing different toxicological endpoints in the UK and across the EU, there remains an absence of animal-free methods for screening for dermal absorption; a measure that assesses the degree to which chemical substances can become systemically available through contact with human skin. Here, we identify some of the major technical barriers that have impacted regulatory recognition of an in vitro skin model for this purpose and propose how these could be overcome on-chip using artificial cells engineered from the bottom-up. As part of our future perspective, we suggest how this could be realised using a digital biomanufacturing pipeline that connects the design, microfluidic generation and 3D printing of artificial cells into user-crafted synthetic tissues. We highlight milestone achievements towards this goal, identify future challenges, and suggest how the ability to engineer animal-free skin models could have significant long-term consequences for dermal absorption screening, as well as for other applications.
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Journal articleMorley JD, George C, Hadler K, et al., 2023,
Crystallography of active particles defining battery electrochemistry
, Advanced Energy Materials, ISSN: 1614-6832Crystallographic features of battery active particles impose an inherent limitation on their electrochemical figures of merit namely capacity, roundtrip efficiency, longevity, safety, and recyclability. Therefore, crystallographic properties of these particles are increasingly measured not only to clarify the principal pathways by which they store and release charge but to realize the full potential of batteries. Here, state-of-the-art advances in Li+, K+, and Na+ chemistries are reviewed to reiterate the links between crystallography variations and battery electrochemical trends. These manifest at different length scales and are accompanied by a multiplicity of processes such as doping, cation disorder, directional crystal growth and extra redox. In light of this, an emphasis is placed on the need for more accurate correlations between crystallographic structure and battery electrochemistry in order to harness crystallographic beneficiation into electrode material design and manufacture, translating into high-performance and safe energy storage solutions.
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Journal articleYasin L, Atkinson A, Cooper SJ, et al., 2023,
Identifiability of the mechanisms governing the reaction kinetics of MIEC electrodes in solid oxide cells
, Electrochimica Acta, Vol: 472, ISSN: 0013-4686The oxygen reduction reaction (ORR) is the main phenomenon occurring in mixed ionic and electronic conductors (MIECs) used as air electrodes in solid oxide cells. Their optimisation requires the identification of the ORR regime, which is typically performed via electrochemical impedance spectroscopy (EIS). In this study we present a physics-based model to simulate the impedance spectra of p-type oxygen-deficient perovskite MIEC materials. The EIS response of four extreme kinetic scenarios, characterised by the rate-determining step (electron-transfer or ion-transfer) and the high/low surface coverage of adsorbed oxygen, is mechanistically interpreted for both dense films and porous electrodes. A strategy for kinetic identification is proposed based on distinctive EIS fingerprints at different oxygen partial pressures (pO2) and cathodic bias. However, distinguishing the kinetic scenarios is not free from ambiguity even in dense films since some scenarios are discriminated only via a quantitative analysis, which may be susceptible to experimental errors in real measurements, and reverse behaviours appear when combining cathodic bias with pO2 variation. More difficulties arise in porous electrodes since bulk oxygen vacancy transport interacts with the ORR response. Application of the proposed strategy using literature data for some common MIEC materials shows the typical challenges of kinetic identification when relying solely on EIS.
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Journal articleBigestans D, Cardin M-A, Kazantzis N, 2023,
Economic performance evaluation of flexible centralised and decentralised blue hydrogen production systems design under uncertainty
, Applied Energy, Vol: 352, ISSN: 0306-2619Blue hydrogen is viewed as an important energy vector in a decarbonised global economy, but its large-scale and capital-intensive production displays economic performance vulnerabities in the face of increased market and regulatory uncertainty. This study analyses flexible (modular) blue hydrogen production plant designs and evaluates their effectiveness to enhance economic performance under uncertainty. The novelty of this work lies in the development of a comprehensive techno-economic evaluation framework that considers flexible centralised and decentralised blue hydrogen plant design alternatives in the presence of irreducible uncertainty, whilst explicitly considering the time value of money, economies of scale and learning effects. A case study of centralised and decentralised blue hydrogen production for the transport sector in the San Francisco area is developed to highlight the underlying value of flexibility. The proposed methodological framework considers various blue hydrogen plant designs (fixed, phased, and flexible) and compares them using relevant economic indicators (net present value (NPV), capex, value-at-risk/gain, etc.) through a detailed Monte Carlo simulation framework. Results indicate that flexible centralised hydrogen production yields greater economic value than alternative designs, despite the associated cost-premium of modularity. It is also shown that the value of flexibility increases under greater uncertainty, higher learning rates and weaker economies of scale. Moreover, sensitivity analysis reveals that flexible design remains the preferred investment option over a wide range of market and regulatory conditions except for high initial hydrogen demand. Finally, this study demonstrates that major regulatory and market uncertainties surrounding blue hydrogen production can be effectively managed through the application of flexible engineering system design that protects the investment from major downside risks whilst allowing access to
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Journal articleYi Y, Demirel P, 2023,
The impact of sustainability-oriented dynamic capabilities on firm growth: investigating the green supply chain management and green political capabilities
, Business Strategy and the Environment, Vol: 32, Pages: 5873-5888, ISSN: 0964-4733Building on the dynamic capabilities literature and natural-resource-based view, the paper examines whether firms can attain sales growth through a range of sustainability-oriented dynamic capabilities including (1) internal green supply chain management capabilities, (2) external green supply chain management capabilities and (3) green political capabilities. Based on a dataset of 277 public US firms between 2010 and 2020, a panel quantile model of firm growth showcases that while internal green supply chain capabilities and green political capabilities affect firms' growth performance positively, external green supply chain capabilities are associated with slower growth. Importantly, the results indicate that the positive growth effects of green political capabilities are short-lived, while those of internal green supply chain capabilities are long-lived. The study contributes to the sustainability-oriented dynamic capabilities literature by showing that different capabilities have different implications for firm growth depending on the firm's base performance and the time periods under consideration.
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Journal articleBonkile MP, Jiang Y, Kirkaldy N, et al., 2023,
Coupled electrochemical-thermal-mechanical stress modelling in composite silicon/graphite lithium-ion battery electrodes
, Journal of Energy Storage, Vol: 73, ISSN: 2352-152XSilicon is often added to graphite battery electrodes to enhance the electrode-specific capacity, but it undergoes significant volume changes during (de)lithiation, which results in mechanical stress, fracture, and performance degradation. To develop long-lasting and energy-dense batteries, it is critical to understand the non-linear stress behaviour in composite silicon-graphite electrodes. In this study, we developed a coupled electrochemical-thermal-mechanical model of a composite silicon/graphite electrode in PyBaMM (an open-source physics-based modelling platform). The model is experimentally validated against a commercially available LGM50T battery, and the effects of C-rates, depth-of-discharge (DoD), and temperature are investigated. The developed model can reproduce the voltage hysteresis from the silicon and provide insights into the stress response and crack growth/propagation in the two different phases. The stress in the silicon is relatively low at low DoD but rapidly increases at a DoD >~80%, whereas the stress in the graphite increases with decreasing temperature and DoD. At higher C-rates, peak stress in the graphite increases as expected, however, this decreases for silicon due to voltage cut-offs being hit earlier, leading to lower active material utilisation since silicon is mostly active at high DoD. Therefore, this work provides an improved understanding of stress evolution in composite silicon/graphite lithium-ion batteries.
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Journal articleSadek M, Calvo R, Mougenot C, 2023,
Co-designing conversational agents: a comprehensive review and recommendations for best practices
, Design Studies, Vol: 89, ISSN: 0142-694XThis paper presents a comprehensive review of fifty-two studies co-designing conversational agents (CAs). Its objectives are to synthesise prior CA co-design efforts and provide actionable recommendations for future endeavours in CA co-design. The review systematically evaluates studies' methodological and contextual aspects, revealing trends and limitations. These insights converge into practical recommendations for co-designing CAs, including (1) selecting the most suitable design technique aligned with desired CA outcomes, (2) advocating continuous stakeholder involvement throughout the design process, and (3) emphasising the elicitation and embodiment of stakeholder values to ensure CA designs align with their perspectives. This paper contributes to standardising and enhancing co-design practices, promising to improve the quality of outcomes in the case of CAs while benefiting stakeholders and users.
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Journal articleHarkin R, Wu H, Nikam S, et al., 2023,
Reuse of grade 23 Ti6Al4V powder during the laser-based powder bed fusion process
, Metals, Vol: 10, ISSN: 2075-4701Titanium alloy powder used for laser-based powder bed fusion (L-PBF) process is costly. One of the solutions is the inclusion of a powder recycling strategy, allowing unused or exposed powder particles to be recuperated post manufacture, replenished and used for future builds. However, during a L-PBF process, powder particles are exposed to high levels of concentrated energy from the laser. Particularly those in close proximity to the melt pool, leading to the formation of spatter and agglomerated particles. These particles can settle onto the powder bed, which can then influence the particle size distribution and layer uniformity. This study analysed extra-low interstitial (ELI) Ti6Al4V (Grade 23) powder when subjected to nine recycle iterations, tracking powder property variation across the successive recycling stages. Characterisation included chemical composition focusing upon O, N, and H content, particle size distribution, morphology and tapped and bulk densities. On review of the compositional analysis, the oxygen content exceeded the 0.13% limit for the ELI grade after 8 recycles, resulting in the degradation from Grade 23 level.
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