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  • Journal article
    Pan Y, Ruan H, Wu B, Regmi YN, Wang H, Brandon NPet al., 2024,

    A machine learning driven 3D+1D model for efficient characterization of proton exchange membrane fuel cells

    , Energy and AI, Vol: 17, ISSN: 2666-5468

    The computational demands of 3D continuum models for proton exchange membrane fuel cells remain substantial. One prevalent approach is the hierarchical model combining a 2D/3D flow field with a 1D sub-model for the catalyst layers and membrane. However, existing studies often simplify the 1D domain to a linearized 0D lumped model, potentially resulting in significant errors at high loads. In this study, we present a computationally efficient neural network driven 3D+1D model for proton exchange membrane fuel cells. The 3D sub-model captures transport in the gas channels and gas diffusion layers and is coupled with a 1D electrochemical sub-model for microporous layers, membrane, and catalyst layers. To reduce computational intensity of the full 1D description, a neural network surrogates the 1D electrochemical sub-model for coupling with the 3D domain. Trained by model-generated large synthetic datasets, the neural network achieves root mean square errors of less than 0.2%. The model is validated against experimental results under various relative humidities. It is then employed to investigate the nonlinear distribution of internal states under different operating conditions. With the neural network operating at 0.5% of the computing cost of the 1D sub-model, the hybrid model preserves a detailed and nonlinear representation of the internal fuel cell states while maintaining computational costs comparable to conventional 3D+0D models. The presented hybrid data-driven and physical modeling framework offers high accuracy and computing speed across a broad spectrum of operating conditions, potentially aiding the rapid optimization of both the membrane electrode assembly and the gas channel geometry.
  • Journal article
    Wu B, 2024,

    Addressing the battery talent shortage with interdisciplinarity

    , Nature Energy, Vol: 9, Pages: 1044-1045, ISSN: 2058-7546
  • Thesis dissertation
    Hewitt S, 2024,

    Emotions and Exercise: Mapping Emotions through Exercise to Design for a Healthier Lifestyle

    This thesis details an investigation of the relationship between human emotions and exercise. A new understanding of the emotional experiences resulting from taking part in exercise is reported and used to inform the development of visualisations and tools to support those seeking to design new exercise interventions. The key argument of this research is that if we can understand fully the emotional drivers for, and barriers against exercise, we can inform exercisers and designers alike how to best navigate an active lifestyle and the connected emotional experience. Analysis and synthesis of previous literature across the fields of public health, exercise psychology and sports science highlighted that emotions are both barriers and benefits to exercise. This led to an exploration of emotions and emotion models used within the fields of design, behavioural science and emotion psychology and, an investigation into existing design solutions to determine their efficacy and what makes them successful or unsuccessful. The interest then shifts to the specific relationship between emotions and exercise leading to a systematic literature review which discovers a lack of focused understanding of emotions and exercise types across the published research. Two user focused studies are presented, each exploring this relationship in breadth and depth to help understand better the link between emotions and exercise and build a more comprehensive map of their relationship. The first study, a quantitative exploration, presents an overview of the emotion and exercise relationship and identifies eight key emotions: calmness, excitement, interest, joy, pride, relief, satisfaction and, triumph. Each emotion is experienced differently depending on five variables: participant sex, time of elicitation, level of athlete, number of participants, and exercise type. The findings give a greater understanding of how different variables can affect individual’s emotional experiences and all
  • Journal article
    Heath BE, Suzuki R, LePenru NP, Skinner J, Orme CDL, Ewers RM, Sethi SS, Picinali Let al., 2024,

    Spatial ecosystem monitoring with a Multichannel Acoustic Autonomous Recording Unit (MAARU)

    , Methods in Ecology and Evolution, Vol: 15, Pages: 1568-1579, ISSN: 2041-210X

    1. Multi-microphone recording adds spatial information to recorded audio with emerging applications in ecosystem monitoring. Specifically placing sounds in space can improve animal count accuracy, locate illegal activity like logging and poaching, track animals to monitor behaviour and habitat use and allow for ‘beamforming’ to amplify sounds from target directions for downstream classification. Studies have shown many advantages of spatial acoustics, but uptake remains limited as the equipment is often expensive, complicated, inaccessible or only suitable for short-term deployments.2. With an emphasis on enhanced uptake and usability, we present a low-cost, open-source, six-channel recorder built entirely from commercially available components which can be integrated into a solar-powered, online system. The MAARU (Multichannel Acoustic Autonomous Recording Unit) works as an independent node in long-term autonomous, passive and/or short-term deployments. Here, we introduce MAARU's hardware and software and present the results of lab and field tests investigating the device's durability and usability.3. MAARU records multichannel audio with similar costs and power demands to equivalent omnidirectional recorders. MAARU devices have been deployed in the United Kingdom and Brazil, where we have shown MAARUs can accurately localise pure tones up to 6 kHz and bird calls as far as 8 m away (±10° range, 100% and >60% of signals, respectively). Louder calls may have even further detection radii. We also show how beamforming can be used with MAARUs to improve species ID confidence scores.4. MAARU is an accessible, low-cost option for those looking to explore spatial acoustics accurately and easily with a single device, and without the formidable expenses and processing complications associated with establishing arrays. Ultimately, the added directional element of the multichannel recording provided by MAARU allows for enhanced recording
  • Journal article
    Wu H, Tian F, Tang C, Guo Z, Li Net al., 2024,

    Novel Heat Stamping of Ti6Al4V panels with high drawability and low springback

    , MATEC Web of Conferences, Vol: 401, ISSN: 2261-236X

    Conventional commonly used titanium stamping techniques like hot forming and superplastic forming each have distinct disadvantages. Hot forming usually leads to limited formability and significant springback, whilst superplastic forming often results in long cycle times, high energy use, and costly tooling. A novel, energy-efficient, and cost-effective Heat Stamping process emerges as a promising solution. Two types of Ti6Al4V components, cup-shaped and U-shaped, were produced using the novel Heat Stamping process, and their properties were examined. A defect-free cup-shaped component achieving a considerably high draw ratio of up to 1.8, was successfully fabricated. A moderate enhancement in the hardness of the component indicated a superior post-form strength achieved by Heat Stamping. Further analysis of the U-shaped components shows that the one produced using the novel method demonstrated a notable reduction in springback angle, from 4.8° to 0.7°, highlighting the potential of H eat Stamping in achieving high shape accuracy for near-net-shape forming.
  • Journal article
    Li H, Zhou H, Li N, 2024,

    An integrated convolutional neural network-based surrogate model for crashworthiness performance prediction of hot-stamped vehicle panel components

    , MATEC Web of Conferences, Vol: 401, ISSN: 2261-236X

    During the structural design of vehicle components, Finite Element (FE) modelling has been extensively used for simulations of physical experiments. A typical design optimisation task requires iterative simulations to identify the optimum design, where FE simulations can be too time-consuming. Surrogate models have been developed to approximate complex simulations, which can reduce computational time and improve the efficiency of the design cycle. This paper presents a novel application of convolutional neural network (CNN) on rapid predictions of crashworthiness performance of vehicle panel components considering manufacturability. The dataset for training the model was generated based on the FE results of hot-stamped ultra-high strength steel (UHSS) B-pillar components. The formed components were analysed with a simplified lateral crash test to evaluate the deformation under impact. The trained model can instantly predict the deformation of the designed component with high accuracy compared to the FE results. Due to its high computational efficiency and precision, the surrogate model enables faster and more extensive design evaluations.
  • Conference paper
    Chen L, Song Y, Ding S, Sun L, Childs P, Zuo Het al., 2024,

    TRIZ-GPT: An LLM-Augmented Method For Problem-Solving

    , ASME 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Publisher: American Society of Mechanical Engineers

    <jats:title>Abstract</jats:title> <jats:p>TRIZ, the Theory of Inventive Problem Solving, is derived from a comprehensive analysis of patents across various domains, offering a framework and practical tools for problem-solving. Despite its potential to foster innovative solutions, the complexity and abstractness of TRIZ methodology often make its application challenging. This can require users to have a deep understanding of the theory, as well as substantial practical experience and knowledge across various disciplines. The advent of Large Language Models (LLMs) presents an opportunity to address these challenges by leveraging their extensive knowledge bases and reasoning capabilities for innovative solution generation within TRIZ-based problem-solving process. This study explores and evaluates the application of LLMs within the TRIZ-based problem-solving process. The construction of TRIZ case collections establishes a solid empirical foundation for our experiments and offers valuable resources to the TRIZ community. A specifically designed workflow, utilizing step-by-step reasoning and evaluation-validated prompt strategies, effectively transforms concrete problems into TRIZ problems and finally generates inventive solutions. We present a case study in the mechanical engineering field that highlights the practical application of this LLM-augmented method. This showcases GPT-4’s ability to generate solutions that closely resonate with original solutions and suggests more implementation mechanisms.</jats:p>
  • Journal article
    Hair SW, Cooper SJ, Shaffer MSP, 2024,

    Beyond slurry cast: patterning of a monolithic active material sheet to form free-standing, solvent-free, and low-tortuosity battery electrodes

    , Cell Reports Physical Science, Vol: 5, ISSN: 2666-3864

    Commercial lithium-ion battery electrodes today are manufactured by slurry casting active material powder onto a metal current collector foil. This manufacturing process has become embedded over recent decades but limits commercial cell performance. This paper presents patterning of a monolithic active material sheet as an alternative to slurry casting. The concept is proven experimentally by laser drilling a pyrolytic graphite sheet to increase the gravimetric active material capacity from 10 mA h g−1 to 450 mA h g−1, when used as a negative lithium-intercalation electrode. Cell-level calculations show that, without changing the chemistry, a pyrolytic graphite sheet electrode with a hexagonal array of 5 μm diameter, 20 μm pitch channels could increase the gravimetric energy density of a LGM50 cell by 22% to 322 W h kg−1. By moving beyond slurry casting, patterned monolithic electrodes could enable batteries with lower cost, reduced energy intensity, and enhanced performance.
  • Journal article
    Huang Q, Daubner S, Schneider D, Zheng X, Liu S, Du Y, Nestler Bet al., 2024,

    Multiphase transformation and mechanical analysis of polycrystalline Cu x Li y Sn nanoparticle during lithiation via phase diagram-guided phase-field approach

    , ELECTROCHIMICA ACTA, Vol: 495, ISSN: 0013-4686
  • Journal article
    Tu Y, Wu B, Ai W, Martinez-Paneda Eet al., 2024,

    Mechanical Failure of Core-Shell Cathode Particles: The Effects of Concentration-Dependent Material Properties and Phase Field Fracture Modelling

    , ECS Meeting Abstracts, Vol: MA2024-01, Pages: 488-488

    <jats:p> The use of core-shell cathode particles in lithium-ion batteries is an attractive approach to enhancing energy density whilst retaining lifetime, through reducing undesired reactions at the electrode-electrolyte interface and limiting the volume change of the electrode particles. However, mechanical failure through the fracture and debonding of the core-shell interface is a major challenge. In this work, we employ a coupled finite-element model to predict and mitigate the mechanical failure of core-shell cathode structures, taking as example a particle of NMC811 (core) coated with NMC111 (shell). In particular, we focus on two aspects:</jats:p> <jats:p>The first one involves the assumptions of material properties as inputs of the model. The material properties are often considered constant by battery modelling researchers, yet these parameters can vary significantly during charge/discharge. For example, experiments have unveiled a three-orders-of-magnitude drop in the diffusion coefficient of NMC materials during discharge [1]. Here, we incorporate material properties obtained from experimental data, including concentration-dependent diffusion coefficient obtained from GITT measurement and partial molar volume derived from in situ X-ray diffraction data. Our results indicate that when assuming a concentration-dependent partial molar volume, the maximum values of tensile hoop stress in the shell are nearly three times lower than those predicted with constant average properties, diminishing the likelihood of fracture.</jats:p> <jats:p>When accounting for concentration-dependent diffusion coefficient, large concentration gradient is observed near the outer surface of the core due to reduced lithium mobility at high states of lithiation, hindering full electrode capacity utilisation. The significant concentration gradient and capacity underutilisation align with direct observations from experiments [2]
  • Conference paper
    Daugintis R, Alary B, Geronazzo M, Picinali Let al., 2024,

    Effects of binaural rendering personalisation and reverberation on speech-on-speech masking

    , AES 5th International Conference on Audio for Virtual and Augmented Reality, Publisher: Audio Engineering Society

    This study investigates the effect of head-related transfer function (HRTF) personalisation on understanding binaurally rendered target speech masked by interfering speakers in reverberant conditions. During a listening test, participants had to identify a correct colour-number combination from a virtual talker rendered in front of them while ignoring two interfering talkers positioned either in front or at the back. The sound was rendered with either an individual HRTF or one of two non-individual ones. These were selected for each participant as the best or the worst–matching from the same HRTF dataset, based on predictions of a computational auditory model for sound localisation. Two types of reverb from measured spatial room impulse responses (SRIRs) were applied to the speech: realistic dichotic reverberation decoded from 4th-order Ambisonic SRIRs or diotic reverb based on the omnidirectional Ambisonic channel IR as a baseline. Preliminary results show that realistic dichotic reverb improves speech perception when interfering speech is co-located with the target. No significant differences were observed across HRTF conditions on a group level, but individual HRTF-related performance differences exist, requiring further intra-subject analyses and data collection to characterise the individual results.
  • Journal article
    Ballou N, Denisova A, Ryan R, Rigby CS, Deterding Set al., 2024,

    The Basic Needs in Games Scale (BANGS): a new tool for investigating positive and negative video game experiences

    , International Journal of Human-Computer Studies, Vol: 188, ISSN: 1071-5819

    Players’ basic psychological needs for autonomy, competence, and relatedness are among the most commonly used constructs used in research on what makes video games so engaging, and how they might support or undermine user wellbeing. However, existing measures of basic psychological needs in games have important limitations—they either do not measure need frustration, or measure it in a way that may not be appropriate for the video games domain, they struggle to capture feelings of relatedness in both single- and multiplayer contexts, and they often lack validity evidence for certain contexts (e.g., playtesting vs experience with games as a whole). In this paper, we report on the design and validation of a new measure, the Basic Needs in Games Scale (BANGS), whose 6 subscales cover satisfaction and frustration of each basic psychological need in gaming contexts. The scale was validated and evaluated over five studies with a total of 1246 unique participants. Results supported the theorized structure of the scale and provided evidence for discriminant, convergent and criterion validity. Results also show that the scale performs well over different contexts (including evaluating experiences in a single game session or across various sessions) and over time, supporting measurement invariance. Further improvements to the scale are warranted, as results indicated lower reliability in the autonomy frustration subscale, and a surprising non-significant correlation between relatedness satisfaction and frustration. Despite these minor limitations, BANGS is a reliable and theoretically sound tool for researchers to measure basic needs satisfaction and frustration with a degree of domain validity not previously available.
  • Journal article
    Ferraro P, Penzkofer A, King C, Shorten Ret al., 2024,

    Feedback control for distributed ledgers: an attack mitigation policy for DAG-based DLTs

    , IEEE Transactions on Automatic Control, Vol: 69, Pages: 5492-5499, ISSN: 0018-9286

    In this paper we present a feedback approach to the design of an attack mitigation policy for DAG-based Distributed Ledgers. We develop a model to analyse the behaviour of the ledger under the so called Tips Inflation Attack , which endangers the liveness of transactions, and we design a control strategy to counteract this attack strategy. The efficacy of this approach is showcased through a theoretical analysis, in the form of two theorems about the stability properties of the ledger with and without the controller, and extensive Monte Carlo simulations of an agent-based model of the distributed ledger.
  • Journal article
    Ewers RM, Orme CDL, Pearse WD, Zulkifli N, Yvon-Durocher G, Yusah KM, Yoh N, Yeo DCJ, Wong A, Williamson J, Wilkinson CL, Wiederkehr F, Webber BL, Wearn OR, Wai L, Vollans M, Twining JP, Turner EC, Tobias JA, Thorley J, Telford EM, Teh YA, Tan HH, Swinfield T, Svátek M, Struebig M, Stork N, Sleutel J, Slade EM, Sharp A, Shabrani A, Sethi SS, Seaman DJI, Sawang A, Roxby GB, Rowcliffe JM, Rossiter SJ, Riutta T, Rahman H, Qie L, Psomas E, Prairie A, Poznansky F, Pillay R, Picinali L, Pianzin A, Pfeifer M, Parrett JM, Noble CD, Nilus R, Mustaffa N, Mullin KE, Mitchell S, Mckinlay AR, Maunsell S, Matula R, Massam M, Martin S, Malhi Y, Majalap N, Maclean CS, Mackintosh E, Luke SH, Lewis OT, Layfield HJ, Lane-Shaw I, Kueh BH, Kratina P, Konopik O, Kitching R, Kinneen L, Kemp VA, Jotan P, Jones N, Jebrail EW, Hroneš M, Heon SP, Hemprich-Bennett DR, Haysom JK, Harianja MF, Hardwick J, Gregory N, Gray R, Gray REJ, Granville N, Gill R, Fraser A, Foster WA, Folkard-Tapp H, Fletcher RJ, Fikri AH, Fayle TM, Faruk A, Eggleton P, Edwards DP, Drinkwater R, Dow RA, Döbert TF, Didham RK, Dickinson KJM, Deere NJ, de Lorm T, Dawood MM, Davison CW, Davies ZG, Davies RG, Dančák M, Cusack J, Clare EL, Chung A, Chey VK, Chapman PM, Cator L, Carpenter D, Carbone C, Calloway K, Bush ER, Burslem DFRP, Brown KD, Brooks SJ, Brasington E, Brant H, Boyle MJW, Both S, Blackman J, Bishop TR, Bicknell JE, Bernard H, Basrur S, Barclay MVL, Barclay H, Atton G, Ancrenaz M, Aldridge DC, Daniel OZ, Reynolds G, Banks-Leite Cet al., 2024,

    Thresholds for adding degraded tropical forest to the conservation estate

    , Nature, Vol: 631, Pages: 808-813, ISSN: 0028-0836

    Logged and disturbed forests are often viewed as degraded and depauperate environments compared with primary forest. However, they are dynamic ecosystems1 that provide refugia for large amounts of biodiversity2,3, so we cannot afford to underestimate their conservation value4. Here we present empirically defined thresholds for categorizing the conservation value of logged forests, using one of the most comprehensive assessments of taxon responses to habitat degradation in any tropical forest environment. We analysed the impact of logging intensity on the individual occurrence patterns of 1,681 taxa belonging to 86 taxonomic orders and 126 functional groups in Sabah, Malaysia. Our results demonstrate the existence of two conservation-relevant thresholds. First, lightly logged forests (<29% biomass removal) retain high conservation value and a largely intact functional composition, and are therefore likely to recover their pre-logging values if allowed to undergo natural regeneration. Second, the most extreme impacts occur in heavily degraded forests with more than two-thirds (>68%) of their biomass removed, and these are likely to require more expensive measures to recover their biodiversity value. Overall, our data confirm that primary forests are irreplaceable5, but they also reinforce the message that logged forests retain considerable conservation value that should not be overlooked.
  • Conference paper
    Li Y, Zhang Y, Yang Y, Zihan T, Hu Z, Xie C, Pan Z, Chen C, Qi T, Zhu Z, He Q, Li S, Yin Y, Han J, Childs P, Cascini G, Li Met al., 2024,

    The effects of short-term meditation on the creativity of novice designers: a pilot design task study using TTCT-figural assessment

    , 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024), Publisher: AHFE International, Pages: 51-60, ISSN: 2771-0718

    Creativity is long regarded as one of the fundamental traits that indicates design capability. The concept of creativity encompasses the capacity to produce innovative and novel concepts or ideas, to devise or articulate imagination and intellect, and to stimulate the potential of imagination and ingenuity embodying their capacity to conceive, craft, and develop innovative ideas for products. Previous studies have revealed the connection and functionality between meditation and creativity. However, general creativity measurements, which studies to date have mainly focused on, might not be able to demonstrate the performance of designers in a creative process adequately.Therefore, this study applied a design task-based evaluation with traditional TTCT assessment, which might be more suitable to describe the creative performance of novice designers. The study aims to explore: (1) the relationship between short-term meditation and creativity; (2) the effects of short-term meditation on the design qualities in design tasks of novice designers.42 first-year design students were recruited and were divided into meditation group (n=24) and control group (n=18). Participants conducted a demographic survey and the Torrance Tests of Creative Thinking (TTCT, in its figural variant) firstly. The meditation group was then given a 110-minute audio tape-based meditation intervention, and the control group was given a 110-minute audio tape intervention, which is a recording of scientific articles. Both interventions were performed twice a week on the weekends. After that, TTCT was given to the participants again. Then each participant received an interview on the changes in mood state and creativity. After the TTCT on the second day, the participants completed the Design with Morphological Table Task (DwMT) to assess their design qualities in a product design task. Through data analysis, TTCT results indicate that short-term meditation can significantly improve the creativity of nov
  • Conference paper
    Wang Y, Qian Q, Boyle D, 2024,

    Probabilistic constrained reinforcement learning with formal interpretability

    , International Conference on Machine Learning, Publisher: MLResearchPress, Pages: 51303-51327, ISSN: 2640-3498

    Reinforcement learning can provide effective reasoning for sequential decision-making problems with variable dynamics. Such reasoning in practical implementation, however, poses a persistent challenge in interpreting the reward function and the corresponding optimal policy. Consequently, representing sequential decision-making problems as probabilistic inference can have considerable value, as, in principle, the inference offers diverse and powerful mathematical tools to infer the stochastic dynamics whilst suggesting a probabilistic interpretation of policy optimization. In this study, we propose a novel Adaptive Wasserstein Variational Optimization, namely AWaVO, to tackle these interpretability challenges. Our approach uses formal methods to achieve the interpretability for convergence guarantee, training transparency, and intrinsic decision-interpretation. To demonstrate its practicality, we showcase guaranteed interpretability with a global convergence rate Θ(1/√T) in simulation and in practical quadrotor tasks. In comparison with state-of-the-art benchmarks, including TRPO-IPO, PCPO, and CRPO, we empirically verify that AWaVO offers a reasonable trade-off between high performance and sufficient interpretability.
  • Journal article
    Picinali L, Vickers D, 2024,

    Virtual reality in hearing research: Opportunities and future challenges

    , Acoustics Bulletin, Vol: 50, Pages: 46-47, ISSN: 0308-437X
  • Thesis dissertation
    Giannari A, 2024,

    Modelling of brain neuronal networks and therapy design for neurodegenerative diseases via nonlinear control

    This thesis introduces a novel computational framework for modelling heterogeneous neuronal networks as well as for developing optimal virtual treatment regimens via the application of nonlinear control. The modularity, scalability and adaptability of the proposed framework are attributed to the segregation of the neuron and network dynamics via a control-inspired feedback structure. This allows for the independent manipulation of the connectivity matrices that define the network structure and size. The involvement of biophysically realistic variables and parameters make it ideal for the study of healthy networks as well as ones that are compromised by neurodegeneration under the possible influence of pharmaceutical substances. We focus on providing scalable one-dimensional and two-dimensional realistic lateral inhibition models, which perform contrast enhancement and edge detection on visual stimuli, with the latter being responsible for the perception of optical illusions by the human eye retina. The abnormal perception of the illusions is an early symptom of diabetic retinopathy, a neurodegenerative disease that attacks the synaptic couplings within the lateral inhibition network. Based on this, we produce diabetic lateral inhibition models that fail to perceive the optical illusions by altering the parameters that are impaired due to the pathophysiology of diabetic retinopathy. We consider the healthy and diabetic images of optical illusions as computational phenotypes and the error between them is used to design an adaptive terminal error iterative learning controller to find the optimal drug amount sufficient to recover the functionality of the network and therefore to restore the perception of the optical illusions. The virtual drug acts upon the defective model parameter that is considered an effective therapeutic target. To the extent of our knowledge, this is the first instance a realistically measurable output is utilised as feedback to a nonlinear contro
  • Journal article
    Liu H, You SS, Gao Z, Hu N, Zhao Yet al., 2024,

    Next generation of gastrointestinal electrophysiology devices

    , Nature Reviews Gastroenterology & Hepatology, Vol: 21, Pages: 457-458, ISSN: 1759-5053

    This Comment reviews the evolution from early electrophysiological studies to advanced diagnostic tools, highlighting the challenges and innovations shaping the future of gastrointestinal diagnostics.
  • Conference paper
    Wang M, Zhou Y, Stewart R, 2024,

    Soft wearable robotics: innovative knitting-integrated approaches for pneumatic actuators design

    , DIS '24: Designing Interactive Systems Conference, Publisher: ACM, Pages: 234-238

    Soft wearable robotics presents an opportunity to bridge robotics and textiles, offering lightweight, flexible, and ergonomic solutions for human-robot interaction, but previous studies on wearable soft robotics primarily focus on actuator performance without also considering wearability and interactivity. A rudimentary attachment method is usually adopted using external fixation devices such as straps to attach actuators to the user’s body, resulting in a poor wearing experience. This study focus on compatible and compact textile architectures to support actuators to be seamlessly integrated into daily wearing. It presents a research-through-design method to propose innovative knitting-integrated approaches for pneumatic actuator design to provide soft wearable robots with both aesthetic and functional values. Through a series of tests in which various knitting techniques and parameters are used to create sleeves that house silicone actuators, it explores design possibilities and understands the complex relationships between textiles and actuators. The findings contribute to advancing soft wearable robotics by offering practical solutions for integrating pneumatic actuators seamlessly into wearable textiles, thereby unlocking new possibilities for human-centered robotic systems.
  • Journal article
    Lei G, Docherty R, Cooper SJ, 2024,

    Materials science in the era of large language models: a perspective

    , Digital Discovery, Vol: 3, Pages: 1257-1272, ISSN: 2635-098X

    Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex code generation to heuristic finding for combinatorial problems. In this paper we offer a perspective on their applicability to materials science research, arguing their ability to handle ambiguous requirements across a range of tasks and disciplines means they could be a powerful tool to aid researchers. We qualitatively examine basic LLM theory, connecting it to relevant properties and techniques in the literature before providing two case studies that demonstrate their use in task automation and knowledge extraction at-scale. At their current stage of development, we argue LLMs should be viewed less as oracles of novel insight, and more as tireless workers that can accelerate and unify exploration across domains. It is our hope that this paper can familiarise materials science researchers with the concepts needed to leverage these tools in their own research.
  • Journal article
    Jakobsson Støre S, Van Zalk N, Granander Schwartz W, Nilsson V, Tillfors Met al., 2024,

    The relationship between social anxiety disorder and ADHD in adolescents and adults: a systematic review

    , Journal of Attention Disorders, Vol: 28, Pages: 1299-1319, ISSN: 1087-0547

    Objective:This review aimed to systematically gather empirical data on the link between social anxiety disorder and ADHD in both clinical and non-clinical populations among adolescents and adults.Method:Literature searches were conducted in PsycInfo, PubMed, Scopus, and Web of Science, resulting in 1,739 articles. After screening, 41 articles were included. Results were summarized using a narrative approach.Results:The prevalence of ADHD in adolescents and adults with SAD ranged from 1.1% to 72.3%, while the prevalence of SAD in those with ADHD ranged from 0.04% to 49.5%. Studies indicate that individuals with both SAD and ADHD exhibit greater impairments. All studies were judged to be of weak quality, except for two studies which were rated moderate quality.Discussion:Individuals with SAD should be screened for ADHD and vice versa, to identify this common comorbidity earlier. Further research is needed to better understand the prevalence of comorbid ADHD and SAD in adolescents.
  • Journal article
    Xie R, Pinson P, Xu Y, Chen Yet al., 2024,

    Robust Generation Dispatch With Purchase of Renewable Power and Load Predictions

    , IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, Vol: 15, Pages: 1486-1501, ISSN: 1949-3029
  • Journal article
    Marcille R, Tandeo P, Thiebaut M, Pinson P, Fablet Ret al., 2024,

    Convolutional Encoding and Normalizing Flows: A Deep Learning Approach for Offshore Wind Speed Probabilistic Forecasting in the Mediterranean Sea

    , ARTIFICIAL INTELLIGENCE FOR THE EARTH SYSTEMS, Vol: 3, ISSN: 2769-7525
  • Journal article
    Hodent C, Blumberg F, Deterding S, 2024,

    Ethical Games: Toward Evidence-Based Guidance for Safeguarding Players and Developers

    , Games: Research and Practice, Vol: 2, Pages: 1-11

    <jats:p>As video games have moved to the mainstream of entertainment and popular culture, they also have given rise to new media fears. These span concerns for player welfare such as gaming addiction, negative effects of ‘screen time,’ gambling-like mechanics, dark patterns and questionable business practices, online toxicity, and extremism. Questions of game worker welfare are similarly making headlines, such as harassment, discrimination, or precarious and unhealthy working conditions. To sort warranted concerns from unwarranted moral panics, the first Ethical Games Conference, held in 2024, gathered the state-of-the-art of research on ethical issues in games to inform evidence-based guidelines for industry and regulators. The selected full papers and opinion pieces of the conference, collected in this special issue, showcase a wide range of issues and barriers, and aspirations to move from avoiding harm to using games for positive social impact.</jats:p>
  • Journal article
    Bonkile M, Jiang Y, Kirkaldy N, Sulzer V, Timms R, Wang H, Offer G, Wu Bet al., 2024,

    Is silicon worth it? Modelling degradation in composite silicon–graphite lithium-ion battery electrodes

    , Journal of Power Sources, Vol: 606, ISSN: 0378-7753

    The addition of silicon into graphite lithium-ion battery anodes has the potential to increase cell energy density. However, understanding the complex degradation behaviour in these composite systems remains a research challenge. Here, we developed a coupled electrochemical–mechanical model of a composite silicon/graphite electrode, including stress-driven crack formation and solid electrolyte interphase layer growth for each material, validated with experimental degradation data from an LG M50T cell. The model reveals self-limiting loss of silicon due to decreasing stress in the silicon as the silicon activity shifts to a lower state-of-charge. Higher C-rates can lead to lower degradation due to lower phase utilisation as voltage cut-offs are reached earlier. Increasing silicon content can reduce the stress in the silicon by distributing reaction current density over more material. Using this model, we explored whether the extra capacity from silicon is generally ‘worth’ the faster degradation compared to graphite-only electrodes. The model shows if you use the silicon, you lose it, as the higher initial capacity is rapidly lost with regular high depth-of-discharge events. However, silicon does have value if it enables full graphite utilisation without range anxiety; if high depth-of-discharge events are minimised then graphite’s superior longevity can be utilised while exploiting silicon’s high specific capacity. The model is integrated into PyBaMM (an open-source physics-based modelling platform); providing the research community and industry with the capability to reproduce our results and further explore the dynamic lifetime behaviour of composite electrodes.
  • Thesis dissertation
    Seah C, 2024,

    Designing and Evaluating Mindfulness Conversational Agents for Persons with Dementia and Caregivers

    Dementia is one of the most prevalent global public health challenges and part of the major causes of dependency and disability worldwide. It is a debilitating disease that impacts not only the person with dementia but their caregiver (the “dyad”). Mindfulness interventions have positive effects for dyads but are rigid, time consuming and are not designed for dyads. Furthermore, using voice based conversational agents has not been done for dyadic mindfulness and may enhance accessibility and personalisation. This thesis explores how novel dyadic mindfulness conversational agents can be designed to benefit dyads, identifying user preferences and user needs, through the development and usage of a working prototype. We explored mindfulness interventions for dyads and technologies like conversational agents for health, before conducting a user research study through virtual semi-structured interviews with 10 experts and 5 dyads to understand the potential needs for the intervention. After which, we developed a working prototype through a user centred design approach comprising 4 cycles, incorporating the feedback from 10 dyads and 4 experts. Lastly, through a 30-day guideline assessment study using the working prototype, 6 dyads were eligible to participate, and completed the study. Assessments, surveys, and interviews were done pre and post study, while dyads filled in daily worksheets to track progress. From the various studies conducted, we identified initial user needs based on participants visualising the prototype. We then developed a working prototype and understood usage preferences and enhanced user needs based on dyad’s experiencing the prototype virtually. After the 30-day guideline assessment study, pre-post assessments showed improvement. Intervention and usage preferences further reveal that dyadic mindfulness conversational agents created using a user centred design approach, integrating user needs iteratively, can be beneficial for dyad
  • Conference paper
    Zhou X, Efthymiadou ME, Papageorgiou LG, Charitopoulos VMet al., 2024,

    Data-driven robust hydrogen infrastructure planning under demand uncertainty using a hierarchical-based decomposition method

    , Publisher: Elsevier, ISSN: 1570-7946
  • Conference paper
    Chen L, Cai Z, Cheang W, Sun L, Childs P, Zuo Het al., 2024,

    An Llm-based concept generation method for solution-driven bio-inspired design

    , DRS 2024, Publisher: Design Research Society, Pages: 1-21, ISSN: 2398-3132

    Bio-inspired design (BID) is a design methodology that employs biological analogies for engineering design, encompassing problem-driven and solution-driven BID. Solution-driven BID starts with knowledge of a specific biological system for technical design. Despite the proven benefits of solution-driven BID, the gap between biological solutions and engineering problems hinders its effective application, with designers frequently encountering misaligned problem-solution pairs and facing multidisciplinary knowledge gaps in the analogical transfer process. Therefore, this research proposes a large language model (LLM)-based concept generation method, designed to automatically search for problems, transfer biological analogy, and generate solution-driven BID concepts in the form of natural language. A concept generator and two evaluators are identified and fine-tuned from the LLM. The method is evaluated by an ablation study, machine-based quantitative assessments, and human subjective evaluations. The results show our method can generate solution-driven BID concepts with high quality.
  • Journal article
    Yin Y, Han J, Childs P, 2024,

    An EEG study on artistic and engineering mindsets in students in creative processes

    , Scientific Reports, Vol: 14, ISSN: 2045-2322

    This study aims to take higher-education students as examples to understand and compare artistic and engineering mindsets in creative processes using EEG. Fifteen Master of Fine Arts (MFA) visual arts and fifteen Master of Engineering (MEng) design engineering students were recruited and asked to complete alternative uses tasks wearing an EEG headset. The results revealed that (1) the engineering-mindset students responded to creative ideas faster than artistic-mindset students. (2) Although in creative processes both artistic- and engineering-mindset students showed Theta, Alpha, and Beta wave activity, the active brain areas are slightly different. The active brain areas of artistic-mindset students in creative processes are mainly in the frontal and occipital lobes; while the whole brain (frontal, oriental, temporal, and occipital lobes) was active in creative processes of engineering-mindset students. (3) During the whole creative process, the brain active level of artistic-mindset students was higher than that of engineering-mindset students. The results of this study fills gaps in existing research where only active brain areas and band waves were compared between artistic- and engineering-mindset students in creative processes. For quick thinking in terms of fluency of generating creative ideas, engineering students have an advantage in comparison to those from the visual arts. Also, the study provided more evidence that mindset can affect the active levels of the brain areas. Finally, this study provides educators with more insights on how to stimulate students’ creative ability.

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