Publications
255 results found
Childs P, 2023, Radial flow rurbocompressors, Proceedings of the Institution of Mechanical Engineers Part A: Journal of Power and Energy, Vol: 237, Pages: 602-602, ISSN: 0957-6509
Yu Z, Sadati H, Perera S, et al., 2023, Tapered whisker reservoir computing for real-time terrain identification-based navigation, Scientific Reports, Vol: 13, Pages: 1-13, ISSN: 2045-2322
This paper proposes a new method for real-time terrain recognition-based navigation for mobile robots. Mobile robots performing tasks in unstructured environments need to adapt their trajectories in real-time to achieve safe and efficient navigation in complex terrains. However, current methods largely depend on visual and IMU (inertial measurement units) that demand high computational resources for real-time applications. In this paper, a real-time terrain identification-based navigation method is proposed using an on-board tapered whisker-based reservoir computing system. The nonlinear dynamic response of the tapered whisker was investigated in various analytical and Finite Element Analysis frameworks to demonstrate its reservoir computing capabilities. Numerical simulations and experiments were cross-checked with each other to verify that whisker sensors can separate different frequency signals directly in the time domain and demonstrate the computational superiority of the proposed system, and that different whisker axis locations and motion velocities provide variable dynamical response information. Terrain surface-following experiments demonstrated that our system could accurately identify changes in the terrain in real-time and adjust its trajectory to stay on specific terrain.
Park D, Han J, Childs PRN, 2023, A data-driven fuzzy front end model for contextual performance and concurrent collaboration, IEEE Transactions on Engineering Management, Vol: 70, Pages: 660-683, ISSN: 0018-9391
A data-driven model for the fuzzy front end (FFE) stage in new product development (NPD) programs, with a series of toolkits to decrease uncertainty and ambiguity of parameter processing, has been developed. Parameters produced in toolkits provided in previous models tend to exist independently, without any interrelationship in the contextual performance relationship of a single functional domain nor concurrent collaboration relationship across multiple functional domains. This results in uncertainty and ambiguity triggered by an incorrect interpretation of parameters. The new model involved inferring a single representative FFE scenario wherein diverse FFE performance structures interlock from the contextual performance and concurrent collaboration perspectives by analyzing various real-world FFE scenarios gathered from NPD expert interviews. This representative scenario was embodied into the model with a performative structure, through deployment of toolkits. Users are informed of the purpose, roles, and meanings of parameters and their relationships and thus can infer each parameter from other parameters. This contributes to reduction in uncertainty and ambiguity in processing parameters. This article proposes an FFE execution concept, giving mathematical reasoning behind the performance structure of the model.
Jagtap SS, Childs PRN, Stettler MEJ, 2023, Energy performance evaluation of alternative energy vectors for subsonic long-range tube-wing aircraft, Transportation Research Part D: Transport and Environment, Vol: 115, ISSN: 1361-9209
Decarbonising long-range aviation is challenging. This study evaluates the performance of six low-carbon fuels and their realistic impacts on aircraft design for a large long-range passenger aircraft using Breguet's range equation. Liquid hydrogen (LH2) and 100 % synthetic paraffin kerosene (SPK) are the only two alternative fuels found to be viable. Using present-day technology, we find that the design-point specific energy consumption (SEC, MJ/tonne-km) of tube-wing aircraft powered by LH2 and 100 % SPK are 11 % higher and 0.2 % lower relative to Jet-A, respectively. At off-design points, SEC of 100 % SPK and LH2 are always similar to and greater than Jet-A, respectively. LH2 aircraft SEC decreases with increasing range and is less sensitive beyond 10,000 km. In a first, we develop an equation that enables LH2 aircraft weight-sizing. Our results should inform studies on LH2 and 100 % SPK aircraft operating costs and lifecycle emissions.
Yin Y, Haoyu Z, Peter C, 2023, Impacts of cognitive factors on creativity quality in design: identification from performance in recall, association and combination, Journal of Intelligence, Vol: 11, Pages: 1-22, ISSN: 2079-3200
The reason why people have different creativity quality levels may depend on their different performances relating to other cognitive factors that are important for creativity. This study was designed to identify the performance of three cognitive factors (recall, association, and combination) that a designer may use in a creative process and then identify how the differing performance for these cognitive factors will affect creativity quality levels. Seventy-one participants were recruited to undertake a design task and complete a semi-structured interview. The results indicate that, in a creative design process, similar performances in recall, association, and combination can result in differences in creativity quality level.
Zuo H, Jing Q, Song T, et al., 2022, WikiLink: An Encyclopedia-Based Semantic Network for Design Creativity, JOURNAL OF INTELLIGENCE, Vol: 10
Yin Y, Pan W, Childs P, 2022, Understanding creativity process through EEG measurement on creativity-related cognitive factors, Frontiers in Neuroscience, Vol: 8, Pages: 1-15, ISSN: 1662-453X
Neurotechnology approaches, such as electroencephalography (EEG), can aid understanding of the cognitive processes behind creativity. To identify and compare the EEG characteristics of creativity-related cognitive factors (remote association, common association, combination, recall and retrieval), 30 participants were recruited to conduct an EEG induction study. From the event-related potential (ERP) results and spectral analysis, the study supports that creativity is related to the frontal lobe areas of the brain and common association is an unconscious process. The results help explain why some creativity-related cognitive factors are involved either more or less readily than others in the creative design process from workload aspects. This study identifies the part of the brain that is involved in the combination cognitive factor and detects the ERP results on cognitive factors. This study can be used by designers and researchers to further understand the cognitive processes of creativity.
Han J, Park D, Hua M, et al., 2022, Is group work beneficial for producing creative designs in STEM design education?, International Journal of Technology and Design Education, Vol: 32, Pages: 2801-2826, ISSN: 0957-7572
Creativity is a significant element in design education, and frequently a significant competency during recruitment for design professions. Group work and individual work are widely employed in higher education. Many studies have highlighted the merits of employing group work in design education, cultivating collaborative design abilities and fostering sought-after employability skills. Although the benefits of group work in design practice and education are widely recognised, few studies have shown evidence that group work outperforms individual work regarding creative design activities in higher education contexts. Therefore, the aim of this research is to explore whether group or individual work is more beneficial for fostering students in generating creative designs in STEM design education. A case study, involving two cohorts of second-year undergraduate students studying a UK Engineering degree Industrial Design programme, is reported. The case study compares the design outputs produced by the two cohorts tackling the same design challenge in a product design module but employing individual and group work, respectively. The case study results show that no significant differences have been found between the design outputs produced by group work and individual work, considering novelty, usefulness and overall creativity. Further analysis reveals that a student’s academic performance is not significantly related to the level of creativity of the design produced. This research indicates design educators should employ both group and individual work to complement each other in design education, and suggests potential solutions to enhance students’ design creativity.
Childs P, Han J, Chen L, et al., 2022, The creativity diamond - a framework to aid creativity, Journal of Intelligence, Vol: 10, Pages: 1-20, ISSN: 2079-3200
There are many facets to creativity and the topic has a profound impact on society. Substantial and sustained study on creativity has been undertaken and much is now known about the fun-damentals and how creativity can be augmented. To draw these elements together a framework has been developed called the creativity diamond, formulated based on reviews of prior work as well as consideration of 20 PhD studies on the topics of creativity, design, innovation and product development. The framework embodies the principles that quantity of ideas breeds quality through selection, and that a range of creativity tools can provoke additional ideas to augment our innate creativity. The creativity diamond proposed is a tool consisting of a divergent phase as-sociated with the development of many distinctive ideas and a convergent phase associated with the refinement of ideas. The creativity diamond framework can be used to prompt and help select which tool or approach to use in a creative environment for innovative tasks. The framework has now been used by many students and professionals in diverse contexts.
Childs P, 2022, Radial flow turbocompressors, Proceedings of the Institution of Mechanical Engineers Part A: Journal of Power and Energy, Vol: 236, Pages: 1-1, ISSN: 0957-6509
Simpson K, Cockbill S, Childs P, 2022, Home energy renovation: UK owner-occupied householder uncertainties, information and data needs, IOP Conference Series: Earth and Environmental Science, Vol: 1085, Pages: 1-8, ISSN: 1755-1307
Homes must become low energy, resilient to climate change and provide comfort for households, as part of the European renovation wave. Renovation involves millions of decisions and actions. Owner-occupied households are a key group of decision-makers, but with conflicting demands on their time and finances. Householders collect information from multiple sources. However, previous research has found that the detail of available information and data on renovation is difficult to find. Therefore, this paper aims to identify householder uncertainties and related information and data needs, to support early-stage energy renovation decision-making. Co-design has been found to be beneficial in designing energy demand reduction strategies, leading to meaningful outcomes for householders, however, it was found to lead to further information requirements. The open virtual information exchange reported here, inspired by co-design and virtual workshop approaches, was effective in identifying uncertainties and gathering feedback on information types and data to address them. Householders' require trusted specialists to visit the home in-person. The information identified could be shared via trials at renovation information hubs, potentially using digital apps to connect renovation opportunity, householders' and trusted practitioners. There is much householder uncertainty around housing renovation and more work is needed to move able-to-pay householders from renovation planning to renovation in practice.
Yu Z, Sadati SMH, Hauser H, et al., 2022, A Semi-Supervised Reservoir Computing System Based on Tapered Whisker for Mobile Robot Terrain Identification and Roughness Estimation, IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 7, Pages: 5655-5662, ISSN: 2377-3766
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Yu Z, Perera S, Hauser H, et al., 2022, A tapered whisker-based physical reservoir computing system for mobile robot terrain identification in unstructured environments, IEEE Robotics and Automation Letters, Vol: 7, Pages: 3608-3615, ISSN: 2377-3766
In this letter, we present for the first time the use of tapered whisker-based reservoir computing (TWRC) system mounted on a mobile robot for terrain classification and roughness estimation of unknown terrain.Hall effect sensors captured the oscillations at different locations along a tapered spring that served as a reservoir to map time-domain vibrations signals caused by the interaction perturbations from the ground to frequency domain features directly. Three hall sensors are used to measure the whisker reservoir outputs and these temporal signals could be processed efficiently by the proposed TWRC system which can provide morphological computation power for data processing and reduce the model training cost compared to the convolutional neural network (CNN) approaches.To predict the unknown terrain properties, an extended TWRC method including a novel detector is proposed based on the Mahalanobis distance in the Eigen space, which has been experimentally demonstrated to be feasible and sufficiently accurate.We achieved a prediction success rate of 94.3\% for six terrain surface classification experiments and 88.7\% for roughness estimation of the unknown terrain surface.
Wagh SM, Napier AA, Clifford M, et al., 2022, Self-Supervised Task Learning For Robotic Underfloor Insulation, Pages: 358-363
Effective under-floor insulation (UFI) of residential buildings to reduce their energy consumption and CO2 emissions is a substantive challenge in retrofitting existing homes. Traditional UFI installation techniques require suspended floors to be taken up, damaging and disrupting the living space for several days. To deliver the low-disruption insulation of suspended floors, a robot has been developed for accessing and spraying thermal insulation to the underside of a suspended floor. Q-Bot has been installing UFI with a fleet of robots in a largely teleoperated mode for several years. In this mode, the operator is in complete control of all actions the robot takes, which is a significant cognitive burden. This paper addresses Q-Bot's steps toward automating the UFI installation process, reducing the operator's cognitive load and eventually freeing the operator to perform other tasks. Years of recorded experience are leveraged to train a simplified U-Net model in a self-supervised fashion, enabling robots to decide where to apply the insulation foam next. Results obtained from the on-site collected data show that the weighted symmetric cross-entropy loss function yields better spray-region prediction results than the base loss, Cross-Entropy. Our method can adapt to various operator preferences, generalise to novel building crawl spaces, and improve with more data.
Yu Z, SMHadi S, Hasitha W, et al., 2021, A method to use nonlinear dynamics in a whisker sensor for terrain identification by mobile robots, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, Publisher: IEEE, Pages: 8437-8443
This paper shows analytical and experimental evidence of using the vibration dynamics of a compliant whisker for accurate terrain classification during steady state motion of a mobile robot. A Hall effect sensor was used to measure whisker vibrations due to perturbations from the ground. Analytical results predict that the whisker vibrations will have a dominant frequency at the vertical perturbation frequency of the mobile robot sandwiched by two other less dominant but distinct frequency components. These frequency components may come from bifurcation of vibration frequency due to nonlinear interaction dynamics at steady state. Experimental results also exhibit distinct dominant frequency components unique to the speed of the robot and the terrain roughness. This nonlinear dynamic feature is used in a deep multi-layer perceptron neural network to classify terrains. We achieved 85.6% prediction success rate for seven flat terrain surfaces with different textures.Index Terms— Robotic whiskers, Surface identification, multi-layer perceptron, Modal analysis.
Jiang P, Dieckmann E, Han J, et al., 2021, A Bibliometric Review of Sustainable Product Design, ENERGIES, Vol: 14
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- Citations: 3
Sikhwal RK, Childs PRN, 2021, Towards Mass Individualisation: setting the scope and industrial implication, Design Science, Vol: 7, Pages: 1-34, ISSN: 2053-4701
Within the last few years, a need for renewed product personalisation has been observed in some markets such as consumer electronics, fashion to meet the exact demands of the customers. Product customisation emphasises the fulfilment of explicit requirements of a defined market segment, but product individualisation targets at satisfying the particular needs of a customer. Mass Individualisation (MI) is a new product design approach comprising of an open hardware platform and multiple modules to be integrated with the platform. It gives freedom to end-users to integrate different modules into the platform as per their choice. Technological and strategic integration of all actors involved in the design process is the primary focus of this research. This paper identifies key areas which need to be focussed on to realise this approach and convert it into an industrial practice by an explorative study of existing product design and customisation approaches. An industrial survey was conducted, and results for the industrial implication and insights on this approach are presented. The findings show that the end product from product design for MI will be more creative and innovative by the networking of all actors, and offers more individualised and technologically advanced products.
Han J, Jiang P, Childs PRN, 2021, Metrics for Measuring Sustainable Product Design Concepts, ENERGIES, Vol: 14
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Park D, Han J, Childs PRN, 2021, 266 Fuzzy front-end studies: current state and future directions for new product development, Research in Engineering Design, Vol: 32, Pages: 377-409, ISSN: 0934-9839
266 fuzzy front-end (FFE) studies in the new product development (NPD) sector were examined. The studies were selected using a bibliometrics method, and chronologically and statistically examined with ten criteria divided into two dimensions. The first dimension is associated with overall attributes of the FFE, consisting of six criteria: the study taxonomy, model type, NPD speed, NPD attributes, model characteristic, and model structure. The second dimension is relevant to the FFE performance structure related to process parameters, comprised of four criteria: the FFE task, activity, performance method, and toolkit. In terms of those two dimensions, the paper looks at previous FFE studies to gain an understanding of features of each FFE study along with related knowledge and theories, as well as identification of evolution trends of FFE studies. Based on the identification, an FFE model development strategy for each criterion is formulated, and this paper proposes possible options for executing those strategies which exert influence on the form of the cluster network. The intention is for the database to be utilised as an overview of all existing FFE studies and allow specific FFE studies to be selected to examine FFE approaches.This paper provides FFE model development guidance on how to deal with the overall attributes and outcomes of the FFE which affect the entirety of the innovation process, and how to manage the performance structure related to process parameters.
Simpson K, Childs P, Whyte J, 2021, Sensitivity analysis of heating a typical UK dwelling and implications for retrofit design, International Hybrid Conference on Carbon Neutral Cities - Energy Efficiency and Renewables in the Digital Era (CISBAT), Publisher: IOP PUBLISHING LTD, Pages: 1-6, ISSN: 1742-6588
The aim of this research is to quantify the impact of heating set point on space heating energy demand for a typical UK dwelling. Retrofit includes fabric energy efficiency improvements. Energy performance certificates (EPCs) inform the householder of typical savings per measure, but this has previously been found to inaccurately estimate space heating energy demand, leading to errors in 'typical savings' presented to householders. The most sensitive inputs have been found to be temperature set point, followed by fabric efficiency. The BREDEM methodology assumes a temperature of 21°C for nine hours a day, rather than ~16°C and ~20°C found in research. The methods used to inform this study are local sensitivity analysis of the domestic energy model, based on a typical dwelling example with calibrated inputs. This is done using an open calibrated Python model, based on BREDEM. The impact of heating patterns on space heating energy demand are modelled pre retrofit; according to differing heating set points, following wall and loft fabric upgrade and full fabric upgrade. The BREDEM heating set point assumptions lead to space heating energy demand predicted ~50-100 kWh/m2/yr higher than real heating set points. Implications for retrofit design and EPCs are discussed.
Wang P, Wang S, Peng D, et al., 2020, Neurocognition-inspired design with machine learning, Design Science, Vol: 6, Pages: 1-19, ISSN: 2053-4701
Generating designs via machine learning has been an on-going challenge in computer-aided design. Recently, deep learning methods have been applied to randomly generate images in fashion, furniture and product design. However, such deep generative methods usually require a large number of training images and human aspects are not taken into account in the design process. In this work, we seek a way to involve human cognitive factors through brain activity indicated by electroencephalographic measurements (EEG) in the generative process. We propose a neuroscience-inspired design with a machine learning method where EEG is used to capture preferred design features. Such signals are used as a condition in generative adversarial networks (GAN). First, we employ a recurrent neural network Long Short-Term Memory as an encoder to extract EEG features from raw EEG signals; this data are recorded from subjects viewing several categories of images from ImageNet. Second, we train a GAN model conditioned on the encoded EEG features to generate design images. Third, we use the model to generate design images from a subject’s EEG measured brain activity. To verify our proposed generative design method, we present a case study, in which the subjects imagine the products they prefer, and the corresponding EEG signals are recorded and reconstructed by our model for evaluation. The results indicate that a generated product image with preference EEG signals gains more preference than those generated without EEG signals. Overall, we propose a neuroscience-inspired artificial intelligence design method for generating a design taking into account human preference. The method could help improve communication between designers and clients where clients might not be able to express design requests clearly.
Simpson K, Whyte J, Childs P, 2020, Data-centric innovation in retrofit: A bibliometric review of dwelling retrofit across North Western Europe, Energy and Buildings, Vol: 229, Pages: 1-9, ISSN: 0378-7788
Data-centric innovation can inform the development of effective retrofit strategies through novel methods of collecting, analysing and sharing data. This bibliometric review uses a text-mining tool to identify research trends in dwelling retrofit research across North Western Europe. The review identifies a major focus on energy efficiency, with sub-themes on: 1) energy performance, 2) heat, power and control technologies, 3) indoor environment quality and 4) retrofit practice. In dwelling retrofit, there is now an established research tradition of using data-centric methods in monitoring and modelling energy performance to inform and learn from energy efficiency interventions. Building on the state-of-the-art, our analyses suggest opportunities for data-centric methods to consider the indoor environment quality and material impacts resulting from energy performance improvements. This information can then be openly communicated across the supply chain. Thus the paper discusses the retrofit themes and data-centric methods within North Western Europe, for an emerging trajectory of data-centric retrofit research and practice.
Baxter W, Roots S, Tuomala E, et al., 2020, Ritual Design Toolkit, London, Publisher: Interaction Foundry
Rituals are intentional behaviours with a distinct emotional outcome. They fill our lives with deeper meaning and are found everywhere from the workplace to the kitchen table. We have made the Ritual Design Toolkit to help you understand rituals, how to harness them, and how to design them. In our own work, we have used the toolkit in a range of applications including enhancing key moments in a customer journey, helping people adopt healthier eating habits and building and strengthening communities. The toolkit can be used for grand rituals and micro-interactions. Whether you are a manager of a team, a packaging designer, or a service enthusiast, you can find guidance here to build more meaningful moments into your work. The toolkit offers a ritual design process consisting of three main steps: scoping, creating and testing rituals.
Spyrakos-Papastavridis E, Childs PRN, Dai JS, 2020, Passivity Preservation for Variable Impedance Control of Compliant Robots, IEEE-ASME TRANSACTIONS ON MECHATRONICS, Vol: 25, Pages: 2342-2353, ISSN: 1083-4435
Liu X, Ouyang M, Orzech M, et al., 2020, In-situ fabrication of carbon-metal fabrics as freestanding electrodes for high-performance flexible energy storage devices, Energy Storage Materials, Vol: 30, Pages: 329-336, ISSN: 2405-8297
Hierarchical 1D carbon structures are attractive due to their mechanical, chemical and electrochemical properties however the synthesis of these materials can be costly and complicated. Here, through the combination of inexpensive acetylacetonate salts of Ni, Co and Fe with a solution of polyacrylonitrile (PAN), self-assembling carbon-metal fabrics (CMFs) containing unique 1D hierarchical structures can be created via easy and low-cost heat treatment without the need for costly catalyst deposition nor a dangerous hydrocarbon atmosphere. Microscopic and spectroscopic measurements show that the CMFs form through the decomposition and exsolution of metal nanoparticle domains which then catalyze the formation of carbon nanotubes through the decomposition by-products of the PAN. These weakly bound nanoparticles form structures similar to trichomes found in plants, with a combination of base-growth, tip-growth and peapod-like structures, where the metal domain exhibits a core(graphitic)-shell(disorder) carbon coating where the thickness is in-line with the metal-carbon binding energy. These CMFs were used as a cathode in a flexible zinc-air battery which exhibited superior performance to pure electrospun carbon fibers, with their metallic nanoparticle domains acting as bifunctional catalysts. This work therefore unlocks a potentially new category of composite metal-carbon fiber based structures for energy storage applications and beyond.
Muranko Z, Aurisicchio M, Baxter W, et al., 2020, Behaviour chains in circular consumption systems: the reuse of FMCGs, Proceedings of the IS4CE2020 Conference of the International Society for the Circular Economy
Simpson C, Whyte J, Childs P, 2020, Residential retrofit: A review of themes, data-centric methods and future directions to accelerate net zero, CIBSE Technical Symposium
Chen X, Liu X, Ouyang M, et al., 2019, Multi-metal 4D printing with a desktop electrochemical 3D printer, Scientific Reports, Vol: 9, ISSN: 2045-2322
4D printing has the potential to create complex 3D geometries which are able to react to environmental stimuli opening new design possibilities. However, the vast majority of 4D printing approaches use polymer based materials, which limits the operational temperature. Here, we present a novel multi-metal electrochemical 3D printer which is able to fabricate bimetallic geometries and through the selective deposition of different metals, temperature responsive behaviour can thus be programmed into the printed structure. The concept is demonstrated through a meniscus confined electrochemical 3D printing approach with a multi-print head design with nickel and copper used as exemplar systems but this is transferable to other deposition solutions. Improvements in deposition speed (34% (Cu)-85% (Ni)) are demonstrated with an electrospun nanofibre nib compared to a sponge based approach as the medium for providing hydrostatic back pressure to balance surface tension in order to form a electrolyte meniscus stable. Scanning electron microscopy, X-ray computed tomography and energy dispersive X-ray spectroscopy shows that bimetallic structures with a tightly bound interface can be created, however convex cross sections are created due to uneven current density. Analysis of the thermo-mechanical properties of the printed strips shows that mechanical deformations can be generated in Cu-Ni strips at temperatures up to 300 °C which is due to the thermal expansion coefficient mismatch generating internal stresses in the printed structures. Electrical conductivity measurements show that the bimetallic structures have a conductivity between those of nanocrystalline copper (5.41×106 S.m−1) and nickel (8.2×105 S.m-1). The potential of this novel low-cost multi-metal 3D printing approach is demonstrated with the thermal actuation of an electrical circuit and a range of self-assembling structures.
Childs PRN, 2019, Aircraft cabin air supply and the internal air system, Journal of Health and Pollution, Vol: 9, Pages: S17-S21, ISSN: 2156-9614
This paper describes systems commonly employed to deliver aircraftcabin air, and the internal air system which is responsible for thesupply of balancing, sealing and cooling air used with the engine tocontrol the operation of bearings, discs and other critical components,as well as bleed air. A series of mechanisms that could be responsiblefor contamination of bleed and cabin air are considered including:ingestion into the compressor intake of poor quality air; leakage froma seal of oil; ingestion from the gases associated with a stall or surgeevent; off-gassing of cabin fittings and emissions from occupants.
Chen X, Liu X, Ouyang M, et al., 2019, Electrospun composite nanofibre supercapacitors enhanced with electrochemically 3D printed current collectors, Journal of Energy Storage, Vol: 26, Pages: 100993-100993, ISSN: 2352-152X
Carbonised electrospun nanofibres are attractive for supercapacitors due to their relatively high surface area, facile production routes and flexibility. With the addition of materials such as manganese oxide (MnO), the specific capacitance of the carbon nanofibres can be further improved through fast surface redox reactions, however this can reduce the electrical conductivity. In this work, electrochemical 3D printing is used as a novel means of improving electrical conductivity and the current collector-electrode interfacial resistance through the deposition of highly controlled layers of copper. Neat carbonised electrospun electrodes made with a 30 wt% manganese acetylacetonate (MnACAC) and polyacrylonitrile precursor solution have a hydrophobic nature preventing an even copper deposition. However, with an ethanol treatment, the nanofibre films can be made hydrophilic which enhances the copper deposition morphology to enable the formation of a percolating conductive network through the electrode. This has the impact of increasing electrode electronic conductivity by 360% from 10 S/m to 46 S/m and increasing specific capacitance 110% from 99 F/g to 208 F/g at 5 mV/s through increased utilisation of the pseudocapacitive active material. This novel approach thus provides a new route for performance enhancement of electrochemical devices using 3D printing, which opens new design possibilities.
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