Imperial College London

ProfessorEricYeatman

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Head of Department of Electrical and Electronic Engineering
 
 
 
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Contact

 

+44 (0)20 7594 6204e.yeatman CV

 
 
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Assistant

 

Ms Anna McCormick +44 (0)20 7594 6189

 
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Location

 

610aElectrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

347 results found

Cursi F, Bai W, Li W, Yeatman EM, Kormushev Pet al., 2022, Augmented Neural Network for Full Robot Kinematic Modelling in SE(3), IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 7, Pages: 7140-7147, ISSN: 2377-3766

Journal article

Arteaga JM, Mitcheson PD, Yeatman EM, 2022, Development of a fast-charging platform for buried sensors using high frequency IPT for agricultural applications, 2022 IEEE Applied Power Electronics Conference and Exposition (APEC), Publisher: IEEE, Pages: 1116-1121

This paper describes the methodology and experimental results for wireless power delivery to a soil-sensors power and data distribution unit from an unmanned aerial vehicle (UAV), using a high frequency inductive power transfer (HF-IPT) link. The configuration features, at the transmit side, a lightweight single-turn air-core coil driven by a 13.56 MHz Class EF inverter mounted on a Matrice 100 drone by DJI, and at the receive side, a two-turn PCB coil with a voltage-tipler Class D rectifier, an off-the-shelf 42 V battery charger and a supercapacitors module for energy storage. The experiments were conducted with a coil-to-coil gap of 250 mm, which corresponds to a coupling factor lower than 5%. In the experiments, a 10 F, 42 V supercapacitors module was charged in eleven minutes with an energy efficiency of 34% from the 80 V DC source that feeds the inverter on the drone to the supercapacitor-based energy storage unit in the sensor module. At higher power (50 W) the HF-IPT system was able to achieve a 68% DC-DC efficiency with a coupling factor of 3.5%. The work reported in this paper is part of a multiple-discipline project which looks to enable the optimal usage of water in agriculture with broader sensing techniques and more frequent sensing cycles.

Conference paper

Kiziroglou ME, Wright SW, Yeatman EM, 2022, Power supply based on inductive harvesting from structural currents, IEEE Internet of Things Journal, Vol: 9, ISSN: 2327-4662

Monitoring infrastructure offers functional optimisation, lower maintenance cost, security, stability and data analysis benefits. Sensor nodes require some level of energy autonomy for reliable and cost-effective operation, and energy harvesting methods have been developed in the last two decades for this purpose. Here, a power supply that collects, stores and delivers regulated power from the stray magnetic field of currentcarrying structures is presented. In cm-scale structures the skin effect concentrates current at edges at frequencies even below 1 kHz. A coil-core inductive transducer is designed. A fluxfunnelling soft magnetic core shape is used, multiplying power density by the square of funnelling ratio. A power management circuit combining reactance cancellation, voltage doubling, rectification, super-capacitor storage and switched inductor voltage boosting and regulation is introduced. The power supply is characterised in house and on a full-size industrial setup, demonstrating a power reception density of 0.36 mW/cm3, 0.54 mW/cm3 and 0.73 mW/cm3 from a 25 A RMS structural current at 360 Hz, 500 Hz and 800 Hz respectively, corresponding to the frequency range of aircraft currents. The regulated output is tested under various loads and cold starting is demonstrated. The introduced method may enable power autonomy to wireless sensors deployed in current-carrying infrastructure.

Journal article

Gil Rosa B, Akingbade OE, Guo X, Gonzalez-Macia L, Crone MA, Cameron LP, Freemont P, Choy K-L, Güder F, Yeatman E, Sharp DJ, Li Bet al., 2022, Multiplexed immunosensors for point-of-care diagnostic applications, Biosensors and Bioelectronics, Vol: 203, ISSN: 0956-5663

Accurate, reliable, and cost-effective immunosensors are clinically important for the early diagnosis and monitoring of progressive diseases, and multiplexed sensing is a promising strategy for the next generation of diagnostics. This strategy allows for the simultaneous detection and quantification of multiple biomarkers with significantly enhanced reproducibility and reliability, whilst requiring smaller sample volumes, fewer materials, and shorter average analysis time for individual biomarkers than individual tests. In this opinionated review, we compare different techniques for the development of multiplexed immunosensors. We review the state-of-the-art approaches in the field of multiplexed immunosensors using electrical, electrochemical, and optical methods. The barriers that prevent translating this sensing strategy into clinics are outlined together with the potential solutions. We also share our vision on how multiplexed immunosensors will continue their evolution in the coming years.

Journal article

Bai W, Cursi F, Guo X, Huang B, Lo B, Yang GZ, Yeatman EMet al., 2022, Task-Based LSTM Kinematic Modeling for a Tendon-Driven Flexible Surgical Robot, IEEE Transactions on Medical Robotics and Bionics, Vol: 4, Pages: 339-342

Tendon-driven flexible surgical robots are normally suffering from the inaccurate modeling and imprecise motion control problems due to the nonlinearities of tendon transmission. Learning-based approaches are experimental data-driven with uncertainties modeled empirically, which can be adopted to improve the inevitable issues. This work proposes a LSTM-based kinematic modeling approach with task-based data for a flexible tendon-driven surgical robot to improve the control accuracy. Real experiments demonstrated the effectiveness and superiority of the proposed learned model when completing path following tasks, especially compared to the traditional modeling.

Journal article

Bacha SC, Bai W, Wang Z, Xiao B, Yeatman EMet al., 2022, Deep Reinforcement Learning-Based Control Framework for Multilateral Telesurgery, IEEE Transactions on Medical Robotics and Bionics, Vol: 4, Pages: 352-355

The upper boundary of time delay is often required in traditional telesurgery control design, which would result in infeasibility of telesurgery across regions. To overcome this issue, this paper introduces a new control framework based on deep deterministic policy gradient (DDPG) reinforcement learning (RL) algorithm. The developed framework effectively overcomes the phase difference and data loss caused by time delays, which facilitates the restoration of surgeon's intention and interactive force. Kalman filter (KF) is employed to blend multiple surgeons' commands and predict the final local commands, respectively. The control framework ensures synchronization tracking performance and transparency. Prior knowledge of time delay is therefore not required. Simulation and experiment results have demonstrated the merits of the proposed framework.

Journal article

Cursi F, Bai W, Yeatman EM, Kormushev Pet al., 2022, Optimization of surgical robotic instrument mounting in a macro-micro manipulator setup for improving task execution, IEEE Transactions on Robotics, ISSN: 1552-3098

In Minimally Invasive Robotic Surgery (MIRS),the surgical instrument is usually inserted inside the patient’sbody through a small incision, which acts as a Remote Centerof Motion (RCM). Serial-link manipulators can be used asmacro robots on which micro surgical robotic instruments aremounted to increase the number of degrees of freedom (DOFs)of the system and ensure safe task and RCM motion execution.However, the surgical instrument needs to be placed in anappropriate configuration when completing the motion tasks.The contribution of this work is to present a novel frameworkthat preoperatively identifies the best base configuration, interms or Roll, Pitch, and Yaw angles, of the micro surgicalinstrument with respect to the macro serial-link manipulator’send-effector in order to achieve the maximum accuracy anddexterity in performing specified tasks. The framework relieson Hierarchical Quadratic Programming (HQP) for the control,Genetic Algorithm (GA) for the optimization, and on a resilienceto error strategy to make sure deviations from the optimum donot affect the system’s performance.Simulation results show that the mounting configuration ofthe surgical instrument significantly impacts the performanceof the whole macro-micro manipulator in executing the desiredmotion tasks, and both the simulation and experimental resultsdemonstrate that the proposed optimization method improves theoverall performance.

Journal article

Bai W, Wang Z, Cao Q, Yokoi H, Fujie MG, Yeatman EM, Yang GZet al., 2022, Anthropomorphic Dual-Arm Coordinated Control for a Single-Port Surgical Robot Based on Dual-Step Optimization, IEEE Transactions on Medical Robotics and Bionics, Vol: 4, Pages: 72-84

Effective teleoperation of the small-scale and highly-integrated robots for single-port surgery (SPS) imposes unique control and human-robot interaction challenges. Traditional isometric teleoperation schemes mainly focus on end-to-end trajectory mapping, which is problematic when applied to SPS robotic control, especially for dual-arm coordinated operation. Inspired by the human arm configuration in boxing maneuvers, an optimized anthropomorphic coordinated control strategy based on a dual-step optimization approach is proposed. Theoretical derivation and solvability of the problem are addressed, and the effectiveness of the method is further demonstrated in detailed simulation and in-vitro experiments. The proposed control strategy has been shown to perform dexterous SPS bimanual manipulation more effectively, involving less instrument-interference and is free from singularities, thereby improving the safety and efficiency of SPS operations.

Journal article

Cursi F, Bai W, Yeatman EM, Kormushev Pet al., 2022, GlobDesOpt: a global optimization framework for optimal robot manipulator design, IEEE Access, Vol: 10, Pages: 5012-5023, ISSN: 2169-3536

Robot design is a major component in robotics, as it allows building robots capable of performing properly in given tasks. However, designing a robot with multiple types of parameters and constraints and defining an optimization function analytically for the robot design problem may be intractable or even impossible. Therefore black-box optimization approaches are generally preferred. In this work we propose GlobDesOpt, a simple-to-use open-source optimization framework for robot design based on global optimization methods. The framework allows selecting various design parameters and optimizing for both single and dual-arm robots. The functionalities of the framework are shown here to optimally design a dual-arm surgical robot, comparing the different two optimization strategies.

Journal article

Cursi F, Bai W, Yeatman EM, Kormushev Pet al., 2022, Model Learning with Backlash Compensation for a Tendon-Driven Surgical Robot, IEEE Robotics and Automation Letters

Robots for minimally invasive surgery are becoming more and more complex, due to miniaturization and flexibility requirements. The vast majority of surgical robots are tendon-driven and this, along with the complex design, causes high nonlinearities in the system which are difficult to model analytically. In this work we analyse how incorporating a backlash model and compensation can improve model learning and control. We combine a backlash compensation technique and a Feedforward Artificial Neural Network (ANN) with differential relationships to learn the kinematics at position and velocity level of highly articulated tendon-driven robots. Experimental results show that the proposed backlash compensation is effective in reducing nonlinearities in the system, that compensating for backlash improves model learning and control, and that our proposed ANN outperforms traditional ANN in terms of path tracking accuracy.

Journal article

Xiao B, Lam HK, Xuan C, Wang Z, M Yeatman Eet al., 2022, Optimization for Interval Type-2 Polynomial Fuzzy Systems: A Deep Reinforcement Learning Approach, IEEE Transactions on Artificial Intelligence

It is known that the interval type-2 (IT2) fuzzy controllers are superior compared to their type-1 counterparts in terms of robustness, flexibility, etc. However, how to conduct the type reduction optimally with the consideration of system stability under the fuzzy-model-based (FMB) control framework is still an open problem. To address this issue, we present a new approach through the membership-function-dependent (MFD) and deep reinforcement learning (DRL) approaches. In the proposed approach, the reduction of IT2 membership functions of the fuzzy controller is completing during optimizing the control performance. Another fundamental issue is that the stability conditions must hold subject to different type-reduction methods. It is tedious and impractical to resolve the stability conditions according to different type-reduction methods, which could lead to infinite possibility. It is more practical to guarantee the holding of stability conditions during type-reduction rather than resolving the stability conditions, the MFD approach is proposed with the imperfect premise matching (IPM) concept. Thanks to the unique merit of the MFD approach, the stability conditions according to all the different embedded type-1 membership functions within the footprint of uncertainty (FOU) are guaranteed to be valid. During the control processes, the state transitions associated with properly engineered cost/reward function can be used to approximately calculate the deterministic policy gradient to optimize the acting policy and then to improve the control performance through determining the grade of IT2 membership functions of the fuzzy controller. The detailed simulation example is provided to verify the merits of the proposed approach.

Journal article

Wang Z, Lam H-K, Guo Y, Xiao B, Li Y, Su X, Yeatman EM, Burdet Eet al., 2022, Adaptive Event-Triggered Control for Nonlinear Systems With Asymmetric State Constraints: A Prescribed-Time Approach, IEEE Transactions on Automatic Control, Pages: 1-8, ISSN: 0018-9286

Journal article

Yang S, Kiziroglou M, Yeatman E, Holmes Aet al., 2021, Passive acoustic transducer as a fluid flow sensor, IEEE Sensors Conference, Publisher: IEEE, Pages: 1-4

Autonomy and minimal disruption are key desirable features for sensors to be deployed in medical, industrial, vehicle and infrastructure monitoring systems. Using a passive structure to transduce the quantity of interest into an acoustic or electromagnetic wave could offer an attractive solution for remote sensing, lifting the requirements of installing active materials, electronics, and power sources in remote, inaccessible, sensitive, or harsh environment locations. Here, we report a simple cavity and ball structure that transduces fluid flow through a pipe into an acoustic signal. A microphone on the outside wall of the pipe records the intensity and arrival rate of the sound pulses generated by collisions between the ball and the cavity walls. Using this approach external measurement of flow is demonstrated with adequate repeatability before any acoustic signal processing. This result is expected to open the way to the implementation of passive, remotely readable sensors for fluid flow and other fluid properties of interest.

Conference paper

Huang Z, Wang Z, Bai W, Huang Y, Sun L, Xiao B, Yeatman EMet al., 2021, A novel training and collaboration integrated framework for human-agent teleoperation., Sensors (Basel, Switzerland), Vol: 21, Pages: 1-15, ISSN: 1424-8220

Human operators have the trend of increasing physical and mental workloads when performing teleoperation tasks in uncertain and dynamic environments. In addition, their performances are influenced by subjective factors, potentially leading to operational errors or task failure. Although agent-based methods offer a promising solution to the above problems, the human experience and intelligence are necessary for teleoperation scenarios. In this paper, a truncated quantile critics reinforcement learning-based integrated framework is proposed for human-agent teleoperation that encompasses training, assessment and agent-based arbitration. The proposed framework allows for an expert training agent, a bilateral training and cooperation process to realize the co-optimization of agent and human. It can provide efficient and quantifiable training feedback. Experiments have been conducted to train subjects with the developed algorithm. The performances of human-human and human-agent cooperation modes are also compared. The results have shown that subjects can complete the tasks of reaching and picking and placing with the assistance of an agent in a shorter operational time, with a higher success rate and less workload than human-human cooperation.

Journal article

Chen X, Kiziroglou ME, Yeatman EM, 2021, Evaluation platform for MEMS-actuated 3D-printed compliant structures, 2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS), Publisher: IEEE, Pages: 188-191

This paper presents experimental results on an evaluation platform for MEMS-actuated compliant structures. A combination of 3 dimensional (3D) flexure design, 3D printing of polymers with controlled stiffness is employed. A modular system design approach allows the interchange and combination of different actuation cantilevers, flexures and structure designs implemented as standalone test parts with minimal assembly requirements. The performance evaluation method includes synchronised electrical excitation and optical displacement measurements, allowing characterisation of motion amplification, dynamic response as well as actuating power transfer. As a demonstrator, a single lever compliant structure was designed, fabricated and tested on the platform to investigate how geometry and material stiffness affect performance. The experimental results reveal that significant improvement of amplification ratio and absolute phase lag can be achieved by selecting a flexure height and material composition suitable for a given application. This method of combined experimental evaluation and custom 3D design and printing is promising for optimising the design of compliant structures for MEMS sensors, actuators and energy transducers with amplified or translated motion capability.

Conference paper

Pandiyan AYS, Kiziroglou ME, Yeatman EM, 2021, Complex impedance matching for far-field acoustic wireless power transfer, 2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS), Publisher: IEEE, Pages: 44-47

In this study, different load matching techniques are analysed to identify the optimum method to deliver power to the receiver for acoustic wireless power transfer systems. Complex impedance matching of the system’s transducers provides an advantage to drive the transmitter off-resonance for cases where there is a resonance mismatch between the transducers due to make, defect or ambient conditions. By studying the effect of impedance matching for different frequencies near the resonance frequency, similar power levels can be achieved for a wider bandwidth of frequencies using complex impedance matching. Thus, increased power can be delivered to the receiver by controlling the frequency of the transmitter, which can be exploited for beam steering along the propagation axis when standing waves are prominent between the transducers. A summary of the power experimentally extracted for the different loading techniques presented in this paper demonstrates a 4 kHz increase in system bandwidth and 140% more power can be delivered by tuning both transducers with complex impedance matching.

Conference paper

Wright SW, Kiziroglou ME, Yeatman EM, 2021, Magnetic flux guidance using H structures for miniature transducers, 2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS), Publisher: IEEE, Pages: 156-159

Limited magnetic flux has been a significant restriction in the applicability of scaled-down inductive energy, sensing and actuating devices. Magnetic flux concentration could potentially address this challenge by offering higher flux density B and thereby higher transduction power density, sensitivity and force in the small scale. In this paper, a study of flux concentration from a flux path perspective is presented. Numerical simulations show that high permeability cylindrical cores can achieve a flux concentration ratio in the scale of their aspect ratio, as they gather flux from their reachable vicinity. Flux guiding structures such as H-shapes can concentrate the flux incident to their surface and guide it through a small cross-section, achieving a higher concentration ratio. In an experimental study, a flux concentration factor of 6 is reported using a single 5 mm diameter, 20 mm high cylinder, and an additional increase factor of 4.3 from the addition of 70 mm × 12 mm × 2 mm flanges. A total B amplification ratio of 26 is demonstrated. As an application demonstrator, this approach is employed in an inductive energy harvester yielding 11.4 mW average power output (0.3 mW/g) from a 0.12 mT RMS, 800 Hz field.

Conference paper

Shi M, Yeatman EM, 2021, A comparative review of artificial muscles for microsystem applications, Microsystems and Nanoengineering, Vol: 7, Pages: 1-19, ISSN: 2055-7434

Artificial muscles are capable of generating actuation in microsystems with outstanding compliance. Recent years have witnessed a growing academic interest in artificial muscles and their application in many areas, such as soft robotics and biomedical devices. This paper aims to provide a comparative review of recent advances in artificial muscle based on various operating mechanisms. The advantages and limitations of each operating mechanism are analyzed and compared. According to the unique application requirements and electrical and mechanical properties of the muscle types, we suggest suitable artificial muscle mechanisms for specific microsystem applications. Finally, we discuss potential strategies for energy delivery, conversion, and storage to promote the energy autonomy of microrobotic systems at a system level.

Journal article

Bautista-Salinas D, Abdelaziz MEMK, Temelkuran B, Yeatman EM, Huins CT, Rodriguez y Baena Fet al., 2021, Towards a Functional Atraumatic Self-Shaping Cochlear Implant, MACROMOLECULAR MATERIALS AND ENGINEERING, Vol: 307, ISSN: 1438-7492

Journal article

Kiziroglou ME, Yeatman EM, 2021, Micromechanics for energy generation, Journal of Micromechanics and Microengineering, Vol: 31, Pages: 1-18, ISSN: 0960-1317

The emergence and evolution of energy micro-generators during the last two decades has delivered a wealth of energy harvesting powering solutions, with the capability of exploiting a wide range of motion types, from impulse and low frequency irregular human motion, to broadband vibrations and ultrasonic waves. It has also created a wide background of engineering energy microsytems, including fabrication methods, system concepts and optimal functionality. This overview presents a simple description of the main transduction mechanisms employed, namely the piezoelectric, electrostatic, electromagnetic and triboelectric harvesting concepts. A separate discussion of the mechanical structures used as motion translators is presented, including the employment of a proof mass, cantilever beams, the role of resonance, unimorph structures and linear/rotational motion translators. At the mechanical-to-electrical interface, the concepts of impedance matching, pre-biasing and synchronised switching are summarised. The separate treatment of these three components of energy microgenerators allows the selection and combination of different operating concepts, their co-design towards overall system level optimisation, but also towards the generalisation of specific approaches, and the emergence of new functional concepts. Industrial adoption of energy micro-generators as autonomous power sources requires functionality beyond the narrow environmental conditions typically required by the current state-of-art. In this direction, the evolution of broadband electromechanical oscillators and the combination of environmental harvesting with power transfer operating schemes could unlock a widespread use of micro-generation in microsystems such as micro-sensors and micro-actuators.

Journal article

Becker T, Borjesson V, Cetinkaya O, Baoxing C, Colomer-Farrarons J, Maeve D, Elefsiniotis A, Govoni L, Hadas Z, Hayes M, Holmes AS, Kiziroglou ME, La Rosa R, Miribel-Català P, Mueller J, Pandiyan A, Plasek O, Riehl P, Rohan J, Sabaté N, Saez M, Samson D, Sebald J, Spies P, Vikerfors A, Yeatman E, Zaghari B, Zahnstecher Bet al., 2021, Energy harvesting for a green internet of things, PSMA

The ubiquitous nature of energy autonomous microsystems, which are easy to install and simple toconnect to a network, make them attractive in the rapidly growing Internet of Things (IoT) ecosystem.The growing energy consumption of the IoT infrastructure is becoming more and more visible. Energyharvesting describes the conversion of ambient into electrical energy, enabling green power suppliesof IoT key components, such as autonomous sensor nodes.Energy harvesting methods and devices have reached a credible state-of-art, but only a few devices arecommercially available and off-the-shelf harvester solutions often require extensive adaption to theenvisaged application. A synopsis of typical energy sources, state-of-the-art materials, and transducertechnologies for efficient energy conversion, as well as energy storage devices and power managementsolutions, depicts a wide range of successful research results. Developing power supplies for actualusage reveals their strong dependence on application-specific installation requirements, powerdemands, and environmental conditions.The industrial challenges for a massive spread of autonomous sensor systems are manifold anddiverse. Reliability issues, obsolescence management, and supply chains need to be analyzed forcommercial use in critical applications. The current gap between use-case scenarios and innovativeproduct development is analyzed from the perspective of the user. The white paper then identifies thekey advantages of energy autonomy in environmental, reliability, sustainability, and financial terms.Energy harvesting could lead to a lower CO2 footprint of future IoT devices by adoptingenvironmentally friendly materials and reducing cabling and battery usage. Further research anddevelopment are needed to achieve technology readiness levels acceptable for the industry. This whitepaper derives a future research and innovation strategy for industry-ready green microscale IoTdevices, providing useful information to the sta

Journal article

Shi M, Holmes AS, Yeatman EM, 2021, NONLINEAR WIND ENERGY HARVESTING BASED ON MECHANICAL SYNCHRONOUS SWITCH HARVESTING ON INDUCTOR, 21st International Conference on Solid-State Sensors, Actuators and Microsystems (Transducers), Publisher: IEEE, Pages: 964-967, ISSN: 2167-0013

Conference paper

Arteaga JM, O'Keefe J, Boyle DE, Mitcheson PD, Yeatman Eet al., 2021, Interrogation and charging of embedded sensors by autonomous vehicles, 2021 21st International Conference on Solid-State Sensors, Actuators and Microsystems (Transducers), Publisher: IEEE, Pages: 296-299

This paper presents a concept and experimental results for end-to-end energy-autonomous sensor systems using unmanned aerial vehicles (drones) as agents for power delivery to and data gathering from sensing devices. Such systems are particularly useful for delay tolerant monitoring scenarios in which the sensing devices are deployed in remote or harsh conditions, often with sparse connectivity, long life and high reliability requirements. Results presented include miniaturisation of wireless charging hardware for drones of low payload capacity, methods for navigation to and alignment with sensors for efficient power transfer, and some data transfer aspects.

Conference paper

Kim J, Yeatman E, Thompson A, 2021, Plasmonic optical fiber for bacteria manipulation—characterization and visualization of accumulation behavior under plasmo-thermal trapping, Biomedical Optics Express, Vol: 12, Pages: 3917-3933, ISSN: 2156-7085

In this article, we demonstrate a plasmo-thermal bacterial accumulation effect usinga miniature plasmonic optical fiber. Combined action of far-field convection and a near-fieldtrapping force (referred to as thermophoresis)—induced by highly localized plasmonicheating—enabled large-area accumulation of Escherichia coli. The estimated thermophoretictrapping force agreed with previous reports, and we applied speckle imaging analysis to mapthe in-plane bacterial velocities over large areas. This is the first time that spatial mapping ofbacterial velocities has been achieved in this setting. Thus, this analysis technique providesopportunities to better understand this phenomenon and to drive it towards in vivo applications.

Journal article

Kassanos P, Yang GZ, Yeatman E, 2021, An Interdigital Strain Sensor through Laser Carbonization of PI and PDMS Transfer

Additive methods using inks have attracted significant attention for printing sensors. Laser carbonization of polyimide is an ink-less alternative. In this paper laser carbonization and transfer to polydimethylsiloxane (PDMS) are used for the realization of interdigital electrode-based impedance strain sensors. These were fabricated employing high-resolution laser engraver optics and are characterized under mechanical deformations with an impedance analyzer to assess their sensitivity. The sensors achieved appreciable strain sensitivities (~1%/N) that improve with increasing excitation frequency (500 Hz to 50 kHz), demonstrating the applicability of the sensor and the fabrication process for strain sensing.

Conference paper

Hu M, Kassanos P, Keshavarz M, Yeatman E, Lo Bet al., 2021, Electrical and Mechanical Characterization of Carbon-Based Elastomeric Composites for Printed Sensors and Electronics

Printing technologies have attracted significant interest in recent years, particularly for the development of flexible and stretchable electronics and sensors. Conductive elastomeric composites are a popular choice for these new generations of devices. This paper examines the electrical and mechanical properties of elastomeric composites of polydimethylsiloxane (PDMS), an insulating elastomer, with carbon-based fillers (graphite powder and various types of carbon black, CB), as a function of their composition. The results can direct the choice of material composition to address specific device and application requirements. Molding and stencil printing are used to demonstrate their use.

Conference paper

Barbot A, Wales D, Yeatman E, Yang GZet al., 2021, Microfluidics at fibre tip for nanolitre delivery and sampling, Advanced Science, Vol: 8, Pages: 1-10, ISSN: 2198-3844

Delivery and sampling nanolitre volumes of liquid can benefit new invasive surgical procedures.However, the dead volume and difficulty in generating constant pressure flow limits the use of small tubes such as capillaries.This work demonstrates sub-millimetre microfluidic chips assembled directly on the tip of a bundle of two hydrophobic coated 100 μm capillaries to deliver nanolitre droplets in liquid environments.Droplets are created in a specially designed nanopipette and propelled by gas through the capillary to the microfluidic chip where a passive valve mechanism separates liquid from gas, allowing their delivery.By adjusting the driving pressure and microfluidic geometry we demonstrate both partial and full delivery of 10 nanolitre droplets with 0.4 nanolitre maximum error, as well as sampling from the environment.This system will enable drug delivery and sampling with minimally invasive probes, facilitating continuous liquid biopsy for disease monitoring and in-vivo drug screening.

Journal article

Fu H, Mei X, Yurchenko D, Zhou S, Theodossiades S, Nakano K, Yeatman EMet al., 2021, Rotational energy harvesting for self-powered sensing, JOULE, Vol: 5, Pages: 1074-1118, ISSN: 2542-4351

Journal article

Holmes AS, Kiziroglou ME, Yang SKE, Yuan C, Boyle DE, Lincoln DM, McCabe JDJ, Szasz P, Keeping SC, Williams DR, Yeatman EMet al., 2021, Minimally invasive online water monitor, IEEE Internet of Things Journal, ISSN: 2327-4662

Sensor installation on water infrastructure is challenging due to requirements for service interruption, specialised personnel, regulations and reliability as well as the resultant high costs. Here, a minimally invasive installation method is introduced based on hot-tapping and immersion of a sensor probe. A modular architecture is developed that enables the use of interchangeable multi-sensor probes, non-specialist installation and servicing, low-power operation and configurable sensing and connectivity. A prototype implementation with a temperature, pressure, conductivity and flow multi-sensor probe is presented and tested on an evaluation rig. This paper demonstrates simple installation, reliable and accurate sensing capability as well as remote data acquisition. The demonstrated minimally invasive multi-sensor probes provide an opportunity for the deployment of water quality sensors that typically require immersion such as pH and spectroscopic composition analysis. This design allows dynamic deployment on existing water infrastructure with expandable sensing capability and minimal interruption, which can be key to addressing important sensing parameters such as optimal sensor network density and topology.

Journal article

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