On the one hand, it is well-known that the model-based damage detection and model updating are insensitive to minor damage and is impeded due to ill-condition issues. Artificial intelligence includes machine learning, deep learning, computer vision, virtual and augumented realization (VR/AR), etc. Various machine learning and deep learning algorithms provide new potential ways to assess the structural conditions by using the big data, which structural health monitoring systems have sampled. In addition, the computer vision and VR/AR aid us to automatically “see” structure damage directly. In this lecture, the recent advances in artificial intelligence-based structural health monitoring are introduced, including the big data driven-based structural condition assessment, big data and model-based structural safety evaluation, and wind and earthquake disaster management.

In an age of proliferating technologies, we must innovate and leverage the right ones for the unique challenges of space exploration. For space, technology carries a specific meaning: the means to enable exciting new missions. We have achieved many new capabilities by leveraging technologies that have seen rapid advances for mission applications. For example, the advantages of rapid 3D printing have been pushed to an additional fourth “dimension,” namely by constructing space systems whose functions evolve over the course of the mission. The use of the smart materials has now made it possible to develop gears that no longer require lubrication and will perform in extreme environment for a long time. Other examples include miniaturization of instruments and systems now flying in JPL’s planetary CubeSats, new robotic systems that can crawl on a wall, and the swarms of thousands of tiny autonomous spacecraft. This presentation will provide an overview of the emerging space missions and the breakthrough technologies that will enable these missions over the next two decades.

While human tissues are mostly soft, wet and bioactive; machines are commonly hard, dry and biologically inert. Bridging human-machine interfaces is of imminent importance in addressing grand societal challenges in healthcare, security, sustainability and joy of living. However, interfacing human and machines is extremely challenging due to their fundamentally contradictory properties. At MIT SAMs Lab, we exploit soft-matter technology to bridge human-machine interfaces. On one side, soft matters such as bioactive hydrogels with similar physiological properties as tissues can naturally integrate with human body, playing functions such as scaffolds, catheters, stents, implants and wearable devices. On the other side, the soft matters embedded with electronic and mechanical components can control and respond to external machines. In this talk, I will first discuss the mechanics to design extreme properties for soft matters, including tough, resilient, adhesive, strong and antifatigue, which are necessary for reliable robust human-machine interfaces. Then I will discuss a new multi-material 3D printing platform to fabricate personalized and customized microstructures devices of soft matters. Based on the soft-matter design and fabrication technologies, we create a set of soft-matter devices such as i). long-term high-efficacy hydrogel neural probe, ii). ingestible and GI-resident hydrogel machine, and iii). untethered fast and forceful hydrogel robots controlled by magnetic fields. We will then discuss a systematic approach to design human-machine interfaces with unprecedented efficacy and biocompatibility based on soft-matter technology.

Recent advances in materials engineering, chip miniaturization, wireless communication, power management, and manufacturing technologies have shaped our perspectives on wearable electronics in ways that wearing a Fitbit is as casual as driving to work. However, establishing a robust sensor-to-skin interface remains as a significant challenge due to the drastic contrast in soft, dynamic human skin and rigid electronics, limiting the adoption of technology to leisure-based applications. Here, we present an engineering solution by combining the respective merits of thin-film nanostructures, soft materials, and miniature electronic components and developing a soft, hybrid, wireless, wearable platform. We exploit conventional CMOS processes to fabricate metal/polymer nanostructures, implemented as dry contact electrodes (thickness ~3 µm) as well as a flexible interconnection system (thickness ~10 µm). The electrodes are further optimized by incorporating an open-mesh network geometric features allowing for prolonged, intimate contact throughout repeated and dynamic deformation of human skin. The skin-electrode impedance and the signal-to-noise ratio are ~18 kΩ and 29.52 dB, respectively, from electromyogram (EMG) recordings, matching the qualities of Ag/AgCl hydrogel electrodes. The stretchable circuit layer contains pad metal structures compatible for integration of surface mount chip components using a conventional reflow soldering process, allowing for easy integration of commercially available integrated circuit solutions. Silicone-based elastomer is used as both the carrier substrate for the thin-film structures and the backing layer providing the necessary adhesiveness to the skin. We verify that the completed system can be stretched up to 10% based on computational and experimental analysis. Finally, we demonstrate the robustness of the system functionality by showcasing human-machine interfaces (HMI) based on a single-channel forearm EMG with a real-time classification distinguishing four different hand gestures (accuracy: 95.9%) as well as the control of a robotic hand using three devices simultaneously.

While many advances have been made in electrode design for neural recording and stimulation there is still a high demand for highly functioning and reliable electrodes for brain recording, imaging and stimulation Electrical Imaging Tomography (EIT) promises to deliver portable and radiation free solution for functional neural imaging, however it is limited by the lack of electrodes designed specifically for brain imaging. A flexible and implantable nanoelectrode has been designed specifically for EIT brain imaging. This nanoelectrode design can be applied anywhere where precise placement with minimal damage is required for chronic stimulation, neural recording or imaging of brain activity.

Surface-functionalizations are of essential importance for diverse areas from biomedicine to biosensing, nanocomposites, water treatment, and energy harvesting devices. One facile and rapid way to functionalize any materials surface is by mussel inspired polydopamine (PDA) coating. It has been realized that dopamine (DA), the precursor, can be coated virtually on any substrates in presence of a buffer of pH ~ 8.5. Over the past 20 years, an overwhelming interest has been noticed around cellulose based materials specially nanofibers (CNFs) shown due to its many unique characteristics including high stiffness and modulus, great transparency well biodegradability, biocompatibility and low production cost. Despite of the facts, pristine cellulose often suffers from certain characteristic limitations in biomaterial applications due to the lack of appropriate surface functionalities. This research therefore aims to develop cellulose based composite materials suitable for biomedical applications, precisely electrode material for biosensors. The electrodes were made of controlled amount of polydopamine treated cellulose nanofiber composite. When investigated the mechanical properties of the composites, significant improvement was observed. Moreover, the composites exhibited good sensing behaviors under electrochemical investigations, leading them to be a promising material for biosensing applications.

Electronic skin are devices that mimic the tactile sensing functionalities of human skin, which a wide variety of applications in touch screens, wearable electronics, prosthetic, and robotics. Important characteristics of electronic skin are high sensitivity, large dynamic range, low hysteresis, high spatial and temporal resolution, large area processability, and the ability to differentiate between various tactile inputs. We herein present various materials selection and architectural design principles to tune these properties to achieve high performance electronic skin devices.

Heart disease is the most common cause of death, so there is a great need for non-invasive continuous monitoring of heart activities in daily life for early diagnosis and treatment. However, existing devices are not suitable for long-term use since they are uncomfortable to wear and heavy due to rigid plastics and thick metals. Here, we introduce a low-profile, comfortable, skin-wearable multifunctional biopatch, capable of wireless monitoring of heart and motion activities. The combination of a thin, tacky elastomeric membrane, skin-like stretchable electrodes, and a small form factor flexible circuit ensures the intimate integration of the device on the skin in adhesive and gel electrolyte-free environment. The results are not only enhanced user comfort and minimized motion artifacts during normal activities but also accurate classifications for various arrhythmias based on R-R interval and ST-segment analysis. In addition, the integrated motion sensor is available to track human activities and alert an emergency when a fall event occurs. This multifunctional soft wearable system would serve as a new wearable tool to advance human healthcare.

Implanted neural sensing is important to unravel the complexity of neuronal circuitries and understand brain function. Implanted neural devices can capture neurochemical signals in the brain real time. During chronic implantation, micromotion between the neural implant and brain tissue is considered as one of key drivers for immune response and astroglial sheath formation around implants. Therefore, micromotion during in-vivo experiments interfere electrochemical sensing signals and longevity in the brain. This research presents experimental design and results of electrochemical and mechanical coupling of micromotion in a brain-like phantom simulating the brain. A piezoelectric actuator was used to generate motion of an electrode implanted in a phantom while applying potentials for cyclic voltammetry. Electrochemical signal analysis of neurotransmitter sensing was performed to identify motional effects varying experimental conditions such as the frequency and amplitude of mechanical motion, and the chemical and mechanical properties of the brain-like phantom changing the concentration of gelatin. The mechanical effect on neural sensing was also analyzed using DFT. We also introduced a computational model of micromotion in the brain to simulate and analyze mechanical effects on electrochemical neural sensing. The experiment and simulation results show mechanical motion affects the current level in the redox peaks of CV the most, and also shifts the peak voltages.

This paper presents a design of microstructure photonic crystal fiber (PCF) based sensor for the detection of glucose in urine inside terahertz radiation spectrum. Properties of the presented sensor have been investigated by the finite element method (FEM). The modeling of the PCF and rigorous numerical investigation is conducted by commercially available COMSOL Multiphysics® version 4.2. Essential properties like sensitivity, confinement loss, numerical aperture and power fraction have been studied inside the invitational terahertz spectrum. It has been observed that, the designed PCF is very simple as far as design is concerned, which enhance the sensing performance. So, it can be anticipated that if such type of devices is install successfully then the conventional system will achieve a new level of excellence.

The high mortality rate in developing countries stemming from poverty and diseases, and the pressure on healthcare budgets in developed countries have evoked a major concern in healthcare delivery. Patient-centered point-of-care testing (PoCT) devices for identifying and detecting infectious diseases through Polymerase Chain Reaction (PCR) are new and emerging. A critical aspect of PCR systems is the need to detect amplified products which is lacking in most conventional PCR systems. In this work, we exploited the phase shift between the temperature and transmission output during PCR cycle to demonstrate a simple, cheap, effective and patient-centered PoCT PCR systems.

This paper presents a method to provide continuous real-time condition monitoring of track health on an autonomous rail system. We use stretchable capacitive sensors installed on rolling stock (train carriages). The capacitive sensor was stretched between two points of the train with relative motion during operation, for instance, the current collector device (or shoe). Any change in relative motion signals, picked up by the capacitance change of the sensor, would indicate operational anomaly. We use our sensor to detect and differentiate between localized track wear, track misalignment and abnormal impact force. For train systems with a rigid legacy of train location detection systems, we propose a system of RFID transmitters and receivers to be lined at regular intervals along the train track and to be mounted on the train carriage, respectively. We propose a strategy to enhance the sensitivity of the capacitive sensor, and adopt Butterworth or wavelet for signal processing.

Surface plasmon resonance is widely studied and used for chemical and biological sensing. Current technology is based on angle resolved resonance detection at specific optical wavelengths. That is, changes in the reflectivity at the resonant angles are correlated to the chemical or biological substance at the surface of the sensor. In this work, we discuss the modeling and numerical techniques used to analyze a method to characterize plasmon resonances through surface acoustic wave (SAW) coupling of the incident light. The design strategies used to optimize the sensing performance of layered structures is described for several materials that are typically used as substrates and thin films.

Acoustic Emission (AE) based damage detection methods have the ability to continuously monitor large surfaces using a sparse sensor array, making it a very powerful tool for structural health monitoring. The Delta-T method, which is an experimental grid-based methodology, has been reported to be capable of providing accurate AE source locations estimates in complex geometries. However, the estimated location is very sensitive to the signal onset time obtained from the time series data. This paper evaluates six different signal onset detection algorithms proposed in the various literature, based on the estimated location obtained from the Delta-T method.

Piezoelectric thin films are of increasing interest in low voltage microelectromechanical systems (MEMS) for sensing, actuation, and energy harvesting. The key figures of merit for actuators and energy harvesting will be discussed, with emphasis on how to achieve these on practical substrates. For example, control of the domain structure of the ferroelectric material allows the energy harvesting figure of merit for the piezoelectric layer to be increased by factors of 4 – 10. To illustrate the functionality of these films, examples of integration into MEMS structures will also be discussed, including adjustable optics for x-ray telescopes, low frequency, and non-resonant piezoelectric energy harvesting devices, and miniaturized ultrasound transducer arrays.

Nowadays there is pressure for commercialization of research from founding agencies, but the process of commercialization of research needs time and support to be successful because there are several stages and limits which should be crossed to achieve a market product. Some of them are related to technical issues but some are related to business problems. One possible path of commercialization is creating new start-up companies. During this presentation, problems of research commercialization will be listed and discussed. Some case studies related to SHM technology will be presented. Particularly, the talk will focus on active thermography and applications, predictive maintenance based on AI algorithms and its application, on sensors design and application, and some UAV-based solutions.

Complex, three dimensional (3D) assemblies of nanomaterials provide sophisticated, essential functions in even the most basic forms of life. Compelling opportunities exist for analogous 3D structures in man-made devices, but existing design options are highly constrained by comparatively primitive capabilities in fabrication and growth . Here we summarize a collection of advances that provide broad access to diverse classes of 3D architectures in advanced materials, with characteristic dimensions that range from nanometers to centimeters and areas that span square centimeters or more. The approach relies on geometric transformation of preformed two dimensional (2D) precursor micro/nanostructures and/or devices into extended 3D layouts by controlled processes of substrate-induced compressive buckling, where the bonding configurations, thickness distributions and other parameters control the final configurations in a deterministic manner. Experimental and theoretical studies demonstrate the capabilities in a large collection of structures with various forms of function. Materials range from device-grade monocrystalline silicon to metals, dielectrics and heterogeneous combinations of these, in 3D forms that can be dynamically adjusted by mechanical means and released into free-standing forms. The results establish unique possibilities for wide-ranging classes of 3D microsystems technologies.

This paper explores 3D printing of functional ceramics AlN, BaTiO3, and Pb(Zr0.52Ti0.48)O3 and their composites. These functional ceramics have seen many successful applications in sensor, actuators, structural health monitoring, energy storage and harvesting. The fabrication process of ceramics typically requires mold casting thus is tedious and lacks design freedom. 3D printing offers unprecedented design freedom, however, most printing technologies have been focused on metals and polymers. Limited progress has been made on ceramics printing due to difficulties in printing and sintering. As a possible solution, this paper investigates the feasibility of using 3D to fabricate functional ceramics. Processing parameters such as particle size distribution, powder surface treatment, binder-powder interaction were investigated to optimize printed ceramic properties. It was shown that material properties such as thermal conductivity, density, dielectric, and piezoelectric constants of printed functional ceramics could be increased over 50%, reaching up to 80% of theoretical values.

Additive manufacturing (AM) is a crucial component of smart manufacturing systems that disrupts traditional supply chains. However, the parts built using the state-of-the-art powder-bed 3D printers have noticeable unpredictable mechanical properties. In this paper, we propose a closed-loop machine learning algorithm as a promising way of improving the underlying failure phenomena in 3D metal printing. We employ machine learning approach through a Deep Convolutional Neural Network to automatically detect the defects in printing the layers, thereby turning metal 3D printers into essentially their own inspectors. By comparing three deep learning models, we demonstrate that transfer learning approach based on Inception-v3 model in Tensorflow framework can be used to retrain our images data set consisting of only 200 image samples and achieves a classification accuracy rate of 100 % on the test set. This will generate a precise feedback signal for a smart 3D printer to recognize any issues with the build itself and make proper adjustments and corrections without operator intervention. The closed-loop ML algorithm can enhance the quality of the AM process, leading to manufacturing better parts with fewer quality hiccups, limiting waste of time and materials.

In this work, near field electrospinning was used to print single, semi-conductive nanowires. The nanowire was printed onto quartz tuning forks and quartz crystal microbalances to produce portable hydrogen sensors. A multi-modal combination of mechanical and electrochemical sensing methods are used to enhance the sensitivity and selectivity of the sensor. The sensors can sense ppm levels and exhibits good selectivity versus methane, hexane, toluene, ammonia, water ethanol and carbon dioxide. Single nanowires have gained popularity for sensing applications owing to high molecular transfer rates and flexibility. As a result, response times of as low as 3s were obtained.

Potential neurocognitive impairments and associated neural structural alterations are a great concern for any deep space mission, especially the planned mission to Mars where astronauts may spend several hundred days on the planet before coming back to the Earth. While the effects of inflight stress, radiation and microgravity on central nervous system function in prolonged missions have been examined, their mechanisms are largely unknown. In this research, neurophysiological signals from various regions in the rat brain are measured to assess their relationship to cognitive functions and alterations in response to space-related stressors using depth electrodes and multichannel data acquisition systems. In this presentation, an SVM feature selection algorithm is introduced and discussed that is designed to analyze brain function and the impact of space-related stressors without requiring or incorporating prior knowledge of underlying brain activity patterns.

Magnetic-driven micro-robotic devices have shown promising potential in enabling applications in micromanipulation, biosensing, targeted drug delivery, and minimally invasive surgery. However, the fabrication of miniaturized magnetic structures with complex geometries has remained the major technical obstacle. In this study, we report the development of a new magnetically-active photopolymerizable resin comprises poly (ethylene glycol) diacrylate monomer, Fe3O4 magnetic nanoparticles, photoinitiator, and other functional additives. Micro-continuous liquid interface production (micro-CLIP) 3D printing process was employed to realize high-resolution and high-speed fabrication of complex structures. The key characteristic properties of resin along with the matching process conditions were investigated experimentally, which allows for establishing the set of optimal fabrication conditions in fabricating magnetic micro-actuators towards potential applications.

Biological monitoring technology based on pressure sensor is a very useful human diagnosis method for assistive equipment, which can comfortable and uncomfortable state for user and patient on wearing position. Through various studies, pressure monitoring technology of wearable devices has been introduced in various fields. Especially, pressure monitoring for prosthetic arm and artificial leg was critical element in maintaining the safety of the amputees. In this research, the fabrication and characterization of a novel flexible pressure sensor designed to measure the pressure between human body and assistive device for biomechanical techniques. the sensor design is targeted for use in robotic and prosthetic limb, where feedback and ability to detect forces associated with slip were crucial. To fabricate the pressure sensor, finite element method (FEM), additive manufacturing (3D-printing) and signal processing were used. The pressure sensor was capacitive type flexible pressure sensor. FEM was used comsol for optimal structure design with deformation and capacitance maximum value to 500 kPa in sensor, in addition to result from practical experiments. Sensor with a full scale volume thickness under 10 mm were produced using 3D-printer of FDM method. Passive two-terminal electrical component part of capacitive pressure sensor was manufactured conductive thermoplastic material and medium side of dielectric layer was manufactured very soft and flexible thermoplastic. Through the inner pattern of dielectric layer, permittivity was controlled for capacitive pressure sensor. The signal processing system composes with combinations of capacitive pressure sensor, voltage divider circuit to amplifying the signal, multiplexer, microcontroller unit included analog to digital converter and indicating program. As a result, capacitive pressure sensing technology could be considered an influential device for maintenance of stability and comfortability to amputees. also it can be provided historical data for medical analysis and treatment.

Many polar gas molecules possess distinct transitions in the terahertz frequency range. In this work, we present the design and fabrication of foam based THz gas sensor. This foam structure is auspicious for use as an effective sensing material owing to its high porosity, greatly reduction in its transmission loss in the Terahertz regime. To optimize the efficacy of cellulose in gas detection, we evaluate the properties of these porosities constructed by different fabrication techniques.

Recently, an increasing trend has been noticed towards synthesizing superhydrophobic surface with a water contact angle (WCA) higher than 150° due to its many potential applications including water repellency, oil spill recovery, self-cleaning, antifouling, anti-icing-deicing and so on. Unfortunately, most of the cases the superhydrophobic surface was achieved utilizing either fluorinated materials or organic-inorganic nanoparticles as the water–solid contact angle varies with the surface chemistry and roughness of the solid surface. Herein, we presented a novel approach for preparation of superhydrophobic coating without involving any such hazardous chemicals with the oath to create sustainable world. The superhydrophobic coating was prepared using cellulose nanofibers (CNFs) via a new one step surface modification process. The as-synthesized cellulose surface shows water contact angle (WCA) value of 161°(±2°). When used this material to coat other substrates such as tissue paper, sponge and fabrics, etc., to test the water repellent capacity, the WCA values were found to be between 136-150°(±3°) for the above surfaces. Moreover, the excellent durability of the coating made it very promising for efficient oil/water separation process to self-cleaning textile.

Nanocellulose-based long fiber (NLF) is a key element of natural fiber-reinforced polymer composites which have ultimate impact for the future technology, owing to its merits in terms of high specific modulus, high strength, environmentally-friendliness and low cost. In this study, NLF is made by aligning cellulose nanofibers (CNFs), which are isolated from wood pulp by a chemical and physical methods. A high degree of alignment of the CNFs leads to increased number of hydrogen bonds among CNFs with enhanced mechanical properties of NLF. In this study, wet spinning, mechanical stretching, electric field and magnetic fields are used simultaneously or continuously to align CNFs effectively. To fabricate strong NLF, the process parameters are experimentally investigated, and their effects are evaluated by using the tensile test, scanning electron microscope

Nanocellulose has a great potential as a renewable material due to its high mechanical strength, high Young’s modulus, low density and eco-friendliness. Once a bulk material is made with it, then the bulk material made with nanocellulose can be a renewable bulk material, which is eco-friendly, lightweight and strong. Furthermore, it is known fact that cellulose has piezoelectricity due to its ordered domain of cellulose including crystal domains of cellulose. Thus, by aligning cellulose domains in the renewable bulk material made by nanocellulose, an eco-friendly and smart material can be developed. This paper aims at testing the feasibility of bulk material processing by using nanocellulose, specifically cellulose nanocrystal (CNC). The fabrication was carried out through steam with high temperature and high pressure to form hydrogen bonds between CNCs, followed by a heat and pressure molding. Its crystalline structure and physical interactions are investigated by using X-ray diffraction. Morphology and mechanical properties are investigated by scanning electron microscope and dynamic mechanical analysis.

This paper describes a double-layered foam filled THz split ring resonator gas sensor. The resonance shift of the metamaterial is used to detect the concentration of a gas. A nanoporous cellulose foam is added to further enhances the adsorption of gas molecules. Different dielectric inserts and multilayer metamaterials are being investigated. Results from experiment and simulation generated from the CST Studio Suite^® 3D EM analysis are presented. In addition, porosity of the foam is optimized by fine tuning the fabrication procedure to improve the measurement.

Multiple sclerosis is a potentially disabling disease of the brain and spinal cord , the immune system ( White Blood Cells ) attack the Myelin Sheath that cover nerve fiber causes communication problems between the brain and the rest of the body . There is no cure for Multiple Sclerosis , treatments typically focuses on speeding recovery from attacks but there are options for relapsing remitting MS include" Beta Interferon and these medications are the most commonly prescribed to treat MS because they reduce the frequency and severity of relapses like Ocrelizumab, Glatiramer, Dimethylfumarate, Gilenya and few from the Blood Barrier to the CNS . The demyelization and axonal damage or loss of Nerves Cells in the CNS System is starting with the breakdown of white Blood Cells to the Blood Brain Barrier which cause a migration of it to the CNS System. VLA-4 Integrin (Very Late Antigen 4) gain access in Multiple Sclerosis by allowing white Blood Cells to penetrate the Blood Brain Barrier throw making links with the Adhesion Molecule Inhibiters which known as VCAM-1 Receptors which located in Endothelial Cells and it block White Blood Cells activity by preventing interaction between them and transmigration of white Blood Cells to the CNS System. The Idea is using Nanoparticles to control the activation of VCAM-1 with VLA-4 Integrin and stop the Penetration of White Blood Cells to the Blood Brain Barrier.

This paper reports an electrospinning of cellulose nanofiber (CNF) and poly(vinyl alcohol) (PVA) blend for fabricating nanocellulose based long filament in terms of experiment and simulation. To enhance spinnability, Triton X-100 and dimethyl sulfoxide (DMSO) was introduced as a surfactant and cosolvent, respectively. Parameters governing the electrospinning of CNF-PVA blend are voltage, spinning speed, nozzle diameter, the distance between the electrodes, and the viscosity of the blend. Node-based analysis of the electrospinning is performed with electrostatic field modeling via MATLAB software. With the simulation results, proper combinations of parameters are determined for CNF-PVA electrospinning. Furthermore, empirical demonstration of the CNF-PVA electrospinning is achieved. Electospun nanofiber mat is investigated by field emission scanning electron microscopy.

Being a naturally occurring biopolymer, cellulose is popular and deeply explored for its amazing mechanical properties. Cellulose nanofibers are modelled and molecular dynamics simulations conducted using GROMACS and All-Optimized Potential for Liquid Simulations (OPLS-AA) force field is used for parameterization. The mechanical properties and structural stability of the cellulose nanofibers are investigated via the simulations. We explore the hydrogen bonding disparities on the CNF structure as it is subjected to different pull forces. The results show that the hydrogen bonds decrease every time a pull force is increased, with the decrement more significant when large pull forces are applied than low pull forces.

In this work, investigations into remnant breakdown strength of natural and synthetic Nanofilled and unfilled Polypropylene (PP) is made when aged under different types of voltage profiles.Synthetic and natural organoclay samples of 2wt-%, 4wt-%, 6wt-%, and 8wt-% were used in the experiments. They were exposed to constant voltage electric aging (constant voltage), an electric field that increases in a step fashion (step voltage), and an electric field that increases at a constant rate with time (ramp voltage). The various types of voltages were applied to the nanocomposites individually to observe how they would behave under different aging conditions.Surface analysis were conducted using a surface profilometer to measure the erosion depth and a 3D HIROX microscope were also used to observe and quantify the degradation volume. Breakdown strength analyses were done on all aged and unaged samples to evaluate the effect of PD on the remnant breakdown strength of samples with and without nanocomposites.During aging, the formation of space charge that causes change in PD characteristics depends on the electric field applied during aging. In the constant electric field aging, space charges formed have more time for their redistribution and the PD characteristics are mainly affected due to the space charges formed during the PD activity.

Continued miniaturization of devices is pushing the limits of Moore’s Law in that compacting elements in ever decreasing sizes of two dimensional structures is over. Direct laser write techniques offer a method to continue device miniaturization by developing 3D architectures for building devices. The dominant technique is through two-photon polymerization of polymeric materials using a “3D etch-a-sketch” type method for producing these structures. In this work, we use the laser Gaussian beam parameters, scanning speed, repetition rate, pulse width, and two-photon polymerization crossection to develop an equation that accurately describes the structure sizes. The results show good agreement with data reported in the literature for a wide range of fabrication parameters.

The leaf stomata of sound part open for water evaporation through transpiration, which makes the plant cool, while the damage to the stomata reduces the transpiration and increases the leaf temperature in diseased areas, resulting the temperature difference. Early detection of crop disease in plant is difficult to identify quickly and lead to respond immediately it is an important issue for food security, however there are only few technologies to detect. The advancement of rapidly evolving non-destructive testing techniques and computer technology that enables deep learning has paved the way for automatic diagnosis of plant diseases using non-destructive testing techniques. In this study, IR image based monitoring technique was studied to be considered to classify the disease of plant in agricultural area. The objective of this study is to automatically detect the plant diseases by using thermal image analysis techniques and deep learning algorithm. Healthy leaves and diseased leaves of Scindapsus (Epipremnum aureum) were compared and analyzed by using thermal images. The temperature of the diseased part of a leaf was 1 ~ 1.5 ℃ higher than sound part of a leaf. For sound leaves, the temperature difference was within 0.5 ℃. In addition, a deep learning model for automatic diagnosis was developed and verified. The model was designed based on VGGNet (Visual Geometry Group) and it was verified after learning using images of cats and dogs. As the number of learning times increases, the loss of training data decreases and the accuracy improves. This study suggests the possibility of automatic diagnosis of plant diseases by using thermal imaging technology and deep learning model.

In order to preemptively respond to environmental problems and global warming issues, the existing heat energy in ocean or waste heat resources has received attention as an important energy source as a renewable energy source, which is not used in conventional power cycle. Organic Rankine Cycle (ORC) can generate electrical power by heating the working refrigerant that evaporates at lower temperatures than waste water, which is the waste heat from internal combustion engines and industrial processes. To operate ORC cycle in low temperature condition, proper selection of working fluid is very critical issue and important to design the system. The problem of selection of working fluid is nowadays is very limited due to ozone depletion as well as global warming issues. Hydrogen fluoride (HFC) refrigerants, mainly used now, for the prevention and control of global warming, are set and regulated as reduction commitments from 2013 to 2020 by the Kyoto Protocol. To meet the new regulations, we should design and select appropriate refrigerants which possess low global warming potential (GWP) and ozone depletion potential (ODP). With a single refrigerant, it is quite difficult to satisfy the above requirement; therefore the development of new environmentally friendly refrigerants is very essential. Alternative refrigerants by mixing with existing refrigerants can the best way to solve the problem. In this study, the convective heat transfer coefficients of binary or ternary refrigerants were obtained through a pool boiling. In addition, simulation was performed prior to the ORC experiment according to the binary or ternary refrigerants. After that, the refrigerant was actually mixed and injected into the ORC system. The correlation of gliding temperature difference (GTD) characteristics of refrigerants and GTD characteristics of cooling water with heat exchanger were investigated. The results show that the efficiency of the ocean temperature difference power generation system increases as the GTD of mixed refrigerant. The maximum efficiency of system is correlated the GTD characteristic which is also linked to cooling water where the heat exchanges in the system.

In this paper, we report a simple but efficient method for fabricating nanofiber yarns. Distinctive feature of this method is without an alternative twisting mechanism during electrospinning process for bundling these fibers, which can reduce the occurrence of breakup during the twisting and simplify the fabrication process. The method has been applied to various polymers like PEDOT:PSS and successfully create yarn structure.

In construction places, 80-90% of accidents are generally caused by unsafe actions and behaviors of workers. These unsafe actions and behaviors by workers are not only caused by violating the standards but also caused by emotional exhaustion, mental stress, and physical factors, including fear, habitual behavior, stress, mood, physical characteristics, and physiological condition. Although the original causes of unsafe actions and behaviors of individuals are not well identified, their actions and behaviors can be monitored using multimodal wearable sensing that includes motion sensing, eye tracking, and EEG monitoring. In addition, recent progress in data analysis and machine learning techniques shows potentials to predict and prevent hazardous episodes. In this presentation, multimodal sensing and machine learning techniques will be introduced and their feasibility to monitor a construction worker’s mental and physiological states and to predict unsafe actions will be discussed.

By utilizing adaptive features, smart materials can be built as sensors and actuators. Energy can be harvested from vibration and human motion. Piezoelectric and electromagnetic power generators were used to transform the mechanical energy from vibration and human motion into electrical energy. On the other hand, robotic exoskeletons that can assist people with impaired mobility have been developed. With the developed device, paralyzed individual can regain the ability to stand up and walk. Smart ankle-foot prostheses with compact cam-spring mechanism have also been implemented to help amputees walk with less effort while having more natural gait. Utilizing additive manufacturing into smart materials has led to 4D printing technology for creating structures that can change their shape and function on-demand and over time. Actuator units were designed and fabricated directly by printing fibers of shape memory polymers in flexible structures. They can serve as tubular stents and grippers for biomedical applications. In this talk, related research projects and key results will be presented.

Research in ultrasonic NDE over the past several decades has been supported by a growing use of specialist modeling tools, to calculate wave propagation behavior, the influences of materials, guided waves, and the scattering of waves from features and defects. Model capabilities are now so good that simulations are being used in a similar manner to experiments, and some important research objectives are not possible at all without them. The NDE research group at Imperial College has worked over many years on the long-term development of some general purpose modeling tools, which have provided essential underpinning to the creation of new capabilities in NDE. This presentation will use some examples of research achievements in NDE to illustrate the vital role of advanced modeling tools in their success.

We propose a dielectric elastomer actuator based active-lens module for dynamically-controllable optical zoom. The active-lens module consists of a couple of active-lenses with a convex and concave shaped hemispherical lens-structure, a stationary lens, and CCD image sensor. Since each active-lens allows bi-directionally-controllable translational movement of lens-structure responding to a hybrid driving force of electro-static force and electrically-induced deformation of a thin dielectric elastomer actuator, the active-lens module is capable of programmably changing relative position of the active-lenses. Due to the benefits from functionality of the active-lenses, our active-lens module can provide electrically-controllable optical zoom in a slim and light-weight configuration.

Refractive index change under external stimuli is an important mechanism for smart optics. Electric polar filler embedded soft medium composite such as liquid crystal can change refractive index by electrical potential due to align of electric filler. This research investigates refractive index change of cellulose nanocrystal (CNC) based transparent electroactive polyurethane for smart optics application. Since CNC has electric polarity, it plays a role of filler which can be aligned by an electrical potential. Polyurethane is used for soft medium which is embedding CNC. All about the preparation of the CNC based transparent electroactive polyurethane is introduced and its optical characterization is explained. Since it is highly transparence and has high refractive index change, it is a promising electroactive material for smart optics.

This paper presents the new G-Fresnel lens-based μ-spectrometer with an image-processing algorithm, such as a color space conversion, in the range of visible light. The proposed μ-spectrometer is developed by using the cost-effective and compact G-Fresnel lens, which diffuses the mixed visible light into the spectrum image, and an image processing algorithm. The RGB color space commonly used in the image signal from CMOS type image sensor is converted into the HSV color space, which is one of the most popular methods to express the color as the numeric value, Hue (H), Saturation (S), and Value (V), using the color space conversion algorithm. Because the HSV color space has the advantages of expressing not only the three primary color of light as the H-value, but also its intensity as the V-value, it was possible to obtain both the wavelength and intensity information of the visible light from its spectrum image. The proposed -spectrometer yielded an inverse linear sensitivity (hue vs. the wavelength). We demonstrated the potential of G-Fresnel lens-based -spectrometer for the wavelength measurement of visible light such as mechanoluminescence (ML), typically green light across the region of 500 nm.

Cellulose nanofiber (CNF) is known to have high mechanical strength, high Young’s modulus, optical transparency, low thermal expansion coefficient and low density, which are beneficial for flexible display substrates and optical films. The purposes of this study is to fabricate ultrathin CNF film and to explore its physical properties. CNF suspension is extracted by 2,2,6,6-tetramethylpiperidin-1-oxyl (TEMPO) oxidation combined with aqueous counter collision (ACC) treatment from bleached hardwood pulp. The CNF suspension is cast on a thin positive photoresist (PR) layer by a doctor blade casting method followed by removing PR layer and drying on a polytetrafluoroethylene (PTFE) sheet to obtain ultrathin CNF film. Morphology of ultrathin CNF film is characterized by atomic force microscopy and the thickness of the film was characterized by FE-SEM. Transparency and birefringence of the prepared ultrathin CNF film are tested by using an UV-visible spectrometer and a digital camera. The piezoelectric response microscopy (PFM) is utilized to analysis the piezoelectric properties of ultrathin CNF film.

Recently, structural energy storage devices with a simultaneous ability to store electrochemical energy and to bear mechanical loads have brought spotlight in electrical vehicles, unmanned air vehicles, and humanoid mobile robots technologies. However, realizing an integrated electro-chemo-mechanical system faces a big difficulty with developing highly conductive electrodes and solid electrolytes with superior mechanical strength and electrochemical functionality. Here in, we report a load-bearing structural supercapacitor by utilizing a bicontinuous PEO-b-P(S-co-DVB) structural electrolyte and carbon-coated Ni-Co nanowires grown on carbon fiber woven fabric. A liquid phase polymer electrolyte between the two electrodes is transformed into a solid-state block copolymer electrolyte. After the polymerization, the electrolyte preserves fine contact with the surface of nanostructured electrode. In the electrolyte point of view, the polymerization-induced microphase separation produces a bi-continuous morphology. The bi-continuously cross-linked hard domain and liquid-like conductive domain in the electrolyte shows both high modulus and high conductivity. As a result, the structural supercapacitor is able to bear tensile and even bending loading while functioning as energy storage device, suggesting its various possible applications.

With the advance of soft electronic industry, soft electro-ionic artificial muscles based on electro-active polymer have been actively investigated from the practical viewpoint. However, due to the few drawbacks of the soft electro-ionic artificial muscles, they have not yet been applied to the practical applications until know. Herein, we report soft electro-ionic artificial muscles based on three dimensional graphene-carbon nanotube-nickel nanostructures (G-CNT-Ni). The G-CNT-Ni were blended in both polymeric electrodes and ionic membranes to fabricate a strong and large-bending soft electro-ionic artificial muscle. Importantly, the G-CNT-Ni exhibited remarkable electrochemical reactivity due to the synergistic effects of large specific surface area, three-dimensionally networked structures, and no restacking phenomena. Moreover, reinforcement of the G-CNT-Ni makes significantly improved blocking force and bending actuation of soft electro-ionic artificial muscle. This investigation can opens up a new way to apply soft electro-ionic artificial muscles to practical applications in next-generation electronic devices.

Materials engineering has greatly contributed to improving the performance of soft active materials, but these improvements have seldom met the compelling needs of science and engineering applications. Here, we demonstrate, for the first time, a new approach to the design of soft active materials, which embraces the complexity of multiphysics phenomena across electrostatics and electrochemistry. Through principled experiments and physically-based models we investigate the integration of electrostatic actuation in ionic polymer-metal composites (IPMCs).

There is ongoing uncertainty about the best way to mitigate the complication strategy in the development of varifocal lenses. Many efforts are being focused on the fabrication of adaptive focus lenses by a simple technique. Since the adaptive focus lenses change its curvature in response to the applied voltage; there has been a multitude of research is actively under progress. In this paper, we propose a compliant, highly transparent, and electroactive polymers based self-deformable microlens for smart optical devices. Especially, a non-ionic PVC gel among electroactive polymers was selected to develop self-deformable microlens to avoid the solvent leakage because its actuation mechanism is not based on solvent-drag deformation but on creep deformation in an electric field, unlike ionic gel electrolytes. To make the convex shape on an actuation area of the proposed module, we put a rigid annular electrode on the electroactive PVC gel and apply pressure input by the rigid annular electrode. Later, we measure the focal length variations of the proposed varifocal lens with various thicknesses of electroactive gels. The resulting focal length values, obtained for the proposed module being large enough to use in small and compact optic devices.

Controlled patterning of a 3D structure consisting of porous microstructures by manipulating conformation and orientation can result in enhanced physical properties of individual architectures, such as high stiffness and excellent energy absorbing ability. However, the physical properties of porous materials may not reach their full potential in their final three-dimensional macroscopic architectures, owing to critical issues in structural regulation and functional restriction. Therefore, addressing the limitations of conventional porous sound absorbers is a potentially important future investigation with regard to 3D microstructures of porous graphene. To address these issues, we carried out this study. Herein, a novel strategy to fabricate the graphene-based cellular foam for sound absorption is reported, in which a unique microscopic cellular structure is designed by controlling graphene layer morphology and differentiation inside the polyurethane framework.

Our understanding of the physics of airflows may benefit from direct full-field pressure measurement. In this work, we demonstrate the possibility of simultaneous planar velocity and pressure measurement of an airflow using pressure-sensitive tracer particles. Specifically, polystyrene microparticles embedded with pressure-sensitive dye PtOEP are fabricated and used to quantify the velocity and pressure variations of an airflow. The velocity field is obtained by particle tracking and the pressure field is inferred from the emission lifetime of the dye. Our experiment offers preliminary evidence for the possibility of simultaneous velocity and pressure measurement of an airflow using pressure-sensitive tracer particles.

Rechargeable power management system (RPMS) is significantly necessary to monitor the performance of power storage in biomedical devices. Failure of power storage device due to the battery pack, in a medical device, can entail dire consequences such as respiratory devices defibrillators and severe trembling. During charging and discharging the cell might become overstressed or underutilized, of which former may degrade the cell's lifespan. We applied an active balancing technique to distribute charges uniformly into the cell and thus increasing its efficiency and lifespan. In this technique, cells in the stack are monitored at regular intervals for their state of charge (SOC) and the average charge among them is calculated. The cell having the lowest voltage is charged by the series combination of the rest of the cells, by using switching device through isolation transformer which acts as the charge transferring device. In this research, the amount of charge transferred to the low voltage cell was controlled by controlling the frequency of the switching ranging from 100-500kHz. This RPMS includes modules for data acquisition and data logger by which the history of battery pack can be checked for any possible future breakdown and prediction of available run time for the battery pack. RPMS also features cell temperature monitoring to keep it within its safe limits. In this presentation, we will discuss the circuit simulation results using Multisim™ and hardware implementation in progress.

This study developed the feedforward control strategy of the piezoelectric micro-stage integrated with a bridge-type compliant mechanism. The micro-stage was assembled with three actuator legs and a moving plate. The actuator leg was consisted of four piezoelectric actuators with compliant mechanism. However, the complex nonlinear coupling between piezo-actuators and the compliant mechanism caused the hysteresis which can obstruct the precise control. The hysteresis of the piezoelectric micro-stage was realized by the 3rd order polynomial model in this study. Furthermore, the polynomial model was revised to consider the hysteresis change depending on the rate of input voltage. The compensator based on the revised polynomial model was designed for the feedforward control. The performance of the compensator was evaluated while changing the input voltage rate. Experiment results show that the tracking error of the compensator with the rate-dependent model quite decreases in compared with the rate-independent model. The feedforward control based on the revised polynomial model can be successfully utilized to the piezoelectric micro-stage regardless of the input voltage rate.

It is known from literature that several electrical characteristics such as Partial Discharge (PD) Resistance of Polypropylene (PP) Films can be improved by homogeneous dispersion of Nanofillers into the polymer matrix. In this work, effect of variation in aging voltage on PD characteristics of PP and its remnant breakdown strength (BDS) is investigated for unfilled (PP+0%) and natural Nanofilled Polypropylene (PP+2% & PP+6%) films. Using PD measurement set up several AC voltages (multiple of inception voltage, Vi) are applied on each sample for a duration of two hours and PD parameters were acquired. Surface erosion of aged PP samples was measured using Profilometer to investigate effects of change in applied voltage and Nanofillers concentrations on the PD Resistance of PP samples.Breakdown Strength Measurement experiment of all unaged and aged PP samples were conducted to dig into the effect of degree of aging of PP samples on their breakdown strengths when the samples contained different amounts of nanofillers. Changes in aging voltage will affect the polymer morphology changing the BDS in turn. Comparison of PD characteristics of all samples (unaged and aged) were done finally and the effect of voltages on PD during aging and consequently the remnant Breakdown Strength in presence and absence of nanofillers were investigated and the results are presented.

Recently, cellulose fiber reinforced ecofriendly polymer composite for structural material is one of issue due to its sustainability, high mechanical properties, light weight and abundancy. For high strength and sustainable blend, a resin with sustainable, high strength and cellulose compatibility is demanded. PVA-lignin composite is one of good candidate for resin materials due to its high mechanical properties and good adhesion with cellulose. However, low waterproof ability is significant disadvantage of this material. In this paper, esterification reaction with maleic acid was adopted to enhance the mechanical properties. The esterification reaction enhanced waterproof ability and adhesion of PVA-lignin resin to cellulose material.