This PDF file contains the front matter associated with SPIE Proceedings Volume 10194, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

Uncertainty quantification (UQ) is the study of the effects of uncertainty on the values of analytical results and the predictions of scientific models. Sources of uncertainty include imprecise knowledge of the exact values of parameters, lack of confidence in the physical models, use of imperfectly calibrated models, and irreducible uncertainties due to physical characteristics. The Air Force Research Laboratory has undertaken the challenge of understanding, developing and analyzing the techniques of UQ as they apply to Laser Beam Control. This paper proposes a simple methodology and simple results with our first attempt of applying UQ as a new analysis tool. The software toolkit which was chosen was an analytical group of algorithms from a Sandia National Laboratory (SNL) package called DAKOTA (Design Analysis Kit for Optimization and Terascale Applications). The specific application of interest to the Air Force Research Laboratory (AFRL) is the analytical prediction of the performance of a Laser Beam Control systems under various scenarios, conditions, and missions. The application of rigorous UQ techniques to the models used to predict beam control performance could greatly improve our confidence in these predictions and also improve the acceptance of advanced Laser Beam Control systems within the science and engineering communities^1,2. The proposed work would follow a multi-step approach, analyzing the more easily quantified sources of uncertainty, and then including increasingly complicated physical phenomena as the work progresses. Will present the initial results, and the first steps in the incorporation of UQ into our Laser Beam Control Modeling and Simulation environments.

The presence of distributed-volume atmospheric aberrations or “deep turbulence” presents unique challenges for beam-control applications which look to sense and correct for disturbances found along the laser-propagation path. This paper explores the potential for branch-point-tolerant reconstruction algorithms and tiled-aperture architectures to correct for the branch cuts contained in the phase function due to deep-turbulence conditions. Using wave-optics simulations, the analysis aims to parameterize the fitting-error performance of tiled-aperture architectures operating in a null-seeking control loop with piston, tip, and tilt compensation of the individual optical beamlet trains. To evaluate fitting-error performance, the analysis plots normalized power in the bucket as a function of the Fried coherence diameter, the log-amplitude variance, and the number of subapertures for comparison purposes. Initial results show that tiled-aperture architectures with a large number of subapertures outperform filled-aperture architectures with continuous-face-sheet deformable mirrors.

We report about developing long-wave infrared diffractive optical components based on liquid crystals. The components show high efficiency and high transparency for the 10.6 μm wavelength of CO₂ laser beam.

The turbulent effect from the Earth’s atmosphere degrades the performance of an optical imaging system. Many studies have been conducted in the study of beam propagation in a turbulent medium. Horizontal beam propagation and correction presents many challenges when compared to vertical due to the far harsher turbulent conditions and increased complexity it induces. We investigate the collection of beam propagation data, analysis, and use for building a mathematical model of the horizontal turbulent path and the plans for an adaptive optical system to use this information to correct for horizontal path atmospheric turbulence.

Digital fabrication methods are reshaping design and manufacturing processes through the adoption of pre-production visualization and analysis tools, which help minimize waste of materials and time. Despite the increasingly widespread use of digital fabrication techniques, comparatively few of these advances have benefited the design and fabrication of textiles. The development of functional fabrics such as knitted touch sensors, antennas, capacitors, and other electronic textiles could benefit from the same advances in electrical network modeling that revolutionized the design of integrated circuits. In this paper, the efficacy of using current state-of-the-art digital fabrication tools over the more common trialand- error methods currently used in textile design is demonstrated. Gaps are then identified in the current state-of-the-art tools that must be resolved to further develop and streamline the rapidly growing field of smart textiles and devices, bringing textile production into the realm of 21st century manufacturing.

The recent ability to integrate materials with different optical and optoelectronic properties in prescribed architectures within flexible fibers is enabling novel opportunities for advanced optical probes, functional surfaces and smart textiles. In particular, the thermal drawing process has known a series of breakthroughs in recent years that have expanded the range of materials and architectures that can be engineered within uniform fibers. Of particular interest in this presentation will be optoelectronic fibers that integrate semiconductors electrically addressed by conducting materials. These long, thin and flexible fibers can intercept optical radiation, localize and inform on a beam direction, detect its wavelength and even harness its energy. They hence constitute ideal candidates for applications such as remote and distributed sensing, large-area optical-detection arrays, energy harvesting and storage, innovative health care solutions, and functional fabrics. To improve performance and device complexity, tremendous progresses have been made in terms of the integrated semiconductor architectures, evolving from large fiber solid-core, to sub-hundred nanometer thin-films, nano-filaments and even nanospheres. To bridge the gap between the optoelectronic fiber concept and practical applications however, we still need to improve device performance and integration. In this presentation we will describe the materials and processing approaches to realize optoelectronic fibers, as well as give a few examples of demonstrated systems for imaging as well as light and chemical sensing. We will then discuss paths towards practical applications focusing on two main points: fiber connectivity, and improving the semiconductor microstructure by developing scalable approaches to make fiber-integrated single-crystal nanowire based devices.

The Internet of Things envisions a web-connected infrastructure of billions of sensors and actuation devices. However, the current state-of-the-art presents another reality: monolithic end-to-end applications tightly coupled to a limited set of sensors and actuators. Growing such applications with new devices or behaviors, or extending the existing infrastructure with new applications, involves redesign and redeployment. We instead propose a modular approach to these applications, breaking them into an equivalent set of functional units (context engines) whose input/output transformations are driven by general-purpose machine learning, demonstrating an improvement in compute redundancy and computational complexity with minimal impact on accuracy. In conjunction with formal data specifications, or ontologies, we can replace application-specific implementations with a composition of context engines that use common statistical learning to generate output, thus improving context reuse. We implement interconnected context-aware applications using our approach, extracting user context from sensors in both healthcare and grid applications. We compare our infrastructure to single-stage monolithic implementations with single-point communications between sensor nodes and the cloud servers, demonstrating a reduction in combined system energy by 22-45%, and multiplying the battery lifetime of power-constrained devices by at least 22x, with easy deployment across different architectures and devices.

New possibilities exist for the development of novel hardware/software platforms havin g fast data acquisition capability with low power requirements. One application is a high speed Adaptive Design for Information (ADI) system that combines the advantages of feature-based data compression, low power nanometer CMOS technology, and stream computing [1]. We have developed a compressive sensing (CS) algorithm which linearly reduces the data at the analog front end, an approach which uses analog designs and computations instead of smaller feature size transistors for higher speed and lower power. A level-crossing sampling approach replaces Nyquist sampling. With an in-memory design, the new compressive sensing based instrumentation performs digitization only when there is enough variation in the input and when the random selection matrix chooses this input.

Recent advancements in two-dimensional (2D) materials have opened significant research opportunities in optics and photonics. While the initial focus on 2D materials was on Graphene, new generation of 2D materials such as hexagonal boron nitride (h-BN), transition metal dichalcogenides (TMDCs), monolayer black phosphorous (BP) and other monolayer structures have shown unique electrical and optical properties. For example, h-BN is an insulator, while monolayers of some TMDCs such as MoS2 and WSe2 are direct band-gap semiconductors. Depending on the choice of material compositional and layer variations their optical properties can be engineered, making them particularly attractive as novel light sources, photodetectors, modulators and photovoltaic components, in particular for few photon applications. Plasmonic properties of 2D materials make them suitable for nanophotonics and monolithic integration with other conventional materials. The National Science Foundation (NSF) is a US federal agency dedicated to promote progress of science and engineering. NSF is the funding source for approximately 24 percent of all federally supported basic research conducted by America's colleges and universities. NSF has recently supported several initiatives related to novel 2D material and device research. In this talk, I will first give an overview of the NSF programs and funding opportunities. The second part of the talk will be focused on the programs related to 2D materials for photonic devices and program specific initiatives. Several highlights of the recent achievements and awards in the field of 2D materials for photonic devices will be presented.

Black phosphorus recently emerged as a promising two-dimensional material due to its widely tunable and direct bandgap, high carrier mobility and remarkable in-plane anisotropic electrical, optical and phonon properties. It serendipitously bridges the zero-gap graphene and the relatively large-bandgap transition metal dichalcogenides such as molybdenum disulfide (MoS₂). In this brief review manuscript, we will first cover the basic properties of few-layer and thin-film black phosphorus. Then we will present a few potential applications of black phosphorus such as radiofrequency transistors and wideband photodetectors. Finally we will discuss the recent observation of efficient bandgap tuning in black phosphorus thin films in a dual-gate transistor, and conclude with the discussion of synthesis of large area and high quality black phosphorus thin films.

2D semiconductors have recently emerged as promising optoelectronic materials, with high quantum efficiency of photoemission, absorption and nonlinear optical properties. With significant progress in understanding the material science of these atomically thin materials, and building devices with stand-alone monolayer materials, it is an opportune time to integrate these materials with existing optoelectronic platform to realize the full potential of the 2D materials. Here, we highlight our recent progress in 2D semiconductor integrated with nanophotonic resonators. Specifically, we report the operation of an optically pumped laser, cavity enhanced electroluminescence and cavity enhanced second harmonic generation.

Van de Waals (vdW) heterostructures – which consist of precisely assembled atomically thin electronic materials - exhibit unusual quantum behavior. These quantum materials-by-design are of fundamental interest in basic scientific research and hold tremendous potential in advanced technological applications. Problematically, the fundamental optoelectronic response in these heterostructures is difficult to access using the standard techniques within the traditions of materials science and condensed matter physics. In the standard approach, characterization is based on the measurement of a small amount of one-dimensional data, which is used to gain a precise picture of the material properties of the sample. However, these techniques are fundamentally lacking in describing the complex interdependency of experimental degrees of freedom in vdW heterostructures. In this talk, I will present our recent experiments that utilize a highly data-intensive approach to gain deep understanding of the infrared photoresponse in vdW heterostructure photodetectors. These measurements, which combine state-of-the-art data analytics and measurement design with fundamentally new device structures and experimental parameters, give a clear picture of electron-hole pair interactions at ultrafast time scales.

We have studied the ultrafast conversion of electrons localized in vertical Au-hBN-Au tunnel junctions to free-space photons, mediated by resonant slot antennas. We achieve polarized, directional and resonantly enhanced light emission from inelastic electron tunneling and establish a novel platform for studying the interaction of electrons with strong electromagnetic fields. Further, we show that plasmonic antennas made from a gold nanoparticle dimer coupled with a semiconducting 2D material (MoS₂) offer control over emission directionality.

Artificial metamaterials – metallo-dielectric composites tailored on deep-subwavelength scale – enable implementation of electromagnetic responses not found in nature, leading to potentially useful applications as well as yielding new insights into the fundamental nature of light. Here we show how we have leveraged ultrasmooth planar nanoplasmonic waveguides deposited by ion-beam-assisted sputter deposition to implement easy-to-fabricate bulk metamaterials operating at visible and ultra-violet wavelengths and having refractive indices ranging from highly anisotropic and positive [1] to quasi-isotropic and negative [2]. Exploiting these structures to tailor the flow of light in exotic ways, we realize devices ranging from high-contrast, near-field nanoparticle optical sensors working in the visible, to the first implementation of a Veselago flat lens [3] functioning in the near ultraviolet. Substituting Al for Ag as the constituent plasmonic metal of choice, we investigate the extension of bulk metamaterial operation into the mid-ultraviolet, for lithographic applications beyond the diffraction limit. [1] T. Xu and H.J. Lezec, Nat. Comm. 5, 4141 (2014). [2] T. Xu, A. Agrawal, M. Abashin, K.J. Chau, and H.J. Lezec, Nature 497, 470 (2013). [3] V.G. Veselago, Sov. Phys. Usp. 10, 509 (1968).

A superlens that can create sub-diffraction-limited imaging has attracted extensive interest over the past decade. In this paper, we discuss our recent work of infrared superlenses based on perovskites and doped semiconductors. Perovskite oxides show pronounced phonon resonances in the range of 10 to 30 μm, giving rise to negative permittivities around the resonant frequencies. Consequently, we can match a pair of perovskite materials with permittivities in opposite signs to fulfill the superlensing condition. Using a scattering-type scanning near-field optical microscope (s-SNOM) coupled with a tunable free-electron laser, we investigate the evanescent waves in the image plane of perovskite superlenses to address precisely the surface polariton modes, which are important to enhance imaging resolution. Sub-diffractionlimited images with resolution of λ/14 have been achieved at the superlensing wavelength. We also demonstrate a nearfield superlens based on doped semiconductors in the mid-infrared region. Highly doped n-GaAs induces a resonant enhancement of evanescent waves, leading to a significantly improved spatial resolution at the wavelength around 20 μm that is adjustable by changing the doping level. Experimentally, gold stripes below the GaAs superlens are imaged with a λ/6 subwavelength resolution by s-SNOM. Full-wave simulation results are in very good agreement with the observed superlensing effect. These results promise a wide range of applications for infrared imaging, spectroscopy and biochemical sensing at the nanoscale.

In recent years, surface imaging of various biological dynamics and biomechanical phenomena has seen a surge of interest. Imaging of processes such as exocytosis and kinesin motion are most effective when depth is limited to a very thin region of interest at the edge of the cell or specimen. However, many objects and processes of interest are of size scales below the diffraction limit for safe, visible wavelength illumination. Super-resolution imaging methods such as structured illumination microscopy and others have offered various compromises between resolution, imaging speed, and bio-compatibility. In this talk, I will present our most recent progress in plasmonic structured illumination microscopy (PSIM) and localized plasmonic structured illumination microscopy (LPSIM), and their applications in bio-imaging. We have achieved wide-field surface imaging with resolution down to 75 nm while maintaining reasonable speed and compatibility with biological specimens. These plasmonic enhanced super resolution techniques offer unique solutions to obtain 50nm spatial resolution and 50 frames per second wide imaging speed at the same time.

III-V materials, which exhibit high absorption coefficients and charge carrier mobility, are ideal templates for solar energy conversion applications. This work describes the photoelectrochemistry research in several IIIV/electrolyte junctions as an enabler for device design for solar chemical reactions. By designing lattice-matched epitaxial growth of InGaP and GaP on GaAs and Si, respectively, extended depletion region electrodes achieve photovoltages which provide an additional boost to the underlying substrate photovoltage. The InGaP/GaAs and GaP/Si electrodes drive hydrogen evolution currents under aqueous conditions. By using nanowires of InN and InP under carefully controlled growth conditions, current and capacitance measurements are obtained to reveal the nature of the nanowire-electrolyte interface and how light is translated into photocurrent for InP and a photovoltage in InN. The materials system is expanded into the III-V nitride semiconductors, in which it is shown that varying the morphology of GaN on silicon yields insights to how the interface and light conversion is modulated as a basis for future designs. Current extensions of this work address growth and tuning of the III-V nitride electrodes with doping and polarization engineering for efficient coupling to solar-driven chemical reactions, and rapid-throughput methods for III-V nanomaterials synthesis in this materials space.

While decreasing the thickness of active layers is important in reducing the cost of solar cells, the absorption of incident light is challenging as the thickness becomes smaller than the wavelength. Metal nano-structures can be used on the top or bottom of the active layers to couple light of different plasmonic and photonic modes. Metal nano-structures can also be used as an intermediate layer within an active layer or between two active layers as in tandem solar cells. In this work, we discuss two photovoltaic cells based on plasmonic-inspired designs—one with silicon strips on the top and grooves on the silver back contact layer and the other with a periodically perforated metal layer in-between the two active layers.

The union of mico / nano electromechanical systems with metamaterials offers a new route to achieve reconfigurable devices which control the emission of energy. Here we propose and demonstrate the idea of metamaterial MEMS capable of modifying the emitted energy without changing the temperature. Rather our device only alters the spectral emissivity, thus realize a differential emissivity equivalent to a nearly 20-degree Celsius temperature change across the thermal infrared. We pixelate our device and thereby achieve a spatio-temporal emitter capable of displaying thermal infrared patterns up to speeds of 110 kHz. Our results are not limited to the thermal infrared band, but may be scaled to nearly any sub-optical range of the electromagnetic spectrum, and verify the potential of MEMS metamaterials to operate as reconfigurable multifunctional devices with unprecedented energy control capabilities.

Embedded combat medical personnel require accurate and timely biometric data to ensure appropriate life saving measures. Injured warfighter’s operating in remote environments require both assessment and monitoring often while still engaged with enemy forces. Small wearable devices that can be placed on injured personnel capable of collecting essential biometric data, including the capacity to remotely deliver collected data in real-time, would allow additional medical monitoring and triage that will greatly help the medic in the battlefield. These new capabilities will provide a force multiplier through remote assessment, increased survivability, and in freeing engaged warfighter’s from direct monitoring thus improving combat effectiveness and increasing situational awareness. Key questions around what information does the medic require and how effective it can be relayed to support personnel are at their early stages of development. A low power biometric wearable device capable of reliable electrocardiogram (EKG) rhythm, temperature, pulse, and other vital data collection which can provide real-time remote monitoring are in development for the Soldier.

Electrical Bioimpedance (EBI) is a well spread technology used in clinical practice across the world. Advancements in Textile material technology with conductive textile fabrics and textile-electronics integration have allowed exploring potential applications for Wearable Measurement Sensors and Systems exploiting. The sensing principle of electrical bioimpedance is based on the intrinsic passive dielectric properties of biological tissue. Using a pair of electrodes, tissue is electrically stimulated and the electrical response can be sensed with another pair of surface electrodes. EBI spectroscopy application for cerebral monitoring of neurological conditions such as stroke and perinatal asphyxia in newborns have been justified using animal studies and computational simulations. Such studies have shown proof of principle that neurological pathologies indeed modify the dielectric composition of the brain that is detectable via EBI. Similar to stroke, Traumatic Brain Injury (TBI) also affects the dielectric properties of brain tissue that can be detected via EBI measurements. Considering the portable and noninvasive characteristics of EBI it is potentially useful for prehospital triage of TBI patients where. In the battlefield blast induced Traumatic Brain Injuries are very common. Brain damage must be assessed promptly to have a chance to prevent severe damage or eventually death. The relatively low-complexity of the sensing hardware required for EBI sensing and the already proven compatibility with textile electrodes suggest the EBI technology is indeed a candidate for developing a handheld device equipped with a sensorized textile cap to produce an examination in minutes for enabling medically-guided prompt intervention.

Monitoring vital signs from human body is very important to healthcare and medical diagnosis, because they contain valuable information about arterial occlusions, arrhythmia, atherosclerosis, autonomous nervous system pathologies, stress level, and obstructive sleep apnea. Existing methods, such as electrocardiogram (ECG) sensor and photoplethysmogram (PPG) sensor, requires direct contact to the skin and it can causes skin irritation and the inconvenience of long-term wearing. For reducing the inconvenience in the conventional sensors, microwave and millimeter-wave sensors have been proposed since 1970s using micro-Doppler effect from one’s cardiopulmonary activity. The Doppler radar sensor can remotely detect the respiration and heartbeat up to few meters away from the subject, but they have a multiple subject issue and are not suitable for an ambulatory subject. As a compromise, a noncontact proximity vital sign sensor has been recently proposed and developed. The purpose of this paper is to review the noncontact proximity vital sign sensors for detection of respiration, heartbeat rate, and/or wrist pulse. This sensor basically employs near-field perturbation of radio-frequency (RF) planar resonator due to the proximity of the one’s chest or radial artery at the wrist. Various sensing systems based on the SAW filter, phase-locked loop (PLL) synthesizer, reflectometer, and interferometer have been proposed. These self-sustained systems can measure the nearfield perturbation and transform it into DC voltage variation. Consequently, they can detect the respiration and heartbeat rate near the chest of subject and pulse from radial artery at the wrist.

Facial surface electromyography (sEMG) is a powerful tool for objective evaluation of human facial expressions and was accordingly suggested in recent years for a wide range of psychological and neurological assessment applications. Owing to technical challenges, in particular the cumbersome gelled electrodes, the use of facial sEMG was so far limited. Using innovative facial temporary tattoos optimized specifically for facial applications, we demonstrate the use of sEMG as a platform for robust identification of facial muscle activation. In particular, differentiation between diverse facial muscles is demonstrated. We also demonstrate a wireless version of the system. The potential use of the presented technology for user-experience monitoring and objective psychological and neurological evaluations is discussed.

We developed melanoidin nanoparticles for in vivo noninvasive photoacoustic mapping of sentinel lymph nodes, photoacoustic tomography of gastro-intestinal tracts, and photothermal ablation cancer therapy. In addition, we developed cell-integrated poly(ethylene glycol) hydrogels for in vivo optogenetic sensing and therapy. Real-time optical readout of encapsulated heat-shock-protein-coupled fluorescent reporter cells made it possible to measure the nanotoxicity of cadmium-based quantum dots in vivo. Using optogenetic cells producing glucagon-like peptide-1, we performed lightcontrolled diabetic therapy for glucose homeostasis. Finally, we developed a smart contact lens composed of biosensors, drug delivery systems, and power sources for the treatment of diabetes as a model disease.

Miniaturized wirelessly powered implants capable of operating and communicating deep in the body are necessary for the next-generation of diagnostics and therapeutics. A major challenge in developing these minimally invasive implants is the tradeoff between device size, functionality, and operating depth. Here, we review two different wireless powering methods, inductive and ultrasonic power transfer, examine how to analyze their power transfer efficiency, and evaluate their potential for powering implantable medical devices. In particular, we show how ultrasonic wireless power transfer can address these challenges due to its safety, low attenuation, and millimeter wavelengths in the body. Finally, we demonstrate two ultrasonically powered implants capable of active power harvesting and bidirectional communication for closed-loop operation while functioning through multiple centimeters of tissue.

In this paper, numerous inkjet-/3D-/4D-printed wearable flexible antennas, RF electronics, modules and sensors fabricated on paper and other polymer (e.g. LCP) substrates are introduced as a system-level solution for ultra-low-cost mass production of autonomous Biomonitoring, Positioning and Sensing applications. This paper briefly discusses the state-of-the-art area of fully-integrated wearable wireless sensor modules on paper or flexible LCP and show the first ever 4D sensor module integration on paper, as well as numerous 3D and 4D multilayer paper-based and LCP-based RF/microwave, flexible and wearable structures, that could potentially set the foundation for the truly convergent wireless sensor ad-hoc “on-body networks of the future with enhanced cognitive intelligence and “rugged” packaging. Also, some challenges concerning the power sources of “nearperpetual” wearable RF modules, including flexible miniaturized batteries as well as power-scavenging approaches involving electromagnetic and solar energy forms are discuessed. The final step of the paper will involve examples from mmW wearable (e.g. biomonitoring) antennas and RF modules, as well as the first examples of the integration of inkjet-printed nanotechnology-based (e.g.CNT) sensors on paper and organic substrates for Internet of Things (IoT) applications. It has to be noted that the paper will review and present challenges for inkjetprinted organic active and nonlinear devices as well as future directions in the area of environmentally-friendly “green”) wearable RF electronics and “smart-skin conformal sensors.

Current-generation wearable devices have had success continuously measuring the activity and heart rate of subjects during exercise and daily life activities, resulting in interesting new data sets that can, though machine learning algorithms, predict a small subset of health conditions. However, this information is only very peripherally related to most health conditions, and thus offers limited utility to a wide range of the population. In this presentation, I will discuss emerging sensor technologies capable of measuring new and interesting parameters that can potentially offer much more meaningful and actionable data sets. Specifically, I will present recent work on wearable chemical sensors that can, for the first time, continuously monitor a suite of parameters like glucose, alcohol, lactate, and electrolytes, all while wirelessly delivering these results to a smart phone in real time. Demonstration platforms featuring patch, temporary tattoo, and mouthguard form factors will be described, in addition to the corresponding electronics necessary to perform sensor conditioning and wireless readout. Beyond chemical sensors, I will also discuss integration strategies with more conventional electrophysiological and physical parameters like ECG and strain gauges for cardiac and respiration rate monitoring, respectively. Finally, I will conclude the talk by introducing a new form of wireless communications in body-area networks that utilize the body itself as a channel for magnetic energy. Since the power consumption of conventional RF circuits often dominates the power of wearable devices, this new magnetic human body communication technique is specifically architected to dramatically reduce the path loss compared to conventional RF and capacitive human body communication techniques, thereby enabling ultra-low-power body area networks for next-generation wearable devices.

This paper highlights emerging medical applications for magnetoelastic sensing and actuation, each taking advantage of the wireless capabilities and small form factor enabled by the magnetoelastic transduction technique. Magnetoelastic transduction leverages the strong coupling between stress, strain, and magnetization intrinsic to some materials – notably amorphous metals and rare earth crystalline alloys. This coupling provides inherently wireless transduction that does not require any onboard power; these traits are especially advantageous in diagnostic and therapeutic medical implant applications. This paper first describes the basic transduction technique, and considerations for design and fabrication of medical systems which utilize the technique. These considerations include material selection, magnetic biasing, packaging, and interrogation approaches. The first application highlighted is stent monitoring, in which the masssensitive magnetoelastic resonator is integrated along the inner sidewall of the stent to provide early detection of stent occlusion. Prototype tests indicate clinical feasibility and a full scale range from zero stent occlusion to full stent occlusion. Wireless ranges of up to 15 cm in situ have been achieved using 25 mm long resonators. The second application is wireless strain sensing, which can be useful for orthopedic implants and orthodontia. A differential strain sensor is described, with a dynamic range of 0-1.85 mstrain – accommodating typical palatal expander strain – and a sensitivity of 12.5x10³ ppm/mstrain. Finally, a wireless actuator intended to agitate fluid for mitigation of encapsulation of glaucoma drainage devices is shown. Peak actuator vibration amplitudes of 1.5 μm – sufficient to affect cell adhesion in other studies – are recorded at a wireless range of 25-30 mm.

Assistive technologies (AT) play an important role in the lives of people with disabilities. Most importantly, they allow individuals with severe physical disabilities become more independence. Inherent abilities of the human tongue originated from its strong representation in the motor cortex, its direct connection to the brain through well-protected cranial nerves, and easy access without a surgery have resulted in development of a series of tongue-operated ATs that tap into the dexterous, intuitive, rapid, precise, and tireless motion of the tongue. These ATs not only help people with tetraplegia as a result of spinal cord injury or degenerative neurological diseases to access computers/smartphones, drive wheelchairs, and interact with their environments but also have the potential to enhance rehabilitation paradigms for stroke survivors. In this paper, various types of tongue operated ATs are discussed based on their working principles and task based performances. Comparisons are drawn based on widely accepted and standardized quantitative measures, such as throughput, information transfer rate, typing speed/accuracy, tracking error, navigation period, and navigation accuracy as well as qualitative measures, such as user feedback. Finally, the prospects of using variations of these versatile devices to enhance human performance in environments that limit hand and finger movements, such as space exploration or underwater operations are discussed.

This work reports a platform technology toward the development of closed-loop neuromodulation. A neural implant based on the SoC developed in our laboratory is used as an example to illustrate the necessary functionalities for the efficacious implantable system. We also present an example of using the system to investigate the epidural stimulation for partial motor function recovery after spinal cord injury in a rat model. This hardware-software co-design tool demonstrate its promising potential towards an effective closed-loop neuromodulation for various biomedical applications.

Traumatic peripheral nerve injuries suffered during amputation commonly results in debilitating neuropathic pain in the affected limb. Modern prosthetic technologies allow for intuitive, simultaneous control of multiple degrees of freedom. However, these state-of-the-art devices require separate, independent control signals for each degree of freedom, which is currently not possible. As a result, amputees reject up to 75% of myoelectric devices preferring instead to use body-powered artificial limbs which offer subtle sensory feedback. Without meaningful and intuitive sensory feedback, even the most advanced myoelectric prostheses remain insensate, burdensome, and are associated with enormous cognitive demand and mental fatigue. The ideal prosthetic device is one which is capable of providing intuitive somatosensory feedback essential for interaction with the environment. Critical to the design of such a bioprosthetic device is the development of a reliable biologic interface between human and machine. This ideal patient-prosthetic interface allows for transmission of both afferent somatosensory information and efferent motor signals for a closed-loop feedback system of neural control. Our lab has developed the Regenerative Peripheral Nerve Interface (RPNI) as a biologic nerve interface designed for stable integration of a prosthetic device with transected peripheral nerves in a residual limb. The RPNI is constructed by surgically implanting the distal end of a transected peripheral nerve into an autogenous muscle graft. Animal experiments in our lab have shown recording of motor signals from RPNI’s implanted into both rodents and monkeys. Here, we achieve high amplitude EMG signals with a high signal to noise (SNR) ratio.

This talk will discuss the current goals and efforts of point of care and personal health monitoring systems: what they can do now and what is in the works. These interfaces can be used in a precision medicine context—making diagnoses and getting the right drugs to the right patients at the right time. Many of the same sensors and engineering are being prototyped now for neural interfaces and recording devices with applications in visual, auditory, and motor cortex, allowing basic research along with preliminary applications in actuation and sensing. While miniaturization and electronics development using established manufacturing protocols can provide the current engineering foundations, novel biochemical ligands and molecular detectors can provide the needed flexibility for next-generation devices.

The development of methods for interfacing high performance functional devices with biology could impact regenerative medicine, smart prosthetics, and human-machine interfaces. Indeed, the ability to three-dimensionally interweave biological and functional materials could enable the creation of devices possessing unique geometries, properties, and functionalities. Yet, most high quality functional materials are two dimensional, hard and brittle, and require high crystallization temperatures for maximal performance. These properties render the corresponding devices incompatible with biology, which is three-dimensional, soft, stretchable, and temperature sensitive. We overcome these dichotomies by: 1) using 3D printing and scanning for customized, interwoven, anatomically accurate device architectures; 2) employing nanotechnology as an enabling route for overcoming mechanical discrepancies while retaining high performance; and 3) 3D printing a range of soft and nanoscale materials to enable the integration of a diverse palette of high quality functional nanomaterials with biology. 3D printing is a multi-scale platform, allowing for the incorporation of functional nanoscale inks, the printing of microscale features, and ultimately the creation of macroscale devices. This three-dimensional blending of functional materials and ‘living’ platforms may enable next-generation 3D printed devices.

Forthcoming wearable/flexible electronics with compelling shape diversity and mobile usability have garnered significant attention as a kind of disruptive technology to drastically change our daily lives. From a power source point of view, conventional rechargeable batteries (represented by lithium-ion batteries) with fixed shapes and dimensions are generally fabricated by winding (or stacking) cell components (such as anodes, cathodes and separator membranes) and then packaging them with (cylindrical-/rectangular-shaped) metallic canisters or pouch films, finally followed by injection of liquid electrolytes. In particular, the use of liquid electrolytes gives rise to serious concerns in cell assembly, because they require strict packaging materials to avoid leakage problems and also separator membranes to prevent electrical contact between electrodes. For these reasons, the conventional cell assembly and materials have pushed the batteries to lack of variety in form factors, thus imposing formidable challenges on their integration into versatile-shaped electronic devices. Here, as a facile and efficient strategy to address the aforementioned longstanding challenge, we demonstrate a new class of printed solid-state Li-ion batteries and also all-inkjet-printed solid-state supercapacitors with exceptional shape conformability and aesthetic versatility which lie far beyond those achievable with conventional battery technologies.

Successful integration of ultrathin flexible or stretchable systems with new applications, such as medical devices and biodegradable electronics, have intrigued many researchers and industries around the globe to seek materials and processes to create high-performance, non-invasive and cost-effective electronics to match those of state-of-the-art devices. Nevertheless, the crucial concept of transmitting data or power wirelessly for such unconventional devices has been difficult to realize due to limitations of radio-frequency (RF) electronics in individual components that form a wireless circuitry, such as antenna, transmission line, active devices, passive devices etc. To overcome such challenges, these components must be developed in a step-by-step manner, as each component faces a number of different challenges in ultrathin formats. Here, we report on materials and design considerations for fabricating flexible and stretchable electronics systems that operate in the microwave level. High-speed flexible active devices, including cost effective Si-based strained MOSFETs, GaAs-based HBTs and GaN-based HEMTs, performing at multi-gigahertz frequencies are presented. Furthermore, flexible or stretchable passive devices, including capacitors, inductors and transmission lines that are vital parts of a microwave circuitry are also demonstrated. We also present unique applications using the presented flexible or stretchable RF components, including wearable RF electronics and biodegradable RF electronics, which were impossible to achieve using conventional rigid, wafer-based technology. Further opportunities like implantable systems exist utilizing such ultrathin RF components, which are discussed in this report as well.

Additively manufactured components, although extensively customizable, are often limited in functionality. Multi-process additive manufacturing (AM) grants the ability to increase the functionality of components via subtractive manufacturing, wire embedding, foil embedding and pick and place. These processes are scalable to include several platforms ranging from desktop to large area printers. The Multi^3D System is highlighted, possessing the capability to perform the above mentioned processes, all while transferring a fabricated component with a robotic arm. Work was conducted to fabricate a patent inspired, printed missile seeker. The seeker demonstrated the advantage of multi-process AM via introduction of the pick and place process. Wire embedding was also explored, with the successful interconnect of two layers of embedded wires in different planes. A final demonstration of a printed contour bracket, served to show the reduction of surface roughness on a printed part is 87.5% when subtractive manufacturing is implemented in tandem with AM. Functionality of the components on all the cases was improved. Results included optical components embedded within the printed housing, wires embedded with interconnection, and reduced surface roughness. These results highlight the improved functionality of components through multi-process AM, specifically through work conducted with the Multi^3D System.

Three-dimensional (3D) printing of fiber reinforced composites represents an enabling technology that may bring toughness and specific strength to complex parts. Recently, direct-write 3D printing has been offered as a promising route to manufacturing fiber reinforced composites that show high specific strength. These approaches primarily rely on the use of shear-alignment during the extrusion process to align fibers along the printing direction. Shear alignment prevents fibers from being oriented along principle stress directions of the final designed part. This paper describes a new direct-write style 3D printing system that incorporates magnetic fields to actively control the orientation of reinforcing fibers during the printing of fiber reinforced composites. Such a manufacturing system is fraught with complications from the high shear dominated alignment experienced by the fibers during extrusion to the slow magnetic alignment dynamics of fibers in viscous media. Here we characterize these issues and suggest effective operating windows in which magnetic alignment is a viable approach to orienting reinforcing particles during direct-write 3D printing.

The development of portable non-invasive brain computer interface technologies with higher spatio-temporal resolution has been motivated by the tremendous success seen with implanted devices. This talk will discuss efforts to overcome several major obstacles to viability including approaches that promise to improve spatial and temporal resolution. Optical approaches in particular will be highlighted and the potential benefits of both Blood-Oxygen Level Dependent (BOLD) and Fast Optical Signal (FOS) will be discussed. Early-stage research into the correlations between neural activity and FOS will be explored.

Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

As we move through an environment, we are constantly making assessments, judgments, and decisions about the things we encounter. Some are acted upon immediately, but many more become mental notes or fleeting impressions -- our implicit "labeling" of the world. In this talk I will describe our work using physiological correlates of this labeling to construct a hybrid brain-computer interface (hBCI) system for efficient navigation of a 3-D environment. Specifically, we record electroencephalographic (EEG), saccadic, and pupillary data from subjects as they move through a small part of a 3-D virtual city under free-viewing conditions. Using machine learning, we integrate the neural and ocular signals evoked by the objects they encounter to infer which ones are of subjective interest. These inferred labels are propagated through a large computer vision graph of objects in the city, using semi-supervised learning to identify other, unseen objects that are visually similar to those that are labelled. Finally, the system plots an efficient route so that subjects visit similar objects of interest. We show that by exploiting the subjects' implicit labeling, the median search precision is increased from 25% to 97%, and the median subject need only travel 40% of the distance to see 84% of the objects of interest. We also find that the neural and ocular signals contribute in a complementary fashion to the classifiers' inference of subjects' implicit labeling. In summary, we show that neural and ocular signals reflecting subjective assessment of objects in a 3-D environment can be used to inform a graph-based learning model of that environment, resulting in an hBCI system that improves navigation and information delivery specific to the user's interests.

Brain-computer interface (BCI) research has progressed rapidly, with BCIs shifting from animal tests to human demonstrations of controlling computer cursors and even advanced prosthetic limbs, the latter having been the goal of the Revolutionizing Prosthetics (RP) program. These achievements now include direct electrical intracortical microstimulation (ICMS) of the brain to provide human BCI users feedback information from the sensors of prosthetic limbs. These successes raise the question of how well people would be able to use BCIs to interact with systems that are not based directly on the body (e.g., prosthetic arms), and how well BCI users could interpret ICMS information from such devices. If paralyzed individuals could use BCIs to effectively interact with such non-anthropomorphic systems, it would offer them numerous new opportunities to control novel assistive devices. Here we explore how well a participant with tetraplegia can detect infrared (IR) sources in the environment using a prosthetic arm mounted camera that encodes IR information via ICMS. We also investigate how well a BCI user could transition from controlling a BCI based on prosthetic arm movements to controlling a flight simulator, a system with different physical dynamics than the arm. In that test, the BCI participant used environmental information encoded via ICMS to identify which of several upcoming flight routes was the best option. For both tasks, the BCI user was able to quickly learn how to interpret the ICMSprovided information to achieve the task goals.

he National Energy Technology Laboratory (NETL) under the Department of Energy (DOE) Fossil Energy (FE) Program is leading the effort to not only develop near zero emission power generation systems, but to increaser the efficiency and availability of current power systems. The overarching goal of the program is to provide clean affordable power using domestic resources. Highly efficient, low emission power systems can have extreme conditions of high temperatures up to 1600 oC, high pressures up to 600 psi, high particulate loadings, and corrosive atmospheres that require monitoring. Sensing in these harsh environments can provide key information that directly impacts process control and system reliability. The lack of suitable measurement technology serves as a driver for the innovations in harsh environment sensor development. Advancements in sensing using optical fibers are key efforts within NETL’s sensor development program as these approaches offer the potential to survive and provide critical information about these processes. An overview of the sensor development supported by the National Energy Technology Laboratory (NETL) will be given, including research in the areas of sensor materials, designs, and measurement types. New approaches to intelligent sensing, sensor placement and process control using networked sensors will be discussed as will novel approaches to fiber device design concurrent with materials development research and development in modified and coated silica and sapphire fiber based sensors. The use of these sensors for both single point and distributed measurements of temperature, pressure, strain, and a select suite of gases will be addressed. Additional areas of research includes novel control architecture and communication frameworks, device integration for distributed sensing, and imaging and other novel approaches to monitoring and controlling advanced processes. The close coupling of the sensor program with process modeling and control will be discussed for the overarching goal of clean power production.

We describe an innovative and scalable strategy of transforming a commercial unclad sapphire optical fiber to an allalumina nanostructured sapphire optical fiber (NSOF) that overcomes decades-long challenges faced in the field of sapphire fiber optics. The strategy entails fiber coating with metal Al followed by subsequent anodization to form anodized alumina oxide (AAO) cladding of highly organized pore channel structure. We show that Ag nanoparticles entrapped in AAO show excellent structural and morphological stability and less susceptibility to oxidation for potential high-temperature surface-enhanced Raman Scattering (SERS). We reveal, with aid of numerical simulations, that the AAO cladding greatly increases the evanescent-field overlap both in power and extent and that lower porosity of AAO results in higher evanescent-field overlap. This work has opened the door to new sapphire fiber-based sensor design and sensor architecture.

Femtosecond Infrared (fs-IR) laser written fiber Bragg gratings (FBGs), have demonstrated great potential for extreme sensing. Such conditions are inherent to advanced power plant technologies and gas turbine engines, under development to reduce greenhouse gas emissions; and the ability to measure temperature gradients in these harsh environments is currently limited by the lack of sensors and controls capable of withstanding the high temperature, pressure and corrosive conditions present. This paper reviews our fabrication and deployment of hundreds of fs-IR written FBGs, for monitoring temperature gradients of an oxy-fuel fluidized bed combustor and an aerospace gas turbine combustor simulator.

This paper demonstrates optical fibers as high-temperature sensor platforms. Through engineering and onfiber integration of functional metal oxide sensory materials, we report the development of an integrated sensor solution to perform temperature and chemical measurements for high-temperature energy applications. Using the Rayleigh optical frequency domain reflectometry (OFDR) distributed sensing scheme, the temperature and hydrogen concentration were measured along the fiber. To overcome the weak Rayleighbackscattering intensity exhibited by conventional optical fibers, an ultrafast laser was used to enhance the Rayleigh scattering by a direct laser writing method. Using the Rayleigh-enhanced fiber as sensor platform, both temperature and hydrogen reaction were monitored at high temperature up to 750°C with 4-mm spatial resolution.

Real-time temperature mapping is important to offer an optimized thermal design of efficient power transformers by solving local overheating problems. In addition, internal temperature monitoring of power transformers in operation can be leveraged for asset monitoring applications targeted at fault detection to enable condition based maintenance programs. However transformers present a variety of challenging environments such as high levels of electromagnetic interference and limited space for conventional sensing systems to operate. Immersion of some power transformers within insulation oils for thermal management during operation and the presence of relatively large and time varying electrical and magnetic fields in some cases also make sensing and measurement technologies that require electrical wires or active power at the sensing location highly undesirable. In this work, we investigate the dynamic thermal response of standard single-mode optical fiber instrumented on a compact transformer core by using an optical frequency-domain reflectometry scheme, and the spatially resolved on-line monitoring of transformer core temperature rise has been successfully demonstrated. It is found that spectral shifts of the fiber-optic sensor induced by the temperature rises are strongly related to the locations inside the transformer as would be expected. Correlation between thermal behavior of the transformer core as derived from standard IR-based thermal imaging cameras and fiber-optic sensing results is also discussed. The proposed method can easily be extended to cover situations in which high accuracy and high spatial resolution thermal surveillance are required, and offers the potential for unprecedented optimization of magnetic core designs for power transformer applications as well as a novel approach to power transformer asset monitoring.

All automations must, at some point in their lifecycle, interface with one or more humans. Whether operators, end-users, or bystanders, human responses can determine the perceived utility and acceptance of an automation. It has been long believed that human trust is a primary determinant of human-automation interactions and further presumed that calibrating trust can lead to appropriate choices regarding automation use. However, attempts to improve joint system performance by calibrating trust have not yet provided a generalizable solution. To address this, we identified several factors limiting the direct integration of trust, or metrics thereof, into an active mitigation strategy. The present paper outlines our approach to addressing this important issue, its conceptual underpinnings, and practical challenges encountered in execution. Among the most critical outcomes has been a shift in focus from trust to basic interaction behaviors and their antecedent decisions. This change in focus inspired the development of a testbed and paradigm that was deployed in two experiments of human interactions with driving automation that were executed in an immersive, full-motion simulation environment. Moreover, by integrating a behavior and physiology-based predictor within a novel consequence-based control system, we demonstrated that it is possible to anticipate particular interaction behaviors and influence humans towards more optimal choices about automation use in real time. Importantly, this research provides a fertile foundation for the development and integration of advanced, wearable technologies for sensing and inferring critical state variables for better integration of human elements into otherwise fully autonomous systems.

We developed the Situation awareness-based Agent Transparency (SAT) model to support human operators’ situation awareness of the mission environment through teaming with intelligent agents. The model includes the agent's current actions and plans (Level 1), its reasoning process (Level 2), and its projection of future outcomes (Level 3). Human-inthe-loop simulation experiments have been conducted (Autonomous Squad Member and IMPACT) to illustrate the utility of the model for human-autonomy team interface designs. Across studies, the results consistently showed that human operators’ task performance improved as the agents became more transparent. They also perceived transparent agents as more trustworthy.

In this paper, a human-autonomy interaction approach is presented that enables autonomy to proactively dialogue with human teammates to maintain common understanding of the underlying processes. A class of human-autonomy systems where the role of the autonomy is to assist a human teammate in decision making tasks is considered. The autonomy maintains its knowledge of the processes and the environment in a Bayesian engine, and uses a Bayesian inference framework to provide decision support. Any discrepancy in the knowledge of the process between the autonomy and the human teammate may lead to inefficient decision support. The presented curious partner interaction framework uses a dialogue-based approach to resolve differences between the human and the autonomy. The dialog acts as a feedback mechanism to revise the Bayesian engine representation of the autonomy’s knowledge to establish common ground. An application to military operations is considered where a digital assistant uses the curious partner framework to provide decision support to a commander.

Humans, interacting with cyber–physical systems (CPS), formulate beliefs about the system’s dynamics. It is natural to expect that human operators, tasked with teleoperation, use these beliefs to control the remote robot. For tracking tasks in the resulting human–cyber–physical system (HCPS), theory suggests that human operators can achieve exponential tracking (in stable systems) without state estimation provided they possess an accurate model of the system’s dynamics. This internalized inverse model, however, renders a portion of the system state unobservable to the human operator—the zero dynamics. Prior work shows humans can track through observable linear dynamics, thus we focus on nonlinear dynamics rendered unobservable through tracking control. We propose experiments to assess the human operator’s ability to learn and invert such models, and distinguish this behavior from that achieved by pure feedback control.

Amplifying human ability for controlling complex environments featuring autonomous units can be aided by learned models of human and system performance. In developing a command and control system that allows a small number of people to control a large number of autonomous teams, we employ an autonomics framework to manage the networks that represent mission plans and the networks that are composed of human controllers and their autonomous assistants. Machine learning allows us to build models of human and system performance useful for monitoring plans and managing human attention and task loads. Machine learning also aids in the development of tactics that human supervisors can successfully monitor through the command and control system.

There has been increased impetus to leverage Small Unmanned Aerial Systems (SUAS) for collaborative sensing applications in which many platforms work together to provide critical situation awareness in dynamic environments. Such applications require critical sensor observations to be made at the right place and time to facilitate the detection, tracking, and classification of ground-based objects. This further requires rapid response to real-world events and the balancing of multiple, competing mission objectives. In this context, human operators become overwhelmed with management of many platforms. Further, current automated planning paradigms tend to be centralized and don’t scale up well to many collaborating platforms. We introduce a decentralized approach based upon information-theory and distributed fusion which enable us to scale up to large numbers of collaborating Small Unmanned Aerial Systems (SUAS) platforms. This is exercised against a military application involving the autonomous detection, tracking, and classification of critical mobile targets. We further show that, based upon monte-carlo simulation results, our decentralized approach out-performs more static management strategies employed by human operators and achieves similar results to a centralized approach while being scalable and robust to degradation of communication. Finally, we describe the limitations of our approach and future directions for our research.

Considering context and the relationship between objects and events in the environment is a key component to developing the situational awareness necessary to accomplish abstract goals or effectively share information. We extend state of the art perception algorithms, which can identify specific objects in the environment, using cognitive reasoning to develop a deeper understanding of the scene based on the both the objects and their spatial relationships. Such understanding could impact the choice of tasks, routes, or observation positions in a military mission.

Autonomous reconnaissance missions are called for in extreme environments, as well as in potentially hazardous (e.g., the theatre, disaster-stricken areas, etc.) or inaccessible operational areas (e.g., planetary surfaces, space). Such future missions will require increasing degrees of operational autonomy, especially when following up on transient events. Operational autonomy encompasses: (1) Automatic characterization of operational areas from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and data gathering; (3) automatic feature extraction including anomaly detection and region-of-interest identification; (4) automatic target prediction and prioritization; (5) and subsequent automatic (re-)deployment and navigation of robotic agents. This paper reports on progress towards several aspects of autonomous C⁴ISR systems, including: Caltech-patented and NASA award-winning multi-tiered mission paradigm, robotic platform development (air, ground, water-based), robotic behavior motifs as the building blocks for autonomous tele-commanding, and autonomous decision making based on a Caltech-patented framework comprising sensor-data-fusion (feature-vectors), anomaly detection (clustering and principal component analysis), and target prioritization (hypothetical probing).

This paper considers incorporating autonomy into human-centric Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) environments. Specifically, it focuses on identifying ways that current autonomy technologies can augment human control and the challenges presented by additive autonomy. Three approaches to this challenge are considered, stemming from prior work in two converging areas. In the first, the problem is approached as augmenting what humans currently do with automation. In the alternate approach, the problem is approached as treating humans as actors within a cyber-physical system-of-systems (stemming from robotic distributed computing). A third approach, combines elements of both of the aforementioned.

Internet of Things will open the digital world for future services working across company borders. Together with autonomous systems intelligent things will communicate and work together without direct influence of human technicians or service managers. IT-security will become one of the most important challenges to ensure a stable service performance and to provide a trustful environment to let people use such service without any concerns regarding data privacy and eligibility of the outcomes.

The mission of the Inland California Translational Consortium (ICTC), an independent research consortium comprising a unique hub of regional institutions (City of Hope [COH], California Institute of Technology [Caltech], Jet Propulsion Laboratory [JPL], University of California Riverside [UCR], and Claremont Colleges Keck Graduate Institute [KGI], is to institute a new paradigm within the academic culture to accelerate translation of innovative biomedical discoveries into clinical applications that positively affect human health and life. The ICTC actively supports clinical translational research as well as the implementation and advancement of novel education and training models for the translation of basic discoveries into workable products and practices that preserve and improve human health while training and educating at all levels of the workforce using innovative forward-thinking approaches.

Astronauts are experiencing ophthalmological changes including optic disc edema, globe flattening, choroidal folds, and significant hyperopic shifts. In a handful of cases in which it was measured, intracranial pressure as measured by lumbar punctures was elevated post-flight. The severity of symptoms is highly variable and the underlying etiology is unknown, but a spaceflight associated cephalad-fluid shift is thought to play a role. NASA requires portable, non-invasive, clinically-validated approaches to assessing the ocular and the cerebral physiological, anatomical, and functional changes. Multispectral Imaging (MSI) that enables instruments installed on satellites in space to observe Earth was applied in an ophthalmic medical device that is clinically being used on Earth and now being evaluated for use on humans in space. The Annidis RHA™ (Ottawa, Canada) uses narrow band light emitting diodes (LEDs) to create discrete slices of anatomical structures of the posterior pole of the eye. The LEDs cover a frequency range from 520 to 940 nm, which allow for specific visualization of the different features of the posterior segment of the eye including retina, choroid and optic nerve head. Interestingly, infrared illumination at 940 nm reflects from the posterior sclera, retro-illuminating the choroidal vasculature without the need for invasive contrast agents. Abnormalities in retinal, choroidal or cerebral venous drainage and/or arterial flow may contribute to the microgravity ocular syndrome (MOS) in astronauts; hence this space technology may prove to be invaluable for diagnosing not only the health of our planet but also of the humans living on it and above it.

There is special synergy between NASA space instruments and medical devices, especially those that may be implanted in the human body. For example, in both cases instruments have to be small, typically have to consume little power and often have to operate in harsh environments. JPL has a long history in using this synergy to leverage from the technology developed for space missions for application in medical fields. In this talk, we discuss the general overlap of technological requirements in the medical field and space science. We will highlight some examples where JPL instrumentation and engineering has been transferred successfully.

We describe here the Early Detection Research Network (EDRN) for Cancer’s knowledge environment. It is an open source platform built by NASA’s Jet Propulsion Laboratory with contributions from the California Institute of Technology, and Giesel School of Medicine at Dartmouth. It uses tools like Apache OODT, Plone, and Solr, and borrows heavily from JPL’s Planetary Data System’s ontological infrastructure. It has accumulated data on hundreds of thousands of biospecemens and serves over 1300 registered users across the National Cancer Institute (NCI). The scalable computing infrastructure is built such that we are being able to reach out to other agencies, provide homogeneous access, and provide seamless analytics support and bioinformatics tools through community engagement.

Many challenges exist in understanding the human body as a whole, its adaptability, its resilience, its immunological response, its healing and regeneration power. New knowledge is usually obtained by exploring unique conditions and environments and space is one such variable. Primarily, these attributes have been studied in space for the purpose of understanding the effect of the space environment on long duration space travel. However a myriad of lessons learned have emerged that are important for terrestrial medicine problems such as cardiovascular changes, intracranial pressure changes, vision changes, reduced immunity, etc. For medical study purposes, the changes induced by the space environment on the human body are in general fast and predictable; they persist while in the space environment but also revert to the initial pre-flight healthy state upon return to Earth. This provides a unique cycle to study wellness and disease prediction as well as to develop more effective countermeasures for the benefit of people on earth. At a scientific level, the environment of space can be used to develop new lines of investigations and new knowledge to push the terrestrial state of the art (i.e. study of phase diagrams, identification of new system’s states, etc). Moreover, the specialized requirements for space medicine have driven advances in terrestrial medical technologies in areas such as monitoring, diagnostic, prevention and treatment. This talk will provide an overview of compelling examples in key areas of interest for terrestrial medical applications.

Imaging and Imaging Spectroscopy in the ultraviolet (UV), visible, and near infrared (NIR) part have a wide range of applications in astrophysics, planetary studies, heliophysics, commercial and medical diagnostics. A major part of system performance is contributed by the detector metrics. JPL-developed sensors developed using 2D-doping and custom coatings provide high performance across the UV, visible, and NIR region of the spectrum. Applying these 2-D surface and interface engineering technologies to detector structures with gain (e.g., Avalanche Photodiodes or APDs or electron multiplying charged-coupled devices or EMCCDs) enables photon-counting capabilities in solid state format rather than image tube detectors. Initially developed for space exploration applications for detecting faint signals in harsh environments while using low voltage and low power, these high efficiency detectors can be repurposed for medical applications that have much of the same requirements. For example, endogenous and induced fluorescence signatures in tissues as emergent diagnostic tools for abnormal tissue behaviors can potentially be detected using these detectors with high efficiency. Using JPL high efficiency imaging arrays, transient fluorescence signatures could be detected with small amount of stimulation. This brings the added advantage of precise fluorescence signature quantification, without damage to the host organism or tissue. In this work, we present fluorescence detection of phantom samples that serve as proof of concept demonstration while calibrating the instrument.

Over the past years we have worked on: (1) Viral-based approaches to non-invasive whole-brain cargo delivery: Genetically-encoded tools that can be used to visualize, monitor, and modulate mammalian neurons are revolutionizing neuroscience. These tools are particularly powerful in rodents and invertebrate models where intersectional transgenic strategies are available to restrict their expression to defined cell populations. However, use of genetic tools in non-transgenic animals is often hindered by the lack of vectors capable of safe, efficient, and specific delivery to the desired cellular targets. To begin to address these challenges, we have developed an in vivo Cre-based selection platform (CREATE) for identifying adeno-associated viruses (AAVs) that more efficiently transduce genetically defined cell populations. Our platform's novelty and power arises from the additional selective pressure imparted by a recovery step that amplifies only those capsid variants that have functionally transduced a genetically-defined, Cre-expressing target cell population. The Cre-dependent capsid recovery works within heterogeneous tissue samples without the need for additional steps such as selective capsid recovery approaches that require cell sorting or secondary adenovirus infection. As a first test of the CREATE platform, we selected for viruses that transduced the brain after intravascular delivery and found a novel vector, AAV-PHP.B, that is 40- to 90-fold more efficient at transducing the brain than the current standard, AAV9. AAV-PHP.B transduces most neuronal types and glia across the brain. We also demonstrate here how whole-body tissue clearing can facilitate transduction maps of systemically delivered genes. Since CNS disorders are notoriously challenging due to the restrictive nature of the blood brain barrier our discovery that recombinant vectors can be engineered to overcome this barrier is enabling for the whole field. With the exciting advances in gene editing via the CRISPR-Cas, RNA interference and gene replacement strategies, the availability of potent gene delivery methods provided by vectors such as our reported AAV-PHP.B is key to advancing the field of genome engineering. • Deverman BE, Pravdo P, Simpson B, Banerjee A, Kumar, S.R., Chan K, Wu WL, Yang B, Gradinaru V. Cre-Dependent Capsid Selection Yields AAVs for Global Gene Transfer to the Adult Brain. Nature Biotechnol. 2016 Feb 34(2):204-9. PMID: 26829320 • Yang B, Treweek JB, Kulkarni RP, Deverman BE, Chen CK, Lubeck E, Shah S, Cai L, Gradinaru V. Single-cell phenotyping within transparent intact tissue through whole-body clearing. Cell. 2014 Aug 14;158(4):945-58. PMCID: PMC4153367. (2) The mesopontine tegmentum, including the pedunculopontine and laterodorsal tegmental nuclei (PPN and LDT), provides major cholinergic inputs to midbrain and regulates locomotion and reward. To delineate the underlying projection-specific circuit mechanisms, we employed optogenetics to control mesopontine cholinergic neurons at somata and at divergent projections within distinct midbrain areas. Bidirectional manipulation of PPN cholinergic cell bodies exerted opposing effects on locomotor behavior and reinforcement learning. These motor and reward effects were separable via limiting photostimulation to PPN cholinergic terminals in the ventral substantia nigra pars compacta (vSNc) or to the ventral tegmental area (VTA), respectively. LDT cholinergic neurons also form connections with vSNc and VTA neurons; however, although photo-excitation of LDT cholinergic terminals in the VTA caused positive reinforcement, LDT-to-vSNc modulation did not alter locomotion or reward. Therefore, the selective targeting of projection-specific mesopontine cholinergic pathways may offer increased benefit in treating movement and addiction disorders. • Xiao C, Cho JR, Zhou C, Treweek BJ, Chan K, McKinney SL, Yang B, and Gradinaru V. Cholinergic Mesopontine Signals Govern Locomotion and Reward Through Dissociable Midbrain Pathways. Neuron 2016 Apr 20;90(2)33-47. PMCID: PMC4840478

The emerging field of bioelectronic medicine seeks methods for deciphering and modulating electrophysiological activity in the body to attain therapeutic effects at target organs. Current approaches to interfacing with peripheral nerves and muscles rely heavily on wires, creating problems for chronic use, while emerging wireless approaches lack the size scalability necessary to interrogate small-diameter nerves. Furthermore, conventional electrode-based technologies lack the capability to record from nerves with high spatial resolution or to record independently from many discrete sites within a nerve bundle. We recently demonstrated (Seo et al., arXiV, 2013; Seo et al., Neuron, 2016) "neural dust," a wireless and scalable ultrasonic backscatter system for powering and communicating with implanted bioelectronics. There, we showed that ultrasound is effective at delivering power to mm-scale devices in tissue; likewise, passive, battery-less communication using backscatter enabled high-fidelity transmission of electromyogram (EMG) and electroneurogram (ENG) signals from anesthetized rats. In this talk, I will review recent developments from my group and collaborators in this area.

Quantum cascade lasers (QCLs) are becoming mature infrared emitting devices that convert electrical power directly into optical power and generate laser radiation in the mid wave infrared (MWIR) and long wave infrared (LWIR) regions. These lasers operate at room temperature in the 3.5 μm to >12.0 μm region. QCLs operate at longer wavelengths into the terahertz region; however, these require some level of cryogenic cooling. Nonetheless, QCLs are the only solid-state sources that convert electrical power into optical power directly in these spectral regions. Three critical advances have contributed to the broad range of applications of QCLs, since their first demonstration in 1994 [1]. The first of these was the utilization of two phonon resonance for deexcitation of electrons from the lower lasing level [2]; the second is the utilization of epi-down mounting with hard solder of QCLs for practical applications [3]; and the third is the invention of nonresonant extraction for deexciting electrons from the lower laser level and simultaneously removing constraints on QCL structure design for extending high power room temperature operation to a broad range of wavelengths [4]. Although QCLs generate CW radiation at room temperature at wavelengths ranging from ~3.5 μm to <12.0 μm, two spectral regions are very important for a broad range of applications. These are the first and the second atmospheric transmission windows from ~3.5 μm to ~ 5.0 μm and from ~8.0 μm to ~12.0 μm, respectively. Both of these windows (except for the spectral region near 4.2 μm, which is dominated by the infrared absorption from atmospheric carbon dioxide) are relatively free from atmospheric absorption and have a range of applications that involve long distance propagation.

In this presentation we will review our most recent results on development of Quantum Cascade Lasers (QCLs) for analytical and industrial applications. QCLs have demonstrated the capability to cover the entire range of Mid-IR, Far-IR, and THz wavelengths by skillful tuning of the material design and composition and by use of intrinsic material properties via a set of techniques collectively called “bandgap engineering”. The use of MOCVD, pioneered on industrial scale by AdTech Optics, has enabled the deployment of QCL devices into a diverse range of environments and applications. QCLs can be tailored to the specific application requirements due to their unprecedented flexibility in design and thanks to the leveraging of well-known III-V fabrication technologies inherited from the NIR domain. Nevertheless, several applications and new frontiers in R and D need the constant support of new developments in device features, capabilities, and performances. We have developed a wide range of devices, from high power, high efficiency multi-mode sources, to narrow-band, single mode devices with low-power consumption, and from non-linear, multi-wavelength generating devices to broadband sources and multi-emitter arrays. All our devices are grown and processed using MOCVD technology and allow us to attain competitive performances across the whole mid-IR spectral range. This talk will present an overview of our current achievements. References 1. M. Troccoli, “High power emission and single mode operation of quantum cascade lasers for industrial applications”, J. Sel. Topics in Quantum Electron., 21 (6), 1-7 (2015). Invited Review. 2. Seungyong Jung, Aiting Jiang, Yifan Jiang, Karun Vijayraghavan, Xiaojun Wang, Mariano Troccoli, and Mikhail A. Belkin, “Broadly Tunable Monolithic Terahertz Quantum Cascade Laser Sources”, Nature Comm. 5, 4267 (2014).. 3. Mariano Troccoli, Arkadiy Lyakh, Jenyu Fan, Xiaojun Wang, Richard Maulini, Alexei G Tsekoun, Rowel Go, C Kumar N Patel, “Long-Wave IR Quantum Cascade Lasers for emission in the λ = 8-12μm spectral region”, Opt. Mat. Expr., 3 (9), 1546-1560 (2013).

5.6μm quantum cascade lasers based on Al_0.78In_0.22As/In_0.69Ga_0.31As active region composition with measured pulsed room temperature wall plug efficiency of 28.3% are reported. Injection efficiency for the upper laser level of 75% was measured by testing devices with variable cavity length. Threshold current density of 1.7kA/cm² and slope efficiency of 4.9W/A were measured for uncoated 3.15mm x 9µm lasers. Threshold current density and slope efficiency dependence on temperature in the range from 288K to 348K can be described by characteristic temperatures T₀~140K and T₁~710K, respectively. Pulsed slope efficiency, threshold current density, and wallplug efficiency for a 2.1mm x 10.4µm 15-stage device with the same design and a high reflection-coated back facet were measured to be 1.45W/A, 3.1kA/cm² , and 18%, respectively. Continuous wave values for the same parameters were measured to be 1.42W/A, 3.7kA/cm² , and 12%. Continuous wave optical power levels exceeding 0.5W per millimeter of cavity length was demonstrated. When combined with the 40-stage device data, the inverse slope efficiency dependence on cavity length for 15-stage data allowed for separate evaluation of the losses originating from the active region and from the cladding layers of the laser structure. Specifically, the active region losses for the studied design were found to be 0.77cm^-1, while cladding region losses – 0.33cm^-1. The data demonstrate that active region losses in mid wave infrared quantum cascade lasers largely define total waveguide losses and that their reduction should be one of the main priorities in the quantum cascade laser design.

For high speed high mobility devices, the conventional notion of the electron mobility determining the device speed no longer applies. The ballistic transport plays the dominant role. The electron response becomes faster with the mobility increase in a limited range of relatively low mobility values. With a further increase in the electron mobility, first the plasmonic ringing determines the characteristic response time and then the viscous transport becomes dominant for small feature sizes. The minimum response time and the maximum device modulation frequency correspond to the subpicosecond and terahertz ranges, respectively. The recent experiments of the FET switching using femtosecond optical laser pulses are in good agreement with the predicted sub picosecond switching times and demonstrate a larger sensitivity enhancement due to the constructive interference of the impinging THz pulse and the optical pulse field rectified by the device nonlinearity.

As for other imaging sensor markets, whatever is the technology, the commercial spread of terahertz (THz) cameras has to fulfil simultaneously the criteria of high sensitivity and low cost and SWAP (size, weight and power). Monolithic silicon-based 2D sensors integrated in uncooled THz real-time cameras are good candidates to meet these requirements. Over the past decade, LETI has been studying and developing such arrays with two complimentary technological approaches, i.e. antenna-coupled silicon bolometers and CMOS Field Effect Transistors (FET), both being compatible to standard silicon microelectronics processes. LETI has leveraged its know-how in thermal infrared bolometer sensors in developing a proprietary architecture for THz sensing. High technological maturity has been achieved as illustrated by the demonstration of fast scanning of large field of view and the recent birth of a commercial camera. In the FET-based THz field, recent works have been focused on innovative CMOS read-out-integrated circuit designs. The studied architectures take advantage of the large pixel pitch to enhance the flexibility and the sensitivity: an embedded in-pixel configurable signal processing chain dramatically reduces the noise. Video sequences at 100 frames per second using our 31x31 pixels 2D Focal Plane Arrays (FPA) have been achieved. The authors describe the present status of these developments and perspectives of performance evolutions are discussed. Several experimental imaging tests are also presented in order to illustrate the capabilities of these arrays to address industrial applications such as non-destructive testing (NDT), security or quality control of food.

We discuss an effective method for the detection and identification of substances using a high noisy THz signal. In order to model such a noisy signal, we add to the THz signal transmitted through a pure substance, a noisy THz signal obtained in real conditions at a long distance (more than 3.5 m) from the receiver in air. The insufficiency of the standard THz-TDS method is demonstrated. The method discussed in the paper is based on time-dependent integral correlation criteria calculated using spectral dynamics of medium response. A new type of the integral correlation criterion, which is less dependent on spectral characteristics of the noisy signal under investigation, is used for the substance identification. To demonstrate the possibilities of the integral correlation criteria in real experiment, they are applied for the identification of explosive HMX in the reflection mode. To explain the physical mechanism for the false absorption frequencies appearance in the signal we make a computer simulation using 1D Maxwell's equations and density matrix formalism.

We propose also new method for the substance identification by using the THz pulse frequency up-conversion and discuss an application of the cascade mechanism of molecules high energy levels excitation for the substance identification.

This paper discusses the effects of gain drift and variation often referred to as “ΔG/G” in CMOS mm-wave radiometers as well as the techniques employed to suppress its effects on radiometric and passive imaging instruments. The paper presents a demonstration of a CMOS Dicke-switched radiometer which uses correlated double sampling to eliminate gain variation, and investigates the contributions of the ΔG/G behavior to the demonstrated instrument’s measured NEΔT through experimental approaches. Finally the paper describes how the discrepancies between calculation and measurement can be attributed to limited performance of Dicke switches in silicon and how further development is needed to truly hit useful NEΔT resolutions in the 1°K range.

Progress towards the development of a longwave infrared quantum cascade laser (QLC) based standoff surface contaminant detection platform is presented. The detection platform utilizes reflectance spectroscopy with application to optically thick and thin materials including solid and liquid phase chemical warfare agents, toxic industrial chemicals and materials, and explosives. The platform employs an ensemble of broadband QCLs with a spectrally selective detector to interrogate target surfaces at 10s of m standoff. A version of the Adaptive Cosine Estimator (ACE) featuring class based screening is used for detection and discrimination in high clutter environments. Detection limits approaching 0.1 μg/cm² are projected through speckle reduction methods enabling detector noise limited performance.

The design, build, and validation of a breadboard version of the QCL-based surface contaminant detector are discussed. Functional test results specific to the QCL illuminator are presented with specific emphasis on speckle reduction.

We present recent results on development of swept external cavity quantum cascade lasers (ECQCLs) for rapid and precise measurements of trace gases. Rapid tuning of a swept-ECQCL over its entire tuning range at rates up to 100 Hz and a spectral resolution of <0.2 cm^-1 provides an important capability for detection of gas mixtures in transient sources such as chemical plumes. We present examples of using the swept-ECQCL for quantitative measurements of multicomponent gas-phase mixtures in turbulent plumes for standoff detection applications.

Techniques which apply tunable quantum cascade lasers (QCLs) for target illumination suffer from fluctuations of the laser beam direction. This manuscript describes a method to stabilize the beam direction by using an active feedback loop. This approach corrects and stabilizes the laser pointing direction using the signal from a 4-element photo sensor as input to control an active 2 dimensional Galvo mirror system. Results are presented for measurements using known perturbations as well as actual mode hops intrinsic to external cavity QCL during wavelength tuning.

Integrated optic notch filters are key building blocks for higher-order spectral filter responses and have been demonstrated in many technology platforms from dielectrics (such as Si₃N₄) to semiconductors (Si photonics). Photonic-assisted RF processing applications for notch filters include identifying and filtering out high-amplitude, narrowband signals that may be interfering with the desired signal, including undesired frequencies detected in radar and free-space optical links. The fundamental tradeoffs for bandwidth and rejection depth as a function of the roundtrip loss and coupling coefficient are investigated along with the resulting spectral phase response for minimum-phase and maximum-phase responses compared to the critical coupling condition and integration within a Mach Zehnder interferometer. Based on a full width at half maximum criterion, it is shown that maximum-phase responses offer the smallest bandwidths for a given roundtrip loss. Then, a new role for passive notch filters in combination with high-speed electro-optic phase modulation is explored around narrowband phase-to-amplitude demodulation using a single ring operating on one sideband. Applications may include microwave processing and instantaneous frequency measurement (IFM) for radar, space and defense applications.

Current micro-bolometers are broadband detectors and tend to absorb a broad window of the IR spectrum for thermal imaging. Such systems are limited due to their lack of sensitivity to blackbody radiation, as well as the inability to spectrally discern multiple wavelengths in the field of view for hyperspectral imaging (HSI). As a result, many important applications such as low concentration chemical detection cannot be performed. One solution to this problem is to employ a system with thermoelectrically cooled or liquid nitrogen cooled sensors, which can lead to higher sensitivity in detection. However, one major drawback of these systems is the size, weight and power (SWaP) issue as they tend to be rather bulky and cumbersome, which largely challenges their use in unmanned aerial vehicles. Further, spectral filtering is commonly performed with large hardware and moving gratings, greatly increasing the SWaP of the system. To this point, Lumilant’s effort is to develop wavelength selective uncooled IR filters that can be integrated onto a microbolometer, to exceed the sensitivity imposed by the blackbody radiation limit. We have demonstrated narrowband absorbers and electrically tunable filters addressing the need for low-SWaP platforms.

LiFePO₄ is a highly researched cathode material that serves as an alternative material for traditional commercial lithiumion batteries such as LiCoO₂. Currently, there are a number of different methods to synthesize LiFePO₄ including: hydrothermal, solid state, spray pyrolysis, and coprecipitation. Our proposed method has the potential to provide an ecologically friendly and economically competitive way to synthesize LiFePO₄ by utilizing ionic liquid and water, as a composite synthesis medium. The addition of water to ionic liquid can be beneficial as it can act as a mineralizer to bring insoluble precursors to form LiFePO₄ seed crystals. Furthermore, this method provides the possibility of recycling the ionic liquid for repeated synthesis processes. In this work, we study the effects of ionic liquid to water ratio on the crystallinity and morphology of the synthesized material. Our group was able to conclude a reaction medium utilizing a ratio of equal parts of 1-ethyl-3-methyl imidazolium trifluoromethane sulfonate (EMIM Otf) and water, or a slightly favored ionic liquid ratio, increases the efficacy of the synthesis route. Crystallinity and purity was determined by X-ray diffraction (XRD), scanning electron microscopy (SEM) was used to determine morphology and crystal sizes, and energy dispersion spectroscopy (EDX) was used for elemental analysis.

Aluminum nitride (AlN) is a piezoelectric material often used as thin film in SAW/BAW devices. Furthermore, there is an increasing interest in its use for energy harvesting applications. Despite it has a relatively low piezoelectric coefficient, it is a suitable choice for energy harvesting applications and due to its low dielectric constant and good mechanical properties. In addition, it is a lead-free material. The films were deposited by reactive pulsed magnetron sputtering using the Double Ring Magnetron DRM 400. This sputter source together with suitable powering and process control allows depositing piezoelectric AlN very homogeneously on 8” substrates with deposition rates of up to 200 nm/min. With the developed technology, film thicknesses of several ten microns are technically and economically feasible. Moreover, by adjusting process parameters accordingly, it is possible to tune properties, like film stress, to application specific requirements. Additionally, it is known that the doping of AlN with Scandium results in a significantly increased piezoelectric coefficient. The influence of process parameters and Sc concentration on film properties were determined by piezometer, pulse echo, SEM, XRD, EDS and nanoindentation measurements. Energy harvesting measurements were done using an electromechanical shaker system for the excitation of defined vibrations and a laservibrometer for determination of the displacement of the samples. The generated power was measured as function of electric load at resonance. An rms power of up to 140μW using AlN films and of 350μW using AlScN films was generated on Si test pieces of 8x80mm². Furthermore, energy harvesting measurements using manually bended steel strips of 75x25mm² coated with AlScN were carried out as well. When using only a single actuation, energy of up to 8μJ could be measured. By letting the system vibrate freely, the damped vibration at resonance 50Hz resulted in a measured energy of 420μJ.

Dense (1−x)KNbO₃-x(Ba_1/2Bi_1/2)(Zn_1/2Nb_1/2)O₃ (0 ≤ x ≤ 0.25) ceramics were prepared by the solid state reaction method. X-ray diffraction data show the average crystal structure to evolve from orthorhombic at x = 0 to pseudocubic at x = 0.25. Raman spectroscopy suggests the absence of polar order for x ≥ 0.25 ceramics. Polarisation versus electrical field measurements show a continuous decrease in the spontaneous polarisation with increasing x. Electrical-field-induced strain measurements reveal a piezoelectric-to-electrostrictive crossover. An electrostriction coefficient of 0.043 m⁴/C² was measured for x = 0.15.

In chemical analysis, there are numerous applications requiring results in (near) real-time and measurement on-site. In many remote or not-easily-accessible locations, measuring analytical systems (e.g., sensors, microinstruments) require energy autonomy for unattended operation over prolonged periods of time. In this paper, energy harvesting and energy scavenging approaches that may be used for this purpose are critically evaluated and two examples of current research are briefly described. One involves energy harvested from a water-stream (by taking advantage of the electrochemical potential difference between the soil adjacent to the stream and the surface water of the stream) and the other, using a self-powering detector of visible light developed on a flexible polymeric substrate.