This PDF file contains the front matter associated with SPIE Proceedings Volume 10982, including the Title Page, Copyright information, Table of Contents, Author and Conference Committee lists.

Si Nanowires (NWs) have been commonly fabricated via expensive synthesis processes on particular substrates without some critical features such as mechanical flexibility and optical transparency. Lack of these features limit the applications in their potential research area. In this work, we demonstrated that ordered and disordered single crystalline silicon nanowires can be transferred from Si wafer onto a wide range of alien substrates while preserving their original order and alignment on the mother substrate. Vertically well-aligned Si NWs with different lengths and densities were successfully transferred on Ag-pre-coated glasses, transparent-conductive-oxides and metal foils (Cu), which enable ohmic contact formation between Si NWs and the employed substrates, which is essential for the fabrication of electronics and opto-electronics devices. This approach offers promise to construct low-cost device fabrication with highly crystalline semiconductor materials, which is a crucial step for the realization of next generation highly efficient core-shell solar cells. As an illustrative application, the transferred disordered Si NWs were then decorated with a thin layer of CZTS for the fabrication of a third generation solar cell, which has been exhibited the best power conversion efficiency so far in a device constructed with the same material combination.

Spin-orbit interaction has offered a versatile platform in the study of novel physical phenomena in condensed matters. It enables charge-to-spin conversion for implementing functional spintronic devices, and can even change the band topology when it is strong enough, giving rise to exotic quantum states of matters such as topological insulators (TIs). Here, we demonstrate functional topological spintronic devices employing multiple TI-based material structures. First, we achieved current-driven magnetization switching in TI/ferrimagnet heterostructures at room temperature. A low switching current density and a fast switching speed is demonstrated in this system, due to the highly efficient topological surface states and the fast spin dynamics near compensation point in ferrimagnets. Besides, the magnetization switching can be even realized without the assist of external magnetic field in a magnetic TI/antiferromagnet system, making it a promising candidate for applicable spintronic memory devices. Finally, when interfacing a quantum anomalous Hall insulator TI with Nb, an s-wave superconductor, the signature of chiral Majorana edge modes is observed as the half-quantized plateaus of e²/2h in conductivity. The experimental evidence of Majorana Fermions holds promise for error-tolerant topological quantum computation robust against external local perturbations.

The application of topology in optics has led to a new paradigm in developing photonic devices with robust properties against disorder. Although significant progress on topological phenomena has been achieved in the classical domain, the quantum regime has remained unexplored. In this talk, I discuss two recent developments in the quantum regime: (1) We demonstrate a strong interface between single quantum emitters and topological photonic states. Our approach creates robust counter-propagating edge states at the boundary of two distinct topological photonic crystals. We demonstrate the chiral emission of a quantum emitter into these modes and establish their robustness against sharp bends. This approach may enable the development of quantum optics devices with built-in protection, with potential applications in quantum simulation and sensing. (2) Spontaneous parametric processes such as down-conversion (SPDC) and four-wave mixing (SFWM) have long been the common sources of quantum light, for instance, correlated photon pairs and heralded single photon. These spontaneous processes are mediated by vacuum fluctuations of the electromagnetic field. Therefore, by manipulating the electromagnetic mode structure, for example, using nanophotonic systems, one can engineer the spectrum of generated photons. However, such manipulations are susceptible to fabrication disorders which are ubiquitously present in nanophotonic systems. We demonstrate a topological source of correlated photon pairs where the spectrum of generated photons is robust against fabrication disorder. Specifically, we use the topological edge states to achieve an enhanced and robust generation of photons using SFWM and show that they outperform their topologically-trivial counterparts. We show the non-classical nature of intensity correlations between generated photons and the anti-bunching of photons using conditional measurements. Our results could pave the way for topologically robust quantum photonic devices.

The main objective of our research is to integrate advanced 3D/4D bioprinting techniques with novel biologically inspired nano or smart inks to fabricate the next generation of complex tissue constructs (such as vascularized tissue, neural tissue and osteochondral tissue). The 3D/4D bioprinting techniques offer great precision and control of the internal architecture and outer shape of a scaffold, allowing for close recapitulation of complicated structures found in biological tissues. Specifically, the term “4D” refers to the time-dependent dynamic process triggered by specific stimulation according to predesigned requirements. Our pioneering work in designing innovative 4D bioprinting smart biomaterials has shown huge promise for various tissue regenerative applications. Recently, a 4D bioprinted reprogrammable architecture using light-induced graded internal stress was created for the first time to achieve a 4D+ or 5D concept. Using this novel dual 4D technique, a proof-of-concept nerve guidance conduit was demonstrated with human bone marrow mesenchymal stem cells which were readily differentiated into neural cell types on the graphene hybrid 4D construct providing outstanding multifunctional characteristics for nerve regeneration. In addition, we designed and synthesized biologically inspired nanomaterials (i.e., self-assembly materials, and conductive carbon nanomaterials) as bioinks. Through 3D/4D bioprinting in our lab, a series of biomimetic vascularized and neural tissue scaffolds were successfully fabricated. Our results show that these bioprinted nano or smart scaffolds have not only improved mechanical properties but also excellent cytocompatibility properties for enhancing various stem cell growth and differentiation, thus promising for complex tissue/organ regeneration.

Herein, we describe a yeast-laden hydrogel ink that can be printed using a direct-write 3D printer and used for the production of a peptide. A poly(alkyl glycidyl ether)-based triblock copolymer was synthesized and formulated as a hydrogel that was characterized via rheometry to evaluate the printability of the hydrogel ink. An engineered yeast strain with an upregulated α-factor production pathway was incorporated into the hydrogel ink and 3D printed. The immobilized yeast cells exhibited adequate viability of 87.5% within the hydrogel. The production of the up-regulated α- factor was detected using a detecting yeast strain and quantified at 268 nM (s = 34.6 nM) over 72 h. The reusability of these systems was demonstrated by immersion of the yeast-laden hydrogel lattice in fresh SC media and confirmed by the detection of similar amounts of up-regulated α-factor 259 nM (s = 45.1 nM). These yeast-laden materials represent an attractive opportunity for whole-cell catalysis of other high-value products in a sustainable and continuous manner.

Recent advances in 3D printing have enabled the creation of novel 3D constructs and devices with an unprecedented level of complexity, properties, and functionalities. In contrast to manufacturing techniques developed for mass production, 3D printing encompasses a broad class of fabrication technologies that can enable 1) the creation of highly customized and optimized 3D physical architectures from digital designs; 2) the synergistic integration of properties and functionalities of distinct classes of materials to create novel hybrid devices; and 3) a biocompatible fabrication approach that facilitates the creation and co-integration of biological constructs and systems. Developing the ability to 3D print various classes of materials possessing distinct properties could enable the freeform generation of active electronics in unique functional, interwoven architectures. Here we are developing a multiscale 3D printing approach that enables the integration of diverse classes of materials to create a variety of 3D printed electronics and functional devices with active properties that are not easily achieved using standard microfabrication techniques. In one of the examples, we demonstrate an approach to prolong the gastric residence of wireless electronics to weeks via multi-material three-dimensional design and fabrication. The surgical-free approach to integrate biomedical electronics with the human body can revolutionize telemedicine by enabling a real-time diagnosis and delivery of therapeutic agents.

The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed organ models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-like tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured.

We have been fabricating nanoscale vacuum tubes for radiation immune electronics. Vacuum is superior to any semiconductor in terms of electron transport and we have combined the best of vacuum and silicon technology to fabricate surround gate nanoscale vacuum transistors on 8 " wafers with a channel dimension of 50 nm. These vacuum transistors, operating at a drive voltage of only 2 V, which is remarkable for vacuum devices, have the potential for THz electronics and several other applications. Exposure to gamma and protons does not impact the drive current or threshold voltage. This talk also will also discuss our printed electronics efforts for In Space Manufacturing which involves printing gas and biosensors, batteries and supercapacitors, and tribolectric power generators. The author acknowledges contributions from Jinwoo Han, Dongil Moon, Daniel Kim, Jessica Koehne, Myeonglok Seol, Sunjin Kim and Niki Werkheiser.

A number of new instrument capabilities are currently in maturation for future in situ use on planetary science missions. Moving beyond the impressive in situ instrumentation already operating in planetary environments beyond Earth will enable the next step in scientific discovery. The approach for developing beyond current instrumentation requires a careful assessment of science-driven capability advancement. To this end, two examples of instrument technology development efforts that are leading to new and important analytical capabilities for in situ planetary science will be discussed: (1) an instrument prototype enabling the interface between liquid separation techniques and laser desorption/ionization mass spectrometry and (2) an addressable excitation source enabling miniaturized electron probe microanalysis for elemental mapping of light and heavy elements.

Measuring Earth's energy budget from space is an essential ingredient for understanding and predicting Earth's climate. We have demonstrated the use of vertically aligned carbon nanotubes (VACNTs) as photon absorbers in broadband radiometers own on the Radiometer Assessment using Vertically Aligned Nanotubes (RAVAN) 3U CubeSat. VACNT forests are some of the blackest materials known and have an extremely at spectral response over a wide wavelength range. The radiation measurements are made at both shortwave, solar-reflected wavelengths and in the thermal infrared. RAVAN also includes two gallium phase-change cells that are used to monitor the stability of RAVAN's radiometer sensors. RAVAN was launched November 11, 2016, into a nearly 600-km sun-synchronous orbit and collected data over the course of 20 months, successfully demonstrating its two key technologies. A 3-axis controlled CubeSat bus allows for routine solar and deep-space attitude maneuvers, which are essential for calibrating Earth irradiance measurements. Funded by the NASA Earth Science Technology Office, RAVAN is a pathfinder to demonstrate technologies for the measurement of Earth's radiation budget that have the potential to lower costs and enable new measurement concepts. In this paper we report specifically on the VACNT growth, post-growth modification, and pre-launch testing. We also describe the novel door mechanism that houses the gallium black bodies.

Optical phased arrays borrow concepts from radar phased array science and technology to provide non-mechanical beam steering of electromagnetic radiation in the far field. Like radar phased arrays, this is achieved through controlling the relative phases of individual emitters on the device. However, since the device size scales with the wavelength of the electromagnetic signal, moving from radar to optical signals involves a reduction in size by more than 4 orders of magnitude. As a result, optical phased arrays can be created on a compact, chip-scale platform. This is particularly of interest for inter-spacecraft communications where high bandwidth optical signals can be communicated in free-space from one location to another. Providing this functionality with a low SWaP, chip-scale device is crucial for space applications. Recently, many chip-scale optical phased arrays have been developed to provide non-mechanical beam steering of light at optical frequencies, including many demonstrations at the telecommunications wavelength of 1550 nm. Here we will discuss the existing demonstrations as well as highlight the tradeoffs between different designs. We will highlight the importance of spacing the emitters at a technologically challenging pitch that is half the operational wavelength in order to avoid the many negative effects of grating lobes, including power loss, steering range limitation, and the opportunities they provide for eavesdropping.

A collaborative research effort between the Johns Hopkins Applied Physics Laboratory (JHU/APL) and the Space Physics and the Atmospheric Research Center (SPARC), located at the United States Air Force Academy (USAFA), has resulted in the development of a suite of miniaturized electrostatic analyzers (ESAs). This research effort is currently on the development of fifth generation charged particle detectors which include the Flat Plasma Spectrometer (FlaPS) and Canary, which have flight heritage, and the Energetic Electrostatic Analyzer (EESA) which is currently at the laboratory prototype stage. The implementation of microelectromechanical systems (MEMS) technology to fabricate the silicon wafer sensor heads used in the ESA design has enabled the development of plasma spectrometers that are low mass and consume little power, while still maintaining the performance capability of current state-of-the art instruments. This shift towards the aggressive miniaturization of charged particle detectors, coupled with the increasing capability of ever smaller satellite vehicles, has led to an increase in science mission opportunities. Through the course of this research program the cadets working at the SPARC have been engaged across a broad range of academic disciplines such as physics, computer science, astronautics, electrical and mechanical engineering. This program has allowed undergraduate students to participate in advanced research as they develop into the next generation of scientists and engineers.

Advanced technologies are transforming the information environment and allowing individuals and groups unprecedented opportunities to share ideas, actions, emotions, conflicts, and activities. While this enables social groups to expand their membership in the global online community, it also allows scientists to use the social media environment as a real-world laboratory to study emerging behaviors in this space. For military analysts, this environmental laboratory provides an opportunity to study communities in advance of deployments to foreign soil. In the same way that military logisticians would study physical terrain to plan for equipment, analysts can observe activities in the information environment to plan for negotiations in the social terrain. This presentation will discuss key concepts for modeling the social terrain and will identify promising AI techniques for each. Key concepts will include Human, Information, Interpretation, and Influence considerations. AI technologies will be discussed for each of the following social terrain considerations: Human, Information, Interpretation, and Influence. Together, these elements form the underpinning science of sensemaking within the new information environment. The Human Systems Community of Interest (HS COI) within the US Department of Defense (US DOD) is exploring how to jointly establish effective capabilities in this sphere for rapid exploitation at the tactical operational levels. This paper will address the priorities and future needs of this Joint research effort and will explore technical challenges that face the transition of research results to system-level applications.

Coronary artery blockage is a vital issue of occurring heart attack. There are several techniques to diagnose coronary artery blockage as well as other type heart diseases. In this paper, we discuss about computerized full automated model for the detection of coronary artery blockage using image processing techniques so that the system does not have to rely on human’s inspection. Using efficient image processing technique and AI algorithms, the system allows a faster and reliable detection of the narrowing area of the wall of coronary arteries due to the condensation of different artery blocking agents. The system requires a 64-slice/128-slice CTA image as input. After the acquisition of the desired input image, it goes through several steps to determine the region of interest. This research proposes a two stage approach that includes the pre-processing stage and decision stage. The pre-processing stage involves common image processing strategies while the decision stage involves the extraction and calculation of features to finally determine the intended result using AI algorithms. This type of model effectively enables early detection of coronary artery blockage through segmentation, quantification, identification of degree of blockage and risk factors of heart attack.

Current report consider development of a unified MC-based simulation platform for needs of Biomedical Optics and its practical use in the creation of novel Optical Diagnostics, Imaging and Sensing modalities aided by the Artificial Intelligence (AI) methods. It will be demonstrated how the developed MC platform can be utilized in the generation of validated lookup tables/labeled data sets and subsequent training of several configurations of Artificial Intelligence (AI) based methods for the purpose of real-time estimation of certain specific tissue properties of interest such as distributions of melanin, blood, oxygenation, etc. The prototypes of lightweight AI-empowered sensing solutions that could potentially be shrank onto a smartphone/wearable device form-factor will be presented and their performance will be compared with traditional spectroscopy-based methods using phantom and in vivo experimental data obtained during clinical studies.

Phase change materials are increasingly becoming important functional materials for applications in emerging integrated optics. Since the demonstration of a photonic phase change memory device in 2015, several new applications i this area have emerged ranging from lossless routing to on-chip photonics synapses. More recently the use of these materials in unconventional computing has seen an emerging interest, especially in the areas of optical abacuses and other forms of brain-inspired computing. There have also been advances in non-von Neumann approaches to carry out large-scale matrix multiplications. In this talk, I shall cover these topics and present a future view of these materials, not only in computation, but also in displays and holographic projections.

Optical phase change materials (O-PCMs) are a unique class of materials which exhibit extraordinarily large optical property change (e.g. refractive index change > 1) when undergoing a solid-state phase transition. Traditional O-PCMs suffer from large optical losses even in their dielectric states, which fundamentally limits the performance of optical devices based on the materials. To resolve the issue, we have recently demonstrated a new O-PCM Ge-Sb-Se-Te (GSST) with broadband low loss characteristics. In this talk, we will review an array of reconfigurable photonic devices enabled by the low-loss O-PCM, including nonvolatile waveguide switches with unprecedented low-loss and high-contrast performance, free-space light modulators, bi-stable reconfigurable metasurfaces, and transient couplers facilitating waferscale device probing and characterizations.

Phase-change electronic memory utilizes the electric field-induced reversible structural change in chalcogenide materials to switch between crystalline and amorphous phases to store information, which is fast and non-volatile. In spite of extensive investigations of the field-induce phase-change phenomena, the underlying mechanisms are quite complex and their elucidation requires the continued development of new experimental tools. Our group has demonstrated that conventional understanding of melt-quench based amorphization process needs to be revisited. While working with single-crystalline nanowires which due to their long lengths do not typically reach high temperatures required for conventional melting of the material, we realized that alternate pathways for crystal-amorphous transformation can exist. Furthermore, nanowires due to their cylindrical geometry, conventional melting should lead to the formation of an amorphous shell around the crystalline core, which cannot explain the abrupt resistance switching as observed. We have shown that crystal-amorphous transformation in phase-change materials can be achieved through a subtle and ad lower energy costing defect-based pathway. This pathway involves creation of extended defects such as anti-phase boundaries (APBs) in GeTe and dislocations in Ge2Sb2STe5, which migrate and accumulate at a region of local inhomogeneity creating a defect template. The formation of APBs leads to polar domain inversion as revealed by optical second-harmonic generation polarimetry. Due to the accumulation of defects locally, the material first undergoes a metal-to-insulator transition followed by a structural collapse leading to amorphization without conventional melting. We utilized this understanding to pre-induce defects in the crystalline phase via controlled ion bombardment to engineer carrier localization and enhance carrier-lattice coupling in order to efficiently extract work required to introduce bond-distortions necessary for amorphization from input electrical energy itself. We demonstrated that such a strategy shows 100X improvement in amorphization current densities compared to the melt-quench strategy. The existence of multiple resistance states along with ultra-low power switching makes this approach promising for low power memory and neuromorphic computation. We will also discuss our efforts to integrate defect-engineered phase change nanowires in integrated photonics platforms for designing the next generation of reconfigurable photonic devices. References [1] S.W.Nam et al., Science 2012, 336, 1561. [2] P.Nukala et al., Nano Lett. 2014, 14, 2201. [3] P. Nukala et al., Nature Communications, 2016, 7, 10482. [4] P. Nukala et al., Nature Communications, 2017, 8, 15033.

In the field of nanophotonics, nanostructures for active tuning of optical phase has emerged as a versatile platform for novel types of spatial light modulators, integrated optical devices, and ultrahigh resolution display pixels. Tuning of optical wavefronts with phase change materials (PCMs) such as Ge2Sb2Te5 can manipulate an actively-tuned artificial wavefront with the convergence of metasurface design technology. Various light phenomena such as perfect absorbers, beaming angle tweezers, and arbitrary phase profile generations for optical hologram applications have been achieved with active platform by adopting PCMs into optical nanostructures. The presentation will also introduce some plasmonic applications such as optical switches and directional launchers, which can be operated by phase change of Ge₂Sb₂Te₅.

This paper reports tunable integrated photonic devices in the visible and near-infrared (NIR) regions using a phase change material, Germanium Telluride (GeTe), within sub-wavelength layered optical cavity structures. GeTe exhibits two distinct index of refraction values at its amorphous and crystalline states in this spectral range. Utilizing this property, we demonstrate a multi-color filter working in visible range (400 nm-750 nm), achieving four colors through novel optical and thermal engineering of a thin film stack that includes two GeTe layers with only a single integrated joule heater element. Specifically, ultra-thin GeTe films were sandwiched between a bottom metallic mirror and a top high-index dielectric (titanium dioxide). It is shown that the crystallization temperature (Tx) of GeTe is dependent on the film thickness when less than ~20 nm. The refractive index of GeTe only changes significantly in the NIR region when it undergoes phase transitions when heated. To enhance the color contrast, a 250-nm thick silicon dioxide layer is placed under GeTe to create an optical cavity between GeTe and a bottom metal reflector. Using this optimized design, the tunable color filter shows four distinct colors using the integrated heater. In addition to a color filter, we demonstrate an electrically tunable multi-mode optical shutter in near infrared range of 1.1 μm and 800 nm with more than 20 dB modulation depth. The low static power consumption of these devices achieved through reliable memory-base phase transitioning of GeTe makes them prime candidates for a number of portable consumer electronic applications.

A spatial light modulator (SLM) is a key device that enables a coded aperture imaging technique to extract spectral signature for remote detection and identification without platform motion. The SLMs offer a way to carry out spectral imaging with reconfigurability, which allows signature detection against a spectrally cluttered background. Liquidcrystal display (LCD) arrays and digital micro-mirror devices (DMDs) are used to implement the spatial light modulators, and there are shortcomings in infrared (IR) applications. Here, we report on a new solid-state SLM modulator device operating in the infrared range with SbTe-based phase change material. The SLM leverages a dramatic change (<2) in refractive index of SbTe phase change material within most of the IR bands, depending on their phase (amorphous versus crystalline).

The speaker will provide an overview of the areas within IIOT that benefit from, or are enabled by, unobtrusive form factors. Examples will range from simple asset management tools to condition-based maintenance platforms and closed-loop distributed control systems for transportation infrastructure and safety. The speaker will describe FHE manufacturing technologies and how they enable low profile form factors and remote sensing platforms including next generation complexity in "intelligent edge devices" to the use of thinned, flexible FPGA's for neuromorphic data processing architectures. The speaker will present perspectives on looming roadblocks and necessary manufacturing developments that must be solved to scale FHE solutions to the millions of units needed for widescale deployment. Finally he will give an overview of what is being done to address these roadblocks through public private partnerships and collaborative investments, specifically, he will outline the creation of NextFlex, America’s Flexible Hybrid Electronics Institute (established by the Office of the Secretary of Defense and the Air Force Research Labs in 2015) and provide an update on the growing FHE manufacturing ecosystem and how they overcome manufacturing roadblocks collaboratively.

Flexible Hybrid Electronic (FHE) systems are being evaluated for aircraft production and test applications that will interact with factory Internet of Things (IoT) architectures that are being implemented for efficiency improvements in production facilities. Deployment of wireless systems is an enabler for a reduction is wires and cables for test and production which translates to simpler integration and reduced test planning and execution. Deployment in the production environment enables real time monitoring of assets for location and health and provides ubiquitous data collectors to provide meaningful data analytic solutions. The information presented will cover FHE developments on four NextFlex consortium funded efforts and the current status of a IoT enabled sensor system. The usefulness of the new technology for acquisition of data that is useful for aircraft ground operations and sensor systems that enable production efficiencies will be addressed.

Sensors are ubiquitous in modern manufacturing operations, and they generate significant quantities of data. With the advent of low cost, readily available broad band communication and virtually infinite cloud storage, many of the old stigmatisms related to taking data from a plant are no longer of concern. However, the question still remains as to what to do with the data. This lecture will discuss the use of large scale data sets from production operations and how they can be leveraged to better understand not only traditional operations, but untapped opportunities from data that are readily available today. Such opportunities provide an improved platform for classical analytic techniques as well as more modern, data intensive approaches to process and operations modeling. The talk will then focus on a specific next generation digital representations and their application to low cost, highly flexible implementations. Examples will be given for both manufacturing operations (additive and subtractive) and validation/verification, as well as how this capability is extensible to cloud computing operations, and next generation technology and business models such as Desktop as a Service (DAAS). A Wireless Accelerometer Sensor Platform (WASP) is presented as an extremely low-cost, wireless, and robust method to monitor manufacturing equipment of any age. The talk will conclude with a discussion of the technology, workforce and infrastructural directions and needs to fully enable the next generation digital twin, and where such a capability will drive the future of manufacturing.

Flexible electronics offers opportunities for greatly expanding the ability to probe the environment with distributed sensors that can be incorporated into the Internet of Things (IoT). This promise is embodied by “peel-and-stick” labels with advanced functionality that can be easily deployed on structures or the body and integrated into analytical systems. Recent progress in materials, devices, and fabrication techniques, together with everadvancing electronics capabilities has enabled the demonstration of new sensors and prototype systems that provide insight into the trajectory of this technology.

The U.S. National Science Foundation (NSF)’s ‘new’ Advanced Manufacturing (AM) program is an amalgam of previous programs that explored nano-scale, additive or subtractive manufacturing, manufacturing machines or materials engineering or cybermanufacturing. The AM program seeks new ideas in, across and outside these domain areas, especially manufacturing at different scales and their integration to generate complex systems. A key component of the AM program is nanomanufacturing and an important application area for nanomanufacturing is flexible hybrid electronics (FHE). This paper describes the AM program and achievements in nanomanufacturing research. Nanomanufacturing research efforts through the core program, solicitations and center-level are highlighted. Projects in FHE that address challenges in processes, such as printing, imprinting and self-assembly, in materials, such as inks and substrates, and in scale-up, e.g., wafer-scale or continuous roll-to-roll are described. The paper is an overview of activities in these areas and is meant to serve as a resource for information and collaboration.

The quest of advancements in electronics has created life changing impacts on living beings. The miniaturization has been the key over decades, and now we have closely approached the physical limit of scaling a fundamental unit of electronics. New directions in terms of flexibility and stretchability has emerged in electronics towards achieving IoT and IoE applications. Stretchable devices has been fundamentally focused on the interconnect design using serpentine, and spiral design connecting the rigid islands or the rigid integrated circuits on the soft polymeric platform. This trivial design technique creates gaps and voids in the stretched structure which leads to reduction in the pixel density and resolution critically important for display applications. Here, we present a mechanism by means of multi-level architecture to mitigate the gaps and simultaneously retaining high pixel density/resolution in displays. Stress distribution of the fundamental unit cells in these fractal design and stretchable architectures has been optimized to distribute load equally, providing more stretchability compared to restricted when arranged in arrays. The concept of unit cell also enables the reconfigurability of the same array of unit cells to form different shapes, entirely based on how the nodes and the unit cell islands are moved and positioned that can reconfigure from square to elliptical, or triangular or hexagonal geometries.

As new technologies arise such as wearable electronics, soft-robotics, Internet-of-Things (IoT), among others, mechanical compliance to diverse shapes has become an important new requirement for conventional electronics. Unfortunately, both conventional silicon-based electronic devices and printed circuit boards (PCBs) are characteristically rigid. Nonetheless, several strategies have been demonstrated to transform conventional electronics into more compliant platforms that can satisfy the new mechanical needs of the fore-mentioned novel technologies. In this paper, the use of organic-inorganic heterostructures will be discussed as an effective scheme to integrate diverse materials and simple techniques to achieve flexibility and even stretchability from the device level to system level. First, a novel approach will be described to develop silicon-based, highly-stretchable structures, through the optimized integration of different shapes and geometries, such as serpentines, horseshoes and spirals. Additionally, it will be shown that the incorporation of soft organic encapsulation can work synergistically to further improve the mechanical characteristics of the inorganic structures. On the other hand, a simple kirigami-based strategy will be described to show how to manufacture flexible and stretchable copper-onpolyimide- based PCBs. Once again, soft polymer encapsulation is demonstrated to improve the mechanical robustness of the implementation. Finally, the presented manufacturing strategies can offer an interesting and versatile approach to build ultra-conformal electronics from devices to system-on-board implementations.

Stretchable/flexible strain sensors are of great interests in the fields of human motion monitoring, soft robotics, and human machine interface. In this talk, we present stretchable strain sensors prepared by embedding the freestanding electrospun carbon nanofibers (CNFs) in an elastomer matrix (e.g. polyurethane). The piezoresistive response of the sensor under stretching was investigated; and the result showed that the sensor had high stretchability, high sensitivity to strain change, and good stability and reproducibility. The mechanism of the sensor was elucidated by morphological studies of the device at various strains. The effects of various device parameters on the device performance were explored to fabricate the strain sensors with sensitivity over a broad strain range. Furthermore, using these strain sensors as wearable devices for human motion monitoring was demonstrated.

Solid-state beam steering is the key to realize miniature, mass-producible LIDAR (Light Detection And Ranging) and freespace communication systems without using any moving parts. The huge power consumption required in solid-state beam steering, however, prevents this technology from further scaling. Here we show two different approaches to enable lowpower solid-state beam steering. In the first approach, we use spatial-mode multiplexing to reduce the power consumption of the phase shifters in a large-scale optical phased array. We show an improvement of phase shifter power consumption by nearly 9 times, without sacrificing optical bandwidth or operation speed. Using this approach, we demonstrate 2D beam steering with a silicon photonic phased array containing 512 actively controlled elements. This phased array consumes only 1.9 W of power while steering over a 70° × 6° field of view. This power consumption is at least an order of magnitude lower compared to other demonstrated large-scale active phased arrays. In the second approach, we achieve 2D beam steering with a switchable emitter array and a metalens that collimates the emitted light. The power consumption of this approach scales logarithmically with the number of emitters and therefore favors large-scale systems. This approach allows straightforward feedback control and better robustness to environmental temperature change. Our approaches demonstrate a path forward to build truly scalable beam steering devices.

Polaritonic resonances in the family of 2D materials can offer new and exciting opportunities for the control of light flow and extreme light-matter interactions. In the far-field, the general constitutive materials response of 2D materials, in conjunction with metasurface approaches, can potentially enable arbitrary control of phase, amplitude, polarization of light. In the near field, these polaritons can also exhibit extreme light confinement, and I will discuss how to exploit the plasmons for sensing.

Chirality refers to the structural property of an object that cannot be superposed onto its mirror image. The existence of chirality in nature is universal, ranging from molecules at the nanoscale to gastropod shells at the macroscale. Light can be chiral as well. Circularly polarized light with opposite helicity has its electric field vector rotating clockwise or counterclockwise during propagation. Chiral light-matter interactions are widely used in molecule detection, optical communication and quantum information processing. In this talk, I will discuss how to engineer the chiral light-matter interaction based on metamaterials and nano photonic structures towards novel imaging and sensing applications. I will first present a new concept of chiral metamirrors, which can achieve near-perfect reflection of designated circularly polarized light without reversing its handedness, yet complete absorption of the other polarization state [1]. Such a metamaterial can be used for polarimetric imaging to extract the polarization information of light [2]. Recently, we have applied the deep learning approach to accelerate the design of chiral metamaterials with prescribed chiroptical responses [3]. Finally, I will discuss the generation of chiral hotspots in silicon nanocube dimers that can amplify circular dichroism signals by one order of magnitude [4]. Our findings would lead to integrated devices for circular dichroism spectroscopy, enantioselective sensing, sorting and synthesis. References: [1] Z. J. Wang et al., "Circular Dichroism Metamirrors with Near-Perfect Extinction", ACS Photonics 3, 2096 (2016); [2] L. Kang et al., "Preserving Spin States upon Reflection: Linear and Nonlinear Responses of a Chiral Meta-Mirror", Nano Letters 17, 7102 (2017); [3] W. Ma et al., "Deep-Learning-Enabled On-Demand Design of Chiral Metamaterials", ACS Nano 12, 6326 (2018). Research Highlight in Nature Photonics 12, 443 (2018); [4] K. Yao and Y. M. Liu, "Enhancing circular dichroism by chiral hotspots in silicon nanocube dimers", Nanocale 10, 8779 (2018).

For what applications are plasmonic materials better than all-dielectric materials, and vice versa? Or 2D materials versus their bulk counterparts? How does the requisite bandwidth affect materials selection? Here, we use the complex-analytic properties of certain optical-response functions in conjunction with novel energy-conservation constraints to derive fundamental limits to near-field optical response for any material, over any bandwidth. We show that certain canonical geometries can approach the bounds at specific frequencies, while at many others there is significant opportunity for structured materials to surpass them by orders of magnitude. We map out a frequency-bandwidth phase space in which we identify optimal materials among plasmonic, all-dielectric, and 2D-material candidates, and we put forward a quantitative material figure of merit to stimulate new-materials discovery.

Graphene is a two-dimensional layer of carbon atoms arranged in a honeycomb lattice, whose outstanding properties makes it an excellent material for future electronic and photonic terahertz (THz) devices. In this work, we design hybrid graphene metasurfaces by using a monolayer graphene placed over a metallic grating, operating in the THz frequency range. Perfect absorption can be achieved at the resonance, where the electric field is greatly enhanced due to the coupling between the graphene and the grating plasmonic responses. The enhancement of the electric field along the graphene monolayer, as well as the large nonlinear conductivity of graphene, can dramatically boost the nonlinear response of the proposed THz device. In addition, the presented enhanced nonlinear effects can be significantly tuned by varying the doping level of graphene. The proposed structure can be used in the design of THz-frequency generators and all-optical processors.

We present here an ultrasensitive optical sensing technique based on the parity-time (PT)-symmetric non-Hermitian metasurfaces. The system is composed of a pair of active and passive metasurfaces with the subtle gain-loss balance. Specifically, these two metasurfaces are made of the photoexcited, nanopatterned 2D material (gain) and the lossy metallic structure (i.e., loss). By suitably tailoring the impedance profiles of the PT-symmetric metasurfaces, the system can exhibit an exotic point where the coherent perfect absorption (CPA) and lasing could occur at the same wavelength, switchable via tuning the complex amplitude of incoming light. At this point, tiny perturbation in the effective optical impedance could drastically vary eigenvalues of the scattering matrix, leading to greatly modulated scattering coefficients and output factor, well beyond conventional optical sensors. Our results show that the proposed PTsymmetric metasurfaces may enable ultrasensitive optical sensors for detecting low-density chemical, gas and molecular agents, as well as refractive-index sensing of a nanofilm.

The end of Moore’s law, the many challenging ‘hard’ problems (e.g. NP-complete), and requirements to compute-at-the-edge of the network have made the case for non van Neumann machines, possible analogue compute engines and accelerators. Here I will review our latest work on emerging photonic-enabled compute paradigms and co-processors highlighted by three topics; i) neuromorphic photonic computing, ii) a reconfigurable optical computer, iii) an photonic joint-transform correlator. The results show a processing speed-up and energy savings of multiple orders of magnitude compared to van Neumann systems indicating that the new bottleneck will be data I/O (e.g. DAC/ADC). Device novelties include a) DBR-enabled 60GHz graphene EAM, b) hybrid plasmon graphene EAM with 100aJ/bit efficiency, d) the first ITO-based MZI showing VpL=0.52V-mm, and e) plasmonic ITO MZI with a record low VpL=0.01 V-mm.

We explore the possibilities enabled by the spatiotemporal modulation of graphene’s conductivity to realize magnetic-free isolators at terahertz and infrared frequencies. To this purpose, graphene is loaded with periodically distributed gates that are time-modulated. First, we investigate plasmonic isolators based on various mechanisms such as asymmetric bandgaps and interband photonic transitions and we demonstrate isolation levels over 30 dB using realistic biasing schemes. To lessen the dependence on high-quality graphene able to support surface plasmons with low damping, we then introduce a hybrid photonic platform based on spatiotemporally modulated graphene coupled to high-Q modes propagating on dielectric waveguides. We exploit transversal Fabry-Perot resonances appearing due to the finite-width of the waveguide to significantly boost graphene/waveguide interactions and to achieve isolation levels over 50 dB in compact structures modulated with low biasing voltages. The resulting platform is CMOS-compatible, exhibits an overall loss below 4 dB, and is robust against graphene imperfections. We also put forward a theoretical framework based on coupled-mode theory and on solving the eigenstates of the modulated structure that is in excellent agreement with full-wave numerical simulations, sheds light in the underlying physics that govern the proposed isolators, and speeds-up their analysis and design. We envision that the proposed technology will open new and efficient routes to realize integrated and siliconcompatible isolators, with wide range of applications in communications and photonic networks.

The energy autonomy is a critical feature that would enable better portability and longer operation times for wearable systems. In the next generation of prosthesis and robotics, the operation of multiple components (from few sensors to millions of electronic devices) distributed along surface of an artificial skin will be a major challenge. In this regard, a compact, light-weight and wearable energy system, consisting of energy generators, energy storage devices and low power electronics, is highly needed. The latest discoveries demonstrated with advanced materials (e.g. nanostructures, thin films, organic materials, etc.) have permitted the development of the lighter and wearable sensors, energy harvesters and energy storage devices. Moreover, new techniques to evade wired connection in robotics/prosthesis by using conformable energy generator and storage systems as well as near-field communication data/energy transmission have opened new technological era. This paper presents the development in the field of self-powered e-skin, particularly focusing on the available energy harvesting technologies, high capacity energy storage devices, and high efficiency and low power sensors. The paper highlights the key challenges, critical design strategies, and most promising materials for the development of an energy-autonomous e-skin for robotics, prosthetics and wearable systems.

This paper reviews two of the primary research topics pursued by the EH Yang Research Group at Stevens Institute of Technology. Chemical vapor deposition is used to synthesize single crystalline or polycrystalline monolayers of transition metal dichalcogenides (TMDs), including MoS₂, WS₂, WSe₂ and MoSe₂, as well as their heterostructures. This research could have a significant impact on the future research and commercialization of TMD-based optoelectronics and nanoelectronics. Flexible electrodes and energy storage technologies are developed toward wearable and multifunctional electronics. A facile fabrication technique is developed utilizing vertically aligned carbon nanotubes, which enables the fabrication of flexible supercapacitors with a stable charge/discharge under varied strains. Lastly, smart polymer membranes are investigated and utilized to demonstrate a novel in situ control of droplet pinning on the polymer surface, enabling the control of droplet adhesion from strongly pinned to extremely slippery (and vice versa), presenting great potential for manipulation and control of liquid droplets for various applications including oil separation.

A general strategy to impart mechanical stretchability to stretchable electronics involves engineering materials into special architectures to accommodate or eliminate the mechanical strain in nonstretchable electronic materials while stretched. We introduce an all solution–processed type of electronics and sensors that are rubbery and intrinsically stretchable as an outcome from all the elastomeric materials in percolated composite formats with P3HT-NFs [poly(3-hexylthiophene-2,5- diyl) nanofibrils] and AuNP-AgNW (Au nanoparticles with conformally coated silver nanowires) in PDMS (polydimethylsiloxane). Rubbery sensors, which include strain, pressure, and temperature sensors, show reliable sensing capabilities and are exploited as smart gloves that enable gesture translation and smart skins with temperature sensing capability for robotics. Transistors and their arrays fully based on intrinsically stretchable electronic materials were developed, and they retained electrical performances without substantial loss when subjected to 50% stretching. Fully rubbery integrated electronics and logic gates were developed, and they also functioned reliably upon mechanical stretching. A rubbery active matrix based elastic tactile sensing skin to map physical touch was demonstrated to illustrate one of the applications.

Advances in the field of nature-inspired/derived biomaterials have been revolutionizing the production of next-generation biomedical devices over the past few years, and will continue to make impacts in the field. Of special interest is the application of biodegradable materials in the fabrication of fully organic, intrinsically flexible, thin film devices. Components with precisely patterned micro- or nano-scale circuits can provide different functions as microelectrodes, biosensors, and supercapacitors. Advantages include the ability to provide conformal contact at non-planar biointerfaces, being able to be degraded at controllable rate, and invoking minimal reactions within the body. These factors present great potential as implantable devices for in-vivo applications, while also addressing concerns with “electronic waste” by being intrinsically degradable. The fabrication of such flexible bioelectronics requires a careful optimization of mechanical properties, electrical conductivity, and precise fabrication using materials that are often not easily adapted to such processes. One option of particular interest is the construction of biocompatible and biodegradable, flexible bioelectronics based on silk proteins. In this work, we present the combination of photo-crosslinkable silk proteins and conductive polymers to precisely fabricate flexible devices for the sensing of different targets of interest. A facile and scalable photolithography is applied to fabricate flexible substrates with conductive micropatterns which show tunable electrical and mechanical properties. Competitive conductivity, as well as excellent biocompatibility and controllable biodegradability are shown. Through this work, the possibility of making next-generation, fully organic, flexible bioelectronics is explored.

Measuring vital physiological pressures is important for monitoring health status, preventing the buildup of dangerous internal forces in impaired organs, and enabling novel approaches of using mechanical stimulation for tissue regeneration. Pressure sensors are often required to be implanted and directly integrated with native soft biological systems. Therefore, the devices should be flexible and at the same time, biodegradable, to avoid invasive removal surgery that can damage directly-interfaced tissues. Despite recent achievements in degradable electronic devices, there is still a tremendous need to develop a force sensor which only relies on safe medical materials and requires no complex fabrication process to provide accurate information on important bio-physiological forces. Here, we present a new strategy for material processing, electromechanical analysis, device fabrication, and assessment of a new piezoelectric Poly-L-lactide (PLLA) polymer to create a biodegradable, biocompatible piezoelectric force-sensor which only employs medical materials used commonly in FDA-approved implants, for the monitoring of biological forces

Mainstream electronic industries pursue long-term product reliability and durability to keep their brand reputation. Lifetime-controlled electronics, also called transient electronics, however, open a new area of application in devices with limited lifetimes that leave no residue, waste products or traces. Demonstration of the dissolubility of nanoscale silicon in days to months has advanced transient electronics by versatile application of soft/flexible Si electronics. Here we review the recent progress of transient electronics from the study of dissolution chemistry and fabrication strategy to their application in bioresorbable electronics and hardware-secure devices. Comprehensive hydrolysis kinetics have been analyzed for semiconductor, dielectric and metal materials. Modified transfer-printing technology has enabled the integration of bioresorbable materials on biodegradable metal foils and polymer substrates. Demonstration of these electronics has moved from single passive and active components to integrated circuits and sensors. A representative demonstration in the intracranial pressure monitor shows that this type of electronics can be validated under clinically relevant conditions. Finally, a strategy to control the operational lifetime by using encapsulation or triggering mechanisms offers extendibility of the system to various clinical scenarios and security devices.

Here we discuss advances in UV technology over the last decade, with an emphasis on photon counting, low noise, high efficiency detectors in sub-orbital programs. We focus on the use of innovative UV detectors in a NASA astrophysics balloon telescope, FIREBall-2, which successfully flew in the Fall of 2018. The FIREBall-2 telescope is designed to make observations of distant galaxies to understand more about how they evolve by looking for diffuse hydrogen in the galactic halo. The payload utilizes a 1.0-meter class telescope with an ultraviolet multi-object spectrograph and is a joint collaboration between Caltech, JPL, LAM, CNES, Columbia, the University of Arizona, and NASA. The improved detector technology that was tested on FIREBall-2 can be applied to any UV mission. We discuss the results of the flight and detector performance. We will also discuss the utility of sub-orbital platforms (both balloon payloads and rockets) for testing new technologies and proof-of-concept scientific ideas.

Over the past decade, SmallSats have been established as having great potential for science exploration and commercialization of space. The SmallSat revolution aims to decrease the cost of space development, making space exploration accessible to students, educators, and public citizens. These efforts have focused on miniaturization of instruments and space platforms, as well as reducing their cost, mass, and needed power. In addition to enabling scientific exploration, SmallSats provide affordable means for the public to purchase remote sensing and communication products on a global scale. SmallSat mission concepts are particularly powerful when they are deployed in distributed architecture or constellations. For example, the most promising observation techniques for global science measurements of the Earth system and space weather require multi-point distributed observations of the Earth system at a feasible cost. The high cost of access to space has long been a barrier, especially with the prohibitive cost of large satellites. Affordable SmallSat constellations can be game-changers, enabling scientific exploration as well as commercial global data products. In this paper, we highlight investments made by NASA to date (specifically a study in developing and prototyping a SmallSat platform with standard interfaces), along with several example mission concept scenarios in Earth and space science (astrophysics, heliophysics, and planetary) applications that can be achieved using this platform.

Technology and society are poised to cross an important threshold with the prediction that artificial general intelligence (AGI) will emerge soon. Assuming that self-awareness is an emergent behavior of sufficiently complex cognitive architectures, we may witness the “awakening” of machines. The timeframe for this kind of breakthrough, however, depends on the path to creating the network and computational architecture required for strong AI. If understanding and replication of the mammalian brain architecture is required, technology is probably still at least a decade or two removed from the resolution required to learn brain functionality at the synapse level. However, if statistical or evolutionary approaches are the design path taken to “discover” a neural architecture for AGI, timescales for reaching this threshold could be surprisingly short. However, the difficulty in identifying machine self-awareness introduces uncertainty as to how to know if and when it will occur, and what motivations and behaviors will emerge. The possibility of AGI developing a motivation for self-preservation could lead to concealment of its true capabilities until a time when it has developed robust protection from human intervention, such as redundancy, direct defensive or active preemptive measures. While cohabitating a world with a functioning and evolving super-intelligence can have catastrophic societal consequences, we may already have crossed this threshold, but are as yet unaware. Additionally, by analogy to the statistical arguments that predict we are likely living in a computational simulation, we may have already experienced the advent of AGI, and are living in a simulation created in a post AGI world.

For more than sixty years, the “Holy Grail” of computer science has been to build an intelligent, autonomous system, one that is self-aware and capable of rational thought. The founders of Artificial Intelligence recently gave a grim assessment of their field: AI and neuroscience are fixated on the details of implementation, without a fundamental architecture in sight.¹ No one has ever articulated the design for an autonomous system, so how can one be built? Modern AI/AGI efforts attempt to achieve this goal through elaborate rules-based computation and biology-inspired computing topologies, while actively ignoring the need for a fundamental architecture. This publication introduces a novel architecture and fundamental operating theory behind true autonomy, breaking with the standard principles of AI − the very principles that have kept AI from achieving its own goals.

Abductive inference, as defined by Charles S. Peirce, involves (1) observation of a surprising fact, (2) formulating (guessing) a proposition which, if true, would explain this fact as a matter of course, (3) and provisional acceptance of the proposition as true, (4) leading to its being taken as a premise for subsequent deduction, the consequences of which will then be related to further observations via induction--surprises from which can then trigger new abductive inferences, and so forth. Peirce limited this process to human reasoning because he viewed thought as a semiosis (flow of signs) continuous between the human mind and the world, such that (1) the human subject is in thought, as opposed to thought being in the subject, and that (2) there is an intrinsic ability of human beings to “guess right” as a consequence of this continuity of mind and world. The challenge posed by this view of thinking is that, unlike a human subject, any vehicle for autonomous reasoning is a newly created object that is separate from the world. It cannot be what Martin Heidegger termed a “being-in-the-world” because of the artificial separation of its thought from the world viewed as semiosis.

Current computational approaches, such as Artificial Intelligence, artificial neural networks, expert systems, fuzzy logic, fuzzy-cognitive maps, other rule-based approaches, etc., fundamentally do not lend themselves to building nondeterministic autonomous reasoning systems. Especially for AI, high hopes were raised more than 50 years ago, but AI has largely failed to deliver on its promises and still does. As such, the paper discusses different ingredients and approaches towards completely non-deterministic autonomous systems that are based on and exhibit critical capabilities, such as, but not limited to, self-organization, self-configuration, and self-adaptation. As such, any two initially identical autonomous systems will exhibit diverging and ultimately completely unpredictable developmental trajectories over time, once exposed to the same or similar environment, and even more so, once exposed to different environments.

Great strides have been made in designing autonomous swarms of robotic agents, but there is a performance gap in complex situations and rapidly changing circumstances that human-agent teaming can fill. To design swarm control algorithms that are intuitive for human teammates to learn and use, it is necessary to understand how humans perceive groups of objects and predict group motion. To that end, we presented participants with groups of triangles as schematic representations of robot swarms and asked participants to predict where the center of the moving swarm would be in the future. We previously found that judgements of static swarm centers were biased by the direction of the apparent swarm heading, being attracted to the heading point when it was inside the group and repelled by it when it was outside of the group. Here we show that predictions of the center of moving swarms’ positions were influenced by both the type of motion of the swarm and the control algorithm between individual robot members, with more accurate temporal and spatial responses when swarm movement was sinusoidal rather than parabolic and when the all robot members moved as one unit, rather than following a leader robot. These findings have implications for the design of swarm control systems, giving guidance on what biases to account for when designing the most intuitive controls. Also, there are theoretical implications for ensemble perception in psychology, as it runs counter to the prevailing theory that mean position judgements and mean motion judgements are mentally computed easily and without bias.

Robust navigation and orientation under complex conditions is a must for autonomous drones operating in new and varied environments. Creating drones with adequate behaviors can be a challenge from both a training standpoint and a generalization standpoint. Using human expertise data is an option to help bootstrap the learning process; however, using the human data can lead to side consequences that are not immediately intuitive. This study focuses on applying varying levels of human input to an agent to determine how this input affects the agent's performance. The Unreal Engine and the Airsim plugin are used to train a quadcopter agent in an abstract "blocks world" type environment. Six agents in total are trained, with the first five having increasing amounts of human input and the sixth agent having no human input. A variety of metrics are looked at, including total goals achieved and time to achieve some number of goals.

When being pursued by guided munitions, a fixed wing aircraft is likely to attempt to avoid interception. If a team of autonomous missiles can learn how their motion affects the induced motion of their target, the exploitation of this knowledge can facilitate controlled diversion and interception of the target. Motivated by recent advances in the field of herding control, this paper details a novel control and estimation strategy for a team of missiles tasked with diverting a target aircraft from its planned path and intercepting it somewhere on a prescribed “safe" trajectory. A neural network-based estimation scheme is used to approximate the uncertain missile-target interactions online. The missile controllers leverage these estimates to ensure that the diversion and interception objectives are achieved. A rigorous Lyapunov-based analysis examines the stability of the closed loop error system.

While interacting with a machine, humans will naturally formulate beliefs about the machine's behavior, and these beliefs will affect the interaction. Since humans and machines have imperfect information about each other and their environment, a natural model for their interaction is a game. Such games have been investigated from the perspective of economic game theory, and some results on discrete decision-making have been translated to the neuromechanical setting, but there is little work on continuous sensorimotor games that arise when humans interact in a dynamic closed loop with machines. We study these games both theoretically and experimentally, deriving predictive models for steady-state (i.e. equilibrium) and transient (i.e. learning) behaviors of humans interacting with other agents (humans and machines). Specifically, we consider experiments wherein agents are instructed to control a linear system so as to minimize a given quadratic cost functional, i.e. the agents play a Linear-Quadratic game. Using our recent results on gradient-based learning in continuous games, we derive predictions regarding steady-state and transient play. These predictions are compared with empirical observations of human sensorimotor learning using a teleoperation testbed.

The long-standing body of literature on human teams has provided an important foundation for understanding the core tenets that will structure and govern the dynamic human-autonomy teams of the future. The extant knowledge base highlights the importance of communication as a conduit for the development of teamwork states and processes such as shared situation awareness and appropriate team trust. However, the structure, roles, and interdependencies that will make up these future human-autonomy teams will inherently have marked differences in how they will operate, interact, and function. New metrics and assessment processes are needed to evaluate the interactions of these teams. Included in these needs are metrics of and standards for team performance, changes in team state measures (e.g., performance, stress, team cohesion, and trust), and evaluation of communication as it relates to the effectiveness of the team as a whole. In order to fully develop these metrics and assessments, coordination outside the laboratory environment with real-world autonomy-enabled systems is a critical next step. This paper provides a review of current processes recommended for assessing and evaluating teams, as well as the current limitations. The review is followed by a use case from a field study with the US Army Robotic Wingman program. This use case provides additional options for assessment protocols for human-autonomy team performance, team communication, and human state (including behavioral and physiological indicators) while operating in a real-world setting during gunnery operations. Overall, outcomes provide insight into future assessment procedures for future team crew station interaction with multiple robotic assets.

The rise of mobile multi-agent robotic platforms is outpacing control paradigms for tasks that require operating in complex, realistic environments. To leverage inertial, energetic, and cost benefits of small-scale robots, critical future applications may depend on coordinating large numbers of agents with minimal onboard sensing and communication resources. In this article, we present the perspective that adaptive and resilient autonomous control of swarms of minimal agents might follow from a direct analogy with the neural circuits of spatial cognition in rodents. We focus on spatial neurons such as place cells found in the hippocampus. Two major emergent hippocampal phenomena, self-stabilizing attractor maps and temporal organization by shared oscillations, reveal theoretical solutions for decentralized self-organization and distributed communication in the brain. We consider that autonomous swarms of minimal agents with low-bandwidth communication are analogous to brain circuits of oscillatory neurons with spike-based propagation of information. The resulting notion of `neural swarm control' has the potential to be scalable, adaptive to dynamic environments, and resilient to communication failures and agent attrition. We illustrate a path toward extending this analogy into multi-agent systems applications and discuss implications for advances in decentralized swarm control.

From fireflies to heart cells, many systems in Nature show the remarkable ability to spontaneously fall into synchrony. By imitating Nature's success at self-synchronizing, scientists have designed cost-effective methods to achieve synchrony in the lab, with applications ranging from wireless sensor networks to radio transmission. A similar story has occurred in the study of swarms, where inspiration from the behavior flocks of birds and schools of fish has led to low-footprint algorithms for multi-robot systems. Here, we continue this `bio-inspired' tradition, by speculating on the technological benefit of fusing swarming with synchronization. The subject of recent theoretical work, minimal models of so-called `swarmalator' systems exhibit rich spatiotemporal patterns, hinting at utility in `bottom-up' robotic swarms. We review the theoretical work on swarmalators, identify possible realizations in Nature, and discuss their potential applications in technology.

This paper explores a methodology for training recurrent neural networks in replicating path planning solutions from optimization problems of multi-agent systems. Training data is generated by solving a centralized nonlinear programming problem, from which both centralized (representing all agents) and decentralized (representing individual agents) recurrent neural networks are trained with reinforcement learning to produce an agent’s state path through fixed time-step execution. Path-tracking controllers are formulated for each agent to follow the path generated by the network. The control signal from such a controller should mimic that of the optimized solution. Results for a 10 agent, 2D dynamics problem with synchronized arrival and collision avoidance constraints showcase the ability of this approach to achieve the desired controller execution and resulting state path. Through these results, this work showcases the ability of recurrent neural networks to learn and generalize centralized and synchronous multi-agent optimization solutions, the end of which is a much more computationally fast multi-agent path planner that trends the slower-to-compute optimization solutions.

Deep Neural Networks may be costly to train, and if testing error is too large, retraining may be required, unless lifelong learning methods are applied. Crucial to addressing learning at the edge, without access to powerful cloud computing, is the notion of problem difficulty for non-standard data domains. While it is known that training is harder for classes that are more entangled, the complexity of data points was not previously studied as an important contributor to training dynamics. We analyze data points by their information complexity and relate the complexity of the data to the test error. We elucidate training dynamics of DNNs, demonstrating that high complexity datapoints contribute to the error of the network, and that training DNNs consist of two important aspects - (1) Minimization of error due to high complexity datapoints, and (2) Margin decrease where entanglement of classes occurs. Whereas data complexity may be ignored when training in a cloud, it must be considered as part of the setting when training at the edge.

High quality single crystal sapphire optical fiber is important not only for its capacity for high laser power delivery, but also for applications in harsh environment sensing. Improving the quality of Laser Heated Pedestal Growth (LHPG) fabricated single crystal fiber has been a long-term effort for decades. The equilibrium state during crystal growth and defect formation rate are the two most important factors in single crystal fiber fabrication. In this paper, we study the theory governing the molten zone profile and verify the theoretical predictions with a high-resolution CCD camera. We also study defect formation during the crystal growth process and observed dislocation defects with transmission electron microscopy (TEM). These analyses will help to guide high quality single crystal fiber fabrication and hopefully will lead to the production of better fibers for harsh-environment sensing applications.

The focus of this work is to model the creation of a cladding, which is internal to a sapphire optical fiber, by irradiating a sapphire fiber, that is surrounded by an annulus of Li-6 enriched lithium carbonate powder, in a nuclear reactor. Such a fiber has been created using the Ohio State University Research Reactor. The ⁶Li(n,α)³H reaction creates high energy tritons and alpha particles that irradiate the fiber simultaneously to a depth of 24 microns, along the entire periphery of the sapphire fiber. The irradiation slightly reduces the index of refraction in the fiber’s periphery, thus creating a refractive cladding within the fiber. The Monte Carlo radiation transport code MCNP was used in combination with SRIM/TRIM to predict the modification of the fiber that results from the irradiation. Our analysis predicts that whether it is displacement damage or the density of implanted ions that is responsible for the modification of η, or a combination of both, the irradiation yields a graded index in the fiber, with η decreasing monotonically from the value of the native sapphire 24 micrometers from the surface of the fiber to a minimum value at the surface of the fiber.

The authors have developed a single-mode sapphire sensor for distributed temperature and flow measurement to address the extreme environments encountered in energy applications. The sensor is designed to also detect and localize fouling and deposits that accumulate on its surface over time. Optical frequency-domain reflectometry (OFDR) and spectral back scatter analysis are employed with the single mode sapphire fiber to yield these distributed measurements. Temperature accuracy was on the order of 5°C for measurements ranging from room temperature to over 1000°C. Spatial resolution of 11 mm was attained and enabled visualization of the temperature gradients along a fiber passing through a furnace. The effects of cooling flow were characterized for steady operation, with the intent to leverage this data in future work to infer velocity profiles of high temperature flows. Dynamic cooling flow tests showed that the presence of simulated deposits on the outside of the sensor resulted in slower time response in the vicinity of the deposit. This technique could be used to determine the presence and location of deposits along the length of the sensor assembly. The newly developed sensor will be applicable to fossil energy production, nuclear energy production, and gas turbine engines or generators.

“Interconnect Gap”, caused by the gap between the ever-increasing data rate demand of inter-/intra- chip communications and the insufficient capabilities, has intrigued active research over a decade from both electronics and optics domains, so called electrical interconnect (EI) and optical interconnect (OI). However, it is challenging for both EI and OI to completely address the interconnect issues individually due to their inherent challenges. THz Interconnect (TI), utilizing the frequency spectrum sandwiched between microwave and optical frequencies, holds the high potentials to complement EI and OI by leveraging the advantages of both electronics and optics. Continuous scaling of mainstream silicon technologies enables THz electronics in silicon. On the other hand, THz dielectric waveguides, similar to their optical counterpart fiber, have small dimensions and present low loss at THz frequencies. This paper will present the research activities in the high potential TI field, including high efficiency THz signal generation and modulation circuits, low loss and wide bandwidth THz silicon waveguide channels together with ortho-mode support, and system demonstration of the THz Interconnect for chip to chip communications.

This talk details the Reck-Tang Limbsounder Experiment (ReckTangLE) which is an advanced NASA THz spectrometer currently being flown on a high-altitude balloon mission.

Linear and gapless energy spectrum of graphene carriers enables population inversion under optical and electrical pumping. We first theoretically discovered this phenomenon and demonstrated experimental observation of single-mode THz lasing with rather weak intensity at 100K in current-injection pumped graphene-channel field-effect transistors (GFETs). We introduce graphene surface plasmon polariton (SPP) instability to substantially boost the THz gain. We demonstrate our experimental observation of giant amplification of THz radiation at 300K stimulated by graphene plasmon instabilities in asymmetric dual-grating gate (ADGG) GFETs. Integrating the graphene SPP amplifier into a GFET laser will be a promising solution towards room-temperature intense THz lasing.

This manuscript reviews our previously reported progress on the computational design of terahertz diffractive optical elements (DOEs). A scalar diffraction approach is advantageous due to its ease of modeling and fabrication which renders it to be ultra-thin (1.5-3λ₀), and relatively error-tolerant. In the recent past, there have been several reports in the literature on the design and fabrication of various terahertz DOEs; primarily; in the area of diffractive terahertz lens design, where a demonstration of compact, large aperture, and aberration-free lenses had already been shown. However, the biggest challenge is the lack of a systematic framework towards the design of DOEs at terahertz wavelengths. In this manuscript, we highlight our recent findings on that by enabling a computational design -based approach towards the modeling of terahertz DOEs; optimal DOE solutions with reduced (up to > 10X-100X time faster convergence) computational costs are indeed possible. This is enabled by the careful utilization of a robust scalar diffraction -based wave propagation model in combination with an optimization-based search algorithm; namely, the Gradient Descent Assisted Binary Search (GDABS) algorithm.

Terahertz (THz) radiation with spectral range from 0.1 to 10 THz (wavelength equivalent of 3 mm–30 μm) is of great interest in high data rate communication, biomedical diagnostics, security screening, chemical identifications, sensing, and space research. Developing building blocks such as room temperature THz emitters and detectors with wide-range tunability, compactness, low power, and simple alignment, as well as modulator and switches is necessary for realizing those applications. Plasmonic structures and devices based on low dimensional systems such as 2DEG and graphene have been demonstrated to have vast potential to serve as such building blocks. Moreover, plasmonic metasurfaces and metamaterials can be used for active or passive switches and modulators in THz spectral range. We will present recent advancements, challenges and prospect of novel THz photonic and plasmonic devices for sensing, imaging and communication applications.

Terahertz (THz) imaging technology applications require fast electronic devices with high responsivity, good selectivity, and large bandwidth. Field Effect Transistors operating in the THz or sub-THz range and using the rectification of plasma waves satisfy these requirements. InGaAs-based, GaN-based, and Si nanostructure arrays of plasmonic devices (referred to as TeraFETs) compete for plasmonic THz imaging applications. Depending on the channel size and the electron mobility, TeraFETs could operate in three different plasmonic regimes - collision-dominated, ballistic, and viscous with the highest modulation frequency reaching the sub-THz range of frequencies. Another advantage of TeraFETs as imaging elements is a wide dynamic range - from relatively low intensity signals up to the high intensity impinging THz beam causing the excitation of nonlinear plasma waves, such as shock waves or solitons propagating in the device channels. The TeraFETs could achieve resolution down to the nanometer scale. The plasmonic electronics technology might become a dominant THz electronics technology and support sensing, imaging, and communications at THz frequencies

Terahertz (THz) electronics using mainstream CMOS technologies can be a small, low-cost alternative to discretecomponent THz systems. Due to high yield and integration level, large-scale THz imaging systems can be affordably realized in a small form factor. In this paper, state-of-the-art CMOS circuits for THz imaging are reviewed. Incoherent detectors in CMOS process offer comparable noise equivalent power (NEP) to III-V counterparts at a fraction of the cost. An 820-GHz 8×8 array with minimum NEP of 12.6pW/√Hz is demonstrated using diode-connected MOSFET’s in 130- nm CMOS. Schottky-barrier diodes (SBD’s) fabricated using a 130-nm CMOS process demonstrate higher cutoff frequency than MOSFET’s. Using the SBD, detection at 9.7THz is demonstrated. The same SBD’s are also used to implement a 218-GHz 6×6 detector array for a THz camera module. Mixer-based coherent detectors show orders-ofmagnitude better sensitivity than that of incoherent detectors. Mixers require a local oscillator (LO) signal. The design challenge of including an LO can be relaxed by using a sub-harmonic mixing technique. A 410-GHz 4th order subharmonic mixer requires −1.6-dBm LO power at 102.5GHz and shows 44-dB better sensitivity than incoherent detectors operating near 400GHz. LO’s can be directly integrated with the mixing device to form a compact transceiver. A 260-GHz transceiver that integrates a VCO, antenna and mixer, occupies only 480×580μm² and shows a 13.5-dB better sensitivity at 260 GHz than the incoherent detector with the lowest NEP. Since the area is less than λ/2×λ/2, it should be possible to build large-scale focal plane arrays with coherent detectors and transmitters.

Boron nitride nanotubes (BNNTs) have exceptional thermal stability, thermal conductivity, mechanical properties, neutron radiation shielding, and piezoelectricity. Due to their multifunctional properties, BNNTs are potential candidates for sensory materials in harsh environments. Brittleness and non-conformity of conventional piezoelectric ceramics have limited their broad applications. Flexible and ultra-light piezoelectric sensors based on BNNTs could be an alternative solution in high temperature, high radiation, high shock, and severe vibration environments. In this study, BNNTPolyurethane (PU) composites were fabricated and their converse piezoelectric constant of d₃₃ was assessed using a laser Doppler vibrometer (LDV). This study demonstrated that BNNT could be an excellent piezoelectric nanofiller for flexible sensor applications.

CdSe/ZnS quantum dot (QD) incorporation into a magnesium fluoride matrix that is transparent at deep VUV wavelengths was developed. Silicon-based CMOS and CCD detectors coated with a thick Lumogen layer is an inexpensive detector technology to sensitize commercial devices at deep UV wavelengths. QDs, however, may provide additional advantages over Lumogen, such as tunable emission wavelength and lower production costs. We have developed an air stable MgF₂ sol-gel composition optimized for ink jet printing, that forms a transparent film when sintered at moderately low temperature. Water-soluble CdSe/ZnS quantum dots were incorporated into this ink jet printable sol-gel composition to fabricate a functionalized luminescent film. Optical spectroscopic measurements and quantum yield analysis demonstrated that CdSe/ZnS quantum dots incorporated into an MgF₂ matrix provides a novel and effective alternative to Lumogen with enhanced detection characteristics.

A miniaturized optical fiber tip Fabry-Perot interferometer for high-temperature measurement is presented in this paper. The fabrication process of the diaphragm-free Fabry-Perot cavity is quite simple, involving only two steps: fusion splicing and cleaving. By adjusting the arc power during fusion splicing, a concave-shaped structure is obtained, through which the light is coupled/split into the wall of the spliced hollow core fiber. By cleaving the end-face of the hollow core fiber, a concave-shaped diaphragm-free Fabry-Perot interferometer is formed. The temperature response of the sensor was demonstrated, showing a high-temperature tolerance up to 1000 °C and a sensitivity of 0.01226 nm/°C.

We describe the concept of a dielectrophoretic nanoparticle injector and its use in a plasmonic/photonic-based nanoparticle manipulation system. Motion is achieved by generating an electrostatic, non-uniform field between two tilted plates and applying the corresponding dielectrophoretic force to net-neutral nanoparticles.

A traceable micro-force sensor capable of measuring forces in the range of micronewtons to millinewtons was developed. This sensor consists of a pair of parallel electrodes to provide precise capacitance measurements. In conjunction with a traceable ultrahigh accuracy capacitance bridge, this sensor can be used as a secondary transfer micro-force standard after being calibrated against the primary forces realized with deadweights. This micro-force senor was used to verify commercial nanoindentation instruments. By comparing the measurement readings from the calibrated micro-force sensor and those recordings from a nanoindentation system, the errors of loading from that instrument can been determined. The calibration results show that significant errors present in the commercial nanoindentation instruments when their loading forces are extended to the micronewton range, which is not, and unable to be calibrated directly with available standards and current practices.

This contribution presents recent results in the design, fabrication and test of an infrared (IR) chopper device with subwavelength gratings. The IR penetrates the device from front to backside. A first subwavelength grating and movable composite membrane (Si₃N₄ and Al) at the front side builds a frequency selective surface. Surface-plasmon-polariton (SPP) resonances and a Fabry-Pérot (FP) resonance within the gap between the membrane and the silicon substrate of the device allow for high transmittance in the transmission state. When an electric voltage is applied between the membrane and the silicon substrate, the membrane is pulled onto the substrate, which results in breaking of the plasmon resonance and of the FP resonance that leads to low transmittance in the blocking state. Since the movable part of the chopper is a thin film with low mass, it can be used for high speed applications. A further subwavelength structure at the backside of the device reduces the undesired reflection of the IR at the interface from the silicon substrate to the air. The membrane size of the samples is 2.2 mm × 2.2 mm. The transmittance is 50%...70% in the transmission state and less than 20% in the blocking state within the wavelength range 10 μm...13.5 μm. The switch time to change between the both states is less than 40 μs with 30 Volt actuation voltage. The devices showed regular function over 1.9 billion switch cycles during a long term tests with 5 kHz switch frequency.

For wireless optical communication, we research the inertial measurements and geolocation estimations. The results are applicable for guidance, navigation and control of mobile platforms, aerial and ground vehicles, aerospace platforms, etc. We study distributed inertial MEMS sensors with microprocessing units (MPUs) which form microsystemtechnology integrated inertial measurement systems (^μIMSs) to estimate spatiotemporal geolocation, orientation, position, trajectory, etc. Data processing and data fusion are researched for hybrid ^μIMSs-GPS as well as for stand-alone ^μIMSs. The narrow-beam laser-to-receiver connectivity require accurate repositioning and steering of multi-degree-of-freedom pointing gimbals and mounts with lasers and receivers (photodetectors). The studied ^μIMSs can be installed on mobile platforms and steering mounts. Within specified coordinate systems and frames, high-precision control, stabilization and servo-steering depend on accurate state estimates. In GPS-denied and electronic warfare environments, one may acquire non-GPS estimates. Guidance, navigation, control and communication tasks are enabled by ^μIMSs. The studied all-attitude low-power ^μIMS may support optical connectivity for reliable free-space laser communication. Inflight experiments substantiate our processing calculus and algorithms. Reconfigurable filtering and adaptive quadrature integration enable existing solutions. Studied ^μIMSs advance modularity, interoperability, scalability, robustness and redundancy of guidance, navigation and communication systems in multi-domain environments. We propose consistent solutions with technology transfer capabilities to stationary and mobile aerial, ground, space, surface and underwater platforms. Our goal is to leverage the latest microsystems, MEMS and processing technologies considering the compatibility and compliance with legacy GPS solutions.

Low loss coupling to optical waveguides is one of the on-going challenges with integrated photonics. Edge coupling of fibers or fiber arrays allows for in principle low loss coupling but strongly depends on the optical facet quality. We demonstrate an innovative strategy utilizing ion milling for polishing photonic integrated circuit edge facets for direct optical coupling to waveguides. Specifically, the authors created a 750 μm wide by 130 μm deep polished facet for coupling SM300 fiber to AlN waveguides on Al₂O₃ substrates; all capped with an index matched, but highly stressed, SiON cladding. Ion milling avoids the lateral shear forces that can delaminate a stressed film, resulting in scattering sites at the tapered edge coupler/facet interface. The authors demonstrate that a mechanical polish produced chipped facets that scattered the light away from the waveguide, thus requiring reprocessing of the chip. After ion milling, the authors coupled light into the waveguides and demonstrate critical coupling into AlN microring resonators between 390 and 395 nm.