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In integrated photonics, specific wavelengths such as 1,550 nm are preferred due to low-loss transmission and the availability of optical gain in this spectral region. For chip-based photodetectors, two-dimensional materials bear scientifically and technologically relevant properties such as electrostatic tunability and strong light–matter interactions. However, no efficient photodetector in the telecommunication C-band has been realized with two-dimensional transition metal dichalcogenide materials due to their large optical bandgaps. Here we demonstrate a MoTe2-based photodetector featuring a strong photoresponse (responsivity 0.5 A W–1) operating at 1,550 nm in silicon photonics enabled by strain engineering the two-dimensional material. Non-planarized waveguide structures show a bandgap modulation of 0.2 eV, resulting in a large photoresponse in an otherwise photoinactive medium when unstrained. Unlike graphene-based photodetectors that rely on a gapless band structure, this photodetector shows an approximately 100-fold reduction in dark current, enabling an efficient noise-equivalent power of 90 pW Hz–0.5. Such a strain-engineered integrated photodetector provides new opportunities for integrated optoelectronic systems. A strain-induced absorption-enhanced MoTe2-based silicon photonic microring-integrated photodetector is demonstrated, featuring high responsivity of ~0.5 A W–1 at 1,550 nm, with a low noise-equivalent power of 90 pW Hz–0.5. [ABSTRACT FROM AUTHOR]

We demonstrate a passive all-chalcogenide all-optical perceptron scheme. The network’s nonlinear activation function (NLAF) relies on the nonlinear response of Ge2Sb2Te5 to femtosecond laser pulses. We measured the sub-picosecond time-resolved optical constants of Ge2Sb2Te5 at a wavelength of 1500 nm and used them to design a high-speed Ge2Sb2Te5-tuned microring resonator all-optical NLAF. The NLAF had a sigmoidal response when subjected to different laser fluence excitation and had a dynamic range of −9.7 dB. The perceptron’s waveguide material was AlN because it allowed efficient heat dissipation during laser switching. A two-temperature analysis revealed that the operating speed of the NLAF is ≤1 $\le 1$ ns. The percepton’s nonvolatile weights were set using low-loss Sb2S3-tuned Mach Zehnder interferometers (MZIs). A three-layer deep neural network model was used to test the feasibility of the network scheme and a maximum training accuracy of 94.5% was obtained. We conclude that combining Sb2S3-programmed MZI weights with the nonlinear response of Ge2Sb2Te5 to femtosecond pulses is sufficient to perform energy-efficient all-optical neural classifications at rates greater than 1 GHz.

Electro-optic modulators provide a key function in optical transceivers and increasingly in photonic programmable application-specific integrated circuits (ASICs) for machine learning and signal processing. However, both foundry-ready silicon-based modulators and conventional material-based devices utilizing lithium-niobate fall short in simultaneously providing high chip packaging density and fast speed. Current-driven ITO-based modulators have the potential to achieve both enabled by efficient light–matter interactions. Here, we introduce micrometer-compact Mach–Zehnder interferometer (MZI)-based modulators capable of exceeding 100 GHz switching rates. Integrating ITO-thin films atop a photonic waveguide, one can achieve an efficient VπL ${V}_{\pi }L$ = 0.1 V mm, spectrally broadband, and compact MZI phase shifter. Remarkably, this allows integrating more than 3500 of these modulators within the same chip area as only one single silicon MZI modulator. The modulator design introduced here features a holistic photonic, electronic, and RF-based optimization and includes an asymmetric MZI tuning step to optimize the extinction ratio (ER)-to-insertion loss (IL) and dielectric thickness sweep to balance the trade-offs between ER and speed. Driven by CMOS compatible bias voltage levels, this device is the first to address next-generation modulator demands for processors of the machine intelligence revolution, in addition to the edge and cloud computing demands as well as optical transceivers alike.

With the increasing need for large volumes of data processing, transport, and storage, optimizing the trade-off between high-speed and energy consumption in today’s optoelectronic devices is getting increasingly difficult. Heterogeneous material integration into silicon- and nitride-based photonics has showed high-speed promise, albeit at the expense of millimeter-to centimeter-scale footprints. The hunt for an electro-optic modulator that combines high speed, energy efficiency, and compactness to support high component density on-chip continues. Using a double-layer graphene optical modulator integrated on a Silicon photonics platform, we are able to achieve 60 GHz speed (3 dB roll-off), micrometer compactness, and efficiency of 2.25 fJ/bit in this paper. The electro-optic response is boosted further by a vertical distributed-Bragg-reflector cavity, which reduces the driving voltage by about 40 times while maintaining a sufficient modulation depth (5.2 dB/V). Modulators that are small, efficient, and quick allow high photonic chip density and performance, which is critical for signal processing, sensor platforms, and analog- and neuromorphic photonic processors.

When solving, modeling or reasoning about complex problems, it is usually convenient to use the knowledge of a parallel physical system for representing it. This is the case of lumped-circuit abstraction, which can be used for representing mechanical and acoustic systems, thermal and heat-diffusion problems and in general partial differential equations. Integrated photonic platforms hold the prospective to perform signal processing and analog computing inherently, by mapping into hardware specific operations which relies on the wave-nature of their signals, without trusting on logic gates and digital states like electronics. Here, we argue that in absence of a straightforward parallelism a homomorphism can be induced. We introduce a photonic platform capable of mimicking Kirchhoff’s law in photonics and used as node of a finite difference mesh for solving partial differential equation using monochromatic light in the telecommunication wavelength. Our approach experimentally demonstrates an arbitrary set of boundary conditions, generating a one-shot discrete solution of a Laplace partial differential equation, with an accuracy above 95% with respect to commercial solvers. Our photonic engine can provide a route to achieve chip-scale, fast (10 s of ps), and integrable reprogrammable accelerators for the next generation hybrid high-performance computing.

Microelectronic computers have encountered challenges in meeting all of today’s demands for information processing. Meeting these demands will require the development of unconventional computers employing alternative processing models and new device physics. Neural network models have come to dominate modern machine learning algorithms, and specialized electronic hardware has been developed to implement them more efficiently. A silicon photonic integration industry promises to bring manufacturing ecosystems normally reserved for microelectronics to photonics. Photonic devices have already found simple analog signal processing niches where electronics cannot provide sufficient bandwidth and reconfigurability. In order to solve more complex information processing problems, they will have to adopt a processing model that generalizes and scales. Neuromorphic photonics aims to map physical models of optoelectronic systems to abstract models of neural networks. It represents a new opportunity for machine information processing on sub-nanosecond timescales, with application to mathematical programming, intelligent radio frequency signal processing, and real-time control. The strategy of neuromorphic engineering is to externalize the risk of developing computational theory alongside hardware. The strategy of remaining compatible with silicon photonics externalizes the risk of platform development. In this perspective article, we provide a rationale for a neuromorphic photonics processor, envisioning its architecture and a compiler. We also discuss how it can be interfaced with a general purpose computer, i.e. a CPU, as a coprocessor to target specific applications. This paper is intended for a wide audience and provides a roadmap for expanding research in the direction of transforming neuromorphic photonics into a viable and useful candidate for accelerating neuromorphic computing.

Electro-optic signal modulation provides a key functionality in modern technology and information networks. Photonic integration has not only enabled miniaturizing photonic components, but also provided performance improvements due to co-design addressing both electrical and optical device rules. The millimeter to centimeter footprint of many foundry-ready electro-optic modulators, however, limits density scaling of on-chip photonic systems. To address these limitations, here we experimentally demonstrate a coupling-enhanced electro-absorption modulator by heterogeneously integrating a novel dual-gated indium-tin-oxide phase-shifting tunable absorber placed at a silicon directional coupler region. This concept allows utilizing the normally parasitic Kramers-Kronig relations here in an synergistic way resulting in a strong modulation depth to insertion loss ratio of about 1. Our experimental modulator shows a 2 dB extinction ratio for a just 4 μm short device at 4 V bias. Since no optical resonances are deployed, this device shows spectrally broadband operation as demonstrated here across the entire C-band. In conclusion, we demonstrate a modulator utilizing strong index change from both real and imaginary parts of active material enabling compact and high-performing modulators using semiconductor near-foundry materials.

Photonic Random-Access Memories (P-RAM) are an essential component for the on-chip non-von Neumann photonic computing by eliminating optoelectronic conversion losses in data links. Emerging Phase-Change Materials (PCMs) have been showed multilevel memory capability, but demonstrations still yield relatively high optical loss and require cumbersome WRITE-ERASE approaches increasing power consumption and system package challenges. Here we demonstrate a multistate electrically programmed low-loss nonvolatile photonic memory based on a broadband transparent phase-change material (Ge2Sb2Se5, GSSe) with ultralow absorption in the amorphous state. A zero-static-power and electrically programmed multi-bit P-RAM is demonstrated on a silicon-on-insulator platform, featuring efficient amplitude modulation up to 0.2 dB/μm and an ultralow insertion loss of total 0.12 dB for a 4-bit memory showing a 100× improved signal to loss ratio compared to other phase-change-materials based photonic memories. We further optimize the positioning of dual microheaters validating performance tradeoffs. Experimentally we demonstrate a half-a-million cyclability test showcasing the robust approach of this material and device. Low-loss photonic retention-of-state adds a key feature for photonic functional and programmable circuits impacting many applications including neural networks, LiDAR, and sensors for example., (© 2023. The Author(s).)

Photothermal therapy (PTT) represents a promising modality for tumor control typically using infrared light-responsive nanoparticles illuminated by a wavelength-matched external laser. However, due to the constraints of light penetration, PTT is generally restricted to superficially accessible tumors. With the goal of extending the benefits of PTT to all tumor settings, interstitial PTT (I-PTT) is evaluated by the photothermal activation of intratumorally administered Prussian blue nanoparticles with a laser fiber positioned interstitially within the tumor. This interstitial fiber, which is fitted with a terminal diffuser, distributes light within the tumor microenvironment from the "inside-out" as compared to from the "outside-in" traditionally observed during superficially administered PTT (S-PTT). I-PTT improves the heating efficiency and heat distribution within a target treatment area compared to S-PTT. Additionally, I-PTT generates increased cytotoxicity and thermal damage at equivalent thermal doses, and elicits immunogenic cell death at lower thermal doses in targeted neuroblastoma tumor cells compared to S-PTT. In vivo, I-PTT induces significantly higher long-term tumor regression, lower rates of tumor recurrence, and improved long-term survival in multiple syngeneic murine models of neuroblastoma. This study highlights the significantly enhanced therapeutic benefit of I-PTT compared to traditional S-PTT as a promising treatment modality for solid tumors., (© 2022 The Authors. Advanced Healthcare Materials published by Wiley-VCH GmbH.)

In vitro cardiomyocyte (CM) maturation is an imperative step to replicate native heart tissue-like structures as cardiac tissue grafts or as drug screening platforms. CMs are known to interpret biophysical cues such as stiffness, topography, external mechanical stimulation or dynamic perfusion load through mechanotransduction and change their behavior, organization, and maturation. In this regard, a silk-based cardiac tissue (CT) coupled with a dynamic perfusion-based mechanical stimulation platform (DMM) for achieving maturation and functionality in vitro is tried to be delivered. Silk fibroin (SF) is used to fabricate lamellar scaffolds to provide native tissue-like anisotropic architecture and is found to be nonimmunogenic and biocompatible allowing cardiomyocyte attachment and growth in vitro. Further, the scaffolds display excellent mechanical properties by their ability to undergo cyclic compressions without any deformation when places in the DMM. Gradient compression strains (5% to 20%), mimicking the native physiological and pathological conditions, are applied to the cardiomyocyte culture seeded on lamellar silk scaffolds in the DMM. A strain-dependent difference in cardiomyocyte maturation, gene expression, sarcomere elongation, and extracellular matrix formation is observed. These silk-based CTs matured in the DMM can open up several avenues toward the development of host-specific grafts and in vitro models for drug screening., (© 2022 Wiley-VCH GmbH.)

While information is ubiquitously generated, shared, and analyzed in a modern-day life, there is still some controversy around the ways to assess the amount and quality of information inside a noisy optical channel. A number of theoretical approaches based on, e.g., conditional Shannon entropy and Fisher information have been developed, along with some experimental validations. Some of these approaches are limited to a certain alphabet, while others tend to fall short when considering optical beams with a nontrivial structure, such as Hermite-Gauss, Laguerre-Gauss, and other modes with a nontrivial structure. Here, we propose a new definition of the classical Shannon information via the Wigner distribution function, while respecting the Heisenberg inequality. Following this definition, we calculate the amount of information in Gaussian, Hermite-Gaussian, and Laguerre-Gaussian laser modes in juxtaposition and experimentally validate it by reconstruction of the Wigner distribution function from the intensity distribution of structured laser beams. We experimentally demonstrate the technique that allows to infer field structure of the laser beams in singular optics to assess the amount of contained information. Given the generality, this approach of defining information via analyzing the beam complexity is applicable to laser modes of any topology that can be described by well-behaved functions. Classical Shannon information, defined in this way, is detached from a particular alphabet, i.e., communication scheme, and scales with the structural complexity of the system. Such a synergy between the Wigner distribution function encompassing the information in both real and reciprocal space and information being a measure of disorder can contribute into future coherent detection algorithms and remote sensing., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this article., (Copyright © 2021 Maria Solyanik-Gorgone et al.)

Mirror symmetry is an abundant feature in both nature and technology. Its successful detection is critical for perception procedures based on visual stimuli and requires organizational processes. Neuromorphic computing, utilizing brain-mimicked networks, could be a technology-solution providing such perceptual organization functionality, and furthermore has made tremendous advances in computing efficiency by applying a spiking model of information. Spiking models inherently maximize efficiency in noisy environments by placing the energy of the signal in a minimal time. However, many neuromorphic computing models ignore time delay between nodes, choosing instead to approximate connections between neurons as instantaneous weighting. With this assumption, many complex time interactions of spiking neurons are lost. Here, we show that the coincidence detection property of a spiking-based feed-forward neural network enables mirror symmetry. Testing this algorithm exemplary on geospatial satellite image data sets reveals how symmetry density enables automated recognition of man-made structures over vegetation. We further demonstrate that the addition of noise improves feature detectability of an image through coincidence point generation. The ability to obtain mirror symmetry from spiking neural networks can be a powerful tool for applications in image-based rendering, computer graphics, robotics, photo interpretation, image retrieval, video analysis and annotation, multi-media and may help accelerating the brain-machine interconnection. More importantly it enables a technology pathway in bridging the gap between the low-level incoming sensor stimuli and high-level interpretation of these inputs as recognized objects and scenes in the world.

Densely integrated active photonics is key for next generation on-chip networks for addressing both footprint and energy budget concerns. However, the weak light-matter interaction in traditional active Silicon optoelectronics mandates rather sizable device lengths. The ideal active material choice should avail high index modulation while being easily integrated into Silicon photonics platforms. Indium tin oxide (ITO) offers such functionalities and has shown promising modulation capacity recently. Interestingly, the nanometer-thin unity-strong index modulation of ITO synergistically combines the high group-index in hybrid plasmonic with nanoscale optical modes. Following this design paradigm, here, we demonstrate a spectrally broadband, GHz-fast Mach-Zehnder interferometric modulator, exhibiting a high efficiency signified by a miniscule V π L of 95 V μm, deploying a one-micrometer compact electrostatically tunable plasmonic phase-shifter, based on heterogeneously integrated ITO thin films into silicon photonics. Furthermore we show, that this device paradigm enables spectrally broadband operation across the entire telecommunication near infrared C-band. Such sub-wavelength short efficient and fast modulators monolithically integrated into Silicon platform open up new possibilities for high-density photonic circuitry, which is critical for high interconnect density of photonic neural networks or applications in GHz-fast optical phased-arrays, for example.

Nanoparticle-based magnetic hyperthermia is a well-known thermal therapy platform studied to treat solid tumors, but its use for monotherapy is limited due to incomplete tumor eradication at hyperthermia temperature (45 °C). It is often combined with chemotherapy for obtaining a more effective therapeutic outcome. Cubic-shaped cobalt ferrite nanoparticles (Co-Fe NCs) serve as magnetic hyperthermia agents and as a cytotoxic agent due to the known cobalt ion toxicity, allowing the achievement of both heat and cytotoxic effects from a single platform. In addition to this advantage, Co-Fe NCs have the unique ability to form growing chains under an alternating magnetic field (AMF). This unique chain formation, along with the mild hyperthermia and intrinsic cobalt toxicity, leads to complete tumor regression and improved overall survival in an in vivo murine xenograft model, all under clinically approved AMF conditions. Numerical calculations identify magnetic anisotropy as the main Co-Fe NCs' feature to generate such chain formations. This novel combination therapy can improve the effects of magnetic hyperthermia, inaugurating investigation of mechanical behaviors of nanoparticles under AMF, as a new avenue for cancer therapy., (© 2020 The Authors. Published by Wiley-VCH GmbH.)

The replacement of plastic with eco-friendly and biodegradable materials is one of the most stringent environmental challenges. In this respect, cellulose stands out as a biodegradable polymer. However, a significant challenge is to obtain biodegradable materials for high-end photonics that are robust in humid environments. Here, we demonstrate the fabrication of high-quality micro- and nanoscale photonic and plasmonic structures via replica molding using pure cellulose and a blended version with nonedible agro-wastes. Both materials are biodegradable in soil and seawater according to the ISO 17556 standard. The pure cellulose films are transparent in the vis-NIR spectrum, having a refractive index similar to glass. The microstructured photonic crystals show high-quality diffractive properties that are maintained under extended exposure to water. Nanostructuring the cellulose transforms it to a biodegradable metasurface manifesting bright structural colors. A subsequent deposition of Ag endowed the metasurface with plasmonic properties used to produce plasmonic colors and for surface-enhanced Raman scattering.

Continuing demands for increased computing efficiency and communication bandwidth have pushed the current semiconductor technology to its limit. This led to novel technologies with the potential to outperform conventional electronic solutions such as photonic pre-processors or accelerators, electronic-photonic hybrid circuits, and neural networks. However, the efforts made to describe and predict the performance evolution of compute-performance fall short to accurately predict and thereby explain the actually observed development pace with time; that is all proposed metrics eventually deviate from their development trajectory after several years from when they were originally proposed. This discrepancy demands a figure-of-merit that includes a holistic set of driving forces of the compute-system evolution. Here we introduce the Capability-to-Latency-Energy-Amount-Resistance (CLEAR) metric encompassing synchronizing speed, energy efficiency, physical machine size scaling, and economic cost. We show that CLEAR is the only metric to accurately describe the historical compute-system development. We find that even across different technology options CLEAR matches the observed (post-diction) constant rate-of-growth, and also fits proposed future compute-system (prediction). Therefore, we propose CLEAR to serve as a guide to quantitatively predict required compute-system demands at a given time in the future.

Myocardial microenvironment plays a decisive role in guiding the function and fate of cardiomyocytes, and engineering this extracellular niche holds great promise for cardiac tissue regeneration. Platforms utilizing hybrid hydrogels containing various types of conductive nanoparticles have been a critical tool for constructing engineered cardiac tissues with outstanding mechanical integrity and improved electrophysiological properties. However, there has been no attempt to directly compare the efficacy of these hybrid hydrogels and decipher the mechanisms behind how these platforms differentially regulate cardiomyocyte behavior. Here, we employed gelatin methacryloyl (GelMA) hydrogels containing three different types of carbon-based nanoparticles: carbon nanotubes (CNTs), graphene oxide (GO), and reduced GO (rGO), to investigate the influence of these hybrid scaffolds on the structural organization and functionality of cardiomyocytes. Using immunofluorescent staining for assessing cellular organization and proliferation, we showed that electrically conductive scaffolds (CNT- and rGO-GelMA compared to relatively nonconductive GO-GelMA) played a significant role in promoting desirable morphology of cardiomyocytes and elevated the expression of functional cardiac markers, while maintaining their viability. Electrophysiological analysis revealed that these engineered cardiac tissues showed distinct cardiomyocyte phenotypes and different levels of maturity based on the substrate (CNT-GelMA: ventricular-like, GO-GelMA: atrial-like, and rGO-GelMA: ventricular/atrial mixed phenotypes). Through analysis of gene-expression patterns, we uncovered that the engineered cardiac tissues matured on CNT-GelMA and native cardiac tissues showed comparable expression levels of maturation markers. Furthermore, we demonstrated that engineered cardiac tissues matured on CNT-GelMA have increased functionality through integrin-mediated mechanotransduction ( via YAP/TAZ) in contrast to cardiomyocytes cultured on rGO-GelMA.

The class of transparent conductive oxides includes the material indium tin oxide (ITO) and has become a widely used material of modern every-day life such as in touch screens of smart phones and watches, but also used as an optically transparent low electrically-resistive contract in the photovoltaics industry. More recently ITO has shown epsilon-near-zero (ENZ) behavior in the telecommunication frequency band enabling both strong index modulation and other optically-exotic applications such as metatronics. However, the ability to precisely obtain targeted electrical and optical material properties in ITO is still challenging due to complex intrinsic effects in ITO and as such no integrated metatronic platform has been demonstrated to-date. Here we deliver an extensive and accurate description process parameter of RF-sputtering, showing a holistic control of the quality of ITO thin films in the visible and particularly near-infrared spectral region. We are able to custom-engineer the ENZ point across the telecommunication band by explicitly controlling the sputtering process conditions. Exploiting this control, we design a functional sub-wavelength-scale filter based on lumped circuit-elements, towards the realization of integrated metatronic devices and circuits.

Plasmonic metasurfaces have spawned the field of flat optics using nanostructured planar metallic or dielectric surfaces that can replace bulky optical elements and enhance the capabilities of traditional far-field optics. Furthermore, the potential of flat optics can go far beyond far-field modulation and can be exploited for functionality in the near-field itself. Here, we design metasurfaces based on aperiodic arrays of plasmonic Au nanostructures for tailoring the optical near-field in the visible and near-infrared spectral range. The basic element of the arrays is a rhomboid that is modulated in size, orientation, and position to achieve the desired functionality of the micron-size metasurface structure. Using two-photon-photoluminescence as a tool to probe the near-field profiles in the plane of the metasurfaces, we demonstrate the molding of light into different near-field intensity patterns and active pattern control via the far-field illumination. Finite element method simulations reveal that the near-field modulation occurs via a combination of the plasmonic resonances of the rhomboids and field enhancement in the nanoscale gaps in between the elements. This approach enables optical elements that can switch the near-field distribution across the metasurface via wavelength and polarization of the incident far-field light and provides pathways for light matter interaction in integrated devices.

The interaction between excitons and phonons in semiconductor nanocrystals plays a crucial role in the exciton energy spectrum and dynamics, and thus in their optical properties. We investigate the exciton-phonon coupling in giant-shell CdSe/CdS core-shell nanocrystals via resonant Raman spectroscopy. The Huang-Rhys parameter is evaluated by the intensity ratio of the longitudinal-optical (LO) phonon of CdS with its first multiscattering (2LO) replica. We used four different excitation wavelengths in the range from the onset of the CdS shell absorption to well above the CdS shell band edge to get insight into resonance effects of the CdS LO phonon with high-energy excitonic transitions. The isotropic spherical giant-shell nanocrystals show consistently stronger exciton-phonon coupling as compared to the anisotropic rod-shaped dot-in-rod (DiR) architecture, and the 2LO/LO intensity ratio decreases for excitation wavelengths approaching the CdS band edge. The strong exciton-phonon coupling in the spherical giant-shell nanocrystals can be related to the delocalization of the electronic wave functions. Furthermore, we observe the radial breathing modes of the GS nanocrystals and their overtones by ultralow frequency Raman spectroscopy with nonresonant excitation, using laser energies well below the band gap of the heteronanocrystals, and highlight the differences between higher-order optical and acoustic phonon modes.

The crystal structure of graphene flakes is expected to significantly affect their sensing properties. Here we report an experimental investigation on the crystalline structure of graphene aimed at exploring the effects on the gas sensing properties. The morphology of graphene, prepared via Chemical Vapor Deposition (CVD), Liquid Phase Exfoliation (LPE) and Mechanical Exfoliation (ME), is inspected through Raman spectroscopy, Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM). CVD and LPE-graphene structures are found to be more defective with respect to ME-graphene. The defects are due to the jagged morphology of the films rather than originating from intrinsic disorder. The flatness of ME-graphene flakes, instead, explains the absence of defects. Chemiresistors based on the three different graphene preparation methods are subsequently exposed to NO 2 in the concentration range 0.1-1.5 ppm (parts per million). The device performance is demonstrated to be strongly and unambiguously affected by the material structure: the less defective the material is, the higher the response rate is. In terms of signal variation, at 1.5 ppm, for instance, ME-graphene shows the highest value (5%) among the three materials. This study, comparing simultaneously graphene and sensors prepared via different routes, provides the first experimental evidence of the role played by the graphene level of defectiveness in the interaction with analytes. Moreover, these findings can pave the path for tailoring the sensor behavior as a function of graphene morphology.

Organ-on-a-chip platforms seek to recapitulate the complex microenvironment of human organs using miniaturized microfluidic devices. Besides modeling healthy organs, these devices have been used to model diseases, yielding new insights into pathophysiology. Hutchinson-Gilford progeria syndrome (HGPS) is a premature aging disease showing accelerated vascular aging, leading to the death of patients due to cardiovascular diseases. HGPS targets primarily vascular cells, which reside in mechanically active tissues. Here, a progeria-on-a-chip model is developed and the effects of biomechanical strain are examined in the context of vascular aging and disease. Physiological strain induces a contractile phenotype in primary smooth muscle cells (SMCs), while a pathological strain induces a hypertensive phenotype similar to that of angiotensin II treatment. Interestingly, SMCs derived from human induced pluripotent stem cells of HGPS donors (HGPS iPS-SMCs), but not from healthy donors, show an exacerbated inflammatory response to strain. In particular, increased levels of inflammation markers as well as DNA damage are observed. Pharmacological intervention reverses the strain-induced damage by shifting gene expression profile away from inflammation. The progeria-on-a-chip is a relevant platform to study biomechanics in vascular biology, particularly in the setting of vascular disease and aging, while simultaneously facilitating the discovery of new drugs and/or therapeutic targets., (© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Lattice vibrational modes in cadmium chalcogenide nanocrystals (NCs) have a strong impact on the carrier dynamics of excitons in such confined systems and on the optical properties of these nanomaterials. A prominent material for light emitting applications are CdSe/CdS core-shell dot-in-rods. Here we present a detailed investigation of the acoustic phonon modes in such dot-in-rods by nonresonant Raman spectroscopy with laser excitation energy lower than their bandgap. With high signal-to-noise ratio in the frequency range from 5-50 cm -1 , we reveal distinct Raman bands that can be related to confined extensional and radial-breathing modes (RBM). Comparison of the experimental results with finite elements simulation and analytical analysis gives detailed insight into the localized nature of the acoustic vibration modes and their resonant frequencies. In particular, the RBM of dot-in-rods cannot be understood by an oscillation of a CdSe sphere embedded in a CdS rod matrix. Instead, the dot-in-rod architecture leads to a reduction of the sound velocity in the core region of the rod, which results in a redshift of the rod RBM frequency and localization of the phonon induced strain in vicinity of the core where optical transitions occur. Such localized effects potentially can be exploited as a tool to tune exciton-phonon coupling in nanocrystal heterostructures.

The inadequacy of animal models in correctly predicting drug and biothreat agent toxicity in humans has resulted in a pressing need for in vitro models that can recreate the in vivo scenario. One of the most important organs in the assessment of drug toxicity is liver. Here, we report the development of a liver-on-a-chip platform for long-term culture of three-dimensional (3D) human HepG2/C3A spheroids for drug toxicity assessment. The bioreactor design allowed for in situ monitoring of the culture environment by enabling direct access to the hepatic construct during the experiment without compromising the platform operation. The engineered bioreactor could be interfaced with a bioprinter to fabricate 3D hepatic constructs of spheroids encapsulated within photocrosslinkable gelatin methacryloyl (GelMA) hydrogel. The engineered hepatic construct remained functional during the 30 days culture period as assessed by monitoring the secretion rates of albumin, alpha-1 antitrypsin, transferrin, and ceruloplasmin, as well as immunostaining for the hepatocyte markers, cytokeratin 18, MRP2 bile canalicular protein and tight junction protein ZO-1. Treatment with 15 mM acetaminophen induced a toxic response in the hepatic construct that was similar to published studies on animal and other in vitro models, thus providing a proof-of-concept demonstration of the utility of this liver-on-a-chip platform for toxicity assessment.

A highly elastic hybrid hydrogel of methacryloyl-substituted recombinant human tropoelastin (MeTro) and graphene oxide (GO) nanoparticles are developed. The synergistic effect of these two materials significantly enhances both ultimate strain (250%), reversible rotation (9700°), and the fracture energy (38.8 ± 0.8 J m(-2) ) in the hybrid network. Furthermore, improved electrical signal propagation and subsequent contraction of the muscles connected by hybrid hydrogels are observed in ex vivo tests., (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Muscle-based biohybrid actuators have generated significant interest as the future of biorobotics but so far they move without having much control over their actuation behavior. Integration of microelectrodes into the backbone of these systems may enable guidance during their motion and allow precise control over these actuators with specific activation patterns. Here, we addressed this challenge by developing aligned CNT forest microelectrode arrays and incorporated them into scaffolds for stimulating the cells. Aligned CNTs were successfully embedded into flexible and biocompatible hydrogel exhibiting excellent anisotropic electrical conductivity. Bioactuators were then engineered by culturing cardiomyocytes on the CNT microelectrode-integrated hydrogel constructs. The resulting cardiac tissue showed homogeneous cell organization with improved cell-to-cell coupling and maturation, which was directly related to the contractile force of muscle tissue. This centimeter-scale bioactuator has excellent mechanical integrity, embedded microelectrodes and is capable of spontaneous actuation behavior. Furthermore, we demonstrated that a biohybrid machine can be controlled by an external electrical field provided by the integrated CNT microelectrode arrays. In addition, due to the anisotropic electrical conductivity of the electrodes provided from aligned CNTs, significantly different excitation thresholds were observed in different configurations such as the ones in parallel vs. perpendicular direction to the CNT alignment.

A wide-band microwave characterization of nanocomposites based on commercial multiwalled carbon nanotubes (MWCNTs) and epoxy resin is presented. The sample preparation method is discussed in detail. Field emission scanning electron microscopy is used for morphological sample analysis of nanocomposites and MWCNTs. The complex permittivity is measured in a wide frequency band (3 to 18 GHz) using a commercial dielectric probe (Agilent 85070D) and a network analyzer (E8361A). A statistical analysis based on one-way analysis of variance (ANOVA) technique is performed. The aim of this statistical analysis is to investigate the influence of concentration of nanoparticles inside the polymer matrix on the complex permittivity. This can be significantly different in nanocomposites even if the samples have similar electrical properties.