Electronic Structure and Optoelectronic Properties of Bismuth Oxyiodide Robust against Percent‐Level Iodine‐, Oxygen‐, and Bismuth‐Related Surface Defects

In the search for nontoxic alternatives to lead‐halide perovskites, bismuth oxyiodide (BiOI) has emerged as a promising contender. BiOI is air‐stable for over three months, demonstrates promising early‐stage photovoltaic performance and, importantly, is predicted from calculations to tolerate vacancy and antisite defects. Here, whether BiOI tolerates point defects is experimentally investigated. BiOI thin films are annealed at a low temperature of 100 °C under vacuum (25 Pa absolute pressure). There is a relative reduction in the surface atomic fraction of iodine by over 40%, reduction in the surface bismuth fraction by over 5%, and an increase in the surface oxygen fraction by over 45%. Unexpectedly, the Bi 4f_7/2 core level position, Fermi level position, and valence band density of states of BiOI are not significantly changed. Further, the charge‐carrier lifetime, photoluminescence intensity, and the performance of the vacuum‐annealed BiOI films in solar cells remain unchanged. The results show BiOI to be electronically and optoelectronically robust to percent‐level changes in surface composition. However, from photoinduced current transient spectroscopy measurements, it is found that the as‐grown BiOI films have deep traps located ≈0.3 and 0.6 eV from the band edge. These traps limit the charge‐carrier lifetimes of BiOI, and future improvements in the performance of BiOI photovoltaics will need to focus on identifying their origin. Nevertheless, these deep traps are three to four orders of magnitude less concentrated than the surface point defects induced through vacuum annealing. The charge‐carrier lifetimes of the BiOI films are also orders of magnitude longer than if these surface defects were recombination active. This work therefore shows BiOI to be robust against processing conditions that lead to percent‐level iodine‐, bismuth‐, and oxygen‐related surface defects. This will simplify and reduce the cost of fabricating BiOI‐based electronic devices, and stands in contrast to the defect‐sensitivity of traditional covalent semiconductors.     

A novel local thresholding algorithm for trabecular bone volume fraction mapping in the limited spatial resolution regime of in vivo MRI

Recent advances in micro-magnetic resonance imaging have shown the possibility of in vivo assessment of trabecular bone architecture. However, the small feature size and relatively low signal-to-noise ratio (SNR) achievable in vivo cause the intensity histogram to be unimodal. The critical first step in the processing of these images is the extraction of bone volume fraction for each voxel. Here, we propose a local threshold algorithm (LTA) that determines the marrow intensity value in the neighborhood of each voxel based on nearest-neighbor statistics. Using the local marrow intensities we threshold the image and scale the intensities of voxels partially occupied by bone to produce a marrow volume fraction map of the trabecular bone region. We show that structural parameters derived with the LTA are highly correlated with those obtained with the previously published histogram deconvolution algorithm (HDA) and that the LTA is robust to image noise corruption. The LTA is found to correctly identify trabeculae with a significantly higher reliability than HDA. Finally, we demonstrate that the LTA is superior in preserving connectivity by showing for 75 in vivo images that the genus of the trabecular bone surface is always higher than when processed with the HDA.     

Solid Ink Laser Patterning for High-Resolution Information Labels with Supervised Learning Readout

Tagging, tracking, or validation of products are often facilitated by inkjet-printed optical information labels. However, this requires thorough substrate pretreatment, ink optimization, and often lacks in printing precision/resolution. Herein, a printing method based on laser-driven deposition of solid polymer ink that allows for printing on various substrates without pretreatment is demonstrated. Since the deposition process has a precision of <1 µm, it can introduce the concept of sub-positions with overlapping spots. This enables high-resolution fluorescent labels with comparable spot-to-spot distance of down to 15 µm (444,444 spots cm⁻²) and rapid machine learning-supported readout based on low-resolution fluorescence imaging. Furthermore, the defined thickness of the printed polymer ink spots can be used to fabricate multi-channel information labels. Additional information can be stored in different fluorescence channels or in a hidden topography channel of the label that is independent of the fluorescence.     

Iron Oxide‐Labeled Collagen Scaffolds for Non‐Invasive MR Imaging in Tissue Engineering

Non‐invasive imaging holds significant potential for implementation in tissue engineering. It can be used to monitor the localization and function of tissue‐engineered implants, as well as their resorption and remodelling. Thus far, however, the vast majority of effort in this area of research have focused on the use of ultrasmall super‐paramagnetic iron oxide (USPIO) nanoparticle‐labeled cells, colonizing the scaffolds, to indirectly image the implant material. Reasoning that directly labeling scaffold materials might be more beneficial (enabling imaging also in the case of non‐cellularized implants), more informative (enabling the non‐invasive visualization and quantification of scaffold degradation), and easier to translate into the clinic (cell‐free materials are less complex from a regulatory point‐of‐view), three different types of USPIO nanoparticles are prepared and incorporated both passively and actively (via chemical conjugation; during collagen crosslinking) into collagen‐based scaffold materials. The amount of USPIO incorporated into the scaffolds is optimized, and correlated with MR signal intensity, showing that the labeled scaffolds are highly biocompatible, and that scaffold degradation can be visualized using MRI. This provides an initial proof‐of‐principle for the in vivo visualization of the scaffolds. Consequently, USPIO‐labeled scaffold materials seem to be highly suitable for image‐guided tissue engineering applications.     

Highly Robust Indium‐Free Transparent Conductive Electrodes Based on Composites of Silver Nanowires and Conductive Metal Oxides

A hybrid approach for the realization of In‐free transparent conductive layers based on a composite of a mesh of silver nanowires (NWs) and a conductive metal‐oxide is demonstrated. As metal‐oxide room‐temperature‐processed sol–gel SnO_x or Al:ZnO prepared by low‐temperature (100 °C) atomic layer deposition is used, respectively. In this concept, the metal‐oxide is intended to fuse the wires together and also to “glue” them to the substrate. As a result, a low sheet resistance down to 5.2 Ω sq^‐1 is achieved with a concomitant average transmission of 87%. The adhesion of the NWs to the substrate is significantly improved and the resulting composites withstand adhesion tests without loss in conductivity. Owing to the low processing temperatures, this concept allows highly robust, highly conductive, and transparent coatings even on top of temperature sensitive objects, for example, polymer foils, organic devices. These Indium‐ and PEDOT:PSS‐free hybrid layers are successfully implemented as transparent top‐electrodes in efficient all‐solution‐processed semitransparent organic solar cells. It is obvious that this approach is not limited to organic solar cells but will generally be applicable in devices which require transparent electrodes.     

A Mixed-Mode Analog Neural Network Using Current-Steering Synapses

A hardware neural network is presented that combines digital signalling with analog computing. This allows a high amount of parallelism in the synapse operation while maintaining signal integrity and high transmission speed throughout the system. The presented mixed-mode implementation achieves a synapse density of 4 k per mm² in 0.35 μm CMOS. The current-mode operation of the analog core combined with differential neuron inputs reaches an analog precision sufficient for 10 bit parity while running at a speed of 0.8 Teraconnections per second.     

Theranostic USPIO‐Loaded Microbubbles for Mediating and Monitoring Blood‐Brain Barrier Permeation

Efficient and safe drug delivery across the blood‐brain barrier (BBB) remains one of the major challenges of biomedical and (nano‐) pharmaceutical research. Here, it is demonstrated that poly(butyl cyanoacrylate)‐based microbubbles (MB), carrying ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles within their shell, can be used to mediate and monitor BBB permeation. Upon exposure to transcranial ultrasound pulses, USPIO‐MB are destroyed, resulting in acoustic forces inducing vessel permeability. At the same time, USPIO are released from the MB shell, they extravasate across the permeabilized BBB and they accumulate in extravascular brain tissue, thereby providing non‐invasive R ₂*‐based magnetic resonance imaging information on the extent of BBB opening. Quantitative changes in R ₂* relaxometry are in good agreement with 2D and 3D microscopy results on the extravascular deposition of the macromolecular model drug fluorescein isothiocyanate (FITC)‐dextran into the brain. Such theranostic materials and methods are considered to be useful for mediating and monitoring drug delivery across the BBB and for enabling safe and efficient treatment of CNS disorders.     

Enhancing virtual environments with QoS aware resource management

Nowadays, the consolidation of application servers is the most common use for current virtualization solutions. Each application server takes the form of a virtual machine (VM) that can be hosted into one physical machine. In a default Xen implementation, the scheduler is configured to handle equally all of the VMs that run on a single machine. As a consequence, the scheduler shares equally all of the available physical CPU resources among the running VMs. However, when the applications that run in the VM dynamically change their resource requirements, a different solution is needed. Furthermore, if the resource usage is associated with service-level agreements, a predefined equal share of the processor power is insufficient for the VMs. Within the Xen’s primitives, even though it is possible to tune the scheduler parameters, there is no tool to achieve the dynamic change of the share of the processor power assigned to each VM. A combination of a number of primitives, however, appears to be suited as a base for achieving this. In this paper, we present an approach to efficiently manage the quality of service (QoS) of virtualized resources in multicore machines. We evaluate different alternatives within Xen for building an enhanced management of virtual CPU resources. We compare these alternatives in terms of performance, flexibility, and ease of use. We devise an architecture to build a high-level service that combines interdomain communication mechanisms with monitoring and control primitives for local resource management. We achieve this by our solution, a local resource manager (LRM), which adjusts the resources needed by each VM according to an agreed QoS. The LRM has been implemented as a prototype and deployed on Xen-virtualized machines. By means of experiments, we show that the implemented management component can meet the service-level objectives even under dynamic conditions by adapting the resources assigned to the virtualized machines according to demand. With the LRM, we therefore achieve both fine-grain resource allocation and efficient assignment.