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•Comprehensive overview on strategies for both simple and complex biomarkers.•Key approaches in the functionalization of MOFs towards biosensing.•Important role of the MOFs in the ...sensitive and selective detection of bio-molecules.•Key approaches that have the potential for development into Point of Care devices.
It is known that biomolecules are physiologically significant in controlling homeostasis. Any deviation in homeostasis is often detected by a change in the concentrations of these biomolecules. Hence, these biomolecules are often referred to as biomarkers and its accurate detection is of significant importance in clinical diagnosis. Electrochemical sensing is a well-known, simple, cost-effective and convenient method to detect various biomolecules, that also includes an excellent potential for the miniaturization of healthcare devices. Metal-organic frameworks (MOFs) are a recent emerging class of materials that are self-assembled porous network structured architectures of organic linkers connecting metal nodes. Therefore, MOFs are potential candidates to be effectively utilized as electrochemical sensors to detect the biomolecules due to their large surface area, controlled diverse pore structure, enhanced functionality and unique catalytic activity. This review covers the various properties and notable approaches for functionalizing MOFs. Based on these aspects, a systematic and comprehensive overview of MOF-based research for selective electrochemical sensing of physiologically important biomolecules is the main focus of this review.
Low-complexity neural networks (NNs) have successfully been proposed for digital signal processing (DSP) in short-reach intensity-modulated directly detected optical links, where chromatic ...dispersion-induced impairments significantly limit the transmission distance. The NN-based equalizers are usually optimized independently from other DSP components, such as matched filtering. This approach may result in lower equalization performance. Alternatively, optimizing a NN equalizer to perform functionalities of multiple DSP blocks may increase transmission reach while keeping the complexity low with respect to the scenarios where DSP blocks that involve nonlinear equalizers are separated and optimized independently. In this work, we propose a low-complexity NN that performs samples-to-symbol equalization, meaning that the NN-based equalizer includes match filtering and downsampling. We compare it to a samples-to-sample equalization approach followed by match filtering and downsampling in terms of performance and computational complexity. Both approaches are evaluated using three different types of NNs combined with optical preprocessing. We numerically and experimentally show that the proposed samples-to-symbol equalization approach applied for 32 GBd on-off keying (OOK) signals outperforms the samples-domain alternative keeping the computational complexity low with respect to the sample-based approach. Additionally, the different types of NN-based equalizers are compared in terms of performance with respect to computational complexity.
Introduced over ten years ago, cross-correlation-based electron backscatter diffraction has enabled high precision measurements of crystallographic rotations and elastic strain gradients at high ...spatial resolution. Since that time, there have been remarkable improvements in electron detector technology, including the advent of ultra-high speed detectors and the commercialization of direct detectors. In this study, we assess the efficacy of multiple generations of electron detectors for cross-correlation-based analysis using a single crystal Si sample as a reference. We show that, while improvements in precision are modest, there have been significant gains in the rate at which high-quality diffraction patterns can be collected. This has important implications in the size of datasets that can be collected and reduces the impact of drift and sample contamination.
We propose two-dimensional materials as targets for direct detection of dark matter. Using graphene as an example, we focus on the case where dark matter scattering deposits sufficient energy on a ...valence-band electron to eject it from the target. We show that the sensitivity of graphene to dark matter of MeV to GeV mass can be comparable, for similar exposure and background levels, to that of semiconductor targets such as silicon and germanium. Moreover, a two-dimensional target is an excellent directional detector, as the ejected electron retains information about the angular dependence of the incident dark matter particle. This proposal can be implemented by the PTOLEMY experiment, presenting for the first time an opportunity for directional detection of sub-GeV dark matter.
We propose a new low-threshold direct-detection concept for dark matter and for coherent nuclear scattering of solar neutrinos, based on the dissociation of atoms and subsequent creation of color ...center type defects within a lattice. The novelty in our approach lies in its ability to detect single defects in a macroscopic bulk of material. This class of experiments features ultra-low energy thresholds which allows for the probing of dark matter as light as O(10) MeV through nuclear scattering. Another feature of defect creation in crystals is directional information, which presents as a spectacular signal and a handle on background reduction in the form of daily modulation of the interaction rate. We discuss the envisioned setup and detection technique, as well as background reduction. We further calculate the expected rates for dark matter and solar neutrinos in two example crystals for which available data exists, demonstrating the prospective sensitivity of such experiments.
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