CalibFPA: A Focal Plane Array Imaging System based on Online Deep-Learning Calibration

Compressive focal plane arrays (FPA) enable cost-effective high-resolution (HR) imaging by acquisition of several multiplexed measurements on a low-resolution (LR) sensor. Multiplexed encoding of the visual scene is typically performed via electronically controllable spatial light modulators (SLM). An HR image is then reconstructed from the encoded measurements by solving an inverse problem that involves the forward model of the imaging system. To capture system non-idealities such as optical aberrations, a mainstream approach is to conduct an offline calibration scan to measure the system response for a point source at each spatial location on the imaging grid. However, it is challenging to run calibration scans when using structured SLMs as they cannot encode individual grid locations. In this study, we propose a novel compressive FPA system based on online deep-learning calibration of multiplexed LR measurements (CalibFPA). We introduce a piezo-stage that locomotes a pre-printed fixed coded aperture. A deep neural network is then leveraged to correct for the influences of system non-idealities in multiplexed measurements without the need for offline calibration scans. Finally, a deep plug-and-play algorithm is used to reconstruct images from corrected measurements. On simulated and experimental datasets, we demonstrate that CalibFPA outperforms state-of-the-art compressive FPA methods. We also report analyses to validate the design elements in CalibFPA and assess computational complexity

Portable Microfluidic Integrated Plasmonic Platform for Pathogen Detection

Timely detection of infectious agents is critical in early diagnosis and treatment of infectious diseases. Conventional pathogen detection methods, such as enzyme linked immunosorbent assay (ELISA), culturing or polymerase chain reaction (PCR) require long assay times, and complex and expensive instruments, which are not adaptable to point-of-care (POC) needs at resource-constrained as well as primary care settings. Therefore, there is an unmet need to develop simple, rapid, and accurate methods for detection of pathogens at the POC. Here, we present a portable, multiplex, inexpensive microfluidic-integrated surface plasmon resonance (SPR) platform that detects and quantifies bacteria, i.e., Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) rapidly. The platform presented reliable capture and detection of E. coli at concentrations ranging from ~105 to 3.2 × 107 CFUs/mL in phosphate buffered saline (PBS) and peritoneal dialysis (PD) fluid. The multiplexing and specificity capability of the platform was also tested with S. aureus samples. The presented platform technology could potentially be applicable to capture and detect other pathogens at the POC and primary care settings

Bioinspired approaches for toughening of fibre reinforced polymer composites

In Nature, there are a large range of tough, strong, lightweight and multifunctional structures that can be an inspiration to better performingmaterials. Thiswork presents a review of structures found in Nature, frombiological ceramics and ceramics composites, biological polymers and polymers composites, biological cellular materials, biological elastomers to functional biological materials, and their main tougheningmechanisms, envisaging potential mimicking approaches that can be applied in advanced continuous fibre reinforced polymer (FRP) composite structures. For this, themost common engineering compositemanufacturing processes and current composite damage mitigation approaches are analysed. This aims at establishing the constraints of biomimetic approaches development as these bioinspired structures are to be manufactured by composite technologies. Combining both Nature approaches and engineering composites developments is a route for the design and manufacturing of high mechanical performance and multifunctional composite structures, therefore new bioinspired solutions are proposed.This research was funded by the project “IAMAT—Introduction of advanced materials technologies into new product development for the mobility industries”, with reference MITP-TB/PFM/0005/2013, under the MIT-Portugal program and in the scope of projects with references UIDB/05256/2020 and UIDP/05256/2020, exclusively financed by FCT - Fundação para a Ciência e Tecnologia

An efficient hybrid conventional method to fabricate nacre-like bulk nano-laminar composites

Bulk nano-laminar composites were fabricated by a novel technique called Hot-press Assisted Slip Casting (HASC) which combines hot-pressing and slip-casting to improve alignment and volume fraction of the reinforcement. Alumina flakes were used as filler in an epoxy matrix. Microstructure of composites and alignment of flakes were characterized by Scanning Electron Microscope (SEM). Three point bending test and Vickers hardness test were done for mechanical characterization of composites. Flexural tests on Chevron-notched specimens revealed a high work-of-fracture in the case of the fabricated composites reaching to 254 J/m(2). Fracture surface of three point bending samples were examined by SEM. Main fracture mechanism is debonding of flakes from the matrix. With its high volume fraction (60%) of reinforcement phase and high degree of flake alignment, a nacre-like microstructure was achieved with a relatively efficient cost effective and simple hybrid conventional method

Counting Molecules with a Mobile Phone Camera Using Plasmonic Enhancement

Plasmonic field enhancement enables the acquisition of Raman spectra at a single molecule level. Here we investigate the detection of surface enhanced Raman signal using the unmodified image sensor of a smart phone, integrated onto a confocal Raman system. The sensitivity of a contemporary smart phone camera is compared to a photomultiplier and a cooled charge-coupled device. The camera displays a remarkably high sensitivity, enabling the observation of the weak unenhanced Raman scattering signal from a silicon surface, as well as from liquids, such as ethanol. Using high performance wide area plasmonic substrates that enhance the Raman signal 10⁶ to 10⁷ times, blink events typically associated with single molecule motion, are observed on the smart phone camera. Raman spectra can also be collected on the smart phone by converting the camera into a low resolution spectrometer with the inclusion of a collimator and a dispersive optical element in front of the camera. In this way, spectral content of the blink events can be observed on the plasmonic substrate, in real time, at 30 frames per second

Counting Molecules with a Mobile Phone Camera Using Plasmonic Enhancement

Plasmonic field enhancement enables the acquisition of Raman spectra at a single molecule level. Here we investigate the detection of surface enhanced Raman signal using the unmodified image sensor of a smart phone, integrated onto a confocal Raman system. The sensitivity of a contemporary smart phone camera is compared to a photomultiplier and a cooled charge-coupled device. The camera displays a remarkably high sensitivity, enabling the observation of the weak unenhanced Raman scattering signal from a silicon surface, as well as from liquids, such as ethanol. Using high performance wide area plasmonic substrates that enhance the Raman signal 10⁶ to 10⁷ times, blink events typically associated with single molecule motion, are observed on the smart phone camera. Raman spectra can also be collected on the smart phone by converting the camera into a low resolution spectrometer with the inclusion of a collimator and a dispersive optical element in front of the camera. In this way, spectral content of the blink events can be observed on the plasmonic substrate, in real time, at 30 frames per second

Counting Molecules with a Mobile Phone Camera Using Plasmonic Enhancement

Plasmonic field enhancement enables the acquisition of Raman spectra at a single molecule level. Here we investigate the detection of surface enhanced Raman signal using the unmodified image sensor of a smart phone, integrated onto a confocal Raman system. The sensitivity of a contemporary smart phone camera is compared to a photomultiplier and a cooled charge-coupled device. The camera displays a remarkably high sensitivity, enabling the observation of the weak unenhanced Raman scattering signal from a silicon surface, as well as from liquids, such as ethanol. Using high performance wide area plasmonic substrates that enhance the Raman signal 10⁶ to 10⁷ times, blink events typically associated with single molecule motion, are observed on the smart phone camera. Raman spectra can also be collected on the smart phone by converting the camera into a low resolution spectrometer with the inclusion of a collimator and a dispersive optical element in front of the camera. In this way, spectral content of the blink events can be observed on the plasmonic substrate, in real time, at 30 frames per second

Counting Molecules with a Mobile Phone Camera Using Plasmonic Enhancement

Plasmonic field enhancement enables the acquisition of Raman spectra at a single molecule level. Here we investigate the detection of surface enhanced Raman signal using the unmodified image sensor of a smart phone, integrated onto a confocal Raman system. The sensitivity of a contemporary smart phone camera is compared to a photomultiplier and a cooled charge-coupled device. The camera displays a remarkably high sensitivity, enabling the observation of the weak unenhanced Raman scattering signal from a silicon surface, as well as from liquids, such as ethanol. Using high performance wide area plasmonic substrates that enhance the Raman signal 10⁶ to 10⁷ times, blink events typically associated with single molecule motion, are observed on the smart phone camera. Raman spectra can also be collected on the smart phone by converting the camera into a low resolution spectrometer with the inclusion of a collimator and a dispersive optical element in front of the camera. In this way, spectral content of the blink events can be observed on the plasmonic substrate, in real time, at 30 frames per second